ORIGINAL_ARTICLE
Fabrication of (Acrylonitrile Butadiene Styrene/Poly Ethylene Glycol) Nanofiltration Membrane: the Effect of PEG Concentration and Operating Conditions on Membrane Performance
In the current research, ABS-co-PEG nanofiltration membrane was prepared by solution casting technique using N, N dimethyl acetamide as solvent. The effect of PEG concentration as additive in the casting solution on membrane flux, salt rejection, phase inversion time, water content, membrane porosity, membrane tensile strength and fouling was studied. Also the effect of operating conditions such as feed concentration, pressure and temperature on membrane performance were also studied. It was found that increase of PEG content up to 6 %wt in the casting solution initially led to increase in flux and decrease of salt rejection in prepared membranes. The flux was decreased and salt rejection increased by more increase in PEG content from 6 to 10 %wt. In addition, presence of PEG in membrane structure caused to formation of more stable flux during filtration time against fouling. Increase of feed salt concentration caused to flux decreasing. The ABS/PEG membrane showed more stable flux against increase of feed concentration. Moreover, flux was increased by increase of operating pressure and feed temperature. The results also showed a clear trend towards higher values of tensile strength by increase of PEG content ratio.
https://www.ije.ir/article_81691_807e461528f05faf426cbfb6228835ab.pdf
2018-10-01
1609
1616
Nanofiltration
ABS-co-PEG Membrane Fabrication/Characterization
PEG Concentration
Physico-chemical Characterization
Operating conditions
A. R.
Moghadassi
1
Department of Chemical Engineering, Faculty of Engineering, Arak University, Arak, Iran
LEAD_AUTHOR
E.
Bagheripour
2
Department of Chemical Engineering, Faculty of Engineering, Arak University, Arak, Iran
AUTHOR
F.
Parvizian
3
Department of Chemical Engineering, Faculty of Engineering, Arak University, Arak, Iran
AUTHOR
S. M.
Hosseini
4
Department of Chemical Engineering, Faculty of Engineering, Arak University, Arak, Iran
AUTHOR
1. Bagheripour, E., Moghadassi, A.R., Hosseini, S. M., “Preparation of Polyvinylchloride Nanofiltration Membrane: Investigation of the Effect of Thickness, Prior Evaporation Time and Addition of Polyethylenglchol as Additive on Membrane Performance and Properties”, International Journal of Engineering, Transactions C: Aspects, Vol. 29, No. 3, (2016), 280-287.
1
2. Eriksson, P., “Water and salt transport through two types of polyamide composite membranes”, Journal of Membrane Science, Vol. 36, (1988), 297-313.
2
3. Bagheripour, E., Moghadassi, A., Hosseini, S. M., “Incorporated Poly Acrylic Acid-co-Fe3O4 Nanoparticles Mixed Matrix Polyethersulfone based Nanofiltration Membrane in Desalination Process”, International Journal of Engineering, Transactions C: Aspects, Vol. 30, No. 6, (2016), 821-829.
3
4. Daraei, P., Madaeni, S.S., Ghaemi, N., Monfared, H.A., Khadivi, M.A., "Fabrication of pes nanofiltration membrane by simultaneous use of MWCNT and surface graft polymerization method: Comparison of MWCNT and PAA modified MWCNT", Separation and Purification Technology, Vol. 104, (2013), 32-44.
4
5. Mobarakabad, P., Moghadassi, A. and Hosseini, S., "Fabrication and characterization of poly (phenylene ether-ether sulfone) based nanofiltration membranes modified by titanium dioxide nanoparticles for water desalination", Desalination, Vol. 365, (2015), 227-233.
5
6. Du, R.,Zhao, J.,“Properties of poly(N,N-dimethylaminoethyl methacrylate/polysulfone positively charged composite nanofiltration membrane”, Journal of Membrane Science, Vol. 239, (2004) 183-188.
6
7. Bagheripour, E., Hosseini, S. M., Hamidi, A. R., Moghadassi, A. R., "Fabrication and characterization of novel mixed matrix PES based nanofiltration membrane modified by Ilmenite", International Journal of Engineering, Transactions A: Basics, Vol. 30, No. 1, (2017) 7-14.
7
8. Ghaemi, N., Madaeni, S. S., Alizadeh, A., Daraei, P., Vatanpour, V., Falsafi, M., “Fabrication of cellulose acetate/sodium dodecyl sulfate Nano filtration membrane: Characterization and performance in rejection of pesticides”, Desalination, Vol. 290, (2012) 99–106.
8
9. Kesting, R. E., “Synthetic Polymeric Membranes”, Wiley, New York, 1985.
9
10. Maximous, N., Nakhla, G., Wan, W., Wong, K., “Preparation, characterization and performance of Al2O3/PES membrane for wastewater filtration”, Journal of Membrane Science, Vol. 341, No. 1, (2009) 67–75.
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11. Han, R., Zhang, S., Liu, C., Wang, Y., Jian, X., “Effect of NaA zeolite performance”, Journal of Membrane Science, Vol. 345, (2009) 5–12.
11
12. Madaeni, S.S., Arast, N., Rahimpour, F., Arast, Y., “Fabrication optimization of acrylonitrile butadiene styrene (ABS)/polyvinylpyrrolidone nanofiltration membrane using response surface methodology”, Desalination, 280 (2011) 305–312.
12
13. Liu, Y., Koops, G.H., Strathmann, H., “Characterization of morphology controlled polyethersulfone hollow fiber membranes by the addition of polyethylene glycol to the dope and bore liquid solution”, Journal of Membrane Science, Vol. 223, (2003) 187–199.
13
14. Chou, W.L., Yu, D.G., Yang, M.C., Jou, C.H. “Effect of molecular weight and concentration of PEG additives on morphology and permeation performance of cellulose acetate hollow fibers”, Separation and Purification Technology, Vol. 57 (2007) 209–219.
14
15. Saljoughi, E. Amirilargani, M., Mohammadi, T., “Effect of PEG additive and coagulation bath temperature on the morphology, permeability and thermal/chemical stability of asymmetric CA membranes”, Desalination, Vol. 262 (2010) 72–78.
15
16. Chakrabarty,B., Ghoshal,A.K., Purkait, M.K., “Effect of molecular weight of PEG on membrane morphology and transport properties”, Journal of Membrane Science, Vol. 309, No. 1 (2008) 209–221.
16
17. Ebadi Amooghin, A., Sanaeepur, H., Moghadassi, A.R., Kargari, A., Ghanbari, D., Sheikhi Mehrabadi, Z., “Modification of ABS Membrane by PEG for Capturing Carbon Dioxide from CO2/N2 Streams”, Separation Science and Technology, Vol. 45, No. 10 (2010) 1385-1394.
17
18. Han, R.,Zhang,S., Liu, C.,Wang,Y., Jian,X.,“Effect of NaA zeolite performance”, Journal of Membrane Science, Vol. 345, (2009) 5–12.
18
19. Soo Lee, H., Joon Im, S., Hak Kim, J., Jin Kim, H., Pyo Kim, J., Ryul Min, B., “Polyamide thin-film nanofiltration membranes containing TiO2 nanoparticles”, Desalination, Vol. 219 (2008) 48–56.
19
20. Daraei, P., Madaeni, S. S., Ghaemi, N., Salehi, E., Khadivi, M., Moradian, R., Astinchap, B., “Novel polyether sulfonenanocomposite membrane prepared by PANI/Fe3O4 nanoparticles with enhanced performance for Cu(II) removal from water”, Journal of Membrane Science, Vol. 415 (2012) 250–259.
20
21. Gholami, A., Moghadassi .A.R., Hosseini. S.M., Shabani. S., Gholami, F., “Preparation and characterization of polyvinyl chloride based nanocomposite nanofiltration-membrane modified by iron oxide nanoparticles for lead removal from water”, Journal of Industrial and Engineering Chemistry, Vol. 20, (2013) 1517–1522.
21
22. Han, M. J., Nam, S. T., “Thermodynamic and rheological variation in polysulfone solution by PVP and its effect in the preparation of phase inversion membrane”, Journal of Membrane Science, Vol. 202 (2002) 55–61.
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23. Kim J. H., Lee, K. H., “Effect of PEG additive on membrane formation by phase inversion”, Journal of Membrane Science, Vol. 138 (1998) 153–163.
23
24. Saljoughi, E., Sadrzadeh, M., Mohammadi, T., “Effect of preparation variables on morphology and pure water permeation flux through asymmetric cellulose acetate membranes”, Journal of Membrane Science,Vol. 326 (2009) 627–634.
24
25. Sivakumar, M., Raju Mohan, D., Rangarajan, R., “Studies on cellulose acetate polysulfone ultrafiltration membranes II. Effect of additive concentration”, Journal of Membrane Science, Vol. 268, (2006) 208–219.
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26. Boricha, A.G., Murthy,Z.V.P.,“Preparation of N,O-carboxymethyl chitosan/cellulose acetate blend nanofiltration membrane and testing its performance in treating industrial wastewater”, Chemical Engineering Journal, Vol. 157 (2010) 393–400.
26
27. Vankelecom, I. F. J., De Smet, K., Gevers, L.E.M., Jacobs, P.A., “Nanofiltration membrane materials and preparation, in: A.G. Sch¨ afer, A.G. Fane, T.D. White (Eds.), Nanofiltration, Principles and Applications”, Elsevier, Oxford, Chapter 3., (2005) 33–65.
27
28. Vandezande, P., Gevers, L.E.M., Vankelecom, I.F.J., “Solvent resistant nanofiltra- tion: separating on a molecular level”, Chemal Society Review, Vol. 37, No. 2, (2008) 365–405.
28
29. See-Toh, Y. H., Ferreira, F.C., Livingston, A.G., “The influence of membrane formation parameters on the functional performance of organic solvent nanofiltration membranes”, Journal of Membrane Science, Vol. 299, No. 1, (2007) 236–250.
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30. Ismail, A.F., Hassan, A.R., “Formation and characterization of asymmetric nanofiltration membrane: effect of shear rate and polymer concentration”, Journal of Membrane Science, Vol. 270, No. 1, (2006) 57–72.
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31
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32
33. Hosseini, S. M., Gholami, A., Madaeni, S. S., Moghadassi, A. R., Hamidi, A. R., "Fabrication of (polyvinyl chloride/cellulose acetate) electrodialysis heterogeneous cation exchange membrane: Characterization and performance in desalination process", Desalination, Vol. 306 (2012) 51-59.
33
34. Li, X., Zhu, L., Zhu, B., Xu, Y., “High-flux and anti-fouling cellulose nanofiltration membranes prepared via phase inversion with ionic liquid as solvent”, Separation and Purification Technology, Vol. 83 (2011) 66–73.
34
35. Xu, Y. Z., Lebrun, R.E., “Comparison of nanofiltration properties of two membranes using electrolyte and nonelectrolyte solutes”, Desalination, Vol. 122 (1999) 95–106.
35
36. Fane, A. G., Fell, C. J. D., “A review of fouling and fouling control in ultrafiltration”, Desalination, Vol. 62 (1987) 117–136.
36
ORIGINAL_ARTICLE
Adaptive Neuro-fuzzy Inference System Prediction of Zn Metal Ions Adsorption by γ-Fe2o3/Polyrhodanine Nanocomposite in a Fixed Bed Column
This study investigates the potential of an intelligence model namely, Adaptive Neuro-Fuzzy Inference System (ANFIS) in prediction of the Zn metal ions adsorption in comparision with two well known empirical models included Thomas and Yoon methods. For this purpose, an organic-inorganic core/shell structure, γ-Fe2O3/polyrhodanine nanocomposite with γ-Fe2O3 nanoparticle as core with average diameter of 15 nm and polyrhodanine as shell with thickness of 3 nm, was synthesized via chemical oxidation polymerization. The properties of adsorbent were characterized with transmission electron microscope (TEM) and Fourier transform infrared (FT-IR) spectroscopy. Sixty seven experimental data sets including the treatment time (t), the initial concentration of Zn (Co), column height (h) and flow rate (Q) were used as input data to predict the ratios of effluent-to-influent concentrations of Zn (Ct/C0). The results showed that ANFIS model with the R coefficient of 0.99 can predict Ct/C0 more accurately than empirical models. Also it was found that the result of the Thomas and Yoon methods with R coefficient of 0.828 and 0.829, respectively were so close to each other. Finally, performance of our ANFIS model was compare to Thomas and Yoon methods in two different conditions, i.e. variable initial influent concentration and variable column height. High performance of ANFIS model was proved by the comparitive results.
https://www.ije.ir/article_81693_985373d90ef0eba0ba7591c7172dbc7e.pdf
2018-10-01
1617
1623
10.5829/ije.2018.31.10a.02
adaptive neuro-fuzzy inference system
Adsorption
γ-Fe2O3
Polyrhodanine
Fixed Bed Column
M. S.
Lashkenari
1
Faculty of Engineering Modern Technologies, Amol University of Special Modern Technologies, Amol, Iran
LEAD_AUTHOR
A.
KhazaiePoul
2
Faculty of Water and Envirommental Engineering, Shahid Beheshti University, Tehran, Iran
AUTHOR
S.
Ghasemi
3
Faculty of Chemical, Gas and Petroleum Engineering, Semnan University, Semnan, Iran
AUTHOR
M.
Ghorbani
4
Department of Chemical Engineering, Babol Noshirvani University of Technolgy, Babol, Iran
AUTHOR
1. Monteiro, C.M., Castro, P.M. and Malcata, F.X., Microalga-mediated bioremediation of heavy metal-contaminated surface waters, in Biomanagement of metal-contaminated soils. 2011, Springer.365-385.
1
2. Ghorbani, F., Sanati, A., Younesi, H. and Ghoreyshi, A., "The potential of date-palm leaf ash as low-cost adsorbent for the removal of pb (ii) ion from aqueous solution", International Journal of Engineering-Transactions B: Applications, Vol. 25, No. 4, (2012), 269-278.
2
3. Fenjan, S.A., Bonakdari, H., Gholami, A. and Akhtari, A., "Flow variables prediction using experimental, computational fluid dynamic and artificial neural network models in a sharp bend", International Journal of Engineering-Transactions A: Basics, Vol. 29, No. 1, (2016), 14-22.
3
4. Zareie, C. and Najafpour, G., "Preparation of nanochitosan as an effective sorbent for the removal of copper ions from aqueous solutions", International Journal of Engineering-Transactions B: Applications, Vol. 26, No. 8, (2013), 829-836.
4
5. Afkhami, A., Saber-Tehrani, M. and Bagheri, H., "Modified maghemite nanoparticles as an efficient adsorbent for removing some cationic dyes from aqueous solution", Desalination, Vol. 263, No. 1, (2010), 240-248.
5
6. Rahimpour, A., Seyedpour, S.F., Aghapour Aktij, S., Dadashi Firouzjaei, M., Zirehpour, A., Arabi Shamsabadi, A., Khoshhal Salestan, S., Jabbari, M. and Soroush, M., "Simultaneous improvement of antimicrobial, antifouling, and transport properties of forward osmosis membranes with immobilized highly-compatible polyrhodanine nanoparticles", Environmental Science & Technology, Vol. 52, No. 9, (2018), 5246-5258.
6
7. de Franco, M.A.E., de Carvalho, C.B., Bonetto, M.M., de Pelegrini Soares, R. and Féris, L.A., "Diclofenac removal from water by adsorption using activated carbon in batch mode and fixed-bed column: Isotherms, thermodynamic study and breakthrough curves modeling", Journal of Cleaner Production, Vol. 181, (2018), 145-154.
7
8. Volesky, B. and Holan, Z., "Biosorption of heavy metals", Biotechnology Progress, Vol. 11, No. 3, (1995), 235-250.
8
9. Khalili, R. and Eisazadeh, H., "Preparation and characterization of polyaniline/sb2o3 nanocomposite and its application to removal of pb (іі) from aqueous media", International Journal of Engineering-Transactions B: Applications, Vol. 27, No. 2, (2013), 239-246.
9
10. Safari, A., Hosseini, R. and Mazinani, M., "A novel type-2 adaptive neuro fuzzy inference system classifier for modelling uncertainty in prediction of air pollution disaster (research note)", International Journal of Engineering-Transactions B: Applications, Vol. 30, No. 11, (2017), 1746-1751.
10
11. Yurtsever, U., Yurtsever, M., Şengil, İ.A. and Kıratlı Yılmazçoban, N., "Fast artificial neural network (fann) modeling of cd (ii) ions removal by valonia resin", Desalination and Water Treatment, Vol. 56, No. 1, (2015), 83-96.
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12. Elemen, S., Kumbasar, E.P.A.a. and Yapar, S., "Modeling the adsorption of textile dye on organoclay using an artificial neural network", Dyes and Pigments, Vol. 95, No. 1, (2012), 102-111.
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13. Soetaredjo, F.E., Kurniawan, A., Ong, L., Widagdyo, D.R. and Ismadji, S., "Investigation of the continuous flow sorption of heavy metals in a biomass-packed column: Revisiting the thomas design model for correlation of binary component systems", RSC Advances, Vol. 4, No. 95, (2014), 52856-52870.
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14. Callery, O., Healy, M.G., Rognard, F., Barthelemy, L. and Brennan, R.B., "Evaluating the long-term performance of low-cost adsorbents using small-scale adsorption column experiments", Water Research, Vol. 101, (2016), 429-440.
14
15. Jang, J.S.R., Sun, C.T., Mizutani, E. and Ho, Y., "Neuro-fuzzy and soft computing--a computational approach to learning and machine intelligence", Proceedings of the IEEE, Vol. 86, No. 3, (1998), 600-603.
15
16. Ghasemi, S., Ghorbani, M. and Ghazi, M.M., "Synthesis and characterization of organic–inorganic core–shell structure nanocomposite and application for zn ions removal from aqueous solution in a fixed-bed column", Applied Surface Science, Vol. 359, (2015), 602-608.
16
ORIGINAL_ARTICLE
An Effective Method for Utility Preserving Social Network Graph Anonymization Based on Mathematical Modeling
In recent years, privacy concerns about social network graph data publishing has increased due to the widespread use of such data for research purposes. This paper addresses the problem of identity disclosure risk of a node assuming that the adversary identifies one of its immediate neighbors in the published data. The related anonymity level of a graph is formulated and a mathematical model is proposed to solve the problem. The application of the method on a number of synthetic and real-world datasets confirms that the method is general and can be used in different contexts to produce superior results in terms of the utility of the anonymized graph.
https://www.ije.ir/article_81694_e3849caf4384bbe53aed25f3afd8d93e.pdf
2018-10-01
1624
1632
Mathematical Modeling
graph anonymization
graph modification
social network
Privacy
Database Security
R.
Mortazavi
1
School of Engineering, Damghan University, Damghan, Iran
LEAD_AUTHOR
S. H.
Erfani
2
School of Engineering, Damghan University, Damghan, Iran
AUTHOR
1. Asadi Saeed Abad, F. and Hamidi, H., "An Architecture for Security and Protection of Big Data", International Journal of Engineering, Vol. 30, No. 10, (2017), 1479-1486.
1
2. Hemati, H., Ghasemzadeh, M. and Meinel, C., "A Hybrid Machine Learning Method for Intrusion Detection", International Journal of Engineering, Transactions C: Aspects, Vol. 29, No. 9, (2016), 1242-1246.
2
3. Sharma, P. and Kaur, P. D., "Effectiveness of web-based social sensing in health information dissemination-A review", Telematics and Informatics, Vol. 34, No. 1, (2017), 194–219.
3
4. Feder, T., Nabar, S. U. and Terzi, E., "Anonymizing graphs",CoRR, abs/0810.5578, (2008).
4
5. Casas-Roma, J., Herrera-Joancomartí, J. and Torra, V., "k-Degree anonymity and edge selection: improving data utility in large networks", Knowledge and Information Systems, Vol. 50, No. 2, (2017), 447–474.
5
6. Sweeney, L., "k-anonymity: A model for protecting privacy", International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 10, No. 5, (2002), 557–570.
6
7. Mortazavi, R. and Jalili, S., "Enhancing aggregation phase of microaggregation methods for interval disclosure risk minimization", Data Mining and Knowledge Discovery, Vol. 30, No. 3, (2016), 605–639.
7
8. Salari, M., Jalili, S. and Mortazavi, R., "TBM, a transformation based method for microaggregation of large volume mixed data", Data Mining and Knowledge Discovery, Vol. 31, No. 1, (2017), 65–91.
8
9. Machanavajjhala, A., Kifer, D., Gehrke, J. and Venkitasubramaniam, M., "L-diversity: Privacy beyond k-anonymity", ACM Transaction on Knowledge Discovery from Data (TKDD), Vol. 1, No. 1, (2007), 1–52.
9
10. Ying, X. and Wu, X., "Randomizing social networks: a spectrum preserving approach", in Proceedings of the 2008 SIAM International Conference on Data Mining, SIAM, (2008), 739–750.
10
11. Liu, K. and Terzi, E., "Towards identity anonymization on graphs", in Proceedings of the 2008 ACM SIGMOD international conference on Management of data, ACM, (2008), 93–106.
11
12. Stokes, K. and Torra, V., "Reidentification and k-anonymity: A model for disclosure risk in graphs", Soft Computing, Vol. 16, No. 10, (2012), 1657–1670.
12
13. Ninggal, M. I. H. and Abawajy, J. H., "Utility-aware social network graph anonymization", Journal of Network and Computer Applications, Vol. 56, (2015), 137–148.
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14. Floyd, R. W., "Algorithm 97: Shortest Path", Communications of the ACM, Vol. 5, No. 6, (June 1962), 345. doi>10.1145/367766.368168
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15. Hadian, A. and Nobari, S., Minaei-Bidgoli, B., Qu, Q., "Roll: Fast in-memory generation of gigantic scale-free networks", in Proceedings of the 2016 International Conference on Management of Data, SIGMOD ’16, ACM, New York, NY, USA, (2016), 1829–1842.
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16. Girvan, M. and Newman, M. E., "Community structure in social and biological networks", in Proceedings of the national academy of sciences, Vol. 99, No. 12, (2002), 7821–7826.
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17. Watts, D. J. and Strogatz, S. H., "Collective dynamics of ‘small-world’ networks", Nature, Vol. 393, No. 6684, (1998), 440-442.
17
18. Mohammadi, A. and Hamidi, H., "Analysis and evaluation of privacy protection behavior and information disclosure concerns in online social networks", International Journal of Engineering, Vol. 31, No. 8, (2018), 1234-1239.
18
ORIGINAL_ARTICLE
Study and Analysis of A Simple Self Cascode Regulated Cascode Amplifier
This article proposed a simple self cascode RGC amplifier configuration to increase the gain and bandwidth. The cascode amplifier eliminates the miller capacitance between input and output and facilitates high gain, high input and output impedance with high bandwidth. However, the cascode amplifier requires relatively high supply voltage for proper operation and it decreases the output voltage swing by overdrive voltage. These issues are overcome by self cascode based RGC amplifier; even though it has low bandwidth due to the presence of one of its pole at low frequency. The bandwidth and output impedance of the conventional RGC has increased using a split length compensation technique. To improve the overall performance of the amplifier, introduced a simple self cascode RGC without using additional passive elements. The expression of gain and output impedance for the proposed amplifier is derived using small signal analysis. The calculated value of voltage gain for the projected circuit is 58.37 dB which is more than the self cascode based RGC. The power dissipation of the proposed circuit is 1.07 µWatt and it was compared with CS, cascode, self cascode and SC based cascode, RGC, SC based RGC amplifiers.
https://www.ije.ir/article_82196_23b7156e8ce0a9128f6b62fb23a4113c.pdf
2018-10-01
1633
1641
10.5829/ije.2018.31.10a.04
Self cascode
Regulated cascode
self cascode based regulated cascode
simple self cascode Regulated Cascode
P.
Karuppanan
1
Department of Electronics and Communication Engineering, Motilal Nehru National Institute of Technology Allahabad, India
LEAD_AUTHOR
K.
Anuradha
2
Department of Electronics and Communication Engineering, Motilal Nehru National Institute of Technology Allahabad, India
AUTHOR
1. Zhao, X., Zhang, Q., Wang, Y. and Deng, M., “Transconductance and slew rate improvement technique for current recycling folded cascode amplifier”, AEU - International Journal of Electronics and Communications, Vol. 70, No. 3, (2016), 326–330.
1
2 Zhao, C., Liu, J., Shen, F. and Yi, Y., “Low power CMOS power amplifier design for RFID and the Internet of Things”, Computers & Electrical Engineering, Vol. 52, (2016), 157–170.
2
3. Zhao, X., Fang, H., Ling, T. and Xu, J., “Low-voltage process-insensitive frequency compensation method for two-stage OTA with enhanced DC gain”, AEU - International Journal of Electronics and Communications, Vol. 69, No. 3, (2015), 685–690.
3
4. Wang, J., Zhu, Z., Liu, S. and Ding, R., “A low-noise programmable gain amplifier with fully balanced differential difference amplifier and class-AB output stage”, Microelectronics Journal, Vol. 64, (2017), 86–91.
4
5. Comer, D.J., Comer, D.T. and Petrie, C.S., “The utility of the composite cascode in analog CMOS design”, International Journal of Electronics, Vol. 91, No. 8, (2004), 491–502.
5
6. Prodanov, V.I. and Green, M.M., “CMOS current mirrors with reduced input and output voltage requirements”, Electronics Letters, Vol. 32, No. 2, (1996), 104–105.
6
7. Aghnout, S. and Masoumi, N., “Modeling of Substrate Noise Impact on a Single-Ended Cascode LNA in a Lightly Doped Substrate (RESEARCH NOTE)”, International Journal of Engineering - Transactions A: Basics, Vol. 23, No. 1, (2009), 23–28.
7
8. Raj, N., Singh, A.K. and Gupta, A.K., “Low voltage high performance bulk driven quasi-floating gate based self-biased cascode current mirror”, Microelectronics Journal, Vol. 52, (2016), 124–133.
8
9. Sedaghat, S.B., Karimi, G. and Banitalebi, R., “A Low Voltage Full-band Folded Cascoded UWB LNA with Feedback Topology”, International Journal of Engineering - Transactions A: Basics, Vol. 28, No. 1, (2014), 66–73.
9
10. Kaur, J., Prakash, N. and Rajput, S.S., “A Low Voltage High Performance Self Cascode Current Mirror”, International Journal of Electronics and communication Engineering, Vol. 02, No. 5, (2008), 1017–1020.
10
11. Galal, A.I.A., Pokharel, R., Kanaya, H. and Yoshida, K., “High linearity technique for ultra-wideband low noise amplifier in 0.18 μm CMOS technology”, AEU - International Journal of Electronics and Communications, Vol. 66, No. 1, (2012), 12–17.
11
12. Chen, C. L., Hsieh, W. L., Lai, W. J., Chen, K. H. and Wang, C. S., “A high-speed and precise current sensing circuit with bulk control (CCB) technique”, 15th IEEE International Conference on Electronics, Circuits and Systems, IEEE, (2008), 283–287.
12
13. Kundra, S., Soni, P. and Kundra, A., “Low power folded cascode OTA”, International Journal of VLSI design & Communication Systems, Vol. 3, No. 1, (2012), 127–136.
13
14. Shekhar, S., Walling, J.S. and Allstot, D.J., “Bandwidth Extension Techniques for CMOS Amplifiers”, IEEE Journal of Solid-State Circuits, Vol. 41, No. 11, (2006), 2424–2439.
14
ORIGINAL_ARTICLE
Detecting Fake Websites Using Swarm Intelligence Mechanism in Human Learning
The internet and its various services have made users to easily communicate with each other. Internet benefits including online business and e-commerce. E-commerce has boosted online sales and online auction types. Despite their many uses and benefits, the internet and their services have various challenges, such as information theft, which challenges the use of these services. Information theft or phishing attacks are internet attacks that are major approach to success it is social engineering that the phisher has used. In these types of attacks, the attacker deceives the users and steals their valuable information by using a fake website that looks like real websites. The damage caused by fake websites and phishing attacks is so high that researchers are trying to identify these types of websites in different ways. So far, various methods have been developed to identify phishing web sites which most of them based on data- mining and learning machine are trying to identify these malicious websites. Artificial neural network is a data-mining method for identifying phishing websites which is used in most studies; however the error rate of this can be significant in detecting these websites, so learning-based optimization algorithm is used as a Swarm intelligence algorithm to reduce its error. In the proposed method, the error rate of multi-layer artificial neural network in detecting phishing websites is considered as a target function which minimized by using learning-based optimization algorithm. In the proposed method, learning- based optimization algorithm selects weights and bias of multi-layer artificial neural network optimally to minimize the error of clssification as an objective function. The datasets used to evaluate the proposed method are Phishing Websites explaind by others. The results of evaluating phishing attack dataset indicate that the rate of error of fake website detection in the proposed method is constantly reduced by repetition. The results of our assessment also indicate that the average accuracy, sensitivity, specificity, precision of the proposed method are 93.42, 92.27, 93.19 and 92.78%, respectively. The decision tree and regression are more accurate in detecting fake websites than artificial neural network.
https://www.ije.ir/article_82197_b296a320487dffdabd86d466f9fb2665.pdf
2018-10-01
1642
1650
Fake Websites
Phishing Attacks
Artificial Neural Network
Swarm Intelligence Algorithm
Learning based Optimization Algorithm
F.
Parandeh Motlagh
1
Department of Computer Engineering, Kerman branch, Islamic Azad University, Kerman, Iran
LEAD_AUTHOR
A.
Khatibi Bardsiri
2
Department of Computer Engineering, Bardsir branch, Islamic Azad University, Bardsir, Iran
AUTHOR
1. Cotten, S.R., Ford, G., Ford, S. and Hale, T.M., "Internet use and depression among older adults", Computers in Human Behavior, Vol. 28, No. 2, (2012), 496-499.
1
2. Tsang, S., Koh, Y.S., Dobbie, G. and Alam, S., "Detecting online auction shilling frauds using supervised learning", Expert Systems with Applications, Vol. 41, No. 6, (2014), 3027-3040.
2
3. Derouet, E., "Fighting phishing and securing data with email authentication", Computer Fraud & Security, Vol. 2016, No. 10, (2016), 5-8.
3
4. Krombholz, K., Hobel, H., Huber, M. and Weippl, E., "Advanced social engineering attacks", Journal of Information Security and applications, Vol. 22, (2015), 113-122.
4
5. Chawla, M. and Chouhan, S.S., "A survey of phishing attack techniques", International Journal of Computer Applications, Vol. 93, No. 3, (2014).
5
6. Basnet, R.B., Sung, A.H. and Liu, Q., "Feature selection for improved phishing detection", in International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, Springer., (2012), 252-261.
6
7. James, L., "Phishing exposed, Elsevier, (2005).
7
8. May, O.A.D., "23, 2011 from the us patent and trademark office re", US Applied, No. 11/980,690.
8
9. Qi, M. and Yang, C., "Research and design of phishing alarm system at client terminal", in Services Computing, 2006. APSCC'06. IEEE Asia-Pacific Conference on, IEEE., (2006), 597-600.
9
10. Kirda, E. and Kruegel, C., "Protecting users against phishing attacks with antiphish", in Computer Software and Applications Conference, 2005. COMPSAC 2005. 29th Annual International, IEEE. Vol. 1, (2005), 517-524.
10
11. Zhang, Y., Hong, J.I. and Cranor, L.F., "Cantina: A content-based approach to detecting phishing web sites", in Proceedings of the 16th international conference on World Wide Web, ACM. (2007), 639-648.
11
12. Intelligence, M., "Annual security report", Symantec Corp, (2010), http://www.symantec.com/connect/blogs/messagelabsintelligence-annual-security-report-2009-security-yearreview.
12
13. Mohammad, R.M., Thabtah, F. and McCluskey, L., "Tutorial and critical analysis of phishing websites methods", Computer Science Review, Vol. 17, (2015), 1-24.
13
14. Iuga, C., Nurse, J.R. and Erola, A., "Baiting the hook: Factors impacting susceptibility to phishing attacks", Human-centric Computing and Information Sciences, Vol. 6, No. 1, (2016), 8.
14
15. Jain, A.K. and Gupta, B.B., "Phishing detection: Analysis of visual similarity based approaches", Security and Communication Networks, Vol. 2017, No., (2017).
15
16. Khonji, M., Iraqi, Y. and Jones, A., "Phishing detection: A literature survey", IEEE Communications Surveys & Tutorials, Vol. 15, No. 4, (2013), 2091-2121.
16
17. Rao, R.V., Savsani, V.J. and Vakharia, D., "Teaching–learning-based optimization: An optimization method for continuous non-linear large scale problems", Information Sciences, Vol. 183, No. 1, (2012), 1-15.
17
18. Mohammad, R., Thabtah, F.A. and McCluskey, T., "Phishing websites dataset", (2015).
18
ORIGINAL_ARTICLE
A Hierarchy Topology Design Using a Hybrid Evolutionary Algorithm in Wireless Sensor Networks
Wireless sensor network a powerful network contains many wireless sensors with limited power resource, data processing, and transmission abilities. Wireless sensor capabilities including computational capacity, radio power, and memory capabilities are much limited. Moreover, to design a hierarchy topology, in addition to energy optimization, find an optimum clusters number and best location of cluster heads are two important issues. Many routing protocols are introduced to discover the optimal routes in order to remove intermediate nodes to reduce the sensors energy consumption. Therefore, for energy consumption optimization in a network, routing protocols and clustering techniques along with composition and aggregation of data are provided. In this paper, to design a hierarchy topology, a hybrid evolutionary approach, a combination of genetic and imperialist competition algorithms is applied. First, the genetic algorithm is applied to achieve an optimal clusters number where all effective network parameters are taken in into account. Aftermath, the optimal positions of cluster heads inside every cluster are calculated utilizing the imperialist approach. Our results show a significant increment in the network lifetime, lower data-packet lost, higher robust routing compared with standard LEACH and the ICA based LEACH.
https://www.ije.ir/article_82198_155bef875131ddf8174ea724dc234749.pdf
2018-10-01
1651
1658
Wireless Sensor Networks
LEACH Algorithm
Genetic Algorithm
Imperialist Competitive Algorithm
Network Lifetime
S. M.
Hosseinirad
1
Department of Computer Engineering & IT, Payam Noor University (PNU), Tehran, Iran
LEAD_AUTHOR
Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E., “Wireless sensor networks: a survey”, Journal of Computer Networks, Vol. 38 (2002), 393–422.
1
Arampatzis, T., Lygeros, J., Manesis, S., “A survey of applications of wireless sensors and wireless sensor networks”, the 2005 IEEE International Symposium on Mediterrean Conference on Control and Automation 2005, 719-724.
2
Sharma, S., Kumar, R., Machine, B., “Issues and Challenges in Wireless Sensor Networks”, International Conference on Intelligence and Research Advancement (ICMIRA) 2013, India.
3
Anastasi, G., Conti, M., Di Francesco, M., Passarella, A., “Energy conservation in wireless sensor networks: A survey,” Journal of Ad-Hoc networks, Vol. 7 (2009), 537-568.
4
Dargie, W., Poellabauer, C., “Fundamentals of Wireless Sensor Networks: Theory and Practice”, Wiley Black well (2010).
5
C. Zhua, C. Zhenga, L.Shuc, G. Hana, "A survey on coverage and connectivity issues in wireless sensor networks", Journal of Network and Computer Applications, Vol. 35 (2012), 619–632.
6
N. Enami, N. M. Charkari, and K. D. Ahmadi, “Intelligent clustering for balanced energy consumption in wireless sensor networks”, Journal of International Journal Advanced Computer Technology, Vol. 3, No. 2 (2011) 60-70.
7
Akkaya, K., Younis, M., “A survey on routing protocols for wireless sensor networks”, Journal ofAd-Hoc networks, Vol. 3 (2005), 325–349.
8
Asorey-Cachedaa, R., Garcia-Sanchezb, A.J., Garcia-Sanchezb, F., Garcia-Harob, J., “A survey on non-linear optimization problems in wireless sensor networks”, Journal of Network and Computer Applications, Vol. 82 (2017), 1–20.
9
Hruschka, E.R., Ricardo, J.G.B., Freitas, A.A., “A Survey of Evolutionary Algorithms for Clustering”, Journal of IEEE Transactions on Systems, Vol. 39 (2009), 133-155.
10
Shah, R.C., Rabaey, J.M., “Energy aware routing for low energy ad hoc sensor networks”, Wireless Communications and Networking Conference, WCNC (2002), Vol. 1, 350-355.
11
Arjunan, S., Pothula, S., “A survey on unequal clustering protocols in Wireless Sensor Networks”, Journal of Computer and Information Sciences, Vol. 31 (2017).
12
Karaboga, D., Okdem, S., Ozturk, C., “Cluster based wireless sensor network routing using artificial bee colony algorithm,” Journal of Wireless Networks, Vol. 18 (2012), 847-860.
13
Vaidyanathan, S., Vaidyanathan, M., “Wireless Sensor Networks-Issues & Challenges”, Journal of Information Systems: Behavioral & Social Methods, 2011, 7-12.
14
Boyinbode, O., Le, H., Mbogho A., “A Survey on Clustering Algorithms for Wireless Sensor Networks”, 13th International Conference on Network-Based Information Systems (NBiS) 2010, Japan.
15
Ye, M., Li, C., Chen G., Wu, J., “An Energy Efficient Clustering Scheme in Wireless Sensor Networks”, Ad-Hoc & Sensor Wireless Networks, , Vol.1 (2006), 1-21.
16
Kaur, S., Naaz Mir, R., “Clustering in Wireless Sensor Networks- A Survey”, International Journal of Computer Network and Information Security, Vol. 6 (2016), 38-51.
17
Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H., “Energy-efficient communication protocol for wireless microsensor networks”, the 33rd IEEE Annual Hawaii International Conference on in System Sciences, Vol. 2 (2000), 10 -16.
18
Rahmanian, A., Omranpour, H., Akbari, M., “A novel Genetic Algorithm in LEACH-C routing protocol for sensor networks”, 24th Canadian Conference on Electrical and Computer Engineering (CCECE) 2011, Canada.
19
Younis, O., Fahmy, S., “HEED: A Hybrid Energy-Efficient Distributed Clustering Approach for Ad Hoc Sensor Networks”, Journal of IEEE Transactions on Mobile Computing, Vol. 3 (2004), No. 4, 366-379.
20
Hosseinirad, S.M., Basu, S.K., “Wireless sensor network design through Genetic Algorithm”, Journal of AI and Data Mining, Vol. 2 (2014), No. 1, 85-96.
21
Hosseinirad, S.M., Alimohammadi, M., Basu, S.K., Pouyan, A.A., “LEACH Routing Algorithm Optimization through Imperialist Approach” International Journal of EngineeringTransaction A: Basics, Vol. 27 (2013), No. 1, 39-50.
22
Haupt, R.L., Haupt, S.E., “Practical Genetic Algorithms”, John Wiley & Sons, 2004.
23
Karaboga, D., Okdem, S., Ozturk, C.,“Cluster based wireless sensor network routing using artificial bee colony algorithm”, Journal of Wireless Networks, Vol. 18 (2012), No. 7, 847-860.
24
Blum, C., Li, X., “Swarm intelligence in optimization”, Springer, 2008.
25
Hussain, S., Matin, A.W., Islam, O., “Genetic Algorithm for hierarchical wireless sensor networks,” Journal of Networks, Vol. 2 (2007), No. 5, 87-97.
26
ORIGINAL_ARTICLE
A Secure Routing Algorithm for Underwater Wireless Sensor Networks
Recently, underwater Wireless Sensor Networks (UWSNs) attracted the interest of many researchers and the past three decades have held the rapid progress of underwater acoustic communication. One of the major problems in UWSNs is how to transfer data from the mobile node to the base stations and choosing the optimized route for data transmission. Secure routing in UWSNs is necessary for packet delivery. A few researches have been done on secure routing in UWSNs. In this article, a new secure routing algorithm called Secure Routing Algorithm for Underwater (SRAU) sensor networks is proposed to resist against wormhole and sybil attacks. The results indicate acceptable performance in terms of increasing the packet delivery ratio regarding the wormhole and sybil attacks, increasing network lifetime through balancing the network energy consumption, high detection rates against the attacks, and decreasing the end to end delay.
https://www.ije.ir/article_82199_163224471ef734162100ab90ffd38865.pdf
2018-10-01
1659
1665
Underwater wireless sensor networks
Security
routing
wormhole and sybil attacks
M.
Ahmadi
1
Department of Computer Engineering, Karaj Branch, Islamic Azad University, Karaj, Iran
AUTHOR
S. M.
Jameii
2
Department of Computer Engineering, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
LEAD_AUTHOR
1. Ribeiro, F.J.L., Pedroza, A.d.C.P. and Costa, L.H.M.K., "Underwater monitoring system for oil exploration using acoustic sensor networks", Telecommunication Systems, Vol. 58, No. 1, (2015), 91-106.
1
2. Li, X., Han, G., Qian, A., Shu, L. and Rodrigues, J., "Detecting sybil attack based on state information in underwater wireless sensor networks", in Software, Telecommunications and Computer Networks (SoftCOM), 2013 21st International Conference on, IEEE., (2013), 1-5.
2
3. Du, X., Peng, C. and Li, K., "A secure routing scheme for underwater acoustic networks", International Journal of Distributed Sensor Networks, Vol. 13, No. 6, (2017), doi: 10.1177/1550147717713643.
3
4. Bharamagoudra, M.R. and Manvi, S.S., "Agent‐based secure routing for underwater acoustic sensor networks", International Journal of Communication Systems, Vol. 30, No. 13, (2017), e3281.
4
5. Dargahi, T., Javadi, H.H. and Shafiei, H., "Securing underwater sensor networks against routing attacks", Wireless Personal Communications, Vol. 96, No. 2, (2017), 2585-2602.
5
6. Ateniese, G., Capossele, A., Gjanci, P., Petrioli, C. and Spaccini, D., "Secfun: Security framework for underwater acoustic sensor networks", in Proceedings of MTS/IEEE OCEANS. (2015), 1-9.
6
7. Basagni, S., Petrioli, C., Petroccia, R. and Spaccini, D., "Carp: A channel-aware routing protocol for underwater acoustic wireless networks", Ad Hoc Networks, Vol. 34, (2015), 92-104.
7
8. Gomathi, R. and Manickam, J.M.L., "Energy efficient shortest path routing protocol for underwater acoustic wireless sensor network", Wireless Personal Communications, Vol. 98, No. 1, (2018), 843-856.
8
9. Bu, R., Wang, S. and Wang, H., "Fuzzy logic vector–based forwarding routing protocol for underwater acoustic sensor networks", Transactions on Emerging Telecommunications Technologies, Vol. 29, No. 3, (2018), doi: 10.1002/ett.3252.
9
10. Taghizadeh, S. and Mohammadi, S., "Lebrp-a lightweight and energy balancing routing protocol for energy-constrained wireless ad hoc networks", International Journal of Engineering-Transactions A: Basics, Vol. 27, No. 1, (2013), 33-38.
10
11. Pouyan, A. and Yadollahzadeh Tabari, M., "Estimating reliability in mobile ad-hoc networks based on monte carlo simulation", International Journal of Engineering, Vol. 7, No. 5, (2014), 739-746.
11
12. Zhang, R., Sun, J., Zhang, Y. and Huang, X., "Jamming-resilient secure neighbor discovery in mobile ad hoc networks", IEEE Trans. Wireless Communications, Vol. 14, No. 10, (2015), 5588-5601.
12
13. Zhang, Y., Liu, W., Lou, W. and Fang, Y., "Location-based compromise-tolerant security mechanisms for wireless sensor networks", IEEE Journal on Selected Areas in Communications, Vol. 24, No. 2, (2006), 247-260.
13
14. Heinzelman, W.R., Chandrakasan, A. and Balakrishnan, H., "Energy-efficient communication protocol for wireless microsensor networks", in System sciences, 2000. Proceedings of the 33rd annual Hawaii international conference on, IEEE., (2000), doi: 10.1109/HICSS.2000.926982.
14
ORIGINAL_ARTICLE
A New High Frequency Grid Impedance Estimation Technique for the Frequency Range of 2 to150 kHz
Grid impedance estimation is used in many power system applications such as grid connected renewable energy systems and power quality analysis of smart grids. The grid impedance estimation techniques based on signal injection uses Ohm’s law for the estimation. In these methods, one or several signal(s) is (are) injected to Point of Common Coupling (PCC). Then the current through and voltage of PCC are measured. Finally, the impedance is assumed as ratio of voltage to current signals in frequency domain. In a noisy system, energy of the injected signal must be sufficient for an accurate approximation. However, power quality issues and regulations limit the energy and the voltage levels of the injected signal. There are three main issues in impedance estimation using signal injection: I) Power quality of grid, II) frequency range of estimation, and finally III) accuracy of estimation. In this paper, the stationary wavelet denoising algorithm is employed instead of increasing the energy of injection signal(s). In the paper, a novel method is proposed for impedance estimation based on selecting several appropriate injection signals and denoising the measured signals. The proposed method is able to impedance estimation in a wide frequency range without any effect on power quality. Finally, simulation results have been carried out to validate the proposed method.
https://www.ije.ir/article_82200_c5dc428f4a77be6c2f0c62e5d970a0c4.pdf
2018-10-01
1666
1674
Impedance Estimation
Frequency Response
Discrete Fourier Transform
Power quality
smart grids
M. M.
AlyanNezhadi
alyan.nezhadi@gmail.com
1
Image Processing and Data Mining Lab, Shahrood University of Technology, Shahrood, Iran
LEAD_AUTHOR
H.
Hassanpour
2
Image Processing and Data Mining Lab, Shahrood University of Technology, Shahrood, Iran
AUTHOR
F.
Zare
f.zare@qut.edu.au
3
Power Engineering Group, University of Queensland, Queensland, Australia
AUTHOR
1. Davari, P., Hoene, E., Zare, F., and Blaabjerg, F., “Improving 9-150 kHz EMI Performance of Single-Phase PFC Rectifier”, In Cips 2018 - 10th International Conference on Integrated Power Electronics Systems, VDE-VERLAG, (2018).
1
2. AlyanNezhadi, M.M., Zare, F., and Hassanpour, H., “Passive grid impedance estimation using several short-term low power signal injections”, In 2nd International Conference of Signal Processing and Intelligent Systems (ICSPIS), IEEE, (2016), 1–5.
2
3. Ciobotaru, M., Agelidis, V.G., Teodorescu, R., and Blaabjerg, F., “Accurate and Less-Disturbing Active Antiislanding Method Based on PLL for Grid-Connected Converters”, IEEE Transactions on Power Electronics, Vol. 25, No. 6, (2010), 1576–1584.
3
4. Asiminoaei, L., Teodorescu, R., Blaabjerg, F., and Borup, U., “A Digital Controlled PV-Inverter With Grid Impedance Estimation for ENS Detection”, IEEE Transactions on Power Electronics, Vol. 20, No. 6, (2005), 1480–1490.
4
5. Ciobotaru, M., Teodorescu, R., and Blaabjerg, F., “On-line grid impedance estimation based on harmonic injection for grid-connected PV inverter”, In IEEE International Symposium on Industrial Electronics, IEEE, (2007), 2437–2442.
5
6. Cespedes, M., and Sun, J., “Adaptive Control of Grid-Connected Inverters Based on Online Grid Impedance Measurements”, IEEE Transactions on Sustainable Energy, Vol. 5, No. 2, (2014), 516–523.
6
7. Tarkiainen, A., Pollanen, R., Niemela, M., and Pyrhonen, J., “Identification of Grid Impedance for Purposes of Voltage Feedback Active Filtering”, IEEE Power Electronics Letters, Vol. 2, No. 1, (2004), 6–10.
7
8. Das, J.C., “Passive Filters—Potentialities and Limitations”, IEEE Transactions on Industry Applications, Vol. 40, No. 1, (2004), 232–241.
8
9. Zadehbagheri, M., Ildarabadi, R., and Baghaeinejad, M., “A Novel Method for Modeling and Simulation of Asymmetrical Impedance-source Converters”, International Journal of Engineering - Transactions B: Applications, Vol. 31, No. 5, (2018), 741–751.
9
10. Familiant, Y.L., Corzine, K.A., Huang, J., and Belkhayat, M., “AC Impedance Measurement Techniques”, In IEEE International Conference on Electric Machines and Drives, IEEE, (2005), 1850–1857.
10
11. Czarnecki, L.S., and Staroszczyk, Z., “Dynamic on-line measurement of equivalent parameters of three-phase systems for harmonic frequencies”, European Transactions on Electrical Power, Vol. 6, No. 5, (2008), 329–336.
11
12. Roinila, T., Vilkko, M., and Sun J., “Online Grid Impedance Measurement Using Discrete-Interval Binary Sequence Injection”, IEEE Journal of Emerging and Selected Topics in Power Electronics, Vol. 2, No. 4, (2014), 985–993.
12
13. Shen, Z., Jaksic, M., Mattavelli, P., Boroyevich, D., Verhulst, J., and Belkhayat, M., “Three-phase AC system impedance measurement unit (IMU) using chirp signal injection”, In Twenty-Eighth Annual IEEE Applied Power Electronics Conference and Exposition (APEC), IEEE, (2013), 2666–2673.
13
14. Ciobotaru, M., Agelidis, V., and Teodorescu, R., “Line impedance estimation using model based identification technique”, In Proceedings of the 2011 14th European Conference on Power Electronics and Applications, IEEE, (2011), 1–9.
14
15. Staroszczyk, Z., “A Method for Real-Time, Wide-Band Identification of the Source Impedance in Power Systems”, IEEE Transactions on Instrumentation and Measurement, Vol. 54, No. 1, (2005), 377–385.
15
16. Roinila, T., Vilkko, M., and Sun, J., “Broadband methods for online grid impedance measurement”, In IEEE Energy Conversion Congress and Exposition, IEEE, (2013), 3003–3010.
16
17. AlyanNezhadi, M.M., Zare, F., and Hassanpour, H., “Grid Impedance Estimation using Several Short-term Low Power Signal Injections”, AUT Journal of Electrical Engineering, (2017), DOI: 10.22060/EEJ.2017.12501.5091.
17
18. Davari, P., Ghasemi, N., Zare, F., O’Shea, P., and Ghosh, A., “Improving the efficiency of high power piezoelectric transducers for industrial applications”, IET Science, Measurement & Technology, Vol. 06, No. 4, (2012), 213–221.
18
19. Schottke, S., Rademacher, S., Meyer, J., and Schegner, P., “Transfer characteristic of a MV/LV transformer in the frequency range between 2 kHz and 150 kHz”, In IEEE International Symposium on Electromagnetic Compatibility (EMC), IEEE, (2015), 114–119.
19
20. Zare, F., Soltani, H., Kumar, D., Davari, P., Delpino, H.A.M., and Blaabjerg, F., “Harmonic Emissions of Three-Phase Diode Rectifiers in Distribution Networks”, IEEE Access, Vol. 5, (2017), 2819–2833.
20
21. Heirman, D., “EMC standards activity”, IEEE Electromagnetic Compatibility Magazine, Vol. 3, No. 2, (2014), 100–103.
21
22. Ye J., Zhang Z., Shen A., Xu J., and Wu F., “Kalman filter based grid impedance estimating for harmonic order scheduling method of active power filter with output LCL filter”, In International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), IEEE, (2016), 359–364.
22
23. Herong G., Guo, X., Deyu W., and Wu, W., “Real-time grid impedance estimation technique for grid-connected power converters”, In IEEE International Symposium on Industrial Electronics, IEEE, (2012), 1621–1626.
23
24. Eidson, B.L., Geiger, D.L., and Halpin, M., “Equivalent power system impedance estimation using voltage and current measurements”, In Clemson University Power Systems Conference, IEEE, (2014), 1–6.
24
25. Khoshnood, A.M., Khaksari, H., Roshanian J., and Hasani, S.M., “Active Noise Cancellation using Online Wavelet Based Control System: Numerical and Experimental Study”, International Journal of Engineering - Transactions A: Basics, Vol. 30, No. 1, (2017), 120–126.
25
26. Whitley, D., “An executable model of a simple genetic algorithm”, Foundations of Genetic Algorithms, Vol. 02, (1993), 45–62.
26
27. Genlin, J., “Survey on genetic algorithm [J]”, Computer Applications and Software, Vol. 02, (2004), 69–73.
27
28. AlyanNezhadi, M.M., Hassanpour, H., and Zare, F., “Grid impedance estimation using low power signal injection in noisy measurement condition based on wavelet denoising”, In 3rd Iranian Conference on Intelligent Systems and Signal Processing (ICSPIS), IEEE, (2017), 81–86.
28
29. Ghoudjehbaklou, H., and Danaei, M.M., “A New Algorithm for Optimum Voltage and Reactive Power Control for Minimizing Transmission Lines Losses”, International Journal of Engineering - Transaction B: Applications, Vol. 14, No. 2, (2001), 91–98.
29
30. Allehyani, A.K., and Beshir, M.J., “Overhead and underground distribution systems impact on electric vehicles charging”, Journal of Clean Energy Technologies, Vol. 04, No. 2, (2016), 125–128.
30
ORIGINAL_ARTICLE
FPGA-based of Thermogram Enhancement Algorithm for Non-destructive Thermal Characterization
Thermal imaging technology is used to translate thermal energy or heat into visible light for analyzing the sample images known as a thermogram. It has numerous applications such as for surveillance, medical diagnosis, and other industry which requires a non-contact temperature measurement, etc. The image results of this proposed algorithm show more visible features in terms of the separation between the sampled object and its background. The extraction process used the integrated Otsu method and the high-value thermal algorithm. The color mapping process helps to highlight the necessary characteristics of the sampled thermal images. This work is synthesized using Xilinx Zync 7000 ZED ZC702. The experimental results extracted more significant features and characteristics of the sampled image. In addition, the proposed algorithm shows a faster processing time and minimizes the resource utilization compared with the other methods.
https://www.ije.ir/article_82201_e216b1cbacd7167e50548e103a5da62e.pdf
2018-10-01
1675
1681
Digital Images
Infrared Thermography
Imaging Analysis
Image Segmentation
Thermal Factors
H. S.
Kim
1
Department of Electronic Engineering, Cheongju University, Cheongju, South Korea
LEAD_AUTHOR
1. Endres, F., Hess J., and Sturm, J. “3-D Mapping with an RGB-D Camera”, IEEE Transactions on Robotics, Vol. 30, No. 1, (2014), 177-187.
1
2. Balageas D.L., Deom A.A., Boscher D.M., “Characterization and nondestructive testing of carbon-epoxy composites by a pulsed photothermal method”, Materials Evaluation Vol. 45, (1987), 465–466.
2
3. Maldague X., “Theory and Practice of Infrared Technology for Nondestructive Testing”, Wiley-Interscience Publication, John Wiley & Sons Inc (2001).
3
4. Lhota J.R., Shepard S.M., Rubadeux B.A., Ahmed T., “Enhanced Spatial and Depth Resolution of Pulsed Thermographic Images”, Review of Progress in Quantitative Nondestructive Evaluation 20A, (2000), 492-498.
4
5. Kumar, S. and Mahto D., “Recent Trends in Industrial and Other Engineering Applications of Non-Destructive Testing: A Review”, International Journal of Scientific and Engineering Research, Vol. 4, No. 9, (2013), 183-195.
5
6. Dua, G. and Mulaveesala R., “Aperiodic Thermal Wave Imaging Approach for Non-Destructive Testing and Evaluation of Steel Material: A Numerical Study”, Journal of Nanoengineering and Nanomanufacturing, Vol. 6, No. 4, 265-269, 2016.
6
7. Mulaveesala R., and Tuli S., “Digitized frequency modulated thermal wave imaging for non-destructive Testing”, Materials Evaluation, Vol. 63, (2005), 1046-50.
7
8. Mulaveesala R., and Ghali V.S., “Coded excitation for infrared non-destructive testing of carbon fiber reinforced plastics”, Review of Scientific Instruments Vol. 82, No. 5 (2011): 054902.
8
9. Ghali V. S., and Mulaveesala R., “Quadratic frequency modulated thermal wave imaging for non- destructive testing”, Progress In Electromagnetics Research, Vol 26 (2012), 11-22.
9
10. Zhou, Z., Malone E., Sato dos Santos G., Li N., Xu H., and Holder D., “Comparison of Different Quadratic Regularization for Electrical Impedance Tomography,” Proc. of 6th Conference of the International Federation for Medical and Biological Engineering, (2015), 200-203.
10
11. Mohd M., Hernan S., and Sharif Z., “Application of K-means clustering in Hot Spot Detection for Thermal Infrared Images”, Proc. of 2017 IEEE Symposium on Computer Applications and Industrial Electronics, (2017), 107-110.
11
12. Etehadtayakol M., Sadri S., and Ng E.Y., “Application of K and Fuzzy C-means for color segmentation of thermal infrared breast images”, Journal of Medical Systems, Vol 34, No. 1, (2010), 35-42.
12
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51. Ashourian, M., Deneshmandpour, Sharifi Tehrani, O., and Moallem, P. “Real Time Implementation of a License Plate Location Recognition System Based on Adaptive Morphology”, International Journal of Engineering Transactions B; Applications, Vol. 26, No. 11, (2013), 1347-1356.
51
ORIGINAL_ARTICLE
A New Structure for Direct Measurement of Temperature Based on Negative Temperature Coefficient Thermistor and Adaptive Neuro-fuzzy Inference System
Thermistors are very commonly used for narrow temperature-range high-resolution applications, such as in medicine, calorimetry, and near ambient temperature measurements. In particular, Negative Temperature Coefficient (NTC) thermistor is very inexpensive and highly sensitive, whose sensing temperature range and sensitivity are highly limited due to the intrinsic nonlinearity and self-heating properties of NTC thermistor at high operation currents. In this research, a new structure is proposed based on adaptive neuro-fuzzy system for the modeling of sensor nonlinearity. Apart from taking self-heating phenomenon of NTC thermistor sensor, the proposed structure also measures temperature directly, without any linearizing circuitry. Neuro-fuzzy network is trained and tested through data produced in the Laboratory environment. Examination of the proposed method on test data achieved a mean squared error of 0.0195, which is considered as a significant accomplishment.
https://www.ije.ir/article_82208_2f6a5def55ba03acf1c618b7677cac68.pdf
2018-10-01
1682
1688
Temperature
Negative Temperature Coefficient Thermistor
Self-heating
Modeling
adaptive neuro-fuzzy inference system
J.
Ghasemi
jghasemi@stu.nit.ac.ir
1
Faculty of Engineering and Technology, University of Mazandaran, Babolsar, Iran
LEAD_AUTHOR
M.
Mehdipoor
2
Department of Electrical Engineering, Amol Institution of Higher Education, Amol, Iran
AUTHOR
J.
Rasekhi
3
Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran
AUTHOR
K.
Gorgani Firouzjah
4
Faculty of Engineering and Technology, University of Mazandaran, Babolsar, Iran
AUTHOR
1. Cotton, N.J., and Wilamowski, B.M., “Compensation of Sensors Nonlinearity with Neural Networks”, In 24th IEEE International Conference on Advanced Information Networking and Applications, IEEE, (2010), 1210–1217.
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2. Samuel Rajesh Babu M.E., R., Deepa M.E., S., and Jothivel M.E., S., “A Closed Loop Control of Quadratic Boost Converter Using PID Controller”, International Journal of Engineering - Transactions B: Applications, Vol. 27, No. 11, (2014), 1653–1662.
2
3. Mahmoudzadeh, S., Mojallali, H., and Pourjafari, N., “An Optimized PID for Capsubots using Modified Chaotic Genetic Algorithm (RESEARCH NOTE)”, International Journal of Engineering - Transactions C: Aspects, Vol. 27, No. 9, (2014), 1377–1384.
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5. Moghadam-Fard, H., and Samadi, F., “Active Suspension System Control Using Adaptive Neuro Fuzzy (ANFIS) Controller”, International Journal of Engineering - Transactions C: Aspects, Vol. 28, No. 3, (2014), 396–401.
5
6. Bahramifar, A., Shirkhani, R., and Mohammadi, M., “An ANFIS-based Approach for Predicting the Manning Roughness Coefficient in Alluvial Channels at the Bank-full Stage”, International Journal of Engineering - Transactions B: Applications, Vol. 26, No. 2, (2012), 177–186.
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9
10. Sarkar, A.R., Dey, D., and Munshi, S., “Linearization of NTC Thermistor Characteristic Using Op-Amp Based Inverting Amplifier”, IEEE Sensors Journal, Vol. 13, No. 12, (2013), 4621–4626.
10
11. Abdulwahab, D., Khan, S., Chebil, J., Ahmed, M.M., Naji, A.W.A.K., and Alam, A.H.M.Z., “Identification of linearized regions of non-linear transducers responses”, In International Conference on Computer and Communication Engineering (ICCCE’10), IEEE, (2010), 1–4.
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20. Chong, W.T., Al-Mamoon, A., Poh, S.C., Saw, L.H., Shamshirband, S., and Mojumder, J.C., “Sensitivity analysis of heat transfer rate for smart roof design by adaptive neuro-fuzzy technique”, Energy and Buildings, Vol. 124, (2016), 112–119.
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22
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26
ORIGINAL_ARTICLE
Improvement Performances of Active and Reactive Power Control Applied to DFIG for Variable Speed Wind Turbine Using Sliding Mode Control and FOC
This paper deals with the Active and Reactive Power control of double-fed induction generator (DFIG) for variable speed wind turbine. For controlling separately the active and the reactive power generated by a DFIG, field oriented control (FOC) and indirect sliding mode control (ISMC) are presented. These non linear controls are compared on the basis of topology, cost, efficiency. The main contribution of this work based to the short time of response with excellent convergence and high decoupled between active and reactive power in one part and in the second part we define the benefit to use indirect model of DFIG to the conception of indirect sliding mode control by using the relationships between stator powers and rotor currents. The simulation results have shown good performances concerning the tracking of the references both in transient and steady state and prove the effectiveness of sliding mode control to track the given references using PWM inverter.
https://www.ije.ir/article_82209_307c239c23d580d2bfb1fb0d537c5a6d.pdf
2018-10-01
1689
1697
Doubly fed induction generator
field oriented control
Indirect Sliding Mode
Wind Energy
pulse with modulation PWM
T.
Douadi
1
LEB – Research Laboratory, Department of Electrical Engineering, Mostefa Benboulaid-Batna 2 University, Algeria
LEAD_AUTHOR
Y.
Harbouche
2
LEB – Research Laboratory, Department of Electrical Engineering, Mostefa Benboulaid-Batna 2 University, Algeria
AUTHOR
R.
Abdessemed
3
LEB – Research Laboratory, Department of Electrical Engineering, Mostefa Benboulaid-Batna 2 University, Algeria
AUTHOR
I.
Bakhti
4
Laboratory of Electromagnetic Induction and Propulsion Systems, Department of Electrical Engineering, Batna University, Algeria
AUTHOR
1. Salehi, M. and Davarani, R.Z., "Effect of different turbine-generator shaft models on the subsynchronous resonance phenomenon in the double cage induction generator based wind farm", International Journal of Engineering-Transactions B: Applications, Vol. 29, No. 8, (2016), 1103-1111.
1
2. Hamidi, H., Mortazave, H. and Salahshoor, A., "Designing and modeling a control system for aircraft in the presence of wind disturbance", International Journal of Engineering-Transactions C: Aspects, Vol. 30, No. 12, (2017), 1856-1862.
2
3. Aroussi, H., Ziani, E. and Bossoufi, B., "Robust control of a power wind system based on the double fed induction generator (DFIG)", Journal of Automation & Systems Engineering JASE, Vol. 9, No. 3, (2015), 156-166.
3
4. Rouabhi, R., Abdessemed, R., Chouder, A. and Djerioui, A., "Power quality enhancement of grid connected doubly-fed induction generator using sliding mode control", International Review of Electrical Engineering, Vol. 10, (2015), 266-276.
4
5. Boualouch, A., Essadki, A., Nasser, T., Boukhriss, A. and Frigui, A., "Power control of dfig in wecs using backstipping and sliding mode controller", International Journal of Electrical Computer Energetic Electronic and Communication Engineering, Vol. 9, (2015), 612-618.
5
6. Karami-Mollaee, A., "Adaptive fuzzy dynamic sliding mode control of nonlinear systems", International Journal of Engineering-Transactions B: Applications, Vol. 29, No. 8, (2016), 1075-1086.
6
7. Vali, M., Rezaie, B. and Rahmani, Z., "Designinga neuro-sliding mode controller for networked control systems with packet dropout", International Journal of Engineering-Transactions A: Basics, Vol. 29, No. 4, (2016), 490-499.
7
8. Mechter, A., Kemih, K. and Ghanes, M., "Sliding mode control of a wind turbine with exponential reaching law", Acta Polytechnica Hungarica, Vol. 12, No. 03, (2015), 167-183.
8
9. Drid, S., "Contribution à la modélisation et à la commande robuste d’une machine à induction double alimentée à flux orienté avec optimisation de la structure d’alimentation: Théorie et expérimentation", PhD Thesis, University of Batna, Algeria, (2005).
9
ORIGINAL_ARTICLE
Iterative Weighted Non-smooth Non-negative Matrix Factorization for Face Recognition
Non-negative Matrix Factorization (NMF) is a part-based image representation method. It comes from the intuitive idea that entire face image can be constructed by combining several parts. In this paper, we propose a framework for face recognition by finding localized, part-based representations, denoted “Iterative weighted non-smooth non-negative matrix factorization” (IWNS-NMF). A new cost function is proposed in order to incorporate sparsity which is controlled by a specific parameter and weights of feature coefficients. This method extracts highly localized patterns, which generally improves the capability of face recognition. After extracting patterns by IWNS-NMF, we use principle component analysis to reduce dimension for classification by linear SVM. The Recognition rates on ORL, YALE and JAFFE datasets were 97.5, 93.33 and 87.8%, respectively. Comparisons to the related methods in the literature indicate that the proposed IWNS-NMF method achieves higher face recognition performance than NMF, NS-NMF, Local NMF and SNMF.
https://www.ije.ir/article_82211_e644008323238e0fe979493df18d8816.pdf
2018-10-01
1698
1707
Non-negative Matrix Factorization
Face recognition
Pattern Analysis
features extraction
Sparse representation
B.
Sabzalian
1
Faculty of Electrical Engineering and Robotics, Shahrood University of Technology, Shahrood, Iran
AUTHOR
V.
Abolghasemi
2
Faculty of Electrical Engineering and Robotics, Shahrood University of Technology, Shahrood, Iran
LEAD_AUTHOR
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2
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29
30. Dailey, M.N., Joyce, C., Lyons, M.J., Kamachi, M., Ishi, H., Gyoba, J. and Cottrell, G.W., “Evidence and a Computational Explanation of Cultural Differences in Facial Expression
30
ORIGINAL_ARTICLE
Investigation on Equivalent Trans-utilization Mode and Benefit of Wind Energy
For economic benefit of wind power generation, the equivalent conversion relationships and models between the different “quality” energy are studied deeply in the conversion processes of wind energy. Considering the effect of load demand characteristics and energy supply price on the wind energy utilization mode comprehensively, the multi-objective trans-utilization optimization model of wind energy is established, which the objections are both the maximum wind energy utilization ratio and comprehensive operational benefit of the energy consumption systems. Then, the quantum-behaved particle swarm optimization method is used to solve the model. By contrast to the traditional unitary energy supply mode, the results showed that the proposed models can improve the wind energy comprehensive utilization rate, and increase energy selling benefit of the energy supply system. The rationality and superiority of models are verified, and that provides a new idea for the large-scale develop and utilize wind energy.
https://www.ije.ir/article_82212_08c3e3076cfddc8eea3fdc0ea2b5a82e.pdf
2018-10-01
1708
1714
Energy Internet
Equivalent Conversion
Energy Selling Benefit
Wind Power Utilization
Y.
Zhanxin
1
Skill Training Center of Sichuan Electric Power Corporation of State Grid, Chengdu, China
LEAD_AUTHOR
Z.
Fang
2
Skill Training Center of Sichuan Electric Power Corporation of State Grid, Chengdu, China
AUTHOR
X.
Lixiong
3
Sichuan Provincial Key Lab. of Intelligent Electric Power Grid, Sichuan University, Chengdu, China
AUTHOR
L.
Hongjun
4
Skill Training Center of Sichuan Electric Power Corporation of State Grid, Chengdu, China
AUTHOR
X.
Dapeng
5
Skill Training Center of Sichuan Electric Power Corporation of State Grid, Chengdu, China
AUTHOR
L.
Junnan
6
Skill Training Center of Sichuan Electric Power Corporation of State Grid, Chengdu, China
AUTHOR
D.
Yu
7
Skill Training Center of Sichuan Electric Power Corporation of State Grid, Chengdu, China
AUTHOR
L.
Yalei
8
Skill Training Center of Sichuan Electric Power Corporation of State Grid, Chengdu, China
AUTHOR
1. Tan, Z., Wu, E., Ju, L., Song, Y., Shen, S. and Zhang, J., “A Model for Contrastive Analysis on Risk of Income From Investment in Different Wind Power Resource Regions”, Power System Technology, Vol. 37, No. 03, (2013), 713–719.
1
2. Hosseini Molla, J., Barforoushi, T. and Adabi Firouzjaee, J., “Distributed Generation Expansion Planning Considering Load Growth Uncertainty: A Novel Multi-Period Stochastic Model”, International Journal of Engineering Transactions C: Aspects, Vol. 31, No. 3, (2018), 405–414.
2
3. She, X., Huang, A.Q., Wang, F. and Burgos, R., “Wind Energy System With Integrated Functions of Active Power Transfer, Reactive Power Compensation, and Voltage Conversion”, IEEE Transactions on Industrial Electronics, Vol. 60, No. 10, (2013), 4512–4524.
3
4. Bai, J.H., Xing, S.X., Jia, D.X. and Chen, L., “Study of Major Questions of Wind Power Digestion and Transmission in China”, Power System and Clean Energy, Vol. 26, No. 01, (2010), 14–17.
4
5. AI, X. and Liu, X., “Chance constrained model for wind power usage based on demand response”, Journal of North China Electric Power University (Natural Science Edition), Vol. 38, No. 03, (2011), 17–22.
5
6. Yu, D., Song, S., Zhang, B. and Han X., “Synergistic Dispatch of PEVs Charging and Wind Power in Chinese Regional Power Grids”, Automation of Electric Power Systems, Vol. 35, No. 14, (2011), 24–29.
6
7. Zheng, L., Hu, W., Lu, Q.Y., Min, Y., Yuan, F. and Gao, Z.H., “Research on planning and operation model for energy storage system to optimize wind power integration”, Proceedings of the CSEE, Vol. 34, No. 16, (2014), 2533–2543.
7
8. Sattarpour, T. and Nazarpour, D., “Assessing the Impact of Size and Site of DGs and SMs in Active Distribution Networks for Energy Losses Cost”, International Journal of Engineering - Transactions A: Basics, Vol. 28, No. 7, (2015), 1002–1010.
8
9. Wu, X., Wang, X., Li, J., Guo, J., Zhang, K. and Chen, J., “A Joint Operation Model and Solution for Hybrid Wind Energy Storage Systems”, Proceedings of the CSEE, Vol. 33, No. 13, (2013), 10–17.
9
10. Deshmukh, M.K. and Deshmukh, S.S., “Modeling of hybrid renewable energy systems”, Renewable and Sustainable Energy Reviews, Vol. 12, No. 1, (2008), 235–249.
10
11. Lu, Q., Chen, T., Wang, H., Li, L., Lu, Y. and Li, W., “Combined heat and power dispatch model for power system with heat accumulator”, Electric Power Automation Equipment, Vol. 34, No. 05, (2014), 79–85.
11
12. Ding, M., Wang, B., Zhao, and Chen, Z., “Configuration Optimization of Capacity of Standalone PV-Wind-Diesel-Battery Hybrid Microgrid”, Power System Technology, Vol. 37, No. 03, (2013), 575–581.
12
13. Xiao, X., Kan, W., Yang, Y., Zhang, S. and Xiao, Y., “Superstructure-based Optimal Planning of Cogeneration Systems With Storage”, Proceedings of the CSEE, Vol. 32, No. 32, (2012), 08-14.
13
14. Li, Z., Zhang, F., Liang, J., Yun, Z. and Zhang J., “Optimization on Microgrid With Combined Heat and Power System”, Proceeding of the CSEE, Vol. 35, No. 14, (2015), 3659–3576.
14
ORIGINAL_ARTICLE
A Collaborative Stochastic Closed-loop Supply Chain Network Design for Tire Industry
Recent papers in the concept of Supply Chain Network Design (SCND) have seen a rapid development in applying the stochastic models to get closer to real-world applications. Regaring the special characteristics of each product, the stracture of SCND varies. In tire industry, the recycling and remanufacturing of scraped tires lead to design a closed-loop supply chain. This paper proposes a two-stage stochastic model for a closed-loop SCND in the application of tire industry. The first stage of model optimizes the expected total cost. Then, financial risk has been considered as the second stage of model to control the uncertainty variables leading to a robust solution. To solve the developed problem, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) have been used. To enhace the efficiency of metaheuristic algorithms, Response Surface Method (RSM) has been applied. Finally, the proposed model is evaluated by different test problem with different complexity and a set of metrics in terms of Pareto optimal solutions.
https://www.ije.ir/article_82213_b5a4b4a3ed4cb8e25fb5b1c719cadadc.pdf
2018-10-01
1715
1722
Stochastic programming
Closed-loop supply chain
Tire Industry
Genetic Algorithm
Particle Swarm Optimization
M.
Hajiaghaei-Keshteli
1
Department of Industrial Engineering, University of Science and Technology of Mazandaran, Behshahr, Iran
LEAD_AUTHOR
K. S.
Abdallah
2
Department of Supply Chain Management, College of International Transport and Logistics, Arab Academy for Science and Technology, Cairo, Egypt
AUTHOR
A. M.
Fathollahi-Fard
3
Department of Industrial Engineering, University of Science and Technology of Mazandaran, Behshahr, Iran
AUTHOR
1. Amin, S.H., Zhang, G. and Akhtar, P., "Effects of uncertainty on a tire closed-loop supply chain network", Expert Systems with Applications, Vol. 73, (2017), 82-91.
1
2. Subulan, K., Taşan, A.S. and Baykasoğlu, A., "Designing an environmentally conscious tire closed-loop supply chain network with multiple recovery options using interactive fuzzy goal programming", Applied Mathematical Modelling, Vol. 39, No. 9, (2015), 2661-2702.
2
3. Chopra, S., "Designing the distribution network in a supply chain", Transportation Research Part E: Logistics and Transportation Review, Vol. 39, No. 2, (2003), 123-140.
3
4. Fathollahi-Fard, A.M. and Hajiaghaei-Keshteli, M., "A stochastic multi-objective model for a closed-loop supply chain with environmental considerations", Applied Soft Computing, Vol. 69, (2018), 232-249.
4
5. Hajiaghaei-Keshteli, M., Sajadifar, S.M. and Haji, R., "Determination of the economical policy of a three-echelon inventory system with (r, q) ordering policy and information sharing", The International Journal of Advanced Manufacturing Technology, Vol. 55, No. 5-8, (2011), 831-841.
5
6. Nourmohamadi Shalke, P., Paydar, M.M. and Hajiaghaei-Keshteli, M., "Sustainable supplier selection and order allocation through quantity discounts", International Journal of Management Science and Engineering Management, Vol. 13, No. 1, (2018), 20-32.
6
7. Fard, A.M.F., Gholian-Jouybari, F., Paydar, M.M. and Hajiaghaei-Keshteli, M., "A bi-objective stochastic closed-loop supply chain network design problem considering downside risk", Industrial Engineering & Management Systems, Vol. 16, No. 3, (2017), 342-362.
7
8. Nasiri, E., Afshari, A. and Hajiaghaei-Keshteli, M., "Addressing the freight consolidation and containerization problem by recent and hybridized meta-heuristic algorithms", International Journal of Engineering-Transactions C: Aspects, Vol. 30, No. 3, (2017), 403-410.
8
9. Farahani, R.Z., Rezapour, S., Drezner, T. and Fallah, S., "Competitive supply chain network design: An overview of classifications, models, solution techniques and applications", Omega, Vol. 45, (2014), 92-118.
9
10. Govindan, K., Soleimani, H. and Kannan, D., "Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future", European Journal of Operational Research, Vol. 240, No. 3, (2015), 603-626.
10
11. Chopra, S. and Meindl, P., Supply chain management. Strategy, planning & operation, in Das summa summarum des management. 2007, Springer.265-275.
11
12. Ferrer, G., "The economics of tire remanufacturing", Resources, Conservation and Recycling, Vol. 19, No. 4, (1997), 221-255.
12
13. Sasikumar, P., Kannan, G. and Haq, A.N., "A multi-echelon reverse logistics network design for product recovery—a case of truck tire remanufacturing", The International Journal of Advanced Manufacturing Technology, Vol. 49, No. 9-12, (2010), 1223-1234.
13
14. Govindan, K. and Soleimani, H., "A review of reverse logistics and closed-loop supply chains: A journal of cleaner production focus", Journal of Cleaner Production, Vol. 142, (2017), 371-384.
14
15. Souza, G.C., "Closed‐loop supply chains: A critical review, and future research", Decision Sciences, Vol. 44, No. 1, (2013), 7-38.
15
16. Fathollahi-Fard, A.M., Hajiaghaei-Keshteli, M. and Tavakkoli-Moghaddam, R., "The social engineering optimizer (SEO)", Engineering Applications of Artificial Intelligence, Vol. 72, (2018), 267-293.
16
17. Fard, A.M.F. and Hajiaghaei-Keshteli, M., "A bi-objective partial interdiction problem considering different defensive systems with capacity expansion of facilities under imminent attacks", Applied Soft Computing, Vol. 68, (2018), 343-359.
17
18. Kannan, G., Noorul Haq, A. and Devika, M., "Analysis of closed loop supply chain using genetic algorithm and particle swarm optimisation", International Journal of Production Research, Vol. 47, No. 5, (2009), 1175-1200.
18
19. Devika, K., Jafarian, A. and Nourbakhsh, V., "Designing a sustainable closed-loop supply chain network based on triple bottom line approach: A comparison of metaheuristics hybridization techniques", European Journal of Operational Research, Vol. 235, No. 3, (2014), 594-615.
19
20. Mirakhorli, A., "Fuzzy multi-objective optimization for closed loop logistics network design in bread-producing industries", The International Journal of Advanced Manufacturing Technology, Vol. 70, No. 1-4, (2014), 349-362.
20
21. Subulan, K., Baykasoğlu, A., Özsoydan, F.B., Taşan, A.S. and Selim, H., "A case-oriented approach to a lead/acid battery closed-loop supply chain network design under risk and uncertainty", Journal of Manufacturing Systems, Vol. 37, (2015), 340-361.
21
22. Fard, A.M.F. and Hajaghaei-Keshteli, M., "A tri-level location-allocation model for forward/reverse supply chain", Applied Soft Computing, Vol. 62, (2018), 328-346.
22
23. Eberhart, R. and Kennedy, J., "A new optimizer using particle swarm theory", in Micro Machine and Human Science, 1995. MHS'95., Proceedings of the Sixth International Symposium on, IEEE., (1995), 39-43.
23
24. Holland, J.H., "Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence, MIT press, (1992).
24
25. Hajiaghaei-Keshteli, M. and Fard, A.M.F., "Sustainable closed-loop supply chain network design with discount supposition", Neural Computing and Applications, (2018), 1-35.
25
26. Cheraghalipour, A., Paydar, M. and Hajiaghaei-Keshteli, M., "An integrated approach for collection center selection in reverse logistics", International Journal of Engineering Transaction A Basics, Vol. 30, No. 7, (2017), 1005-1016.
26
27. Sadeghi-Moghaddam, S., Hajiaghaei-Keshteli, M. and Mahmoodjanloo, M., "New approaches in metaheuristics to solve the fixed charge transportation problem in a fuzzy environment", Neural Computing and Applications, (2017), 1-21.
27
28. Samadi, A., Mehranfar, N., Fathollahi Fard, A. and Hajiaghaei-Keshteli, M., "Heuristic-based metaheuristics to address a sustainable supply chain network design problem", Journal of Industrial and Production Engineering, Vol. 35, No. 2, (2018), 102-117.
28
29. Golshahi-Roudbaneh, A., Hajiaghaei-Keshteli, M. and Paydar, M.M., "Developing a lower bound and strong heuristics for a truck scheduling problem in a cross-docking center", Knowledge-Based Systems, Vol. 129, (2017), 17-38.
29
ORIGINAL_ARTICLE
Integrated Order Batching and Distribution Scheduling in a Single-block Order Picking Warehouse Considering S-Shape Routing Policy
In this paper, a mixed-integer linear programming model is proposed to integrate batch picking and distribution scheduling problems in order to optimize them simultaneously in an order picking warehouse. A tow-phase heuristic algorithm is presented to solve it in reasonable time. The first phase uses a genetic algorithm to evaluate and select permutations of the given set of customers. The second phase uses the route first-cluster method to obtain an effective schedule for a given permutation of customers. Computational experiments represent that integrated approach can lead to significant reduction in the makespan. Moreover, Empirical observations on the performance of the heuristic algorithm are reported.
https://www.ije.ir/article_82214_5418de521d49e0cbcce42335d66bcc0e.pdf
2018-10-01
1723
1733
Warehouse
Order Picking System
Order Batching
Picker-to-Part Systems
Distribution Scheduling
Y.
Zare Mehrjerdi
1
Department of Industrial Engineering, Yazd university, Yazd, Iran
LEAD_AUTHOR
M.
Alipour
2
Department of Industrial Engineering, Yazd university, Yazd, Iran
AUTHOR
A.
Mostafaeipour
3
Department of Industrial Engineering, Yazd university, Yazd, Iran
AUTHOR
1. Experimental validations of the learnable evolution model Henn, S., Koch, S., Doerner, K.F., Strauss, C. and Wäscher, G.J.B.R., "Metaheuristics for the order batching problem in manual order picking systems", Business Research, Vol. 3, No. 1, (2010), 82-105.
1
2. De Koster, M., Van der Poort, E.S. and Wolters, M.J.I.J.o.P.R., "Efficient orderbatching methods in warehouses", International Journal of Production Research, Vol. 37, No. 7, (1999), 1479-1504.
2
3. De Koster, R.J.I.T.o.E.M., "Distribution strategies for online retailers", IEEE Transactions on Engineering Management, Vol. 50, No. 4, (2003), 448-457.
3
4. Gong, Y. and De Koster, R.J.I.T., "A polling-based dynamic order picking system for online retailers", IIE transactions, Vol. 40, No. 11, (2008), 1070-1082.
4
5. Moons, S., Ramaekers, K., Caris, A., Arda, Y.J.F.S. and Journal, M., "Integration of order picking and vehicle routing in a B2C e-commerce context", Flexible Services and Manufacturing Journal, (2017), 1-31.
5
6. Hajiaghaei-Keshteli, M. and Aminnayeri, M.J.A.S.C., "Solving the integrated scheduling of production and rail transportation problem by keshtel algorithm", Applied Soft Computing, Vol. 25, (2014), 184-203.
6
7. Nasiri, E., Afshari, A. and Hajiaghaei-Keshteli, M.J.I.J.o.E.-T.C.A., "Addressing the freight consolidation and containerization problem by recent and hybridized meta-heuristic algorithms", International Journal of Engineering-Transactions C: Aspects, Vol. 30, No. 3, (2017), 403-410.
7
8. Yahyaei, M., Bashiri, M. and Garmeyi, Y.J.I.J.o.E.-T.B.A., "Multi-criteria logistic hub location by network segmentation under criteria weights uncertainty (research note)", International Journal of Engineering-Transactions B: Applications, Vol. 27, No. 8, (2013), 1205-1214.
8
9. Zhang, J., Wang, X., Huang, K.J.C. and Engineering, I., "Integrated on-line scheduling of order batching and delivery under B2C e-commerce", Computers & Industrial Engineering, Vol. 94, (2016), 280-289.
9
10. Chen, Z.-L.J.O.r., "Integrated production and outbound distribution scheduling: Review and extensions", Operations Research, Vol. 58, No. 1, (2010), 130-148.
10
11. Low, C., Chang, C.-M., Gao, B.-Y.J.I.J.o.S.S.O. and Logistics, "Integration of production scheduling and delivery in two echelon supply chain", International Journal of Systems Science: Operations and Logistics, Vol. 4, No. 2, (2017), 122-134.
11
12. Low, C., Chang, C.-M., Li, R.-K. and Huang, C.-L.J.I.J.o.P.E., "Coordination of production scheduling and delivery problems with heterogeneous fleet", International Journal of Production Economics, Vol. 153, (2014), 139-148.
12
13. Low, C., Li, R.-K. and Chang, C.-M.J.I.J.o.P.R., "Integrated scheduling of production and delivery with time windows", International Journal of Production Research, Vol. 51, No. 3, (2013), 897-909.
13
14. Henn, S.J.C. and Research, O., "Algorithms for on-line order batching in an order picking warehouse", Computers & Operations Research, Vol. 39, No. 11, (2012), 2549-2563.
14
15. Bozer, Y.A. and Kile, J.W.J.I.J.o.P.R., "Order batching in walk-and-pick order picking systems", International Journal of Production Research, Vol. 46, No. 7, (2008), 1887-1909.
15
16. Gademann, N. and Velde, S.J.I.t., "Order batching to minimize total travel time in a parallel-aisle warehouse", IIE Transactions, Vol. 37, No. 1, (2005), 63-75.
16
17. Elsayed, E.A.J.T.I.J.o.P.R., "Algorithms for optimal material handling in automatic warehousing systems", The International Journal of Production Research, Vol. 19, No. 5, (1981), 525-535.
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18. Gibson, D.R. and Sharp, G.P.J.E.J.o.O.R., "Order batching procedures", European Journal of Operational Research, Vol. 58, No. 1, (1992), 57-67.
18
19. Henn, S. and Wäscher, G.J.E.J.o.O.R., "Tabu search heuristics for the order batching problem in manual order picking systems", European Journal of Operational Research, Vol. 222, No. 3, (2012), 484-494.
19
20. Henn, S.J.F.S. and Journal, M., "Order batching and sequencing for the minimization of the total tardiness in picker-to-part warehouses", Flexible Services and Manufacturing Journal, Vol. 27, No. 1, (2015), 86-114.
20
21. Lin, C.-C., Kang, J.-R., Hou, C.-C., Cheng, C.-Y.J.C. and Engineering, I., "Joint order batching and picker manhattan routing problem", Computers & Industrial Engineering, Vol. 95, (2016), 164-174.
21
22. Matusiak, M., de Koster, R., Kroon, L. and Saarinen, J.J.E.J.o.O.R., "A fast simulated annealing method for batching precedence-constrained customer orders in a warehouse", European Journal of Operational Research, Vol. 236, No. 3, (2014), 968-977.
22
23. Menéndez, B., Pardo, E.G., Alonso-Ayuso, A., Molina, E., Duarte, A.J.C. and Research, O., "Variable neighborhood search strategies for the order batching problem", Computers & Operations Research, Vol. 78, (2017), 500-512.
23
24. Zhang, J., Wang, X., Chan, F.T. and Ruan, J.J.A.M.M., "On-line order batching and sequencing problem with multiple pickers: A hybrid rule-based algorithm", Applied Mathematical Modelling, Vol. 45, (2017), 271-284.
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26. Ahuja, R.K., "Network flows: Theory, algorithms, and applications, Pearson Education, (2017).
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28. Geismar, H.N., Laporte, G., Lei, L. and Sriskandarajah, C.J.I.J.o.C., "The integrated production and transportation scheduling problem for a product with a short lifespan", INFORMS Journal on Computing, Vol. 20, No. 1, (2008), 21-33.
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31
ORIGINAL_ARTICLE
A Lagrangian Relaxation-based Algorithm to Solve a Home Health Care Routing Problem
Nowadays, a rapid growth in the rate of life expectancy can be seen especially in the developed countries. Accordingly, the population of elderlies has been increased. By another point of view, the number of hospitals, retirement homes along with medical staffs has not been grown with a same rate. Hence, Home Health Care (HHC) operations including a set of nurses and patients have been developed recently by both academia and health practitioners to consider elderlies’ preferences willing to receive their cares at their homes instead of hospitals or retirement homes. To alleviate the drawbacks of pervious works and make HHC more practical, this paper introduces not only a new mathematical formulation considering new suppositions in this research area but also a solution approach based on Lagrangian relaxation theory has been employed for the first time. The main strategy of used algorithm aims to fill the gap between the lower bound and upper bound of problem and finds a solution which has both optimality and feasibility properties. By generating a number of numerical examples, results show the performance of the proposed algorithm analyzed by different criteria as well as the efficiency of developed formulation through a set of sensitivity analyses.
https://www.ije.ir/article_82215_f5533935442de4eccceeac269fc7cc69.pdf
2018-10-01
1734
1740
Home Health Care
vehicle routing problem
Lagrangian Relaxation-based Algorithm
A. M.
Fathollahi-Fard
1
Department of Industrial Engineering, University of Science and Technology of Mazandaran, Behshahr, Iran
AUTHOR
M.
Hajiaghaei-Keshteli
2
Department of Industrial Engineering, University of Science and Technology of Mazandaran, Behshahr, Iran
LEAD_AUTHOR
R.
Tavakkoli-Moghaddam
3
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
AUTHOR
1. Fikar, C. and Hirsch, P., "Home health care routing and scheduling: A review", Computers & Operations Research, Vol. 77, (2017), 86-95.
1
2. Employment, E.C.D.-G.f. and E., E.O.U., "Europe's demographic future: Facts and figures on challenges and opportunities, Office for official publications of the European communities, (2007).
2
3. Braekers, K., Hartl, R.F., Parragh, S.N. and Tricoire, F., "A bi-objective home care scheduling problem: Analyzing the trade-off between costs and client inconvenience", European Journal of Operational Research, Vol. 248, No. 2, (2016), 428-443.
3
4. Lin, C.-C., Hung, L.-P., Liu, W.-Y. and Tsai, M.-C., "Jointly rostering, routing, and rerostering for home health care services: A harmony search approach with genetic, saturation, inheritance, and immigrant schemes", Computers & Industrial Engineering, Vol. 115, (2018), 151-166.
4
5. Liu, R., Xie, X. and Garaix, T., "Hybridization of tabu search with feasible and infeasible local searches for periodic home health care logistics", Omega, Vol. 47, (2014), 17-32.
5
6. Shi, Y., Boudouh, T. and Grunder, O., "A hybrid genetic algorithm for a home health care routing problem with time window and fuzzy demand", Expert Systems with Applications, Vol. 72, (2017), 160-176.
6
7. Sahebjamnia, N., Fard, A.M.F. and Hajiaghaei-Keshteli, M., "Sustainable tire closed-loop supply chain network design: Hybrid metaheuristic algorithms for large-scale networks", Journal of Cleaner Production, Vol. 196, (2018), 273-296.
7
8. Rasmussen, M.S., Justesen, T., Dohn, A. and Larsen, J., "The home care crew scheduling problem: Preference-based visit clustering and temporal dependencies", European Journal of Operational Research, Vol. 219, No. 3, (2012), 598-610.
8
9. Nickel, S., Schröder, M. and Steeg, J., "Mid-term and short-term planning support for home health care services", European Journal of Operational Research, Vol. 219, No. 3, (2012), 574-587.
9
10. Liu, R., Xie, X., Augusto, V. and Rodriguez, C., "Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care", European Journal of Operational Research, Vol. 230, No. 3, (2013), 475-486.
10
11. Mankowska, D.S., Meisel, F. and Bierwirth, C., "The home health care routing and scheduling problem with interdependent services", Health Care Management Science, Vol. 17, No. 1, (2014), 15-30.
11
12. Hiermann, G., Prandtstetter, M., Rendl, A., Puchinger, J. and Raidl, G.R., "Metaheuristics for solving a multimodal home-healthcare scheduling problem", Central European Journal of Operations Research, Vol. 23, No. 1, (2015), 89-113.
12
13. Fikar, C. and Hirsch, P., "A matheuristic for routing real-world home service transport systems facilitating walking", Journal of Cleaner Production, Vol. 105, (2015), 300-310.
13
14. Cappanera, P., Scutellà, M.G., Nervi, F. and Galli, L., "Demand uncertainty in robust home care optimization", Omega, Vol. 80, (2018), 95-110.
14
15. Dukkanci, O. and Kara, B.Y., "Routing and scheduling decisions in the hierarchical hub location problem", Computers & Operations Research, Vol. 85, (2017), 45-57.
15
16. Mestria, M., "New hybrid heuristic algorithm for the clustered traveling salesman problem", Computers & Industrial Engineering, Vol. 116, (2018), 1-12.
16
17. Golshahi-Roudbaneh, A., Hajiaghaei-Keshteli, M. and Paydar, M.M., "Developing a lower bound and strong heuristics for a truck scheduling problem in a cross-docking center", Knowledge-Based Systems, Vol. 129, (2017), 17-38.
17
18. Astorino, A., Gaudioso, M. and Miglionico, G., "Lagrangian relaxation for the directional sensor coverage problem with continuous orientation", Omega, Vol. 75, (2018), 77-86.
18
19. Miller, C.E., Tucker, A.W. and Zemlin, R.A., "Integer programming formulation of traveling salesman problems", Journal of the ACM (JACM), Vol. 7, No. 4, (1960), 326-329.
19
20. Fard, A.M.F., Gholian-Jouybari, F., Paydar, M.M. and Hajiaghaei-Keshteli, M., "A bi-objective stochastic closed-loop supply chain network design problem considering downside risk", Industrial Engineering & Management Systems, Vol. 16, No. 3, (2017), 342-362.
20
21. Fathollahi-Fard, A.M., Hajiaghaei-Keshteli, M. and Tavakkoli-Moghaddam, R., "A bi-objective green home health care routing problem", Journal of Cleaner Production, Vol. 200, (2018), 423-443.
21
22. Taguchi, G., Introduction to quality engineering: Designing quality into products and processes. 1986.
22
23. Fard, A.M.F. and Hajiaghaei-Keshteli, M., "A bi-objective partial interdiction problem considering different defensive systems with capacity expansion of facilities under imminent attacks", Applied Soft Computing, Vol. 68, (2018), 343-359.
23
24. Fathollahi-Fard, A.M., Hajiaghaei-Keshteli, M. and Tavakkoli-Moghaddam, R., "The social engineering optimizer (SEO)", Engineering Applications of Artificial Intelligence, Vol. 72, (2018), 267-293.
24
25. Fathollahi-Fard, A.M. and Hajiaghaei-Keshteli, M., "A stochastic multi-objective model for a closed-loop supply chain with environmental considerations", Applied Soft Computing, Vol. 69, (2018), 232-249.
25
26. Hajiaghaei-Keshteli, M. and Fard, A.M.F., "Sustainable closed-loop supply chain network design with discount supposition", Neural Computing and Applications, (2018), 1-35.
26
27. Nasiri, E., Afshari, A.J. and Hajiaghaei-Keshteli, M., "Addressing the freight consolidation and containerization problem by recent and hybridized meta-heuristic algorithms", International Journal of Engineering-Transactions C: Aspects, Vol. 30, No. 3, (2017), 403-410.
27
28. Sadeghi-Moghaddam, S., Hajiaghaei-Keshteli, M. and Mahmoodjanloo, M., "New approaches in metaheuristics to solve the fixed charge transportation problem in a fuzzy environment", Neural Computing and Applications, (2017), 1-21.
28
29. Samadi, A., N., M., Fathollahi Fard, A.M. and Hajiaghaei-Keshteli, M., "Heuristic approaches to solve the sustainable closed-loop supply chain", Journal of Industrial and Production Engineering, Vol. 35, No. 2, (2018), 102-117.
29
ORIGINAL_ARTICLE
Characteristics of PANi/rGO Nanocomposite as Protective Coating and Catalyst in Dye-sensitized Solar Cell Counter Electrode Deposited on AISI 1086 Steel Substrate
One of the possibilities to mass-produce dye-sensitized solar cell (DSSC) device is if it could be embedded to the area atop metal roof. However, the use of metal substrate is constrained by the corrosion caused by the electrolyte solution used in the DSSC device such as iodide/tri-iodide (I-/I3-). In this study, we propose the utilization of polyaniline/reduced graphene oxide (PANi/rGO) nanocomposite as protective coating and at the same time as catalyst for the DSSC counter electrode on AISI 1086 steel substrates. The work was started by synthesizing PANi and rGO and assembling the PANi/rGO nanocomposite in a DSSC device. The characterization was performed using X-ray diffraction (XRD) for crystal structure, infrared (FTIR) for functional groups, scanning electron microscope (SEM) for surface morphology, potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) for corrosion testing, and semiconductor parameter analyzer (SPA) for the DSSC device performance. The result showed that the decrease of corrosion rates in AISI 1086 steel was proportional to the rGO concentrations in PANi/rGO nanocomposites. The lowest corrosion rate was obtained at the highest rGO composition, i.e. PANi/rGO 8 wt% with corrosion rate (CR) of 0.2 mm/year and protection efficiency of 80.3 %. The DSSC performance test revealed that PANi/rGO composite could be used as an alternative catalyst for I-/I3- based redox electrolyte in the DSSC solar cell applications in replacement for platinum. The highest power conversion efficiency of 5.38 % was obtained from PANi/rGO 4 wt%.
https://www.ije.ir/article_82216_4e4def7889017a4eb60c374c065ae91b.pdf
2018-10-01
1741
1748
AISI 1086 steel
Dye-sensitized Solar Cell counter electrode
Polyaniline
Protective coating
Reduced graphene Oxide
N.
Sofyan
1
Department of Metallurgical and Materials Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia ; Tropical Renewable Energy Center, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia
LEAD_AUTHOR
R. A.
Nugraha
2
Department of Metallurgical and Materials Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia
AUTHOR
A.
Ridhova
3
Department of Metallurgical and Materials Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia
AUTHOR
A. H.
Yuwono
4
Department of Metallurgical and Materials Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia ; Tropical Renewable Energy Center, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia
AUTHOR
A.
Udhiarto
5
Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia
AUTHOR
Xu, S., Liu, C., Wiezorek, J., “20 renewable biowastes derived carbon materials as green counter electrodes for dye-sensitized solar cells,” Materials Chemistry and Physics, Vol. 204 (2018) 294-304.
1
Sofyan, N., Ridhova, A., Yuwono, A.H., and Udhiarto, A., “Fabrication of solar cells with TiO2 nanoparticles sensitized using natural dye extracted from mangosteen pericarps”, International Journal of Technology, Vol. 8, No. 7 (2017) 1229-1238.
2
Narayan, M.R., “Review: Dye Sensitized Solar Cells based on Natural Photosensitizers”, Renewable and Sustainable Energy Reviews, Vol. 16, No. 1, (2012) 208-215.
3
Sofyan, N., Situmorang, F.W., Ridhova, A., Yuwono, A.H., and Udhiarto, A., “Visible light absorption and photosensitizing characteristics of natural yellow 3 extracted from Curcuma Longa L. for dye-sensitized solar cell”, IOP Conference Series: Earth and Environmental Science, Vol. 105, (2018), 0120731-0120736.
4
Li, Z., Chen, L., Meng, S., Guo, L., Huang, J., Liu, Y., Wang, W., and Chen, X., “Field and temperature dependence of intrinsic diamagnetism in graphene: Theory and experiment”, Physical Review B, Vol. 91, No. 9, (2015), 0944291-0944295.
5
Badiei, E., Sangpour, P., Bagheri, M., and Pazouki, M., "Graphene Oxide Antibacterial Sheets: synthesis and characterization, IJE Transactions C: Aspects, Vol. 27, No. 12, (2014), 1803-1808.
6
Emirua, T. F. and Ayele, D. W., “Controlled synthesis, characterization and reduction of graphene oxide: A convenient method for large scale production”, Egyptian Journal of Basic and Applied Sciences, Vol. 4, No. 1, (2016), 74-79.
7
Novoselov, K.S., Geim, A.K., Morozov, S.V., Jiang, D., Zhang, Y., Dubonos, S.V., Grigorieva, I.V., Firsov, A.A., “Electric field effect in atomically thin carbon films”, Science, Vol. 306, No. 5696, (2004), 666-669.
8
Pei, S., Cheng, H-M., “The reduction of graphene oxide”, Carbon, Vol. 50, (2012), 3210-3228.
9
Wang, H., Lin, J., and Shen, Z.X., “Polyaniline (PANi) based electrode materials for energy storage and conversion”, Journal of Science: Advanced Materials and Devices, Vol. 1, (2016), 225-255.
10
Stejskal, J., and Gilbert, R.G., “Polyaniline. Preparation of a conducting polymer”, Pure and Applied Chemistry, Vol. 74, No. 5, (2002), 857-867.
11
Vadiraj, T. K. and Belagali, S., “Characterization of Polyaniline for Optical and Electrical Properties”, IOSR Journal of Applied Chemistry, Vol. 8, No. 1, (2015), 53-56.
12
He, B., Tang, Q., Wang, M., Chen, H., and Yuan, S., “Robust Polyaniline–Graphene Complex Counter Electrodes for Efficient Dye-Sensitized Solar Cells”, ACS Applied Materials and Interfaces, Vol. 6, No. 11, (2014), 8230-8236.
13
Jeong, G. H., Kim, S. J., Han, E. M., and Park, K. H., “Graphene/Polyaniline Nanocomposite Multilayer Counter Electrode by Inserted Polyaniline of Dye-Sensitized Solar Cells”, Molecular Crystals and Liquid Crystals, Vol. 620, No. 1, (2015), 112-116.
14
Wang, G., Zhuo, S. and Xing, W., “Graphene/polyaniline nanocomposite as counter electrode of dye-sensitized solar cells”, Materials Letters, Vol. 69, (2012), 27-29.
15
Cai, K., Zuo, S., Luo, S., Yao, C., Liu, W., Ma, J., Mao. H and Li, Z., “Preparation of polyaniline/graphene composites with excellent anti-corrosion properties and their application in waterborne polyurethane anticorrosive coatings”, RSC Advances, Vol. 6 No. 98, (2016), 95965-95972.
16
Chang, C-H., Huang, T-C., Peng, C-W., Yeh, T-C., Lu, H-I, Hung, W-I, Weng, C-J., Yang, T-I, and Yeh, J-M., “Novel anticorrosion coatings prepared from polyaniline/graphene composites”, Carbon, Vol. 50, No 14, (2012), 5044-5051.
17
Mahato, N. and Cho, M. H., “Graphene integrated polyaniline nanostructured composite coating for protecting steels from corrosion: Synthesis, characterization, and protection mechanism of the coating material in acidic environment”, Construction and Building Materials, Vol. 115, (2016), 618–633.
18
Vaezi, M.R., Nikzad, L., and Yazdani, B., “Synthesis of CoFe2O4-polyaniline nanocomposite and evaluation of its magnetic properties”, International Journal of Engineering, Transactions B: Applications, Vol. 22, No. 4, (2009), 381-386.
19
Zhou, T. N., Qi, X. D. and Fu, Q., “The preparation of the poly (vinyl alcohol)/graphene nanocomposites with low percolation threshold and high electrical conductivity by using the large-area reduced graphene oxide sheets”, Express Polymer Letters, Vol. 7, No. 9, (2013), 747-755.
20
Liu, Y., Li, Y., Zhong, M., Yang, Y., Wen, Y., and Wang, M., “A green and ultrafast approach to the synthesis of scalable graphene nanosheets with Zn powder for electrochemical energy storage”, Journal of Materials Chemistry, Vol. 21, (2011), 15449-15455.
21
Shanmugam, V., Manoharan, S., Anandan, S., Murugan, R., “Performance of dye-sensitized solar cells fabricated with extracts from fruits of ivy gourd and flowers of red frangipani as sensitizers”, Spectrochim Acta A: Moleculer and Biomoleculer Spectroscopy, Vol. 104, (2013), 35-40.
22
Mostafaei, A. and Zolriasatein, A., “Synthesis and characterization of conducting polyaniline nanocomposites containing ZnO nanorods”, Progress in Natural Science: Materials International, Vol. 22, No. 4, (2012), 273-280.
23
Sokolova, M. P., Smirnov, M. A., Kasatkin, I. A., Dmitriev, I. Y., Saprykina, N. N., Toikka, A. M., Lahderanta, E., and Elyashevich, G. K., “Interaction of Polyaniline with Surface of Carbon Steel”, International Journal of Polymer Science, Vol. 2017, (2017), 1-9.
24
Jha, A. R., “Solar Cell Technology and Applications”, Boca Raton: CRC Press Taylor and Francis Group, (2009).
25
Wang, M., Tang, Q., Chen, H., He, B., “Counter electrodes from polyaniline−carbon nanotube complex/graphene oxide multilayers for dye-sensitized solar cell application,” Electrochimica Acta, Vol. 125 (2014) 510-515.
26
Nath, B.C., Mohan, K.J., Saikia, B.J., Ahmed, G.A., Dolui, S.K., “Designing of platinum free NiS anchored graphene/polyaniline nanocomposites-based counter electrode for dye sensitized solar cell,” Journal of Materials Science: Materials in Electronics, Vol. 28, No. 1, (2017) 1042-1050.
27
Chen, X., Liu, J., Qian, K., Wang, J., “Ternary composites of Ni–polyaniline–graphene as counter electrodes for dye-sensitized solar cells,” RSC Advances, Vol. 8, (2018) 10948-10953.
28
ORIGINAL_ARTICLE
Assessment of Particle-size and Temperature Effect of Nanofluid on Heat Transfer Adopting Lattice Boltzmann Model
The investigation of the effect of nanoparticles’ mean diameter and temperature of Al2O3–water nanofluid on velocity and energy field using the lattice Boltzmann method is the main objective of this study. The temperature of the vertical walls is considered constant at Tc and Th, respectively, while the up and the down horizontal surfaces are smooth and insulated against heat and mass. The influences of Grashof number (103, 104, 105) Prandtl number (Pr=3.42, 5.83), the various volume fraction of nanoparticles (φ=0, 0.01, 0.03, 0.05) and particle-size (dp= 24, 47, 100 nm) were carried out on heat transfer and flow fields. It was concluded that addition of nanoparticles causes a significantly affect on temperature and flow fields. The decrement of heat transfer is observed with the increment of solid volume fraction, but it increases when Grashof number and nanoparticles’ mean diameter increase. The decrement of nanoparticles’ mean diameter and Prandtl number have the same effect on Nusselt number. In addition, it was resulted that the thermal conductivity model had insignificantly impact on the mean Nusselt number than the dynamic viscosity model.
https://www.ije.ir/article_82217_f1d7eb41785622e5953406d3d0d32ca4.pdf
2018-10-01
1749
1759
Nanoparticles Mean Diameter
Natural convection
Nanofluid
Lattice Boltzmann Model
A.
Shahriari
1
Department of Mechanical Engineering, University of Zabol, Zabol, Iran
AUTHOR
N.
Jahantigh
2
Department of Mechanical Engineering, University of Zabol, Zabol, Iran
LEAD_AUTHOR
F.
Rakani
3
Department of Computer Sciences, University of Sistan & Baluchestan, Zahedan, Iran
AUTHOR
1. Abu-Nada, E., "Natural convection heat transfer simulation using energy conservative dissipative particle dynamics", Physical Review E, Vol. 81, No. 5, (2010), https://doi.org/10.1103/PhysRevE.81.056704.
1
2. Calcagni, B., Marsili, F. and Paroncini, M., "Natural convective heat transfer in square enclosures heated from below", Applied Thermal Engineering, Vol. 25, No. 16, (2005), 2522-2531.
2
3. Kuznik, F., Vareilles, J., Rusaouen, G. and Krauss, G., "A double-population lattice boltzmann method with non-uniform mesh for the simulation of natural convection in a square cavity", International Journal of Heat and Fluid Flow, Vol. 28, No. 5, (2007), 862-870.
3
4. Chol, S. and Estman, J., "Enhancing thermal conductivity of fluids with nanoparticles", ASME-Publications-Fed, Vol. 231, (1995), 99-106.
4
5. Ghadimi, A., Saidur, R. and Metselaar, H., "A review of nanofluid stability properties and characterization in stationary conditions", International Journal of Heat and Mass Transfer, Vol. 54, No. 17-18, (2011), 4051-4068.
5
6. Shahriari, A., Javaran, E.J. and Rahnama, M., "Effect of nanoparticles brownian motion and uniform sinusoidal roughness elements on natural convection in an enclosure", Journal of Thermal Analysis and Calorimetry, Vol. 131, No. 3, (2018), 2865-2884.
6
7. Ziaei-Rad, M., Saeedan, M. and Afshari, E., "Simulation and prediction of mhd dissipative nanofluid flow on a permeable stretching surface using artificial neural network", Applied Thermal Engineering, Vol. 99, (2016), 373-382.
7
8. Ziaei-Rad, M., Kasaeipoor, A., Rashidi, M.M. and Lorenzini, G., "A similarity solution for mixed-convection boundary layer nanofluid flow on an inclined permeable surface", Journal of Thermal Science and Engineering Applications, Vol. 9, No. 2, (2017), doi: 10.1115/1.4035733.
8
9. Murshed, S., Leong, K. and Yang, C., "Thermophysical and electrokinetic properties of nanofluids–a critical review", Applied Thermal Engineering, Vol. 28, No. 17-18, (2008), 2109-2125.
9
10. Choi, S., Zhang, Z. and Keblinski, P., Nanofluids, encyclopedia of nanoscience and nanotechnology (hs nalwa, editor), vol. 5. P.(757-773). 2004, American Scientific Publisher.
10
11. Khanafer, K., Vafai, K. and Lightstone, M., "Buoyancy-driven heat transfer enhancement in a two-dimensional enclosure utilizing nanofluids", International Journal of Heat and Mass Transfer, Vol. 46, No. 19, (2003), 3639-3653.
11
12. Putra, N., Roetzel, W. and Das, S.K., "Natural convection of nano-fluids", Heat and Mass Transfer, Vol. 39, No. 8-9, (2003), 775-784.
12
13. Wen, D. and Ding, Y., "Formulation of nanofluids for natural convective heat transfer applications", International Journal of Heat and Fluid Flow, Vol. 26, No. 6, (2005), 855-864.
13
14. Hwang, K.S., Lee, J.-H. and Jang, S.P., "Buoyancy-driven heat transfer of water-based al2o3 nanofluids in a rectangular cavity", International Journal of Heat and Mass Transfer, Vol. 50, No. 19-20, (2007), 4003-4010.
14
15. Kim, J., Kang, Y.T. and Choi, C.K., "Analysis of convective instability and heat transfer characteristics of nanofluids", Physics of Fluids, Vol. 16, No. 7, (2004), 2395-2401.
15
16. Lin, K.C. and Violi, A., "Natural convection heat transfer of nanofluids in a vertical cavity: Effects of non-uniform particle diameter and temperature on thermal conductivity", International Journal of Heat and Fluid Flow, Vol. 31, No. 2, (2010), 236-245.
16
17. Jang, S.P., Lee, J.-H., Hwang, K.S. and Choi, S.U., "Particle concentration and tube size dependence of viscosities of Al2O3-water nanofluids flowing through micro-and minitubes", Applied Physics Letters, Vol. 91, No. 24, (2007), https://doi.org/10.1063/1.2824393.
17
18. Xu, J., Yu, B., Zou, M. and Xu, P., "A new model for heat conduction of nanofluids based on fractal distributions of nanoparticles", Journal of Physics D: Applied Physics, Vol. 39, No. 20, (2006), 4486-4490.
18
19. Nguyen, C., Desgranges, F., Roy, G., Galanis, N., Maré, T., Boucher, S. and Mintsa, H.A., "Temperature and particle-size dependent viscosity data for water-based nanofluids–hysteresis phenomenon", International Journal of Heat and Fluid Flow, Vol. 28, No. 6, (2007), 1492-1506.
19
20. Li, J., Li, Z. and Wang, B., "Experimental viscosity measurements for copper oxide nanoparticle suspensions", Tsinghua Science and Technology, Vol. 7, No. 2, (2002), 198-201.
20
21. Masoumi, N., Sohrabi, N. and Behzadmehr, A., "A new model for calculating the effective viscosity of nanofluids", Journal of Physics D: Applied Physics, Vol. 42, No. 5, (2009), https://doi.org/10.1088/0022-3727/42/5/055501.
21
22. Chon, C.H., Kihm, K.D., Lee, S.P. and Choi, S.U., "Empirical correlation finding the role of temperature and particle size for nanofluid (Al2O3) thermal conductivity enhancement", Applied Physics Letters, Vol. 87, No. 15, (2005), https://doi.org/10.1063/1.2093936.
22
23. Kao, P.-H. and Yang, R.-J., "Simulating oscillatory flows in rayleigh–benard convection using the lattice boltzmann method", International Journal of Heat and Mass Transfer, Vol. 50, No. 17-18, (2007), 3315-3328.
23
24. Brinkman, H., "The viscosity of concentrated suspensions and solutions", The Journal of Chemical Physics, Vol. 20, No. 4, (1952), 571-571.
24
25. Fox, R.W., McDonald, A.T. and Pritchard, P.J., "Introduction to fluid mechanics 6th edition, john wiley & sons", Wiley, New York, (2004).
25
ORIGINAL_ARTICLE
Experimental Investigation of Surface Roughness and Kerf Width During Machining of Blanking Die Material on Wire Electric Discharge Machine
Wire electric discharge machine (WEDM) is spark erosion in unconventional machining technique to cut hard and the conductive material with a wire as an electrode. The blanking die material SKD 11 is a high carbon and high chromium tool steel with high hardness and high wearing resistance property. This tool steel has broad application in press tools and dies making industries. In this research study the behavior of six process parameters includes Ton (pulse on time), Toff (pulse off time), IP (peak current), SV (servo voltage), WF (wire feed rate) and WT (wire tension) base on design of experiment method during WEDM of SKD 11 were experimentally studied. The 0.25 mm diameter of the brass wire has used as the electrode to cut the work piece. The surface roughness and kerf width are selected as performance measurement. Response Surface methodology (RSM) is utilized for process optimization as well as for formulating regression model for correlating process parameters with performance measurements.
https://www.ije.ir/article_82218_48c1debb878d35c07a52becca90dbdef.pdf
2018-10-01
1760
1766
Wire Electric Discharge Machine
SKD 11
tool steel
Response Surface Methodology
Surface roughness
Kerf Width
S. S.
Patel
1
Gujarat Technological University, Chandkheda, Ahmedabad, Gujarat, India
LEAD_AUTHOR
J. M.
Prajapati
2
Faculty of Technology and Engineering, M.S. University, Baroda, Gujarat, India
AUTHOR
1. Kumar, A., Panchal, J. and Garg, D., "Optimization of control factors for en-42 on wedm using taguchi method", International Journal of Multidisciplinary and Current Research, Vol. 5, (2017), 371-378.
1
2. Sharma, N., Khanna, R. and Gupta, R., "Multi quality characteristics of wedm process parameters with rsm", Procedia Engineering, Vol. 64, (2013), 710-719.
2
3. Ghodsiyeh, D., Golshan, A. and Izman, S., "Multi-objective process optimization of wire electrical discharge machining based on response surface methodology", Journal of the Brazilian Society of Mechanical Sciences and Engineering, Vol. 36, No. 2, (2014), 301-313.
3
4. Datta, S. and Mahapatra, S., "Modeling, simulation and parametric optimization of wire edm process using response surface methodology coupled with grey-taguchi technique", International Journal of Engineering, Science and Technology, Vol. 2, No. 5, (2010), 162-183.
4
5. Rao, P.S., Ramji, K. and Satyanarayana, B., "Effect of wedm conditions on surface roughness: A parametric optimization using taguchi method", International Journal of Advanced Engineering Sciences and Technologies, Vol. 6, No. 1, (2011), 41-48.
5
6. Rajesh, R. and Anand, M.D., "The optimization of the electro-discharge machining process using response surface methodology and genetic algorithms", Procedia Engineering, Vol. 38, (2012), 3941-3950.
6
7. Ghodsiyeh, D., Golshan, A., Hosseininezhad, N., Hashemzadeh, M. and Ghodsiyeh, S., "Optimizing finishing process in wedming of titanium alloy (TI6AL4V) by zinc coated brass wire based on response surface methodology", Indian Journal of Science and Technology, Vol. 5, No. 10, (2012), 3365-3377.
7
8. Lusi, N., Soepangkat, B.O.P., Pramujati, B. and Agustin, H., "Multiple performance optimization in the wire edm process of skd61 tool steel using taguchi grey relational analysis and fuzzy logic", in Applied Mechanics and Materials, Trans Tech Publ. Vol. 493, (2014), 523-528.
8
9. Sudhakara, D. and Prasanthi, G., "Review of research trends: Process parametric optimization of wire electrical discharge machining (wedm)", International Journal of Current Engineering and Technology, Vol. 2, No. 1, (2014), 131-140.
9
10. Kumar, V., Jangra, K.K., Kumar, V. and Sharma, N., "Wedm of nickel based aerospace alloy: Optimization of process parameters and modelling", International Journal on Interactive Design and Manufacturing (IJIDeM), Vol. 11, No. 4, (2017), 917-929.
10
11. Mohapatraa, K., Satpathya, M. and Sahooa, S., "Comparison of optimization techniques for mrr and surface roughness in wire edm process for gear cutting", International Journal of Industrial Engineering Computations, Vol. 8, No. 2, (2017), 251-262.
11
12. Chakraborty, S. and Bose, D., "Improvement of die corner inaccuracy of inconel 718 alloy using entropy based gra in wedm process", in Advanced Engineering Forum, Trans Tech Publ. Vol. 20, (2017), 29-41.
12
13. Sivaraman, B., Eswaramoorthy, C. and Shanmugham, E., "Optimal control parameters of machining in cnc wire-cut edm for titanium", International Journal of Applied Sciences and Engineering Research, Vol. 4, No. 1, (2015), 102–121.
13
14. Patel, S.S. and Prajapati, J., "Multi-criteria decision making approach: Selection of blanking die material", International Journal of Engineering, Vol. 30, No. 5, (2017), 800-806.
14
15. Hewidy, M., El-Taweel, T. and El-Safty, M., "Modelling the machining parameters of wire electrical discharge machining of inconel 601 using RSM", Journal of Materials Processing Technology, Vol. 169, No. 2, (2005), 328-336.
15
16. Aggarwal, V., Khangura, S.S. and Garg, R., "Parametric modeling and optimization for wire electrical discharge machining of inconel 718 using response surface methodology", The International Journal of Advanced Manufacturing Technology, Vol. 79, No. 1-4, (2015), 31-47.
16
17. Garg, S.K., Manna, A. and Jain, A., "An investigation on machinability of Al/10% ZrO2 (p)-metal matrix composite by wedm and parametric optimization using desirability function approach", Arabian Journal for Science and Engineering, Vol. 39, No. 4, (2014), 3251-3270.
17
ORIGINAL_ARTICLE
Analytical Investigation of Tire-Road Contact Characteristics for Wheelchair Robots Safely Running
To effectively improve the tire grounding behaviors of wheelchair robots, an analytical method is proposed to analyze and optimize the tire grounding safety. Firstly, taking the cushion and tires as the vibration isolation elements with stiffness and damping, the vertical vibration model of the human-wheelchair robot is established. Then, taking the random excitation as the typical input, the formulae of the TDD (tire dynamic deflection) frequency response function H and the RMS (root mean square) response are derived and the response coefficient λ is proposed. Moreover, the influence laws of system parameters on H and λ are revealed. Thirdly, based on λ, the analytical optimization model for the cushion system damping ratio ξ2 is established. Finally, a case study and numerical simulation were carried out. The results show that the relative deviation of the cushion optimal damping is about 0.3%.
https://www.ije.ir/article_82219_1c4b8ff2524190391fe8820867c9a6ab.pdf
2018-10-01
1767
1772
wheelchair Robots
Tire
Safety Analysis
analytical method
Running Process
C.
Zhou
1
School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, China
AUTHOR
L.
Zhao
2
School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, China
LEAD_AUTHOR
Y.
Yu
3
School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, China
AUTHOR
X.
Li
4
School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, China
AUTHOR
1. Kanjanawanishkul, K., “Path following and velocity optimizing for an omnidirectional mobile robot”, International Journal of Engineering, Transactions A: Basics, Vol. 28, No. 4, (2015), 537–545.
1
2. Korayem, M.H., Azimirad, V., and Peydaie, P., “Investigation on the Effect of Different Parameters in Wheeled Mobile Robot Error (TECHNICAL NOTE)”, International Journal of Engineering - Transactions A: Basics, Vol. 20, No. 2, (2007), 195–210.
2
3. Travlos, V., Patman, S., Wilson, A., Simcock, G., and Downs, J., “Quality of Life and Psychosocial Well-Being in Youth With Neuromuscular Disorders Who Are Wheelchair Users: A Systematic Review”, Archives of Physical Medicine and Rehabilitation, Vol. 98, No. 5, (2017), 1004–1017.
3
4. Kundu, A.S., Mazumder, O., Lenka, P.K., and Bhaumik, S., “Design and Performance Evaluation of 4 Wheeled Omni Wheelchair with Reduced Slip and Vibration”, Procedia Computer Science, Vol. 105, No. 105, (2017), 289–295.
4
5. Requejo, P., Maneekobkunwong, S., McNitt-Gray, J., Adkins, R., and Waters, R., “Influence of hand-rim wheelchairs with rear suspension on seat forces and head acceleration during curb descent landings”, Journal of Rehabilitation Medicine, Vol. 41, No. 6, (2009), 459–466.
5
6. Hischke, M., and Reiser, R.F., “Effect of Rear Wheel Suspension on Tilt-in-Space Wheelchair Shock and Vibration Attenuation.”, PM & R : the journal of injury, function, and rehabilitation, (2018), DOI: 10.1016/j.pmrj.2018.02.009.
6
7. Silva, L.C.A., Dedini, F.G., Corrêa, F.C., Eckert, J.J., and Becker, M., “Measurement of wheelchair contact force with a low cost bench test”, Medical Engineering & Physics, Vol. 38, No. 2, (2016), 163–170.
7
8. Ababou, A., Ababou, N., Morsi, T., and Boukhechem, L., “Test Bench for Analysis of Harmful Vibrations Induced to Wheelchair Users”, In Proceedings of the International Conference on Biomedical Electronics and Devices, SCITEPRESS - Science and and Technology Publications, (2014), 147–153.
8
9. Miyawaki, K., and Takahashi, D., “Investigation of whole-body vibration of passenger sitting on wheelchair and of passenger sitting on wheelchair loaded on lifter”, In International Symposium on Micro-NanoMechatronics and Human Science (MHS), IEEE, (2016), 1–6.
9
10. Wang, S., Zhao, L., Hu, Y., and Yang, F., “Impact Responses and Parameters Sensitivity Analysis of Electric Wheelchairs”, Electronics, Vol. 7, No. 6, (2018), 87–104.
10
11. Geng, Z., Popov, A.A., and Cole, D.J., “Measurement, identification and modelling of damping in pneumatic tyres”, International Journal of Mechanical Sciences, Vol. 49, No. 10, (2007), 1077–1094.
11
12. Dąbek, P., and Trojnacki, M., “Tire Models for Studies of Wheeled Mobile Robot Dynamics on Rigid Grounds – A Quantitative Analysis for Longitudinal Motion”, In International Conference on Systems, Control and Information Technologies 2016 (SCIT 2016), Springer, Cham, Vol. 543, (2017), 409–424.
12
13. Levratti, A., Riggio, G., De Vuono, A., Fantuzzi, C., and Secchi, C., “Safe navigation and experimental evaluation of a novel tire workshop assistant robot”, In IEEE International Conference on Robotics and Automation (ICRA), IEEE, (2017), 994–999.
13
14. Zhao, L., Yu, Y., Zhou, C., Li, X., and Yang, F., “Modeling and analytic optimization of dynamic comfort for wheelchair robots undergoing random roads”, International Journal of Modeling, Simulation, and Scientific Computing, (2018), DOI: 10.1142/S1793962318500447.
14
ORIGINAL_ARTICLE
Probability Approach for Prediction of Pitting Corrosion Fatigue Life of Custom 450 Steel
In this study, the pitting type of corrosion growth characteristics, fatigue crack initiation and propagation behavior; axial fatigue tests were carried out on precipitation hardened martensitic Custom 450 steel in the air and 3.5wt% NaCl solution. Using the ratio of the depth to the half-width of the pits; (a/c)= 1.5±0.2 the corrosion pit depth growth law was obtained as a function of stress amplitude and elapsed time, t. Fatigue crack growth rates were determined in the near threshold stress intensity factors regime (∆kth). A model was presented for estimation of corrosion fatigue life based on the time to reach critical pit depth (as crack initiation) and crack propagation life. Then. S-N curves were obtained both in air and NaCl solution from axial fatigue testing. Comparison of data from the proposed model and the experimental results (S-N curves) showed good agreement.
https://www.ije.ir/article_82220_e15c939b429a7cfa2b5f7115a901e833.pdf
2018-10-01
1773
1781
Corrosion fatigue
Corrosion Pit
Crack propagation
High Cycle Fatigue
Custom 450 Steel
A.
Salarvand
1
Department of Mechanical Engineering, Islamic Azad University, Doroud Branch, Iran
AUTHOR
E.
Poursaiedi
2
Department of Mechanical Engineering, University of Zanjan, Zanjan, Iran
LEAD_AUTHOR
A.
Azizpour
3
Department of Mechanical Engineering, University of Zanjan, Zanjan, Iran
AUTHOR
1. Poursaeidi, E., Sanaieei, M., and Bakhtyari, H., “Life Estimate of a Compressor Blade through Fractography”, International Journal of Engineering - Transactions A: Basics, Vol. 26, No. 4, (2012), 393–400.
1
2. Poursaeidi, E., Babaei, A., Behrouzshad, F., and Mohammadi Arhani, M.R., “Failure analysis of an axial compressor first row rotating blades”, Engineering Failure Analysis, Vol. 28, (2013), 25–33.
2
3. Poursaeidi, E., and Pedram, O., “An Outrun Competition of Corrosion Fatigue and Stress Corrosion Cracking on Crack Initiation in a Compressor Blade”, International Journal of Engineering - Transactions B: Applications, Vol. 27, No. 5, (2013), 785–792.
3
4. Lindley, T.C., Mcintyre, P., and Trant, P.J., “Fatigue-crack initiation at corrosion pits”, Metals Technology, Vol. 9, No. 1, (1982), 135–142.
4
5. Kondo, Y., “Prediction of fatigue crack initation life based on pit growth”, Corrosion, Vol. 45, No. 1, (1989), 7–11.
5
6. Kawai, S., and Kasai, K., “Considerations of Allowable Stress of Corrosion Fatigue (Focussed on the Influence of Pitting)”, Fatigue & Fracture of Engineering Materials & Structures, Vol. 8, No. 2, (1985), 115–127.
6
7. Turnbull, A., McCartney, L.N., and Zhou, S., “A model to predict the evolution of pitting corrosion and the pit-to-crack transition incorporating statistically distributed input parameters”, Corrosion Science, Vol. 48, No. 8, (2006), 2084–2105.
7
8. Sriraman, M.R., and Pidaparti, R.M., “Crack Initiation Life of Materials Under Combined Pitting Corrosion and Cyclic Loading”, Journal of Materials Engineering and Performance, Vol. 19, No. 1, (2010), 7–12.
8
9. Cavanaugh, M., Buchheit, R., and Birbilis, N., “Modeling the environmental dependence of pit growth using neural network approaches”, Corrosion Science, Vol. 52, No. 9, (2010), 3070–3077.
9
10. Sriraman, M.R., and Pidaparti, R.M., “Life Prediction of Aircraft Aluminum Subjected to Pitting Corrosion Under Fatigue Conditions”, Journal of Aircraft, Vol. 46, No. 4, (2009), 1253–1259.
10
11. Ishihara, S., Saka, S., Nan, Z.Y., Goshima, T., and Sunada, S., “Prediction of Corrosion Fatigue Lives of Aluminium Alloy on The Basis of Corrosion Pit Growth Law”, Fatigue and Fracture of Engineering Materials and Structures, Vol. 29, No. 6, (2006), 472–480.
11
12. Shi Pan, M.S., “Damage tolerance approach for probabilistic pitting corrosion fatigue life prediction”, Engineering Fracture Mechanics, Vol. 68, No. 13, (2001), 1493–1507.
12
13. Bastidas-Arteaga, E., Bressolette, P., Chateauneuf, A., and Sánchez-Silva, M., “Probabilistic lifetime assessment of RC structures under coupled corrosion–fatigue deterioration processes”, Structural Safety, Vol. 31, No. 1, (2009), 84–96.
13
14. Lin, C.K., and Tsai, W.J., “Corrosion fatigue behaviour of a 15Cr-6Ni precipitation-hardening stainless steel in different tempers”, Fatigue and Fracture of Engineering Materials and Structures, Vol. 23, No. 6, (2000), 489–497.
14
15. Schonbauer, B.M., Stanzl-Tschegg, S.E., Perlega, A., Salzman, R.N., Rieger, N.F., Zhou, S., Turnbull, A., and Gandy, D., “Fatigue life estimation of pitted 12% Cr steam turbine blade steel in different environments and at different stress ratios”, International Journal of Fatigue, Vol. 65, (2014), 33–43.
15
16. Schonbauer, B.M., Perlega, A., Karr, U.P., Gandy, D., and Stanzl-Tschegg, S.E., “Pit-to-crack transition under cyclic loading in 12% Cr steam turbine blade steel”, International Journal of Fatigue, Vol. 76, (2015), 19–32.
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18. Lindström, R., Johansson, L., Thompson, G., Skeldon, P., and Svensson, J.E., “Corrosion of magnesium in humid air”, Corrosion Science, Vol. 46, No. 5, (2004), 1141-1158.
18
19. Harlow, D.G., and Wei, R.P., “A probability model for the growth of corrosion pits in aluminum alloys induced by constituent particles”, Engineering Fracture Mechanics, Vol. 59, No. 3, (1998), 305–325.
19
20. Medved, J.J., Breton, M., and Irving, P.E., “Corrosion pit size distributions and fatigue lives—a study of the EIFS technique for fatigue design in the presence of corrosion”, International Journal of Fatigue, Vol. 26, No. 1, (2004), 71–80.
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21. Xie J., Alpas A.T., Northwood D.O., “A mechanism for the crack initiation of corrosion fatigue of Type 316L stainless steel in Hank’s solution”, Materials Characterization, Vol. 48, No. 4, (2002), 271–277.
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25. Kosa, T., and DeBold, T., “Effect of Heat Treatment and Microstructure on the Mechanical and Corrosion Properties of a Precipitation Hardenable Stainless Steel”, In MiCon 78: Optimization of Processing, Properties, and Service Performance Through Microstructural Control, ASTM International, (1979), 367–392.
25
26. ASTM, “Standard Practice for Conducting Force Controlled Constant Amplitude Axial Fatigue Tests of Metallic Materials”, ASTM E466 - 15, ASTM International, (2002), 4–8.
26
ORIGINAL_ARTICLE
Investigation of Different Validation Parameters of Micro Gas Turbine for Range Extender Electric Truck
Nowadays the demand for reducing pollutant emissions and fuel consumption have paved the way of developing more fuel-efficient power generation system for transportation sector. Micro gas turbine (MGT) system can be an alternative to internal combustion reciprocating engine due to its light-weight and less fuel consumption. In this paper, some major running and operating characteristics of MGT are evaluated for the validation of the system for range extender electric truck. First noise characteristic of the system are investigated, then performance at high ambient temperature and variation of electrical output with and without the use of air filtration are investigated. The noise characteristics of MGT are different from diesel engine. At lower rpm and lower operating temperature, the electrical output of the system increases rapidly. All the found results are either compared with other systems or validated by comparing with the data provided by the manufacturer where necessary. The emission characteristics of MGT are different from other reciprocating engines. With the increase of power output the emissions of MGT reduces significantly. Finally, some noise reduction methods are recommended.
https://www.ije.ir/article_82221_abe94429144e075bc40065aa7668dc7b.pdf
2018-10-01
1782
1788
micro gas turbine
Range Extender Electric Vehicle
Truck
Noise Characteristics
Air Filtration
A.
Arefin
1
Department of Mechanical Engineering, Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh
AUTHOR
R.
Islam
2
Department of Mechanical Engineering, Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh
LEAD_AUTHOR
1. Dinh, T., Marco, J., Greenwood, D., Harper, L., and Corrochano, D., “Powertrain modelling for engine stop–start dynamics and control of micro/mild hybrid construction machines”, Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics, Vol. 231, No. 3, (2017), 439–456.
1
2. Cunha, H.E., and Kyprianidis, K.G., “Investigation of the Potential of Gas Turbines for Vehicular Applications”, In ASME Turbo Expo 2012: Turbine Technical Conference and Exposition, ASME (American Society of Mechanical Engineers), (2012), 51–64.
2
3. Seo, J., Lim, H.S., Park, J., Park, M.R., and Choi, B.S., “Development and experimental investigation of a 500-W class ultra-micro gas turbine power generator”, Energy, Vol. 124, No. 124, (2017), 9–18.
3
4. Bracco, S., and Delfino, F., “A mathematical model for the dynamic simulation of low size cogeneration gas turbines within smart microgrids”, Energy, Vol. 119, No. 119, (2017), 710–723.
4
5. Kiribayashi, S., Yakushigawa, K., and Nagatani, K., “Design and Development of Tether-Powered Multirotor Micro Unmanned Aerial Vehicle System for Remote-Controlled Construction Machine”, Part of the Field and Service Robotics, Springer, Cham, (2018), 637–648.
5
6. Rahman, M., and Malmquist, A., “Modeling and Simulation of an Externally Fired Micro-Gas Turbine for Standalone Polygeneration Application”, Journal of Engineering for Gas Turbines and Power, Vol. 138, No. 11, (2016), 112301–112315.
6
7. Tan, F.X., Chiong, M.S., Rajoo, S., Romagnoli, A., Palenschat, T., and Martinez-Botas, R.F., “Analytical and Experimental Study of Micro Gas Turbine as Range Extender for Electric Vehicles in Asian Cities”, Energy Procedia, Vol. 143, (2017), 53–60.
7
8. Karvountzis-Kontakiotis, A., Mahmoudzadeh Andwari, A., Pesyridis, A., Russo, S., Tuccillo, R., and Esfahanian, V., “Application of Micro Gas Turbine in Range-Extended Electric Vehicles”, Energy, Vol. 147, (2018), 351–361.
8
9. Gounder, J.D., Zizin, A., Oliver, L., Rachner, M., Kulkarni, S.R., and Aigner, M., “Experimental and numerical investigation of spray characteristics in a new FLOX® based combustor for liquid fuels for Micro Gas Turbine Range Extender (MGT-REX)”, In 52nd AIAA/SAE/ASEE Joint Propulsion Conference, American Institute of Aeronautics and Astronautics, (2016).
9
10. Capata, R., “Experimental tests of the operating conditions of a micro gas turbine device”, Journal of Energy & Power Engineering, Vol. 09, (2015), 326–335.
10
11. Nader, W.S.B., Mansour, C.J., and Nemer, M.G., “Optimization of a Brayton external combustion gas-turbine system for extended range electric vehicles”, Energy, Vol. 150, (2018), 745–758.
11
12. Bou Nader, W.S., Mansour, C.J., Nemer, M.G., and Guezet, O.M., “Exergo-technological explicit methodology for gas-turbine system optimization of series hybrid electric vehicles”, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Vol. 232, No. 10, (2018), 1323–1338.
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13. Nada, T., “Performance characterization of different configurations of gas turbine engines”, Propulsion and Power Research, Vol. 03, No. 3, (2014), 121–132.
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14. Dellenback, P.A., “Improved gas turbine efficiency through alternative regenerator configuration”, Journal of Engineering for Gas Turbines and Power, Vol. 124, No. 3, (2002), 441–446.
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15. Buonomano, A., Calise, F., D’Accadia, M.D., Palombo, A., and Vicidomini, M., “Hybrid solid oxide fuel cells–gas turbine systems for combined heat and power: A review”, Applied Energy, Vol. 156, No. 156, (2015), 32–85.
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16. Ehsani, M., Gao, Y., Longo, S., and Ebrahimi, K., “ Modern electric, hybrid electric, and fuel cell vehicles”, CRC press, (2018).
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17. Fernández, R.A., Caraballo, S.C., Cilleruelo, F.B., and Lozano, J.A., “Fuel optimization strategy for hydrogen fuel cell range extender vehicles applying genetic algorithms”, Renewable and Sustainable Energy Reviews, Vol. 81, (2018), 655–668.
17
18. Farrell, J.T., Kelly, K.J., Duran, A.W., Lammert, M.P., and Miller, E.S., “NREL/Industry Range-Extended Electric Vehicle for Package Delivery”, NREL/PR-5400-70558, National Renewable Energy Lab. (NREL), Golden, CO (United States) (2018).
18
19. Sun, H., Qin, J., Hung, T.C., Lin, C.H., and Lin, Y.F., “Performance comparison of organic Rankine cycle with expansion from superheated zone or two-phase zone based on temperature utilization rate of heat source”, Energy, Vol. 149, (2018), 566–576.
19
20. Shah, R.M.A., McGordon, A., Amor-Segan, M., and Jennings, P., “Micro Gas Turbine Range Extender - Validation Techniques for Automotive Applications”, In Hybrid and Electric Vehicles Conference 2013 (HEVC 2013), Institution of Engineering and Technology, (2013).
20
21. Duan, J., Fan, S., Wu, F., Sun, L., and Wang, G., “Power balance control of micro gas turbine generation system based on supercapacitor energy storage”, Energy, Vol. 119, No. 119, (2017), 442–452.
21
22. Sarradj, E., Geyer, T., Jobusch, C., Kießling, S., and Neefe, A., “Noise Characteristics of a Micro Gas Turbine for Use in a Serial Hybrid Concept”, In 8th International Styrian Noise, Vibration & Harshness Congress: The European Automotive Noise Conference, SAE Technical Paper, (2014).
22
23. ISO, “Acoustics - Noise emitted by machinery and equipment - Determination of emission sound pressure levels at a work station and at other specified positions applying accurate environmental corrections”, ISO 11204:2010 (en), (2010), https://www.iso.org/standard/54906.html
23
24. Leitch, R.R., and Tokhi, M.O., “Active noise control systems”, IEE Proceedings A - Physical Science, Measurement and Instrumentation, Management and Education - Reviews, Vol. 6, No. 134, (1987), 525–546.
24
ORIGINAL_ARTICLE
Improvement of Efficiency of Coal-Fired Steam Power Plant by Reducing Heat Rejection Temperature at Condenser Using Kalina Cycle
This paper proposes an approach for improving the plant efficiency by reducing the heat rejection temperature of power cycle using Kalina Cycle System 11 (KCS11) which is integrated at the steam condenser of a 500 MWe SubC (subcritical) coal-fired power plant. It is modelled by using power plant simulation software ‘Cycle Tempo’ at different plant operating conditions. Results show that the additional net electric power of 5.14 MWe from KCS11 improves the net energy and exergy efficiencies of the power plant by about 0.302 % point and 0.27 % point, respectively at full load over the stand-alone coal-fired steam power plant. Thereby, the carbon dioxide (CO2) emission is reduced by about 2.02 t/h at full load. Combined plant efficiencies decrease with decrease in evaporator outlet temperature due to decrease in vapour quality of binary mixture at turbine inlet and higher steam turbine back pressure. Levelized Cost of Electricity (LCoE) generation and payback period of the combined cycle power plant are about Rs 1.734 and 4.237 years, respectively and the cost of fuel saving is about Rs 0.685 per kg of coal which is lower than the fuel cost.
https://www.ije.ir/article_82222_a3410a730addf0dd98fe1588becd2ee6.pdf
2018-10-01
1789
1795
Condenser waste heat
Energy
Exergy
Environment
Kalina Cycle
G.
Khankari
1
Department of Mechanical Engineering, National Institute of Technology Durgapur, West Bengal, India
LEAD_AUTHOR
S.
Karmakar
2
Department of Mechanical Engineering, National Institute of Technology Durgapur, West Bengal, India
AUTHOR
1. He, J., Liu, C., Xu, X., Li, Y., Wu, S. and Xu, J., “Performance research on modified KCS (Kalina cycle system) 11 without throttle valve”, Energy, Vol. 64, (2014), 389–397.
1
2. Matsuda, K., “Low heat power generation system”, Applied Thermal Engineering, Vol. 70, No. 2, (2014), 1056–1061.
2
3. Vidhi, R., Kuravi, S., Goswami, D.,Y. Stefanakos, E. and Sabau, A.S., “Organic Fluids in a Supercritical Rankine Cycle for Low Temperature Power Generation”, Journal of Energy Resources Technology, Vol. 135, No. 4, (2013), 042002.
3
4. Shokati, N., Ranjbar, F. and Mohammadkhani, F., “Comparison of Single-stage and Two-stage Tubular SOFC-GT Hybrid Cycles: Energy and Exergy Viewpoints”, International Journal of Engineering - Transactions A: Basics, Vol. 28, No. 4, (2015), 618–626.
4
5. Kim, H.J., Moon, J.H. and Kim, Y.H., “Design and testing of an algebraic scroll expander for power generation from a waste heat recovery system”, Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, Vol. 229, No. 8, (2015), 1019–1031.
5
6. Hettiarachchi, H.M., Golubovic, M., Worek, W.M. and Ikegami, Y., “The Performance of the Kalina Cycle System 11(KCS-11) With Low-Temperature Heat Sources”, Journal of Energy Resources Technology, Vol. 129, No. 3, (2007), 243–247.
6
7. Nami, H., Mohammadkhani, F. and Ranjbar, F., “Thermodynamic Analysis and Optimization of a Novel Cogeneration System: Combination of a gas Turbine with Supercritical CO2 and Organic Rankine Cycles (TECHNICAL NOTE)”, International Journal of Engineering - Transactions C: Aspects, Vol. 29, No. 12, (2016), 1765–1774.
7
8. Roy, J.P., Mishra, M.K. and Misra, A., “Parametric optimization and performance analysis of a waste heat recovery system using Organic Rankine Cycle”, Energy, Vol. 35, No. 12, (2010), 5049–5062.
8
9. Peris, B., Navarro-Esbrí, J., Molés, F., Collado, R. and Mota-Babiloni, A., “Performance evaluation of an Organic Rankine Cycle (ORC) for power applications from low grade heat sources”, Applied Thermal Engineering, Vol. 75, (2015), 763–769.
9
10. Khankari, G., Karmakar, S., “Power generation from coal mill rejection using Kalina cycle”, Journal of Energy Resources Technology, Vol. 138, No. 5, (2016), 052004.
10
11. Delft University of Technology, Cycle-Tempo Release 5.0, software, (2008), http:// www.tudelft.nl.
11
12. Suresh, M.V.J.J., Reddy, K.S. and Kolar, A.K., “4-E (Energy, Exergy, Environment, and Economic) analysis of solar thermal aided coal-fired power plants”, Energy for Sustainable Development, Vol. 14, No. 4, (2010), 267–279.
12
ORIGINAL_ARTICLE
Investigation of Barium Sulfate Precipitation and Prevention Using Different Scale Inhibitors under Reservoir Conditions
In this work, scaling tendency and amount of precipitation of barium sulfate (BaSO4) were determined; the process is depending on temperature, pressure and mixing ratio of injection and formation of waters. Results showed that BaSO4 precipitation is largely dependent on mixing ratio. Temperature and pressure had no influence on BaSO4 precipitation. Different scale inhibitors, including a new inhibitor package, were used for preventing BaSO4 precipitation. The new scale inhibitor consists of three different acids such as phosphonate acid, hydrochloric acid solution, isopropyl alcohol, ammonium chloride and water. In addition, the lowest interfacial tensionon the boundary of oil and new inhibitor occurred at 10% of hydrochloric acid. Furthermore, effect of temperature, mixing ratio of waters and barium concentration on the inhibition efficiency of BaSO4 formation was studied. Results showed that the new inhibitor has the highest efficiency for preventing BaSO4 precipitation at any temperature, mixing ratio and barium concentration. Moreover, formation damage due to BaSO4 formation with and without scale inhibitors was determined by core flood tests. In the presence of new inhibitor, the damaged rock permeability ratio was improved from 0.59 to 0.924.
https://www.ije.ir/article_82223_abe367b0cabb4fd905d8d1372c39e0a5.pdf
2018-10-01
1796
1802
barium sulfate
Formation Damage
Scale Inhibition
Scale Prediction
A.
Khormali
1
Department of Oil and Gas Fields Development and Operation, Saint-Petersburg Mining University, Saint-Petersburg, Russia
LEAD_AUTHOR
A. R.
Sharifov
2
Department of Oil and Gas Fields Development and Operation, Saint-Petersburg Mining University, Saint-Petersburg, Russia
AUTHOR
D. I.
Torba
3
Department of Oil and Gas Fields Development and Operation, Saint-Petersburg Mining University, Saint-Petersburg, Russia
AUTHOR
BinMerdhah, A. B., “Inhibition of barium sulfate scale at high-barium formation water”, Journal of Petroleum Science and Engineering, Vol. 90-91, (2012), 124-130.
1
Hennessy, A. J. B. and Graham, G. M., “The effect of additives on the co-crystallisation of calcium with barium sulphate”, Journal of Crystal Growth, Vol. 237-239, (2002), 2153-2159.
2
Molchanov, A. A. and Ageev, P. G., “Implementation of new technology is a reliable method of extracting reserves remaining in hydro-carbon deposits”, Journal of Mining institute, Vol. 227, (2017), 530-539.
3
Ahmadi, M. A., Mohammadzadeh, O. and Zendehboudi, S., “A cutting edge solution to monitor formation damage due to scale deposition: Application to oil recovery”, Canadian Journal of Chemical Engineering, Vol. 95, No. 5, (2017), 991-1003.
4
Haghtalab, A., Kamali, M. J. and Shahrabadi, A., “Prediction mineral scale formation in oil reservoirs during water injection”, Fluid Phase Equilibria, Vol. 373, (2014), 43-54.
5
Morenov, V. and Leusheva, E., “Development of drilling mud solution for drilling in hard rocks”, International Journal of Engineering, Transaction A: Basics, Vol. 30, No. 4, (2017), 620-626.
6
Kan, A. T. and Tomson, M. B., “Scale prediction for oil and gas production”, SPE Journal, Vol. 17, No. 2, (2012), 362-378.
7
Ranjbar, M., Khatami, R. and Younessi, R., “Prediction of sulfate scale depositions in oilfield operations using arithmetic of LR fuzzy numbers”, International Journal of Engineering, Transaction B: Applications, Vol. 19, No. 1, (2006), 99-106.
8
Oddo, J. E. and Tomson, M. B., “Why scale forms in the oil field and methods to predict it”, SPE Production & Facilities, Vol. 9, No. 1, (1994), 47-54.
9
Jamialahmadi, M. and Muller-Steinhage, H., “Mechanisms of scale deposition and scale removal in porous media”, International Journal of Oil, Gas and Coal Technology, Vol. 1, No. 1-2, (2008), 81-108.
10
El-Said, M., Ramzi, M. and Abdel-Moghny, T., “Analysis of oilfield waters by ion chromatography to determine the composition of scale deposition”, Desalination, Vol. 249, No. 2, (2009), 748-756.
11
Khormali, A., Petrakov, D. G. and AfshariMoein, M. J., “Experimental analysis of calcium carbonate scale formation and inhibition in waterflooding of carbonate reservoirs”, Journal of Petroleum Science and Engineering, Vol. 146, (2016), 843-850.
12
Shaw, S. S., and Sorbie, K. S., “Synergistic properties of phosphonate and polymeric scale inhibitor blends for barium sulfate scale inhibition”, SPE Production & Operations, Vol. 30, No. 1, (2015), 16-25.
13
Moayed, M. H., Abbaspour, Z. and Sadegian, M. H., “Study of pitting corrosion inhibition of mild steel by nitrite in concrete pore solution by polarization and zero resistance ammetery (ZRA) techniques”, International Journal of Engineering, Transaction B: Applications, Vol. 22, No. 4, (2009), 369-380.
14
Khormali, A., Petrakov, D. G. and NazariMoghaddam, R., “Study of adsorption/desorption properties of a new scale inhibitor package to prevent calcium carbonate formation during water injection in oil reservoirs”, Journal of Petroleum Science and Engineering, Vol. 153, (2017), 257-267.
15
Khormali, A., Sharifov, A. R. and Torba, D. I., “Increasing efficiency of calcium sulfate scale prevention using a new mixture of phosphonate scale inhibitors during waterflooding”, Journal of Petroleum Science and Engineering, Vol. 164, (2018), 245-258.
16
Chew, C. B. and Mat, R., “The efficacy of calcium carbonate scale inhibition by commercial polymer scale inhibitors”, Chemical Engineering Transactions, Vol. 45, (2015), 1471-1476.
17