2019
26
6
6
130
1

An optimal control strategy for parallel hybrid electric vehicles
http://scientiairanica.sharif.edu/article_20996.html
10.24200/sci.2018.20996
1
This paper proposes a new power management strategy (PMS) for parallel hybrid electric vehicles equipped with continuously variable transmission (CVT). The proposed PMS is established on the basis of electric assist control strategy (EACS) and equivalent consumption minimization strategy (ECMS). This control approach is based on maintaining the battery energy within a recommended range, considering the CVT efficiency in selecting the engine operating point, and finding the best power split between the engine and electric motor at certain moments of the driving. In order to evaluate the effectiveness of this scheme, it is compared with EACS, a modified version of EACS and ECMS. It is shown that, in all of the studied driving cycles, the proposed PMS is superior to the considered rival strategies in terms of the fuel consumption and also HC and CO emissions.
0

3245
3254


M.
Delkhosh
School of Mechanical Engineering, Sharif University of Technology, Tehran, P.O. Box 111559567, Iran
Iran
m_delkhosh@mech.sharif.edu


M.
Saadat Foumani
School of Mechanical Engineering, Sharif University of Technology, Tehran, P.O. Box 111559567, Iran
Iran
m_saadat@sharif.ir
Hybrid electric vehicle
continuously variable transmission
fuel consumption
emissions
speed ratio control
electric assist control strategy
equivalent consumption minimization strategy
[1. Martinez, C.M., Hu, X., Cao, D., Velenis, E., Gao, B., and Wellers, M. Energy management in plugin hybrid electric vehicles: recent progress and a connected vehicles perspective", IEEE Trans. Veh. Technol., 66(6), pp. 45344549 (2017). 2. Banvait, H., Anwar, S., and Chen, Y., A rulebased energy management strategy for Plugin Hybrid Electric Vehicle (PHEV)", ACC '09., pp. 39383943 (2009). 3. Boukehili, A., Zhang, Y., and Sun, S. Simulation and comparison of HEV battery control for best fuel economy and longer battery life", WEVJ, 4, pp. 421 426 (2010). 4. Dorri, M. and Shamekhi, A.H. Design and optimization of a new control strategy in a parallel hybrid electric vehicle in order to improve fuel economy", P I Mech. Eng. DJ Aut., 225(6), pp. 747759 (2011). 5. Majdi, L., Gha_ari, A., and Fatehi, N. Control strategy in hybrid electric vehicle using fuzzy logic controller", Robio, pp. 842847 (2009). 6. Safaei, A., Ha'iriYazdi, M.R., Esfahanian, V., Esfahanian, M., Tehrani, M.M., and Nehzati, H. Designing an intelligent control strategy for hybrid powertrains utilizing a fuzzy driving cycle identi_cation agent", P I Mech. Eng. DJ Aut., 229(9), pp. 11691188 (2014). M. Delkhosh and M. Saadat Foumani/Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3245{3254 3253 7. Pisu, P. and Rizzoni, G. A supervisory control strategy for series hybrid electric vehicles with two energy storage systems", VPPC, pp. 6572 (2005). 8. Park, J. and Park, J.H. Development of equivalent fuel consumption minimization strategy for hybrid electric vehicles", Int. J. of Automot Techn., 13(5), pp. 835843 (2012). 9. Wang, F., Mao, X.J., Zhuo, B., Zhong, H., and Ma, Z.L. Parallel hybrid electric system energy optimization control with automated mechanical transmission", P I Mech. Eng. DJ AUT., 223(2), pp. 151167 (2009). 10. Sinoquet, D., Rousseau, G., and Milhau, Y. Design optimization and optimal control for hybrid vehicles", Optim. Eng., 12(1), pp. 199213 (2009). 11. Mansour, C. and Clodic, D. Optimized energy management control for the Toyota hybrid system using dynamic programming on a predicted route with short computation time", Int. J. of Automot. Techn., 13(2), pp. 309324 (2012). 12. Guemri, M., Ne_ati, A., Caux, S., and Ngueveu, S.U. Management of distributed power in hybrid vehicles based on D.P. or fuzzy logic", Optim. Eng., 15(4), pp. 9931012 (2013). 13. Grothey, A. and Yang, X. Toppercentile tra_c routing problem by dynamic programming", Optim. Eng., 12(4), pp. 631655 (2011). 14. Gao, W. and Porandla, S.K. Design optimization of a parallel hybrid electric powertrain", VPPC, pp. 530 535 (2005). 15. Wang, Z., Huang, B., Xu, Y., and Li, W. Optimization of series hybrid electric vehicle operational parameters by simulated annealing algorithm", ICC, pp. 15361541 (2007). 16. Wu, J., Zhang, C.H., and Cui, N.X. PSO algorithmbased parameter optimization for HEV powertrain and its control strategy", Int. J. of Automot. Techn., 9(1), pp. 5359 (2008). 17. Wu, X., Cao, B., Wen, J., and Bian, Y. Particle swarm optimization for plugin hybrid electric vehicle control strategy parameter", VPPC, pp. 15 (2008). 18. Hu, X., Moura, S.J., Murgovski, N., Egardt, B., and Cao, D. Integrated optimization of battery sizing, charging, and power management in plugin hybrid electric vehicles", IEEE T Contr. Syst. T, 24(3), pp. 10361043 (2016). 19. Hu, X., Jiang, J., Egardt, B., and Cao, D. Advanced powersource integration in hybrid electric vehicles: Multicriteria optimization approach", IEEE Trans. Ind. Electron., 62(12), pp. 78477858 (2015). 20. Delkhosh, M., Saadat Foumani, M., and Rostami, P. Optimization of powertrain and control strategy of hybrid electric vehicle", Sci. Iran, 22(5), pp. 18421854 (2015). 21. Ryu, W., Cho, N., Yoo, I., Song, H., and Kim, H. Performance analysis of a CVT clutch system for a hybrid electric vehicle", Int. J. of Automot. Techn., 10(1), pp. 115121 (2009). 22. Wang, C.L., Yin, C.L., Zhang, T., and Zhu, L. Powertrain design and experiment research of a parallel hybrid electric vehicle", Int. J. of Automot. Techn., 10(5), pp. 589596 (2009). 23. Suh, B., Chang, Y.H., Han, S.B., and Chung, Y.J. Simulation of a powertrain system for the diesel hybrid electric bus", Int. J. of Automot. Techn., 13(5), pp. 701711 (2012). 24. Hu, X., Wang, H., and Tang, X. Cyberphysical control for energysaving vehicle following with connectivity", IEEE Trans. Ind. Electron., 64(11), pp. 8578 8587 (2017). 25. Carbone, G., Mangialardi, L., and Mantriota, G. A comparison of the performances of full and half toroidal traction drives", Mech. Mach. Theory, 39(9), pp. 921 942 (2004). 26. Delkhosh, M., Saadat Foumani, M., Azad, N.L., and Rostami, P. A new control strategy for hybrid electric vehicles equipped with continuously variable transmission", P I Mech. Eng. DJ Aut., 230(6), pp. 803816 (2015). 27. Delkhosh, M., Saadat Foumani, M., and Falahati, F. A modi_ed control strategy for parallel hybrid electric vehicles equipped with continuously variable transmission", Sci. Iran., 23(3), pp. 966975 (2016). 28. MontazeriGh, M., Poursamad, A., and Ghalichi, B. Application of genetic algorithm for optimization of control strategy in parallel hybrid electric vehicles", J. of Franklin Inst., 343(4), pp. 420435 (2006). 29. MontazeriGh, M. and Poursamad, A. Application of genetic algorithm for simultaneous optimisation of HEV component sizing and control strategy", Int. J. Altern. Propul., 1(1), pp. 6378 (2006). 30. Long, V.T. and Nhan, N.V. Beesalgorithmbased optimization of component size and control strategy parameters for parallel hybrid electric vehicles", Int. J. of Automot. Techn., 13(7), pp. 11771183 (2012). 31. Delkhosh, M., Saadat Foumani, M., Boroushaki, M., Ekhtiari, M., and Dehghani, M. Geometrical optimization of half toroidal continuously variable transmission using particle swarm optimization", Sci. Iran., 18(5), pp. 11261132 (2011). 32. Delkhosh, M., Saadat Foumani, M., and Boroushaki, M. Geometrical optimization of parallel in_nitely variable transmission to decrease vehicle fuel consumption", Mech. Based Des Struc., 24(4), pp. 483501 (2014). 33. Delkhosh, M. and Saadat Foumani, M. Optimisation of fulltoroidal continuously variable transmission in conjunction with _xed ratio mechanism using particle swarm optimisation", Vehicle Syst. Dyn., 51(5), pp. 671683 (2013). 3254 M. Delkhosh and M. Saadat Foumani/Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3245{3254 34. Sciarretta, A., Back, M., and Guzzella, L. Optimal control of parallel hybrid electric vehicles", IEEE T Contr. Syst. T, 12(3), pp. 352363 (2004). 35. Musardo, C., Staccia, B., MidlamMohler, S., Guezennec, Y., and Rizzoni, G. Supervisory control for NOx reduction of an HEV with a mixedmode HCCI/CIDI engine", ACC, pp. 38773881 (2005). 36. Pisu, P. and Rizzoni, G. A comparative study of supervisory control strategies for hybrid electric vehicles", IEEE T Contr. Syst. T, 15(3), pp. 506518 (2007). 37. Fan, B.S.M., Multidisciplinary Optimization of Hybrid Electric Vehicles: Component Sizing and Power Management Logic, University of Waterloo (2011). 38. Delprat, S., Guerra, T.M., and Rimaux, J. Optimal control of a parallel powertrain: from global optimization to real time control strategy", IEEE Veh. Technol. Conf., 4, pp. 20822088 (2002). 39. Statnikov, R.B. and Matusov, J.B., Multicriteria Optimization and Engineering, 1st Ed., Springer (1995). 40. Marler, R.T. and Arora, J.S. Survey of multiobjective optimization methods for engineering", Struct Multidisc. Optim., 26(6), pp. 369395 (2004). 41. Das, I. and Dennis, J.E. A closer look at drawbacks of minimizing weighted sums of objectives for Pareto set generation in multicriteria optimization problems", Struct. Optim., 14(1), pp. 6369 (1997). 42. Marler, R.T. and Arora, J.S. Survey of multiobjective optimization methods for engineering", Struct. Multidisc. Optim., 26(6), pp. 369395 (2004). 43. Yu, P.L. A class of solutions for group decision problems", Management Sci., 19(8), pp. 936946 (1973). 44. Saipa corporation", [Online]. Available: http://www. saipacorp.com/portal/Home/. 45. ADVISOR library reorganized structure", http:// advvehiclesim.sourceforge.net/LibReorg.html (2003). 46. Gita battery", [Online]. Available: http://www. gitabattery. com/. 47. Delkhosh, M. and Saadat Foumani, M. Multiobjective geometrical optimization of full toroidal CVT", Int. J. of Automot. Techn., 14(5), pp. 707715 (2013).##]
1

Design of conformal cooling channels by numerical methods in a metal mold and calculation of exergy destruction in channels
http://scientiairanica.sharif.edu/article_20894.html
10.24200/sci.2018.50090.1502
1
Shorter cycle times, better product quality and less product outage can be possible with faster cooling. But mold cooling channels can only be made in linear directions and limited forms via classical manufacturing methods. Therefore, it limits that performance of mold cooling. Developed in recent years additive manufacturing technologies are capable of building complex geometries and monoblock 3D products. With this technology it is possible to produce metal molds with conformal cooling channels in different forms and capable of qualified cooling. In this study, conformal cooling channels were designed in order to achieve optimum cooling in monoblock permanent mold. In this study, CFD (Computational Fluid Dynamic) analyses are performed to steady stead conditions for designed conformal cooling channels and classical cooling channel mold. Pressure drops, cooling channel outlet temperatures and exergy destructions are calculated depending on the flow velocity rate in channels. The numerical investigations of the cooling process have shown that approximately 5% higher cooling performance can be achieved with conformal cooling channels. However, the pressure drop in the conformal cooling is observed to be higher than classical cooling channel. In addition, exergy destruction in the conformal cooling channel is approximately 12% greater than the classical cooling channel.
0

3255
3261


A.
Bolatturk
Department of Mechanical Engineering, Suleyman Demirel University, Isparta, Turkey.
Turkey
alibolatturk@sdu.edu.tr


O.
Ipek
Department of Mechanical Engineering, Suleyman Demirel University, Isparta, Turkey.
Turkey
osmanipek@sdu.edu.tr


K.
Kurtulus
Department of Mechanical Engineering, Suleyman Demirel University, Isparta, Turkey.
Turkey
karanikurtulus@sdu.edu.tr


M.
KAN
Department of Mechanical Engineering, Suleyman Demirel University, Isparta, Turkey.
Turkey
mehmetkan@sdu.edu.tr
Metal Mold
Exergy Destruction
Cooling Channel Design
[1. Hsu, F.H., Wang, K., Huang, C.T., and Chang, R.Y. Investigation on conformal cooling system design in injection molding", Advances in Production Engineering & Management, 8(2), pp. 107115 (2013). 2. Holker, R. Haase, M. Khalifa, N.B., and Takkaya, A. E. Hot extrusion dies with conformal cooling channels produced by additive manufacturing", Aluminum Two Thousand World Congress and International Conference on Extrusion and Benchmark ICEB, pp. 4838 4846 (2015). 3. Sachs, E., Wylonis, E. Allen, S. Cima, M., and Guo, H. Production of injection moulding tooling with conformal cooling channels using the three dimensional printing process", Polymer Engineering and Science, 40(5), pp. 12371247 (2000). 4. Eimsaard, K. and Wannisorn, K. Conformal bubbler cooling for molds by metal deposition process", ComputerAided Design, 69, pp. 126133 (2015). 5. Wang, Y., Yu, K.M., and Wang, C.C.L. Spiral and conformal cooling in plastic injection molding", ComputerAided Design, 63, pp. 111 (2015). 6. Vojnov_a, E. The bene_ts of a conforming cooling systems the molds in injection moulding process", Procedia Engineering, 149, pp. 535543 (2016). 7. Venkatesh, G.Y., Ravi, K., and Raghavendra, G. Comparison of straight line to conformal cooling channel in injection molding", Materials Today: Proceedings, 4(2), pp. 11671173 (2017). 8. Jahan, A.S. and Mounayri, H. Optimal conformal cooling channels in 3D printed dies for plastic injection molding", Procedia Manufacturing, 5, pp. 888900 (2016). 9. Park, H. and Dang, X.P. Development of a smart plastic injection mold with conformal cooling channels", Procedia Manufacturing, 10, pp. 4859 (2017). 10. Wang, G., Zhao, G., Li, H., and Guan, Y. Multiobjective optimization design of the heating/cooling channels of the steamheating rapid thermal response mold using particle swarm optimization", Int. J. of Thermal Science, 50, pp. 790802 (2011). 11. Franke, M.M., Hilbinger, R.M., Lohmuller, A., and Singer, R.F. The e_ect of liquid metal cooling on thermal gradients in directional solidi_cation of super alloys: Thermal analysis", Journal of Material Processing Technology, 213, pp. 20812088 (2013). 12. Furumoto, T., Ueda, T., Amino, T., Ksunoki, D., Hosokowa, A., and Tanaka, T. Finishing performance of cooling channel with face protuberance inside the molding die", Journal of Material Processing Technology, 212, pp. 21542160 (2012). DOI: 10.1016/j.jmatprotec.2012.05.016 13. Khairul, M.A., Alim, M.A., Mahbubul, I.M., Saidur, R., Hepbasli, A., and Hossain, A. Heat transfer performance and exergy analyses of a corrugated plate heat exchanger using metal oxide nanouids", International Communications in Heat and Mass Transfer, 50, pp. 814 (2014). 14. Dizaji, H.S., Jafarmadar, S., and Asaadi, S. Experimental exergy analysis for shell and tube heat exchanger made of corrugated shell and corrugated tube", Experimental Thermal and Fluid Science, 81, pp. 475481 (2017). A. Bolatturk et al./Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3255{3261 3261 15. Ipek, O., Kan, M., and Gurel, B. Examination of di_erent heat exchangers and the thermal activities of di_erent designs", Acta Physica Polonica A, 132(3), pp. 580583 (2017). 16. Kan, M., Ipek, O., and Gurel, B. Plate heat exchangers as a compact design and optimization of di_erent channel angles", Acta Physica Polonica A, 128(2B), pp. B49 B52 (2015). 17. Karaail, R. and Ozturk, I. T. Thermoeconomic analyses of steam injected gas turbine cogeneration cycles", Acta Physica Polonica A, 128(2B), pp. B279 B281 (2015). 18. Zehtabiyan, R.N., Damirci, D.S., Fazel, Z.M.H., and Sa_ar, A.M. Generalized heat transfer and entropy generation of strati_ed airwater ow in entrance of a minichannel", Scientia Iranica, B, 24(5), pp. 2406 2417 (2017). 19. Nouri, B.A. and Seyyed, H.M.H. Numerical analysis of thermally developing turbulent ow in partially _lled porous pipes", Scientia Iranica, B, 22(3), pp. 835843 (2015). 20. Altinsoy, _I., C_ elebi Efe, G.F., Yener, T., onder, K.G., and Bindal, C. E_ect of double stage nitriding on 34CrAlNi710 nitriding steel", Acta Physica Polonica A, 132, pp. 663666 (2017). 21. Arunkumar, S., Rao, K.S., and Kumar, T.P. Spatial variation of heat ux at the metalmold interface due to mold _lling e_ects in gravity diecasting", Int. J. of Heat and Mass Transfer, 51(11), pp. 26762685 (2008). 22. Hallam, C.P. and Gri_ths, W.D. A model of the interfacial heattransfer coe_cient for the aluminum gravity diecasting process", Metallurgical and Materials Transactions B, 35(4), pp. 721733 (2004). 23. Imran, A.A., Nabeel, S.M., and Hayder, M.J. Numerical and experimental investigation of heat transfer in liquid cooling serpentine minichannel heat sink with di_erent new con_guration models", Thermal Science and Engineering Progress, 6, pp. 128139 (2018). 24. Fluent, Version 16.1 User's Guide, Fluent Inc., Lebanon (NH) (2016). 25. Klein, S.A. Engineering Equation Solver (EES)", Academic Commercial1. Hsu, F.H., Wang, K., Huang, C.T., and Chang, R.Y. Investigation on conformal cooling system design in injection molding", Advances in Production Engineering & Management, 8(2), pp. 107115 (2013). 2. Holker, R. Haase, M. Khalifa, N.B., and Takkaya, A. E. Hot extrusion dies with conformal cooling channels produced by additive manufacturing", Aluminum Two Thousand World Congress and International Conference on Extrusion and Benchmark ICEB, pp. 4838 4846 (2015). 3. Sachs, E., Wylonis, E. Allen, S. Cima, M., and Guo, H. Production of injection moulding tooling with conformal cooling channels using the three dimensional printing process", Polymer Engineering and Science, 40(5), pp. 12371247 (2000). 4. Eimsaard, K. and Wannisorn, K. Conformal bubbler cooling for molds by metal deposition process", ComputerAided Design, 69, pp. 126133 (2015). 5. Wang, Y., Yu, K.M., and Wang, C.C.L. Spiral and conformal cooling in plastic injection molding", ComputerAided Design, 63, pp. 111 (2015). 6. Vojnov_a, E. The bene_ts of a conforming cooling systems the molds in injection moulding process", Procedia Engineering, 149, pp. 535543 (2016). 7. Venkatesh, G.Y., Ravi, K., and Raghavendra, G. Comparison of straight line to conformal cooling channel in injection molding", Materials Today: Proceedings, 4(2), pp. 11671173 (2017). 8. Jahan, A.S. and Mounayri, H. Optimal conformal cooling channels in 3D printed dies for plastic injection molding", Procedia Manufacturing, 5, pp. 888900 (2016). 9. Park, H. and Dang, X.P. Development of a smart plastic injection mold with conformal cooling channels", Procedia Manufacturing, 10, pp. 4859 (2017). 10. Wang, G., Zhao, G., Li, H., and Guan, Y. Multiobjective optimization design of the heating/cooling channels of the steamheating rapid thermal response mold using particle swarm optimization", Int. J. of Thermal Science, 50, pp. 790802 (2011). 11. Franke, M.M., Hilbinger, R.M., Lohmuller, A., and Singer, R.F. The e_ect of liquid metal cooling on thermal gradients in directional solidi_cation of super alloys: Thermal analysis", Journal of Material Processing Technology, 213, pp. 20812088 (2013). 12. Furumoto, T., Ueda, T., Amino, T., Ksunoki, D., Hosokowa, A., and Tanaka, T. Finishing performance of cooling channel with face protuberance inside the molding die", Journal of Material Processing Technology, 212, pp. 21542160 (2012). DOI: 10.1016/j.jmatprotec.2012.05.016 13. Khairul, M.A., Alim, M.A., Mahbubul, I.M., Saidur, R., Hepbasli, A., and Hossain, A. Heat transfer performance and exergy analyses of a corrugated plate heat exchanger using metal oxide nanouids", International Communications in Heat and Mass Transfer, 50, pp. 814 (2014). 14. Dizaji, H.S., Jafarmadar, S., and Asaadi, S. Experimental exergy analysis for shell and tube heat exchanger made of corrugated shell and corrugated tube", Experimental Thermal and Fluid Science, 81, pp. 475481 (2017). A. Bolatturk et al./Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3255{3261 3261 15. Ipek, O., Kan, M., and Gurel, B. Examination of di_erent heat exchangers and the thermal activities of di_erent designs", Acta Physica Polonica A, 132(3), pp. 580583 (2017). 16. Kan, M., Ipek, O., and Gurel, B. Plate heat exchangers as a compact design and optimization of di_erent channel angles", Acta Physica Polonica A, 128(2B), pp. B49 B52 (2015). 17. Karaail, R. and Ozturk, I. T. Thermoeconomic analyses of steam injected gas turbine cogeneration cycles", Acta Physica Polonica A, 128(2B), pp. B279 B281 (2015). 18. Zehtabiyan, R.N., Damirci, D.S., Fazel, Z.M.H., and Sa_ar, A.M. Generalized heat transfer and entropy generation of strati_ed airwater ow in entrance of a minichannel", Scientia Iranica, B, 24(5), pp. 2406 2417 (2017). 19. Nouri, B.A. and Seyyed, H.M.H. Numerical analysis of thermally developing turbulent ow in partially _lled porous pipes", Scientia Iranica, B, 22(3), pp. 835843 (2015). 20. Altinsoy, _I., C_ elebi Efe, G.F., Yener, T., onder, K.G., and Bindal, C. E_ect of double stage nitriding on 34CrAlNi710 nitriding steel", Acta Physica Polonica A, 132, pp. 663666 (2017). 21. Arunkumar, S., Rao, K.S., and Kumar, T.P. Spatial variation of heat ux at the metalmold interface due to mold _lling e_ects in gravity diecasting", Int. J. of Heat and Mass Transfer, 51(11), pp. 26762685 (2008). 22. Hallam, C.P. and Gri_ths, W.D. A model of the interfacial heattransfer coe_cient for the aluminum gravity diecasting process", Metallurgical and Materials Transactions B, 35(4), pp. 721733 (2004). 23. Imran, A.A., Nabeel, S.M., and Hayder, M.J. Numerical and experimental investigation of heat transfer in liquid cooling serpentine minichannel heat sink with di_erent new con_guration models", Thermal Science and Engineering Progress, 6, pp. 128139 (2018). 24. Fluent, Version 16.1 User's Guide, Fluent Inc., Lebanon (NH) (2016). 25. Klein, S.A. Engineering Equation Solver (EES)", Academic Commercial V8.208.FChart Software, www.fChart.com (2008).##]
1

Proposing a new nonlinear hyperviscoelastic constitutive model to describe uniaxial compression behavior and dependence of stressrelaxation response on strain levels for isotropic tissueequivalent material
http://scientiairanica.sharif.edu/article_20899.html
10.24200/sci.2018.50235.1592
1
Predicting the nonlinear response of biological tissues is challenging issue, due to strain rate (short term) and timedependent (longterm) nature of its response. While many of the tissue properties have already been extensively examined, some are left unnoticed, such as dependence of the stressrelaxation behavior on the strain levels. In this paper, a hyperviscoelastic constitutive model is derived within the integral form presented by Pipkin and Rogers model to remove this limitation. In the suggested model, the hyperelastic and shortterm viscous parts are represented by the suitable strain energy function. The longterm viscous function includes the deformation history, which is expressed through a tensorialrelaxation function and has not been considered elsewhere. The constitutive model involves a number of material parameters. The values of those are identified from experimental data for AdipreneL100 as a tissueequivalent material. Parameters appearing in constitutive law are estimated by fitting the model with the experimental data. It is assumed that the tissue phantom is slightly compressible, isotropic and homogenous. The obtained results indicate that the presented model can describe the nonlinearity, strain rate (shortterm) and timedependent (longterm) effects of materials. The validation of the model is investigated and shows very good agreement with the experimental data.
0

3262
3270


Z.
Matin Ghahfarokhi
Department of Mechanical Engineering, Isfahan University of Technology, Isfahan, P.O. Box 8415683111, Iran
Iran
matin@me.iut.ac.ir


M.
Moghimi Zand
Small Medical Devices, BioMEMS & LoC Lab, School of Mechanical Engineering, College of Engineering, University of Tehran,
Tehran, Postal Code 1439955961, Iran.
Iran
mahdimoghimi@gmail.com


M.
SalmaniTehrani
Department of Mechanical Engineering, Isfahan University of Technology, Isfahan, P.O. Box 8415683111, Iran.
Iran
tehrani@cc.iut.ac.ir
Hyperviscoelastic
modeling
Tissueequivalent material
Straindependent
Stressrelaxation behavior
[1. Trawinski, Z., Wojcik, J., Nowicki, A., Olszewski, R., Balcerzak, A., Frankowska, E., Zegadlo, A., and Rydzynski, P. Strain examinations of the left ventricle phantom by ultrasound and multislices computed tomography imaging", Biocyber. Biomed. Eng., 35, pp. 255263 (2015). 2. Bukala, J., Kwiatkowski, P., and Malachowski, J. Numerical analysis of stent expansion process in coronary artery stenosis with the use of noncompliant ballon", Biocyber. Biomed. Eng., 36, pp. 145156 (2016). 3. Eshghi, S.H., Rajabi, H., Darvizeh, A., Nooraeefar, V., Sha_ei, A., Mirzababaie Mosto_, T., and Monsef, M. A simple method for geometric modeling of biological structures using image processing technique", Sci. Iran., 23(5), pp. 21942202 (2016). 4. Przytulska, M., Gierblinski, I., Kuliusz, J., and Skoczylas, K. Quantitative examination of liver tissue ultrasound elastograms", Biocyber. Biomed. Eng., 31(4), pp. 7585 (2011). 5. Zanetti, M.E., Terzini, M., Mossa, L., Bignardi, C., Costa, P., Audenino, A.L., and Vezzoni, A. A structural numerical model for the optimization of double pelvic osteotomy in the early treatment of canine hip dysplasia", Vet. Comp. Orthop. Traumatol., 4, pp. 19 (2017). Z. Matin Ghahfarokhi et al./Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3262{3270 3269 6. Kemper, A.R., Santago, A.C., Stitzel, J.D., Sparks, J.L., and Duma, S.M. E_ect of strain on the material properties of human liver parenchyma in uncon_ned compression", ASME J. Biomech. Eng., 135, pp. 18 (2013). 7. Rashid, B., Destrade, M., and Gilchrist, M.D. Mechanical characterization of brain tissue in simple shear at dynamic strain rates", J. Mech. Behav. Biomed. Mater., 28, pp. 7185 (2013). 8. Abbasi, A.A., Ahmadian, M.T., Alizadeh, A., and Tarighi, S. Application of hyperelastic models in mechanical properties prediction of mouse oocyte and embryo cells at large deformations", Sci. Iran., 25(2), pp. 700710 (2018). 9. Quapp, K.M. and Weiss, J.A. Material characterization of human medial collateral ligament", ASME J. Biomech. Eng., 120, pp. 757763 (1998). 10. Wang, X., Schoen, J.A., and Rentschler, M.E. Aquantitative comparison of soft tissue compressive viscoelastic model accuracy", J. Mech. Behav. Biomed. Mater., 20, pp. 126136 (2013). 11. Shari_ Sedeh, R., Ahmadian, M.T., and Janabi Shari_, F. Modeling, simulation, and optimal initiation planning for needle insertion into the liver", ASME J. Biomech. Eng., 132, pp. 111 (2010). 12. Matin Ghahfarokhi, Z., Moghimi Zand, M., and Salmani Tehrani, M. Analytical solution and simulation of the liver tissue behavior under uniaxial compression test", Modares Mechanical Engineering, 16(9), pp. 4756 (1395) (in Persion). 13. Matin Ghahfarokhi, Z., Salmani Tehrani, M., Moghimi Zand, M., and Mahzoon, M. A computational study on the e_ect of di_erent design parameters on the accuracy of biopsy procedure", J. A. MECH., 46(2), pp. 221231 (2015). 14. Troyer, K.L., Shetye, S.S., and Puttlitz, C.M. Experimental characterization and _nite element implementation of soft tissue nonlinear viscoelasticity", ASME J. Biomech. Eng., 134, pp. 18 (2012). 15. Zanetti, E.M., Perrini, M., Bignardi, C., and Audenino, A.L. Bladder tissue passive response to monotonic and cyclic loading", Biorheol., 49, pp. 4963 (2012). 16. Natali, A.N., Audenino, A.L., Artibani, W., Fontanella, C.G., Carniel, E.L., and Zanetti, E.M. Bladder tissue biomechanical behavior: Experimental tests and constitutive formulation", J. Biomech., 48, pp. 30883096 (2015). 17. Oaz, H. A biomechanical comparison between tissue sti_ness meter and shore type 00 durometer using fresh human fetal membrane cadavers", Biocyber. Biomed. Eng., 36, pp. 138144 (2016). 18. Khajehsaeid, H., Baghani, M., and Naghdabadi, R. Finite strain numerical analysis of elastomeric bushings under multiaxial loadings: a compressible viscohyperelastic approach", Int. J. Mech. Mat. Des., 9, pp. 385399 (2013). 19. Naghdabadi, R., Baghani, M., and Arghavani, J. A viscoelastic constitutive model for compressible polymers based on logarithmic strain and its _nite element implementation", Finite Elem. Anal. Des., 62, pp. 1827 (2012). 20. Karimi, A., Navidbakhsh, M., and Beigzadeh, B. A viscohyperelastic constitutive approach for modeling polyvinylalcohol sponge", Tissue Cell, 46, pp. 97102 (2014). 21. Tirella, A., Mattei, G., and Ahluwalia, A. Strain rate viscoelastic analysis of soft and highly hydrated biomaterials", J. Biomed. Mat. Res., 102A(10), pp. 33523360 (2014). 22. Miller, K. Constitutive model of brain tissue suitable for _nite element analysis of surgical procedures", J. Biomech., 32, pp. 531537 (1999). 23. Pipkin, A.C. and Rogers, T.G. A nonlinear integral representation for viscoelastic behavior", J. Mech. Phys. Solids., 16, pp. 5972 (1968). 24. Rajagopal, K.R. and Wineman, A.S. Response of anisotropic nonlinearly viscoelastic solids", Math. Mech. Solids., 14, pp. 490501 (2009). 25. Holzapfel, G.A., Nonlinear Solid Mechanics. A Continuum Approach for Engineering, pp. 205256, Wiley, UK (2000). 26. Holzapfel, G.A. and Gasser, T.C. A viscoelastic model for _berreinforced composites at _nite strains: continuum basis, computational aspects and applications", Comput. Meth. Appl. Mech. Eng., 190, pp. 43794403 (2001). 27. Lu, Y.T., Zhu, H.X., Richmond, S., and Middleton, J. A viscohyperelastic model for skeletal muscle tissue under high strain rates", J. Biomech., 43, pp. 2629 2632 (2010). 28. Limbert, G. and Middleton, J. A constitutive model of the posterior cruciate ligament", Med. Eng. Phys., 28, pp. 99113 (2006). 29. Laksari, k., Sadeghipour, K., and Darvish, K. Mechanical response of brain tissue under blast loading", J Mech Behav Biomed Mater, 32, pp. 132144 (2014). 30. Mansouri, M. and Darijani, H. Constitutive modeling of isotropic hyperelastic materials in an exponential framework using a self contained approach", Int. J. Solids Struct., 51(25), pp. 43164326 (2014). 31. Khan, A.S., LopezPamies, O., and Kazmi, R. Thermomechanical large deformation response and constitutive modeling of viscoelastic polymers over a wide range of strain rates and temperatures", Int. J. Plas., 22, pp. 581601 (2006). 32. Khan, A.S. and LopezPamies, O. Time and temperature dependent response and relaxation of a soft polymer", Int. J. Plas., 18, pp. 13591372 (2002). 33. Limbert, G. and Middleton, J. A transversely isotropic viscohyperelastic material application to the modeling of biological soft connective tissues", Int. J. Solis Struct., 41(15), pp. 42374260 (2004).##]
1

Numerical and experimental investigation of impinging turbulent flow of twin jets against a wall
http://scientiairanica.sharif.edu/article_21013.html
10.24200/sci.2018.50369.1663
1
In the present study, impinging of vertical twin jet against a horizontal plate is numerically and experimentally investigated. Four two equation RANS based turbulence models are used and their capabilities to simulate such complicated turbulent flow were examined. The two fluid jets are separated by a thin membrane. The inlet jet hydraulic diameters are the same and the Reynolds number of external flows of jets is 13500. The ratio of width of nozzles (e) to nozzletoplate distance (H) considered as 1:10. The turbulent models used in this work are kε, kε RNG, kω and kω SST. The results obtained by the models were compared with each other as well as twodimensional PIV data to evaluate the capabilities of such models for this kind of flows. By comparing the numerical and experimental results, it is concluded that all of the models can predict acceptable results in the free jet area, but in the near wall region none of the models can predict flow characteristics with reasonable accuracy. It was observed that, at low nozzletoplate distances, the prediction results of the turbulence models are approximately in accordance with the experimental data, particularly for a zone near the midline separating the two jets.
0

3271
3282


M.A.
Modaresi
Department of Mechanical Engineering, Tarbiat Modares University, Tehran, P.O. Box 1411713116, Iran.
Iran
mohamad.ali.modaresi@gmail.com


E.
Shirani
Department of Mechanical Engineering, Foolad Institute of Technology, Fooladshahr, Isfahan, P.O. Box 8491663763, Iran.
Iran
eshirani@cc.iut.ac.ir


M.
charmiyan
Department of Mechanical Engineering, University of Ayatollah Ozma Boroujerdy, Boroujerd, P.O. Box 6919969411, Iran.
Iran
m.charmiyan@gmail.com


F.
Aloui
LAMIH, CNRS UMR 8201, University of Valenciennes and HainautCambresis (UVHC), Campus Mont Houy, Building
Gromaire, F59313, Valenciennes Cedex 9, France.
France
fethi.aloui@gmail.com


A.
Koched
TSI France, Hotel Technologique, Technop^ole de Ch^ateauGombert, 13382 Marseille, France.
France
amine.koched@emn.fr


M.
Pavageau
rue de la houssiniere BP 92208, 44322 Nantes Cedex 03, France.
France
michel.pavageau@emn.fr
Impinging jets
Twinjet
RANS
Turbulence models, PIV
[1. Greco, C., Castrillo, G., Crispo, C., Astarita, T., and Cardone, G. Investigation of impinging single and twin circular synthetic jets ow _eld", Experimental Thermal and Fluid Science, 74, pp. 354367 (2016). 2. Ozmen, Y. Con_ned impinging twin air jets at high Reynolds numbers", Experimental Thermal and Fluid Science, 35, pp. 355363 (2011). M.A. Modaresi et al./Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3271{3282 3281 3. Loubiere, K. and Pavageau, M. Educing coherent eddy structures in air curtain systems", Chemical Engineering and Processing: Process Intensi_cation, 47, pp. 435448 (2008). 4. Felis, F., Pavageau, M., ElicerCortes, J.C., and Dassonville, T. Simultaneous measurements of temperature and velocity uctuations in a double streamtwin jet air curtain for heat con_nement in case of tunnel _re", International Communications in Heat and Mass Transfer, 37, pp. 11911196 (2010). 5. Fernandez, J., ElicerCortes, J.C., Valencia, A., Pavageau, M., and Gupta, S. Comparison of lowcost twoequation turbulence models for prediction ow dynamics in twinjets devices", International Communications in Heat and Mass Transfer, 34, pp. 570578 (2007). 6. Lecaros, M., ElicerCortes, J.C., Fuentes, A., and Felis, F. On the ability of twin jets air curtains to con_ne heat and mass inside tunnels", International Communications in Heat and Mass Transfer, 37, pp. 970977 (2010). 7. Taghinia, J., Rahman, M.M., and Siikonen, T. Numerical investigation of twinjet impingement with hybridtype turbulence modeling", Applied Thermal Engineering, 73, pp. 650659 (2014). 8. Greco, C.S., Ianiro, A., and Cardone, G. Time and phase average heat transfer in single and twin circular synthetic impinging air jets", International Journal of Heat and Mass Transfer, 73, pp. 776788 (2014). 9. ElicerCortes, J.C., Demarco, R., Valencia, A., and Pavageau, M. Heat con_nement in tunnels between two doublestream twinjet air curtains", International Communications in Heat and Mass Transfer, 36, pp. 438444 (2009). 10. Rivera, J., ElicerCortes, J.C., and Pavageau, M. Turbulent heat and mass transfer through air curtains devices for the con_nement of heat inside tunnels", International Communications in Heat and Mass Transfer, 38, pp. 688695 (2011). 11. Charmiyan, M., Azimian, A., Keirsbulc, K.L., Shirani, E., and Aloui, F. Turbulent plane impinging jetphysical insight and turbulence modeling", Journal of Applied Fluid Mechanics, 9, pp. 1117 (2016). 12. Xu, L., Lan, J., Ma, Y.H., Gao, J.M., and Li, Y.L. Numerical study on heat transfer by swirling impinging jets issuing from a screwthread nozzle", International Journal of Heat and Mass Transfer, 115, pp. 232237 (2017). 13. Draksler, M., Koncar, B., Cizelj, L., and Niceno, B. Large eddy simulation of multiple impinging jets in hexagonal con_gurationow dynamics and heat transfer characteristics", International Journal of Heat and Mass Transfer, 109, pp. 1627 (2017). 14. Trinh, X.T., Fenot, M., and Dorignac, E. Flow and heat transfer of hot impinging jets issuing from lobed nozzles", International Journal of Heat and Fluid Flow, 67, pp. 185201 (2017). 15. Tsaoulidis, D. and Angeli, P. Liquidliquid dispersions in intensi_ed impingingjets cells", Chemical Engineering Science, 171, pp. 149159 (2017). 16. Charmiyan, M., Azimian, A.R., Shirani, E., Aloui, F., Degouet, C., and Michaelis, D. 3D tomographic PIV, POD and vortex identi_cation of turbulent slot jet ow impinging on a at plate", International Journal of Mechanical Science and Technology, 31, pp. 53475357 (2017). 17. Charmiyan, M., Azimian, A.R., Shirani, E., and Aloui, F. Capability assessment of _ve di_erent RANSbased turbulence models to simulate the various regions of slot turbulent impingement jet ow", In ASME 2017 Fluids Engineering Division Summer Meeting, p. V01BT11A011 (2017). 18. Chacon Rebollo, T. and Lewandowski, R., Mathematical and Numerical Foundations of Turbulence Models and Applications, Springer, pp. 1517 (2014). 19. Van Leer, B. Towards the ultimate conservative di_erence scheme. II. Monotonicity and conservation combined in a secondorder scheme", Journal of Computational Physics, 14(4), pp. 361370 (1974).##]
1

Lattice Boltzmann simulation of blood flow properties and vessel geometry in open and closed vessels: A numerical study
http://scientiairanica.sharif.edu/article_20900.html
10.24200/sci.2018.50751.1851
1
In the present article, Lattice Boltzmann method is utilized to simulate twodimensional incompressible viscous flow in an open and closed microchannel (vessel). The main focus of the present research is to study physical parameters of blood flow in a vessel. To find the effect of oscillatory flow inside the vessel, we take account of the Reynolds number from 0.05 to 1.5 for numerical computation in the present manuscript in an open straight vessel. In addition, the accuracy of Poiseuille Law is investigated for blood flow in open vessel too. For this purpose, the effect of the vessel diameter and blood viscosity on the blood flow is studied numerically. As extra results, the effect of blood injection to a coronary bifurcation with two closed ends are studied. The blood pressure drop is high at the beginning of the vessel (pressure variation is high between the adjacent points along the vessel), but after the path along the vessel, the speed of dropping pressure decreases and the pressure difference between the adjoining points decreases along the vessel. Finally, the present results have been compared with the available experimental and numerical results that show good agreements.
0

3283
3292


H.
Akhtari
Department of Mechanical Engineering, Urmia University, Urmia, Postal Code: 5756151818, Iran.
Iran
hamed.akhtari@gmail.com


I.
Mirzaee
Department of Mechanical Engineering, Urmia University, Urmia, Postal Code: 5756151818, Iran.
Iran
i.mirzaee@urmia.ac.ir


N.
Pourmahmoud
Department of Mechanical Engineering, Urmia University, Urmia, Postal Code: 5756151818, Iran.
Iran
n.pormahmod@urmia.ac.ir
Lattice Boltzmann method
Blood flow
Poiseuille law
Reynolds number
[1. DiVito, K.A., Daniele, M.A., Roberts, S.A., Ligler, F.S., and Adams, A.A. Microfabricated blood vessels H. Akhtari Shishavan et al./Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3283{3292 3291 undergo neoangiogenesis", Data in Brief, 14, pp. 156 162 (2017). 2. Moccia, S., De Momi, E., El Hadji, S., and Mattos, L.S. Blood vessel segmentation algorithmsreview of methods, datasets and evaluation metrics", Comp. Meth. and Prog. in Biomed., 158, pp. 7191 (2018). 3. Fedosov, D.A., Caswell, B., Suresh, S., and Karniadakis, G.E. Quantifying the biophysical characteristics of Plasmodiumfalciparumparasitized red blood cells in microcirculation", Proc. Nat. Acad. Sci., 108(1), pp. 3539 (2011). 4. Wu, J., Hu, Q., and Ma, X. Comparative study of surface modeling methods for vascular structures", Comp. Med. Imaging Graph., 37(1), pp. 414 (2013). 5. Campochiaro, P.A. Molecular pathogenesis of retinal and choroidal vascular diseases", Prog. Retin. Eye Res., 49, pp. 6781 (2015). 6. De Momi, E., Caborni, C., Cardinale, F., Casaceli, G., Castana, L., Cossu, M., Mai, R., Gozzo, F., Francione, S., and Tassi, L. Multitrajectories automatic planner for Stereo Electro Encephalo Graphy (SEEG)", Int. J. Comput. Assist. Radiol. Surg., 9(6), pp. 10871097 (2014). 7. Essert, C., FernandezVidal, S., Capobianco, A., Haegelen, C., Karachi, C., Bardinet, E., Marchal, M., and Jannin, P. Statistical study of parameters for deep brain stimulation automatic preoperative planning of electrodes trajectories", Int. J. Comput. Assist. Radiol. Surg., 10(12), pp. 19731983 (2015). 8. Navidbakhsh, M. and Rezazadeh, M. An immersed boundarylattice Boltzmann model for simulation of malariainfected red blood cell in microchannel", Scientia Iranica, 19(5), pp. 13291336 (2012). 9. Faria, C., Sadowsky, O., Bicho, E., Ferrigno, G., Joskowicz, L., Shoham, M., Vivanti, R., and De Momi, E. Validation of a stereo camera system to quantify brain deformation due to breathing and pulsatility", Med. Phys., 41(11), p. 113502 (2014). 10. Cardinale, F., Pero, G., Quilici, L., Piano, M., Colombo, P., Moscato, A., Castana, L., Casaceli, G., Fuschillo, D., and Gennari, L. Cerebral angiography for multimodal surgical planning in epilepsy surgery: description of a new threedimensional technique and literature review", World Neurosurg, 84(2), pp. 358 367 (2015). 11. Alishahi, M., Alishahi, M.M., and Emdad, H. Numerical simulation of blood ow in a exible stenosed abdominal real aorta", Scientia Iranica, 18(6), pp. 12971305 (2011). 12. Hern_andezP_erez, M., Puig, J., Blasco, G., de la Ossa, N.P., Dorado, L., D_avalos, A., and Munuera, J. Dynamic magnetic resonance angiography provides collateral circulation and hemodynamic information in acute ischemic stroke", Stroke, 47(2), pp. 531534 (2016). 13. Rochitte, C.E., George, R.T., Chen, M.Y., Arbab Zadeh, A., Dewey, M., Miller, J.M., Niinuma, H., Yoshioka, K., Kitagawa, K., and Nakamori, S. Computed tomography angiography and perfusion to assess coronary artery stenosis causing perfusion defects by single photon emission computed tomography: the CORE320 study", Eur. Heart J., 35(17), pp. 1120 1130 (2014). 14. Pamme, N. Continuous ow separations in micro uidic devices", Lab on a Chip, 7, pp. 16441659 (2007). 15. McNamara, G. and Zanetti, G. Use of the Boltzmann equation to simulate lattice gas automata", Physics of Review Letters, 61(5), pp. 2332 (1998). 16. Chen, S. and Doolen, G.D. Lattice Boltzmann method for uid ows", Ann. Rev. of Fluid Mech., 30(1), pp. 329364 (1998). 17. Succi, S. The Lattice Boltzmann Equation for Fluid Dynamics and Beyond, Oxford University Press: Oxford (2001). 18. Wang, H., Cater, J., Liu, H., Ding, X., and Huang, W. A lattice Boltzmann model for solute transport in open channel ow", J. of Hydrology, 556, pp. 419426 (2018). 19. Cheng, Y. and Zhang, H. Immersed boundary method and lattice Boltzmann method coupled FSI simulation of mitral leaet ow", Comp. and Fluids, 39(5), pp. 871881 (2010). 20. Lecrivain, G., Rayan, R., Hurtado, A., and Hampel, U. Using quasiDNS to investigate the deposition of elongated aerosol particles in a wavy channel ow", Comp. and Fluids, 124, pp. 7885 (2016). 21. Vi, A., Pouransari, H., Zamansky, R., and Mani, A. Particleladen ows forced by the disperse phase: Comparison between lagrangian and eulerian simulations", Int. J. of Multiphase Flow, 79, pp. 144158 (2016). 22. Henn, T., Thater, G., Dorer, W., Nirschl, H., and Krause, M.J. Parallel dilute particulate ow simulations in the human nasal cavity", Comp. and Fluids, 124, pp. 197207 (2016). 23. Wu, J. and Shu, C. An improved immersed boundarylattice Boltzmann method for simulating threedimensional incompressible ows", J. of Comput. Phys., 229, pp. 50225042 (2010). 24. Carreau, P.J. Rhology equations from molecular network theories", J. of Rheo., 16(1), p. 127 (1972). 25. Wang, C.H. and Ho, J.R. A lattice Boltzmann approach for the non newtonian e_ect in the blood ow", Comput. Math. Appl., 62, pp. 7586 (2011). 26. Khodayari Bavil, A. and Razavi, S.E. On the thermo ow behavior in a rectangular channel with skewed circular ribs", Mech. & Ind., 18(2), p. 225 (2017). 27. Bagchi, P. Mesoscale simulation of blood ow in small vessels", Biophys. J., 92, pp. 8581877 (2007). 28. De Hart, J., Baaijens, F.P.T., Peters, G.W.M., and Schreurs P.J.G. A computational uidstructure interaction analysis of a _berreinforced stentless aortic valve", J. of Biomech., 36, pp. 699712 (2003). 3292 H. Akhtari Shishavan et al./Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3283{3292 29. Arokiaraj, M.C., De Santis, G., De Beule, M., and Palacios, I.F. A novel tram stent method in the treatment of coronary bifurcation lesions  _nite element study", PLoS ONE, 11, e0149838 (2016).##]
1

Drivers of crosscountry vehicles
http://scientiairanica.sharif.edu/article_21075.html
10.24200/sci.2018.50781.1862
1
This work offers a new chassis design, namely the wheeltrack, represents a mathematical model of this chassis, and also proves the advantage of the proposed design when driving the vehicle on arbitrary terrain  rough offroad. The proposed approach can find application in the design of unmanned research mechanisms for other planets (Mars Rovers, Lunar Rovers etc.), also for design of robots and transport of rescuers at liquidation of consequences of natural or technological disasters. The article presents the analysis of the requirements for the chassis of extraterrestrial research unmanned mechanism demonstrated high compliance of the proposed approach. The analysis of the requirements for the chassis of extraterrestrial research unmanned mechanism demonstrated high compliance of the proposed approach. We proposed and investigated a mathematical model of wheeltrack, demonstrated the optimization of the proposed mathematical model to machine computing, demonstrated the flexibility and scalability of the mathematical model. The proposed design is an attempt to combine the advantages of a walking and wheel types of travel in one mechanism.
0

3293
3303


A.M.
Muratov
Department of the Transport Technology, Mechanical Engineering and Standardization, Kazakh University of Railway Transport, Kazakhstan, Almaty City, Zhetysu Street, 1 icrodistrict, 73, 19.
Kazakhstan
kups1@mail.ru


A.K.
Kainarbekov
Department of the Radio Engineering, Electronics and Telecommunications, Kazakh University of Railway Transport,
Kazakhstan, Almaty City, Taugul Street, 1 microdistrict, 58, 5.
Kazakhstan
kainarbekov@mail.ru


S.K.
Sultangazinov
Department of the Automation and Transport Information Systems, Kazakh University of Railway Transport, Kazakhstan,
Almaty City, Orbita Street, 2 microdistrict, 12, 36
Kazakhstan
suleke.kzsh@gmail.com


Т.S.
Sarzhanov
Department of the Transport Economics, Kazakh University of Railway Transport, Kazakhstan, Almaty City, Zhambyla Street,
93A, 49.
Kazakhstan
taizhan.s@mail.ru


A.K.
Kazhigulov
Department of the Transport Technology, Mechanical Engineering and Standardization, Kazakh University of Railway Transport,Kazakhstan, Almaty City, Zhetysu Street, 1 icrodistrict, 73, 19.
Kazakhstan
kazhigulov60@mail.ru


A.
Shalkarov
Department of the Transport Construction, Bridges and Tunnels, Kazakh University of Railway Transport, Kazakhstan, Almaty City, Tau Samaly Microdistrict, Tole bi Street, 9.
Kazakhstan
shalkarov56@mail.ru


G.S.
Mussaeva
Department of the Transport Construction, Kazakh University of Railway Transport, Kazakhstan, Almaty City, Kurmangazy
Street, 145A, 3.
Kazakhstan
ergazina.92@mail.ru


K.M.
Bekmambet
Department of the Transport Technology, Mechanical Engineering and Standardization, Kazakh University of Railway Transport,
Kazakhstan, Almaty City, Zhetysu Street, 1 microdistrict, 73, 19.
Kazakhstan
bekmambet1978@mail.ru


B.Sh.
Yessengarayev
Department of the Automation and Transport Information Systems, Kazakh University of Railway Transport, Kazakhstan,
Kyzylorda Region, Kyzylorda City, Baitursynova Street, 18.
Kazakhstan
yessengarayev_zh@railways.kz


A.
Tanirbergenov
Department of the Railway Track, Railway Location Survey and Design, Kazakh University of Railway Transport, Kazakhstan,
Aktobe City, Zarechny Street, Lane 1, 19.
Kazakhstan
kazbaevish@mail.ru
drivers
chassis
transport of rescuers
unmanned research mechanisms
wheeltrack
[1. ElGawwad, K.A., Crolla, D.A., Soliman, A.M.A., and ElSayed, F.M. O_road tyre modelling III: e_ect of angled lugs on tyre performance1", Journal of Terramechanics, 36(2), pp. 6375 (1999). 2. Abdelrahman, M., Zeidis, I., Bondarev, O., Adamov, B., Becker, F., and Zimmermann, K. A description of the dynamics of a fourwheel mecanum mobile system as a basis for a platform concept for special purpose vehicles for disabled person", in Shaping the Future by Engineering: 58th Ilmenau Scienti_c Colloquium, Technische Universitat Ilmenau (2014). 3. Giurgiu, T., Puic_a, C., Pup_az_a, C., Nicolescu, F. A., and Zapciu, M. Mecanum wheel modeling for studying rollerground contact issues", U.P.B. Sci. Bull., Series D, 79(2), pp. 147158 (2017). 4. Surovec, R., Gmiterko, A., Vackov_a, M., Virgala, I., Prada, E., and Pip__k, T. Design of robot vehicle un3302 A.M. Muratov et al./Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3293{3303 dercarriage with ability to operate in broken terrain", Procedia Engineering, 48, pp. 650655 (2012). 5. Harrington, B.D. and Voorhees, C. The challenges of designing the rockerbogie suspension for the mars exploration rover", in 37th Aerospace Mechanisms Symposium, Houston, TX, United States (2004). 6. Malenkov, M.I., Volov, V.A., Guseva, N.K., and Lazarev, E.A. Increasing the mobility of Mars rovers by improving the locomotion systems and their control algorithms", Russian Engineering Research, 35(11), pp. 824831 (2015). 7. Kim, Y., Eom, W., Lee, J.H., and Sim, E.S. Design of mobility system for ground model of planetary exploration rover", Journal of Astronomy and Space Sciences, 29(4), pp. 413422 (2012). 8. http://www.yankodesign.com/2009/03/10/splityourwheel intoeight/ 9. http://www.michelinchallengedesign.com/thechallenge archives/2009bravebold/2009showcaseofselected entrants/transformingmultifunctionalwheels bysuyan gparkandchanghoeheosouthkorea/. 10. Muratov, A.M., Omarov, A.D., Kaynarbekov, A.K., and Sazanbaeva, R.I. Synthesis of the scheme of the walking wheel", p. 227, Bastau, Almaty (2013). 11. Muratov, A.M. and Kaynarbekov, R.I., Walking Drivers, p. 182, Bastau, Almaty: Textbook (2000). 12. Muratov, A.M. and Sazanbaeva, R.I., Improving the Patency of Wheeled Vehicles in O_Road Conditions, Bastau, Almaty: Textbook (2003). 13. Muratov, A.M. and Kaynarbekov, A.K. Trackwalking propulsion of the vehicle, provisional patent RK No11006, 14.11.2001", in Bulletin No 12, Almaty (2001). 14. Omarov, A.D., Muratov, A.M., Kaynarbekov, A., and Bekmambeth, K.M. O_road vehicles", Patent of Kazakh Republic, No. 123/3205, p. 182, Almaty (2014). 15. Briskin, E.S., Zhoga, V.V., Chernyshev, V.V., and Maloletov, A.V. Bases of calculation and designing of walking machine with cyclic vehicles", in Monograph, p. 164, Moscow, Mashinostroenie (2006). 16. Omarov, A.D., Muratov, A., Kaynarbekov, A., and Bekmambeth, K. Vehicles to drive on extra complicated support surface (design and calculations)", in LLP, Alla Prima, Textbook, p. 118, Almaty (2016). 17. Muratov, A., Kaynarbekov, A., and Bekmambeth, K. Walking wheel for terrestrial vehicle. Materials of XII international scienti_c and practice conference", Modern European Science, Chemistry and Chemical Technology Mathematics Technical Science, 9, pp. 58 64 (2016). 18. Muratov, A. and Kaynarbekov, A. Walking wheel for vehicles. Materials of XII international scienti_c and practice conference", Proceedings of Academic Science, 4, pp. 7578 (2016). 19. Omarov, A.D., Muratov, A., and Kaynarbekov, A. The anatomical structure and the kinematic model the wheel  tracks of allterrain vehicles", Industrial Vehicles of Kazakhstan, Almaty, 3(52), pp. 1823 (2016). 20. Kaynarbekov, A. and Taninbergenov, A.K. Walking wheel <>", Collection of Scienti_c Works of Ukrainian State Academy of Railway Transport, Kharkov, Ukraine, 148(1), pp. 164170 (2014). 21. Kaynarbekov, A., Zhumabek, A.G., and Omarova, G.A. The elimination of the defect of the gait of a walking wheel for mounting to vehicles", Monthly Scienti_c Journal, 2(3), pp. 2427 (2014). 22. Chebyshev, P.L., Th_eorie des M_ecanismes Connus Sous le Nom de Parall_e Logrammes, Imprimerie de l'Acad_emie Imp_eriale des Sciences (1853). 23. Bloch, Z.Sh. and Karpin, E.B., Practical Methods for the Synthesis of Planar FourLink Mechanisms, Publishing house of AS SSSR (1943). 24. Levitsky, N.I. Application of quadratic approximation of functions to the solution of problems of synthesis of mechanisms" in, Proceedings of the Seminar on TMM, Publishing house of AS SSSR, 17 (1948). 25. Freudenstein, F. Approximate synthesis of fourbar linkages", Transactions of ASME, 77, pp. 853861 (1955). 26. Hartenberg, R.S. and Danavit, J., Kinematic Synthesis of Linkages, McGrawHill, New York (1964). 27. Liu, Z. and Angeles, J. Leastsquare optimization of planar and spherical ourbar function generator under mobility constraints", Journal of Mechanical Design, December, 114, pp. 569573 (1992).##]
1

Prediction of critical fraction of solid in lowpressure die casting of aluminum alloys using artificial neural network
http://scientiairanica.sharif.edu/article_21225.html
10.24200/sci.2019.50819.1881
1
Casting simulation programs are the computer programs that digitally model the casting of an alloy in the sand, shell or permanent mold and then the cooling and solidification processes. However, obtaining consistent results from the casting modeling depends on providing many parameters and boundary conditions accurately. Critical fraction of solid (CFS), which is one of the most important of these parameters, is defined as the point where the solid dendrites do not allow any flow of the liquid metal in the mushy zone. Since the CFS value varies depending on many factors, inconsistent results can be experienced in the modeling applications. In this study, the CFS value obtained during the solidification of various commercial aluminum alloys' casting process carried out using low pressure die casting method, is predicted by using artificial neural network (ANN) method based on alloy type, grain refiner and modifier additions, initial mold temperature, pressure level parameters. In the scope of the study, 162 experiments are conducted. The results obtained from the low pressure die casting experiments using a special model designed for the study are validated by using SOLIDCast casting simulation. The CFS values obtained from this validation range from 33% to 61%.
0

3304
3312


C.
Teke
Institute of Natural Sciences, Sakarya University, Sakarya, Turkey
Turkey
cteke@sakarya.edu.tr


M.
Colak
Department of Mechanical Engineering, Bayburt University, 69000, Bayburt, Turkey.
Turkey
mcolak@bayburt.edu.tr


A.
Kiraz
Department of Industrial Engineering, Sakarya University, 54187, Sakarya, Turkey.
Turkey
kiraz@sakarya.edu.tr


M.
Ipek
Department of Industrial Engineering, Sakarya University, 54187, Sakarya, Turkey.
Turkey
ipek@sakarya.edu.tr
Critical fraction of solid
artificial neural network
low pressure die casting
casting simulation
[1. Kay_kc_, R. Comparison of classical and computer aided engineering techniques used in casting a large steel part", J. Fac. Eng. Arch. Gazi Univ., 23(2), pp. 257265 (2008). 2. Kay_kc_, R. Use of computer modelling in predicting microporosity in commercial aluminum alloy", 66th World Foundry Congress, 1, Istanbul, Turkey, pp. 235 246 (2004). 3. Stefanescu, D.M. Computer simulation of shrinkage related defects in metal castings  a review", Int. J. Cast Metal Res., 18(3), pp. 129143 (2005). 4. Hsu, F.Y., Jolly, M.R., and Campbell, J. Vortexgate design for gravity casting", Int. J. Cast Metal Res., 19(1), pp. 3844 (2006). 5. Kay_kc_, R. and Akar, N., Computer Aided Casting Design with Solidcast, DTS, Sakarya, Turkey (2010). 6. ASM International Handbook Committee, Properties and Selection: Nonferrous Alloys and SpecialPurpose Materials, ASM International, Ohio (1990). 7. Campbell, J., Castings Practice: The Ten Rules of Castings, ButterworthHeinemann, Amsterdam (2004). 8. Kay_kc_, R. and C_ olak, M. Investigation of e_ect of grain re_ning on feeding of a sand cast Etial160 aluminium alloy", 5th International Advanced Technologies Symposium, 1, Karabuk, Turkey, pp. 742748 (2009). 9. Schmidt, D., SOLIDCast Training Course Workbook, Finite Solutions Inc, Wisconsin (2014). 10. Djurdjevic, M.B., Sokolowski, J.H., and Odanovic, Z. Determination of dendrite coherency point characteristics using _rst derivative curve versus temperature", J. Therm. Anal. Calorim., 109, pp. 875882 (2012). 11. Veldman, N.L.M., Dahle, A.K., StJohn, D.H., and Arnsberg, L. Dendrite coherency of AlSiCu alloys", Metall. and Mat. Trans. A, 32, pp. 147155 (2001). 12. Akar, N., Kay_kc_, R., and K_sao_glu, A.K. Modelling of critical solid fraction factor depending on mold temperature and grain size of Al4,3cu alloy poured into permenant mold", Journal of Polytechnic, 17(2), pp. 8389 (2014). 13. Cain, G., Arti_cial Neural Networks: New Research, Nova Science Publishers, New York (2016). 14. Moghaddam, M.A., Golmezerji, R., and Kolahan, F. Simultaneous optimization of joint edge geometry and process parameters in gas metal arc welding using integrated ANNPSO approach", Scientia Iranica B, 24(1), pp. 260273 (2017). 15. Ate_s, H., Dursun, B., and Kurt, H. Estimation of mechanical properties of welded S355J2+N steel via the arti_cial neural network", Scientia Iranica B, 23(2), pp. 609617 (2016). 16. Soundararajan, R., Ramesh, A., Sivasankaran, S., and Vignesh, M. Modeling and analysis of mechanical properties of aluminium alloy (A413) reinforced with boron carbide (B4C) processed through squeeze casting process using arti_cial neural network model and statistical technique", Materials Today: Proceedings, 4(2), pp. 20082030 (2017). 17. Canakci, A., Varol, T., and Ozsahin, S. Arti_cial neural network to predict the e_ect of heat treatment, reinforcement size, and volume fraction on AlCuMg alloy matrix composite properties fabricated by stir casting method", Int. J. Adv. Manuf. Technol., 78, pp. 305317 (2015). 18. Altinkok, N. Use of arti_cial neural network for prediction of mechanical properties of _Al2O3 particulatereinforced AlSi10Mg alloy composites prepared by using stir casting process", J. Compos. Mater., 40(9), pp. 779796 (2006). 19. Pham, Q.T. and Phan, T.K.D. Apply neural network for improving production planning at Samarang petrol mine", Int. J. of Intell. Comp. & Cyber., 9(2), pp. 126 143 (2016). 20. S_enyi_git, E. and Atici, U. Arti_cial neural network models for lotsizing problem: a case study", Neural Comput. & Applic., 22(6), pp. 10391047 (2013). 21. Simeunovi_c, N., Kamenko, I., Bugarski, V., Jovanovi_c, M., and Lali_c, B. Improving workforce scheduling using arti_cial neural networks model", Adv. Produc. Engineer. Manag., 12(4), pp. 337352 (2017). 3312 C_ . Teke et al./Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3304{3312 22. Ganesan, N., Venkatesh, K., Rama, M.A., and Palani, A.M. Application of neural networks in diagnosing cancer disease using demographic data", Int. J. of Comput. Appl., 1, pp. 7685 (2010). 23. Chougrad, H., Zouaki, H., and Alheyane, O. Deep convolutional neural networks for breast cancer screening", Comput. Methods Programs Biomed., 157, pp. 1930 (2018). 24. Shioji, M., Yamamoto, T., Ibata, T., Tsuda, T., Adachi, K., and Yoshimura, N. Arti_cial neural networks to predict future bone mineral density and bone loss rate in Japanese postmenopausal women", BMC Res. Notes, 10, pp. 590595 (2017). 25. Murphy, M.C., Manduca, A., Trzasko, J.D., Glaser, K.J., Huston J. 3rd, and Ehman, R.L. Arti_cial neural networks for sti_ness estimation in magnetic resonance elastography", Magn. Reson. Med., 80(1), pp. 351360 (2018). 26. NilsazDezfouli, H., AbuBakar, M.R., Arasan, J., Adam, M.B., and Pourhoseingholi, M.A. Improving gastric cancer outcome prediction using single timepoint arti_cial neural network models", Cancer Inform., 16, pp. 111 (2017). 27. Tsai, C.F. and Wu, J.W. Using neural network ensembles for bankruptcy prediction and credit scoring", Expert Syst. Appl., 34, pp. 26392649 (2008). 28. Ko, P.C. and Lin, P.C. Resource allocation neural network in portfolio selection", Expert Syst. Appl., 35, pp. 330337 (2008). 29. Haider, A. and Hanif, M.N. Ination forecasting in Pakistan using arti_cial neural networks", Pak. Econ. Soc. Rev., 47(1), pp. 123138 (2009). 30. Etebari, F. and Naja_ A.A. Intelligent choicebased network revenue management", Scientia Iranica E, 23(2), pp. 747756 (2016). 31. Davis, J.R., Aluminum and Aluminum Alloys, ASM International, Ohio (1993). 32. ASM International Technical Book Committee, Casting Design and Performance, ASM International, Ohio (2009). 33. Kursun Bahadir, S., Sahin, U.K., and Kiraz, A. Modeling of surface temperature distributions on powered etextile structures using an arti_cial neural network", Text. Res. J., 89(3), pp. 311321 (2019). DOI:10.1177/0040517517743689 34. Flores, J.A., Focus on Arti_cial Neural Networks, Nova Science Publishers, New York (2011).##]
1

Microstructure and fatigue fracture mechanism for a heavyduty truck diesel engine crankshaft
http://scientiairanica.sharif.edu/article_20780.html
10.24200/sci.2018.50964.1939
1
The main goal of this research is the experimental and numerical study on the fatigue function and failure of the crankshaft of diesel engine of a heavy truck. To do this, a crankshaft of the diesel engine of a heavy truck that has gone under failure after traveling 955000 km, has been used. To examine the sources of this failure, several experimental studies have been carried out including chemical composition, the strength of the material, determining the hardness and the microstructure of the material. Besides, using an elastic–plastic three dimensional finite element method (FEM) model, the location of the maximum stress in the crankshaft was determined using the ‘‘complete crankshaft model’’ and ‘‘one crank model’’. Using the results of stress analysis, was a basis for the threedimensional crack growth model and fatigue life estimation to determine the stress intensity factor and fatigue life considering the related parameters and boundary conditions method. At the final stage, using the results gotten from the given model for the fatigue crack growth, comparing it with experimental results, and examining the whole process, it was concluded that the scratches in crankpin region, was the main reason for the fatigue failure got from bendingtorsional loadcombination.
0

3313
3324


K.
Alilakbari
Department of Mechanical Engineering, Faculty of Montazeri, Khorasan Razavi Branch, Technical and Vocational University (TVU), Mashhad, Iran
Iran
karim.aliakbari@gmail.com


M.
Imanparast
Department of Mechanical Engineering, University of Sistan and Baluchestan, Zahedan, Iran
Iran
imanparast@eng.usb.ac.ir


R.
Masoudi Nejad
Department of Mechanical Engineering, Foolad Institute of Technology, Fooladshahr, Isfahan, 8491663763, Iran
Iran
reza.masoudinejad@gmail.com
Fatigue crack growth
Fractography
Crankshaft
Finite Element
Fracture mechanics
[1. Hadipour, M., Alambeigi, F., Hosseini, R., and Masoudinejad, R. A study on the vibrational e_ects of adding an auxiliary chassis to a 6ton truck", Journal of American Science, 7(6), pp. 12191226 (2011). 2. Masoudi Nejad, R. Threedimensional analysis of rolling contact fatigue crack and life prediction in railway wheels and rails under residual stresses and wear", Ph.D. Thesis, Ferdowsi University of Mashhad, School of Mechanical Engineering (2017). 3. Masoudi Nejad, R., Farhangdoost, Kh., and Shariati, M. Microstructural analysis and fatigue fracture behavior of rail steel", Mechanics of Advanced Materials and Structures (2018). DOI:10.1080/15376494.2018.1472339 4. Fonte, M.A. and Freitas, M.M. Semielliptical fatigue crack growth under rotating or reversed bending combined with steady torsion", Fatigue & Fracture of Engineering Materials & Structures, 20(6), pp. 895 906 (1997). 5. Espadafor, F.J., Villanueva, J.B., and Garc__a, M.T. Analysis of a diesel generator crankshaft failure", Engineering Failure Analysis, 16(7), pp. 23332341 (2009). 6. Fonte, M., Reis, L., and De Freitas, M. Fatigue crack growth under rotating bending loading on aluminium alloy 7075T6 and the e_ect of a steady torsion", Theoretical and Applied Fracture Mechanics, 80, pp. 5764 (2015). 7. Fonte, M., Reis, L., and De Freitas, M. The e_ect of steady torsion on fatigue crack growth under rotating bending loading on aluminium alloy 7075T6", Frattura ed Integrit_a Strutturale, 8(30), pp. 360368 (2014). 8. Fonte, M.D., Reis, L., Romeiro, F., Li, B., and Freitas, M. The e_ect of steady torsion on fatigue crack growth in shafts", International Journal of Fatigue, 28(56), pp. 609617 (2006). 9. Martins, R.F., Ferreira, L., Reis, L., and Chambel, P. Fatigue crack growth under cyclic torsional loading", Theoretical and Applied Fracture Mechanics, 85, pp. 5666 (2016). 10. Ghahremani Moghadam, D., Farhangdoost, Kh., and Masoudi Nejad, R. Microstructure and residual stress distributions under the inuence of welding speed in friction stir welded 2024 aluminum alloy", Metallurgical and Materials Transactions B, 47(3), pp. 20482062 (2016). 11. Masoudi Nejad, R. Rolling contact fatigue analysis under inuence of residual stresses", MS Thesis, Sharif University of Technology, School of Mechanical Engineering (2013). 12. Masoudi Nejad, R., Salehi, S.M., and Farrahi, G.H. Simulation of railroad crack growth life under the inuence of combination mechanical contact and thermal loads", in 3rd International Conference on Recent Advances in Railway Engineering, Iran (2013). 13. Salehi, S.M., Farrahi, G.H., Sohrabpoor, S., and Masoudi, Nejad, R. Life estimation in the railway wheels under the inuence of residual stress _eld", International Journal of Railway Research, 1(1), pp. 5360 (2014). 14. Masoudi Nejad, R., Salehi, S.M., Farrahi, G.H., and Chamani, M. Simulation of crack propagation of fatigue in Iran rail road wheels and E_ect of residual stresses", in: Proceedings of the 21st International Conference on Mechanical Engineering, Iran (2013). 15. Masoudi Nejad, R., Shariati, M., and Farhangdoost, Kh. 3D _nite element simulation of residual stresses in UIC60 rails during the quenching process", Thermal Science, 21(3), pp. 13011307 (2017). 16. Chien, W.Y., Pan, J., Close, D., and Ho, S. Fatigue analysis of crankshaft sections under bending with consideration of residual stresses", International Journal of Fatigue, 27(1), pp. 119 (2005). 17. Infante, V., Silva, J.M., Silvestre, M.A.R., and Baptista, R. Failure of a crankshaft of an aeroengine: A contribution for an accident investigation", Engineering Failure Analysis, 35, pp. 286293 (2013). 18. De Freitas, M., Reis, L., Da Fonte, M., and Li, B. E_ect of steady torsion on fatigue crack initiation and propagation under rotating bending: Multiaxial fatigue and mixedmode cracking", Engineering Fracture Mechanics, 78(5), pp. 826835 (2011). 19. Moore, D.A., Packer, K.F., Jones, A.J., and Carlson, D.M. Crankshaft failure and why it may happen again", Practical Failure Analysis, 1(3), pp. 6372 (2001). K. Aliakbari et al./Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3313{3324 3323 20. Farrahi, G.H., Hemmati, F., Gangaraj, S.A., and Sakhaei, M. Failure analysis of a four cylinder diesel engine crankshaft made from nodular cast iron", The Journal of Engine Research, 22, pp. 2127 (2011). 21. Fonte, M., Anes, V., Duarte, P., Reis, L., and Freitas, M. Crankshaft failure analysis of a boxer diesel motor", Engineering Failure Analysis, 56, pp. 109115 (2015). 22. Masoudi Nejad, R., Farhangdoost, Kh., and Shariati, M. Threedimensional simulation of rolling contact fatigue crack growth in UIC60 rails", Tribology Transactions, 59(6), pp. 10591069 (2016). 23. Masoudi Nejad, R., Farhangdoost, Kh., Shariati, M., and Moavenian, M. Stress intensity factors evaluation for rolling contact fatigue cracks in rails", Tribology Transactions, 60(4), pp. 645652 (2016). 24. Shariati, M. and Masoudi Nejad, R. Fatigue strength and fatigue fracture mechanism for spot welds in Ushape specimens", Latin American Journal of Solids and Structures, 13(15), pp. 27872801 (2016). 25. Shariati, M., Mohammadi, E., and Masoudi Nejad, R. E_ect of a new specimen size on fatigue crack growth behavior in thickwalled pressure vessels", International Journal of Pressure Vessels and Piping, 150, pp. 110 (2017). 26. Masoudi Nejad, R., Shariati M., and Farhangdoost, Kh. E_ect of wear on rolling contact fatigue crack growth in rails", Tribology International, 94, pp. 118 125 (2016). 27. Masoudi Nejad, R., Farhangdoost, Kh., and Shariati, M. Numerical study on fatigue crack growth in railway wheels under the inuence of residual stresses", Engineering Failure Analysis, 52, pp. 7589 (2015). 28. Masoudi Nejad, R. Using threedimensional _nite element analysis for simulation of residual stresses in railway wheels", Engineering Failure Analysis, 45, pp. 449455 (2014). 29. Masoudi Nejad, R., Shariati, M., Farhangdoost, Kh., and Atrian, A. Rolling contact fatigue analysis of rails under the inuence of residual stresses induced by manufacturing", Scientia Iranica, 26(3), pp. 1427 1437 (2019). 30. Fonte, M., Infante, V., Freitas, M., and Reis, L. Failure mode analysis of two diesel engine crankshafts", Procedia Structural Integrity, 1, pp. 313318 (2016). 31. Alfares, M.A., Falah, A.H., and Elkholy, A.H. Failure analysis of a vehicle engine crankshaft", Journal of Failure Analysis and Prevention, 7(1), pp. 1217 (2007). 32. Silva, F.S. Analysis of a vehicle crankshaft failure", Engineering Failure Analysis, 10(5), pp. 605616 (2003). 33. Becerra, J.A., Jimenez, F.J., Torres, M., Sanchez, D.T., and Carvajal, E. Failure analysis of reciprocating compressor crankshafts", Engineering Failure Analysis, 18(2), pp. 735746 (2011). 34. Aliakbari, K., Safarzadeh, N., and Mortazavi, S.S. The analysis of wheel loader diesel engine crankshaft failure", International Journal of EngineeringTransactions C: Aspects, 31(3), pp. 473 479 (2017). 35. Aliakbari, K. The analysis of lightduty truck diesel engine crankshaft failure", Journal of Stress Analysis, 2(2), pp. 1117 (2018). 36. Aliakbari, K. and Farhangdoost, K. Plastic deformation inuence on material properties of autofrettaged tubes used in diesel engines injection system", Journal of Pressure Vessel Technology, 136(4), p. 041402 (2014). 37. Aliakbari, K. and Farhangdoost, K. The investigation of modeling material behavior in autofrettaged tubes made from aluminium alloys", International Journal of Engineering, 27, pp. 803810 (2014). 38. Conrado, E., Gorla, C., Davoli, P., and Boniardi, M. A comparison of bending fatigue strength of carburized and nitrided gears for industrial applications", Engineering Failure Analysis, 78, pp. 4154 (2017). 39. ASM Handbook Committee, ASM Metals Hand Book, 12, Fractography, 2nd Edition (1992). 40. Bayrakceken, H., Ucun, I., and Tasgetiren, S. Fracture analysis of a camshaft made from nodular cast iron", Engineering Failure Analysis, 13(8), pp. 1240 1245 (2006). 41. Fonte, M., Duarte, P., Reis, L., Freitas, M., and Infante, V. Failure mode analysis of two crankshafts of a single cylinder diesel engine", Engineering Failure Analysis, 56, pp. 185193 (2015). 42. Becerra, J.A., Jimenez, F.J., Torres, M., Sanchez, D.T., and Carvajal, E. Failure analysis of reciprocating compressor crankshafts", Engineering Failure Analysis, 18(2), pp. 735746 (2011). 43. Elishako_, I., Fu, C.M., Jiang, C., Ni, B.Y., Han, X., and Chen, G.S. Comparison of uncertainty analyses for crankshaft applications", ASCEASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 1(4), p. 041002 (2015). 44. Zanotti, A., Calculation of Crankshafts for Internal Combustion Engines, Germanischer Lloyd SE, Hamburg (2012). 45. Zhang, Q., Zuo, Z., and Liu, J. Failure analysis of a diesel engine cylinder head based on _nite element method", Engineering Failure Analysis, 34, pp. 5158 (2013). 46. K_l__caslan, C. and _Ince, U. Failure analysis of cold forged 37Cr4 alloy M10x28 bolts", Engineering Failure Analysis, 70, pp. 177187 (2016). 47. Montazersadgh, H.F. Stress analysis and optimization of crankshafts subject to dynamic loading", Ph.D. Thesis, University of Toledo (2007). 48. Webster, W.D., Co_ell, R., and Alfaro, D. A Three Dimensional Finite Element Analysis of a High Speed 3324 K. Aliakbari et al./Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3313{3324 Diesel Engine Connecting Rod, Society of Automotive Engineers, Warrendale, USA Technical Paper, No. 831322 (1983). 49. Cornell Fracture Group, Accessed 15 March (2015), http://www.cfg.cornell.edu. 50. FRANC3D Concepts and user guide", Cornell Fracture Group, Cornell University, Ithaca, N.Y (1997). 51. Forman, R.G., Kearney, V.E., and Engel, R.M. Numerical analysis of crack propagation in cyclicloaded structures", Journal of Basic Engineering, 89, pp. 459 463 (1967). 52. Elber, W. The signi_cance of fatigue crack closure, in damage tolerance in aircraft structures", ASTM STP, 486, pp. 230242 (1971). 53. NASA Fatigue Crack Growth Computer Program NASGRO Version 3.0", Reference Manual. JSC 22267B, NASA, Lyndon B. Johnson Space Center, Texas (2000). 54. Anderson, T.L., Fracture Mechanics, Fundamentals and Applications, 2nd Ed. CRC press (1994). 55. Newman, J.J. A crack opening stress equation for fatigue crack growth", International Journal of Fracture, 24(4), pp. R131R135 (1984).##]
1

Investigation of transient numerical simulation of solidification and thermal behavior of metal molds with conformal cooling channels
http://scientiairanica.sharif.edu/article_20896.html
10.24200/sci.2018.50988.1953
1
The cooling process in metal molds is one of the important factors in the solidification process of molten metal. Molding defects such as hot spot defects and warping occur in cast products when the cooling is not uniform. However, qualified and faster cooling affects product quality positively. Molding is one of the important processes both in terms of cycle time and product quality, with permanent mold casting, high quality liquid metal casting, and quality product. Selective Laser Melting (SLM) method has been used to design metal mold cores with unique cooling channels to be compactly produced. The effects of the designed cooling channels, heat transfer and solidification of the molten metal are studied in transient numerical terms. The temperature distributions for 1, 3 and 5 seconds after casting were obtained and the solidification processes were investigated according to the standard cooling channels of the original cooling channels. According to the results obtained, it has been observed that solidification is better in originally designed cooling channels.
0

3325
3333


O.
İPEK
Department of Mechanical Engineering, Faculty of Engineering, Suleyman Demirel University, Isparta, Turkey.
Turkey
osmanipek@sdu.edu.tr


A.
BOLATTURK
Department of Mechanical Engineering, Faculty of Engineering, Suleyman Demirel University, Isparta, Turkey.
Turkey
alibolatturk@sdu.edu.tr


M.
KAN
Department of Mechanical Engineering, Faculty of Engineering, Suleyman Demirel University, Isparta, Turkey.
Turkey
mehmetkan@sdu.edu.tr


K.
Kurtuluş
Department of Mechanical Engineering, Faculty of Engineering, Suleyman Demirel University, Isparta, Turkey.
Turkey
karanikurtulus@sdu.edu.tr
Metal Mold
SLM
Conformal Cooling Channels
[1. Hsu, F.H., Wang, K., Huang, C.T., and Chang, R.Y. Investigation on conformal cooling system design in injection molding", Advances in Production Engineering & Management, 8(2), pp. 107115 (2013). 2. Hongjun, L., Zitian, F., Naiyu, H., and Xuanpu, D. A note on rapid manufacturing process of metallic parts based on SLS plastic prototype", Journal of Materials Processing Technology, 142, pp. 710713 (2003). 3. Ferreira, J.C. and Mateus, A. Studies of rapid soft tooling with conformal cooling channels for plastic injection moulding", Journal of Materials Processing Technology, 142, pp. 508516 (2003). 4. Deckers, J., Meyers, S., Kruth, J.P., and Vleugels, J. Direct selective laser sintering/melting of high density alumina powder layers at elevated temperatures", Physics Procedia, 56, pp. 117124 (2014). 5. Dalgarno, K.W. and Stewart, T.D. Manufacture of production injection mould tooling incorporating conformal cooling channels via indirect selective laser sintering", Proceeding of the Institution of Mechanical Engineers, 215(B), pp. 13231332 (2001). 6. Wang, Y., Yu, K.M., and Wang, C.C.L. Spiral and conformal cooling in plastic injection molding", ComputerAided Design, 63, pp. 111 (2015). 7. Xia, C., Fu, F., Lai, J., Yao, X., and Chen, Z. Conjugate heat transfer in fractal treelike channels network heat sink for highspeed motorized spindle cooling", Applied Thermal Engineering, 90, pp. 1032 1042 (2015). 8. Hu, P., He, B., and Ying, L. Numerical investigation on cooling performance of hot stamping tool with various channel designs", Applied Thermal Engineering, 96, pp. 338351 (2016). 9. Wang, H.L., Wu, H.C., Wang, S.K., Hung, T.C., and Yang, R.J. A study of minichannel thermal module design for achieving high stability and high capability in electronic cooling", Applied Thermal Engineering, 51, pp. 11441153 (2013). 10. Vojnov_a, E. The bene_ts of a conforming cooling systems the molds in injection moulding process", Procedia Engineering, 149, pp. 535543 (2016). 11. Venkatesh, G.Y. Ravi, K., and Raghavendra, G. Comparison of straight line to conformal cooling channel in injection molding", Materials Today: Proceedings, 4(2), pp. 11671173 (2017). 12. Jahan, A.S. and Mounayri, H. Optimal conformal cooling channels in 3D printed dies for plastic injection molding", Procedia Manufacturing, 5, pp. 888900 (2016). 13. Venkatesh, G.Y. and Kumar, R. Thermal analysis for conformal cooling channel", 5th International Conference of Materials Processing and Characterization (ICMPC 2016), Materials Today: Proceedings, 4, pp. 25922598 (2017). 14. Zehtabiyan, R.N., Damirci, D.S., Fazel, Z.M.H., and Sa_ar, A.M. Generalized heat transfer and entropy generation of strati_ed airwater ow in entrance of a minichannel", Scientia Iranica, B, 24(5), pp. 2406 2417 (2017). 15. Nouri, B.A. and SeyyedHashemi, M.H. Numerical analysis of thermally developing turbulent ow in partially _lled porous pipes", Scientia Iranica, B, 22(3), pp. 835843 (2015). 16. Imran, A.A., Nabeel, S.M., and Hayder, M.J. Numerical and experimental investigation of heat transfer in liquid cooling serpentine minichannel heat sink with di_erent new con_guration models", Thermal Science and Engineering Progress, 6, pp. 128139 (2018). 17. Park, H. and Dang, X.P. Development of a smart plastic injection mold with conformal cooling channels", Procedia Manufacturing, 10, pp. 4859 (2017). 18. Sachs, E., Wylonis, E., Allen, S., Cima, M., and Guo, H. Production of injection moulding tooling with conformal cooling channels using the three dimensional printing process", Polymer Engineering and Science, 40(5), pp. 12371247 (2000). 19. Eimsaard, K. and Wannisorn, K. Conformal bubbler cooling for molds by metal deposition process", ComputerAided Design, 69, pp. 126133 (2015). 20. Holker, R., Haase, M., Khalifa, N.B., and Takkaya, A.E. Hot extrusion dies with conformal cooling channels produced by additive manufacturing", Aluminum Two Thousand World Congress and International Conference on Extrusion and Benchmark ICEB, pp. 48384846 (2015). 21. Koller, M., Walter, H., and Hameter, M. Transient numerical simulation of the melting and solidi_cation behavior of NaNO3 using a wire matrix for enhancing of the heat transfer", Energies, 9, p. 205 (2016). 22. Kumar Koli, D., Agnihotri, G., and Purohit, R. Advanced aluminium matrix composite: the critical need of automotive and aerospace engineering _elds", Materials Today: Proceeding, 2, pp. 30323041 (2015). 23. Furumoto, T., Ueda, T., Amino, T., Ksunoki, D., Hosokowa, A., and Tanaka, T. Finishing performance of cooling channel with face protuberance inside the molding die", Journal of Material Processing Technology, 212, pp. 21542160 (2012). DOI: 10.1016/j.jmatprotec.2012.05.016 24. Ozsarac, U., I_sik, S_., Varol, F., Emin Unat, M., Ozdemir, C., and Aslanlar, S. Investigation of tensile properties of aluminum 6082T6 alloys joined by cold metal transfer method by using di_erent working time", Acta Physica Polonica A, 132(3), p. 705 (2017). 25. Djendel, M., Allaoui, O., and Boubaaya, R. Characterization of aluminatitania coatings produced by atmospheric plasma spraying on 304 SS steel", Acta Physica Polonica A, 132(3), p. 538 (2017). 26. Aktas, B. , Balak, V., and Carboga, C. Dry sliding wear behavior of borondoped AISI 1020 steels", Acta Physica Polonica A, 132(3), p. 455 (2017). O. _Ipek et al./Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3325{3333 3333 27. Ipek, O., Kan, M., and Gurel, B. Examination of di_erent heat exchangers and the thermal activities of di_erent designs", Acta Physica Polonica A, 132(3), pp. 580583 (2017). 28. Kara_cal_, O. Computational material analysis of structural and hemodynamic model of coronary stent by CFD/FEA in computer aided mechanical engineering approach", Acta Physica Polonica A, 130(1), p. 249 (2016). 29. Kan, M., Ipek, O., and Gurel, B. Plate heat exchangers as a compact design and optimization of di_erent channel angles", Acta Physica Polonica A, 128(2B), pp. B49 B52 (2015). 30. FLUENT Manual, Chapter 21: Modeling Solidi_cation and Melting; ANSYS, Inc.: Canonsburg, PA, USA (2001). 31. Patel, D.R. and Patel, N.S. Development of AlSiC MMCs for making valves", International Journal of Advanced Research and Innovative Ideas in Education, 2(3) pp. 26192628 (2016).##]
1

Evaluation of vehicle braking parameters by multiple regression method
http://scientiairanica.sharif.edu/article_21474.html
10.24200/sci.2019.51584.2262
1
In this study, two pairs of OEM brake discpads have been used. One of these discs belongs to a passenger car, and the other one belongs to a light commercial vehicle. The discpad pair of the passenger car (PC) has been subjected to global brake effectiveness test by full scale inertia dynamometer according to SAE J2522 test standard; and the other one has been subjected to the tests by fullscale inertia dynamometer according to FIAT 7H4020 and 7H2000 standards. During these tests, 13 variables for passenger car discpad pair and 11 variables for light commercial vehicle discpad pair have been measured and recorded. Interrelation of the parameters has been analyzed with multiple regression method and importance levels have been determined. In this study, dependent variables in multiple regression method are selected as braking time, friction coefficient, disc final temperature, brake speed and brake pressure for each braking pair. In multiple regression analysis for PC, for each unit increase in deceleration and friction coefficient, braking time decreases with 7.3 and 60.9 units, respectively. Also, for each unit increase in brake pressure and friction coefficient for LCV, braking time increases with 1.267 and 91.887 units, respectively.
0

3334
3355


Abdullah
Demir
Department of Automotive, Faculty of Technology, Marmara University, Goztepe Campus, Istanbul
Turkey
ademir@marmara.edu.tr


Ali
Oz
Assistant Professor, Department of Motor Vehicles and Transportation Technologies, TBMYO, Mehmet Akif Ersoy University, Burdur
Turkey
alioz@mehmetakif.edu.tr
Braking parameters
braking performance
Friction coefficient
brake discpad pair
multiple regression method
[1. Dhir, D.K. Thermomechanical performance of automotive disc brakes", Materials Today: Proceedings, 5(11), pp. 18641871 (2018). 2. Goktan, A., Guney, A., and Ereke, M. Vehicle brakes", Alliedsignal Automotive, Panel Publishing, p. 48, Istanbul, Turkey (1995). 3. Demir, A. An experimental investigation on the braking performance of coated brake discs/rotors", Doctoral Thesis, Kocaeli University, Institute of Science and Technology, Department of Machine Training, Kocaeli, Turkey (2009). 4. Childs, P.R.N. Clutches and brakes", Mechanical Design Engineering Handbook, Second Edition, pp. 599655 (2019). 5. Limpert, R., Brake Design and Safety, Society of Automotive Engineers, Third Edition, Warrendale (2001). 6. Bijwe, J., Dureja, N., Majumdarb, N., and Satapathy, B.K. Inuence of modi_ed phenolic resins on the fade and recovery behavior of friction materials", Wear, 259(7), pp. 10681078 (2005). 7. Lee, K. Numerical prediction of brake uid temperature rise during braking and heat soaking", SAE Technical Paper Series, 1999010483 (1999). 8. Chang, Y.H., Joo, B.S., Lee, S.M., and Jang, H. Size e_ect of tire rubber particles on tribological properties of brake friction materials", Wear, 394395, pp. 8086 (2018). 9. Owen, C., Automotive Brake Systems, Classroom Manual, Today's Technician, Delmar Cengage Learning (2010). 10. Hiller, M.B. Correlation between parameters of the tribosystem and automotive disc brake squeal", PhD Thesis, University of Paderborn, pp. 1203 (2006). 11. Dmitriev, A.I., Yu Smolin, A., Psakhie, S.G., et al. Computer modelling of local tribological contact by the example of the automotive brake friction pair", Physical Mesomechanics, 11(12), pp. 7384 (2008). 12. Wu, D., Li, J., Shu, X., et al. Test analysis and theoretical calculation on braking distance of automobile with ABS", Part IV, International Federation for Information Processing  IFIP AICT 347, D. Li, Y. Liu, and Y. Chen (Eds.): CCTA 2010, pp. 521527 (2011). 13. BEEP, How to read and understand the aftermarket standard SAE J2430/brake e_ectiveness evaluation procedure test report", Link Testing Laboratories B.E.E.P. Task force (2002). 14. Noon, R.K., Engineering Analysis of Vehicular Accidents, ISBN 9780849381041, pp. 1205, CRC Press, Florida, USA (1994). 15. Nagurnas, S., Mitunevi_cius, V., Unarski, J., et al. Evaluation of veracity of car braking parameters used for the analysis of road accidents", Transport, 22(4), pp. 307311 (2007). 16. Syahrullail, S., Izhan M.I., and Mohammed Ra_q, A.K. Tribological investigation of RBD palm olein in di_erent sliding speeds using pinondisk tribotester", Scientia Iranica, Transactions B: Mechanical Engineering, 21(1), pp. 162170 (2014). 17. Rhee, S.K. Friction properties of a phenolic resin _lled with iron and graphite  sensitivity to load, speed and temperature", Wear, 28(2), pp. 277281 (1974). 18. Filip, P., Weiss, Z., and Rafaja, D. On friction layer formation in polymer matrix composite materials for brake applications", Wear, 252(3), pp. 189198 (2002). 19. Cho, M.H., Kim, S.J., Kim, D., et al. E_ects of ingredients on tribological characteristics of a brake lining: An experimental case study", Wear, 258(11 12), pp. 16821687 (2005). 20. Hong, U.S., Jung, S.L., Cho, K.H., et al. Wear mechanism of multiphase friction materials with di_erent phenolic resin matrices", Wear, 266(78), pp. 739744 (2009). 21. Heussa_, A., Dubar, L., Tison, T., et al. A methodology for the modelling of the variability of brake lining surfaces", Wear, 289, pp. 145159 (2012). 22. ElTayeb, N.S.M. and Liew, K.W. On the dry and wet sliding performance of potentially new frictional brake pad materials for automotive industry", Wear, 266(12), pp. 275287 (2009). 23. Sa_ar, A., Shojaei, A., and Arjmand, M. Theoretical and experimental analysis of the thermal, fade and wear characteristics of rubberbased composite friction materials", Wear, 269(12), pp. 145151 (2010). 24. Liew, K.W. and Nirmal, U. Frictional performance evaluation of newly designed brake pad materials", Materials & Design, 48, pp. 2533 (2013). 25. Rashid, A. Overview of disc brakes and related phenomena  a review", International Journal of Vehicle Noise and Vibration, 10(4), pp. 257301 (2014). 26. Ricciardi, V., Augsburg, K., Gramstat, S., et al. Survey on modelling and techniques for friction estimation in automotive brakes", Appl. Sci., 7(873), Review, pp. 123 (2017). 27. Behrendt, J., Weiss, C., and Ho_mann, N. A numerical study on stickslip motion of a brake pad in steady sliding", J. Sound Vib., 330, pp. 636651 (2011). 3344 A. Demir and A. Oz/Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3334{3355 28. Grkic, A., Muzdeka, S., Arsenic, Z., et al. Model for estimation of the friction coe_cient in automotive brakes under extremely high temperatures", Int. J. Eng. Tech. Res., 2, pp. 290294 (2014). 29. Lee, N. and Kang, C. The e_ect of a variable disc pad friction coe_cient for the mechanical brake system of a railway vehicle", PLoS ONE, 10(8), e0135459 (2015). 30. Carlos, E.A. and Ferro, E. Technical overview of brake performance testing for original equipment and aftermarket industries in the US and European markets", Link Technical Report FEV 200501, pp. 1516 (2005). 31. Demir, A., Samur, R., and Kilicaslan, I. Investigation of the coatings applied onto brake discs on discbrake pad pair", Metalurgija, 48(3), pp. 161166 (2009). 32. Oz, A. Experimental research on reuse of worn brake discs by coating with powders", PhD Thesis, Suleyman Demirel University, Isparta, Turkey (2012). 33. Newbold, P., Carlson, W.L., and Thorne, BM., Statistics for Business and Economics, 8th Ed., ISBN 13: 9780132745659, Pearson Education, Prentice Hall (2013). 34. Ataee, O., Moghaddas, N.H., Lashkaripour, G.R., et al. Predicting shear wave velocity of soil using multiple linear regression analysis and arti_cial neural networks", Scientia Iranica, 25(4), pp. 19431955 (2018). 35. Xiao, X., Yin, Y., Bao, J., et al. Review on the friction and wear of brake materials", Advances in Mechanical Engineering, 8(5), pp. 110 (2016). 36. Verma, P.C. Automotive brake materials: Characterization of wear products and relevant mechanisms at high temperature", Department of Industrial Engineering, PhD Thesis, University of Trento, Italy, pp. 1134 (2016). 37. Luo, Y. and Yang, Z. E_ect of di_erentcondition parameters on frictional properties of nonasbestos phenolic resinbased friction material", Advances in Mechanical Engineering, 9(5), Research Article, pp. 1 14 (2017).##]
1

A collocation algorithm based on quintic Bsplines for the solitary wave simulation of the GRLW equation
http://scientiairanica.sharif.edu/article_20781.html
10.24200/sci.2018.20781
1
In this article, a collocation algorithm based on quintic Bsplines is proposed for the numerical solution of the nonlinear generalized regularized long wave (GRLW) equation. Also, to analyse the linear stability of the numerical scheme, the vonNeumann technique is used. The numerical approach is discussed on three test examples consisting of a single solitary wave, the collision of two solitary waves and the growth of an undular bore. The accuracy of the method is demonstrated by calculating the error in the L2 and L¥ norms and the conservative quantities I1, I2 and I3. The findings are compared with those of previously reported in the literature. Finally, the motion of solitary waves is graphically plotted according to different parameters.
0

3356
3368


H.
Zeybek
Department of Applied Mathematics, Faculty of Computer Science, Abdullah Gul University, 38080 Kayseri, Turkey.
Turkey


S.
Battal Gazi Karako
Department of Mathematics, Faculty of Science and Art, Nevsehir Hac Bektas Veli University, 50300, Nevsehir, Turkey.
Turkey
GRLW equation
Finite element scheme
Quintic Bspline
Solitons
Undular bore
[1. Peregrine, D.H. Calculations of the development of an undular bore", Journal of Fluid Mechanics, 25, pp. 321330 (1966). 2. Peregrine, D.H. Long waves on a beach", Journal of Fluid Mechanics, 27, pp. 815827 (1967). 3. Benjamin, T.B., Bona, J.L., and Mahony, J.J. Model equations for long waves in nonlinear dispersive systems", Philosophical Transactions of the Royal Society of London Series A, 272, pp. 4778 (1972). 4. Morrison, P.J., Meiss, J.D., and Carey, J.R. Scattering of RLWsolitary waves", Physica D, 11, pp. 324336 (1984). 5. Raslan, K.R. Collocation method using quadratic Bspline for the RLW equation", International Journal of Computer Mathematics, 78, pp. 399412 (2001). 6. Da_g, I., Saka, B., and Irk, D. Application of cubic Bsplines for numerical solution of the RLW equation", Applied Mathematics and Computation, 159(2), pp. 373389 (2004). 7. Saka, B., Da_g, I., and Irk, D. Quintic Bspline collocation method for numerical solution of the RLW equation", The ANZIAM Journal, 49(3), pp. 389410 (2008). 8. Saka, B., Sahin, A., and Da_g, I. Bspline collocation algorithms for numerical solution of the RLW equation", Numerical Methods for Partial Di_erential Equations, 27, pp. 581607 (2011). 9. Soliman, A.A. and Hussien, M.H. Collocation solution for RLW equation with septic spline", Applied Mathematics and Computation, 161(2), pp. 623636 (2005). 10. Da_g, I., Saka, B. and Irk, D. Galerkin method for the numerical solution of the RLW equation using quintic Bsplines", Journal of Computational and Applied Mathematics, 190, pp. 532547 (2006). 11. Esen, A. and Kutluay, S. Application of a lumped Galerkin method to the regularized long wave equation", Applied Mathematics and Computation, 174, pp. 833845 (2006). 12. Mei, L. and Chen, Y. Numerical solutions of RLW equation using Galerkin method with extrapolation techniques", Computer Physics Communications, 183, pp. 16091616 (2012). 13. Gardner, L.R.T., Gardner, G.A., Ayoub, F.A., and Amein, N.K. Approximations of solitary waves of the MRLW equation by Bspline _nite element", Arabian Journal for Science and Engineering, 22, pp. 183193 (1997). 14. Haq, F., Islam, S., and Tirmizi, I.A. A numerical technique for solution of the MRLW equation using quartic Bsplines", Applied Mathematical Modelling, 34(12), pp. 41514160 (2010). 15. Karako_c, S.B.G., Ya_gmurlu, N.M., and Ucar, Y. Numerical approximation to a solution of the modi _ed regularized long wave equation using quintic Bsplines", Boundary Value Problems, 2013, pp. 117 (2013). 16. Karako_c, S.B.G., Ak, T., and Zeybek, H. An e_cient approach to numerical study of the MRLW equation with Bspline collocation method", Abstract and Applied Analysis, 2014, pp. 115 (2014). 17. Khalifa, A.K., Raslan, K.R., and Alzubaidi, H.M. A collocation method with cubic Bsplines for solving the MRLW equation", Journal of Computational and Applied Mathematics, 212, pp. 406418 (2008). 18. Raslan, K.R. and ELDanaf, T.S. Solitary waves solutions of the MRLW equation using quintic Bsplines", Journal of King Saud University  Science, 22(3), pp. 161166 (2010). 19. Ali, A. Mesh free collocation method for numerical solution of initialboundary value problems using radial basis functions", Ph.D. Thesis, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Pakistan (2009). 20. Da_g, I., Irk, D., and Sari, M. The extended cubic Bspline algorithm for a modi_ed regularized long wave equation", Chinese Physics B, 22(4), pp. 16 (2013). 21. Abo Essa, Y.M., Abouefarag, I., and Rahmo, E.D. The numerical solution of the MRLW equation using the multigrid method", Applied Mathematics, 5, pp. 33283334 (2014). 22. Bona, J.L., McKinney, W.R., and Restrepo, J.M. Stable and unstable solitarywave solutions of the generalized regularized longwave equation", Journal of Nonlinear Science, 10, pp. 603638 (2000). 23. Hammad, D.A. and ElAzab, M.S. A 2N order compact _nite di_erence method for solving the generalized regularized long wave (GRLW) equation", Applied Mathematics and Computation, 253, pp. 248 261 (2015). 24. Huang, D.M. and Zhang, L.W. Elementfree approximation of generalized regularized long wave equation", Mathematical Problems in Engineering, 2014, pp. 110 (2014). 25. Mokhtari, R. and Mohammadi, M. Numerical solution of GRLW equation using Sinccollocation method", Computer Physics Communications, 181, pp. 12661274 (2010). 3368 H. Zeybek and S. Battal Gazi Karako_c/Scientia Iranica, Transactions B: Mechanical Engineering 26 (2019) 3356{3368 26. Roshan, T. A PetrovGalerkin method for solving the generalized regularized long wave (GRLW) equation", Computers and Mathematics with Applications, 63, pp. 943956 (2012). 27. Soliman, A.A. Numerical simulation of the generalized regularized long wave equation by He's variational iteration method", Mathematics and Computers in Simulation, 70, pp. 119124 (2005). 28. Zhang, L. A _nite di_erence scheme for generalized regularized longwave equation", Applied Mathematics and Computation, 168, pp. 962972 (2005). 29. Kaya, D. and ElSayed, S.M. An application of the decomposition method for the generalized KdV and RLWequations", Chaos, Solitons and Fractals, 17, pp. 869877 (2003). 30. Hamdi, S., Enright, W.H., Schiesser, W.E., and Gottlieb, J.J. Exact solutions and invariants of motion for general types of regularized long wave equations", Mathematics and Computers in Simulation, 65, pp. 535545 (2004). 31. Ramos, J.I. Solitary wave interactions of the GRLW equation", Chaos, Solitons & Fractals, 33, pp. 479491 (2007). 32. Mohammadi, R. Exponential Bspline collocation method for numerical solution of the generalized regularized long wave equation", Chinese Physics B, 24, pp. 114 (2015). 33. Zeybek, H. and Karako_c, S.B.G. A numerical investigation of the GRLW equation using lumped Galerkin approach with cubic Bspline", SpringerPlus, 5, pp. 117 (2016). 34. Karako_c, S.B.G. and Zeybek, H. Solitarywave solutions of the GRLW equation using septic Bspline collocation method", Applied Mathematics and Computation, 289, pp. 159171 (2016). 35. Irk, D. and Da_g, I. Quintic Bspline collocation method for the generalized nonlinear Schrodinger equation", Journal of the Franklin Institute, 348, pp. 378392 (2011). 36. Ismail, M.S. Numerical solution of complex modi_ed Kortewegde Vries equation by collocation method", Communications in Nonlinear Science and Numerical Simulation, 14, pp. 749759 (2009). 37. Mittal, R.C. and Tripathi, A. Numerical solutions of generalized BurgersFisher and generalized Burgers Huxley equations using collocation of cubic Bsplines", International Journal of Computer Mathematics, 93, pp. 10531077 (2015). 38. Ak, T., Karako_c, S.B.G., and Biswas, A. Application of PetrovGalerkin _nite element method to shallow water waves model: modi_ed Kortewegde Vries equation", Scientia Iranica, 24, pp. 11481159 (2017). 39. Prenter, P.M., Splines and Variational Methods, J. Wiley, New York (1975). 40. Rubin, S.G. and Graves, R.A., A Cubic Spline Approximation for Problems in Fluid Mechanics, NASA TR R436, Washington, DC (1975).##]
1

Simulation in virtual reality: Robotic training and surgical applications
http://scientiairanica.sharif.edu/article_21617.html
10.24200/sci.2019.50451.1702
1
Two case studies are performed in this study; one with 4dof robotic system, the other 6dof industrial robot arm . Both robot arms are actually operated in Mechatronics Laboratory, Gaziantep University. Different motion trajectories are designed, and implemented for training, medical tasks and surgical operations base. Simulations are built by using VR Toolbox in Matlab. Virtual reality environment is achieved through Simulink with real time examples . The motions and trajectories necessary for training and surgical applications are directly seen. This enables the surgeons training with many benefits; greater control during tasks reduced training periods, possibility of error free tasks for example.
0

3369
3374


A.J.R.
Almusawi
Department of Mechatronics Engineering, University of Baghdad, Iraq
Iraq


L.C.
Dulger
Department of Mechanical Engineering, Faculty of Engineering, Gaziantep University, Gaziantep, Turkey
Turkey
canan.dulger@ieu.edu.tr


S.
Kapucu
Department of Mechanical Engineering, Faculty of Engineering, Gaziantep University, Gaziantep, Turkey
Turkey
robotic surgery (RS)
robotic training (RT)
virtual reality (VR)
Virtual Reality Model (VRM)
Thoracoscopic surgery
[1. Fulcar, V.N. and Shivramwar, M.V. Applications of Haptics technology in advance robotics", IEEE 2010, pp. 273277 (2010). 2. Staub, C., Can, S., Jensen, B., Knoll, A., and Kohlbecher, S. Human computer interfaces for interaction with surgical tools in robotic surgery", The 4th IEEE RAS/EMBS Int. Conf. on Biomedical Rob. and BiomechatronicsItaly, 2012IEEE, pp. 8186 (2012). 3. Khor, W.S., Baker, B., Amin, K., Chan, A., Patel, K., and Wong, J. Augmented and virtual reality in surgerythe digital surgical environment: applications, limitations and legal pitfalls", Annals of Translational Medicine, 4(23), p. 454 (2016). 4. AlMashhadany, Y.I. Scara robot: Modeled, simulated, and virtualreality veri_ed", Communications in Comp. and Information Science, CCIS 330, Springer Verlag, pp. 94102 (2016). 5. Buckley, C.E., Nugent, E., Ryan, D., and Neary, P.C. Virtual realityA new era in surgical training", Chapter 7INTECH, Book: Virtual Reality in Psychological, Medical and Pedagogical Applications, pp. 139 166 (2012). 6. Nooshabadi, Z.S., Abdi, E., Farahmand, F., Narimani, R., and Chizari, M. A Meshless method to simulate the interactions between a large soft tissue and a surgical grasper", Scientia Iranica, 23(1), pp. 295300 (2016). 7. Almusawi, A.R.J., Dulger, L.C., and Kapucu, S. Robotic arm dynamic and simulation with virtual reality model (VRM)", CoDIT'16IEEE, Malta, pp. 335340 (2016). 8. Almusawi, A.R.J. Implementation of learning motion to control a robotic arm using haptic technology", PhD Thesis, Gaziantep University (2016). 9. Almusawi, A.R.J., Dulger, L.C., and Kapucu, S. A new arti_cial neural network approach in solving inverse kinematics of robotic arm (Denso VP6242)", Computational Intelligence and Neuroscience, pp. 110 (2016). 10. Robotic Arm Edge OWI535 Robot, Product Instruction Manual (2008). 11. Quanser.com. [assessed July 2018]. http://www. quanser.com/products/denso 12. Leon, E.D., Nair, S.S., and Knoll, A. User friendly Matlabtoolbox for symbolic robot dynamic modeling used for control design", IEEEInt. Conf. on Robotics and Biomimetics, pp. 21812188 (2012). 13. Corke, P., Robotics, Vision and Control Fundamental Algorithms in MATLAB, V.73: SpringerVerlag BerlinHeidelberg, pp. 191205 (2011). 14. www.MathWorks, Virtual Reality Modeling Language (VRML)MATLAB/Simulink".##]