Abstract
In this paper, the superior performance of a novel space exploration and unimodal region elimination global optimization algorithm, SEUMRE, is demonstrated through comparisons with other well known global optimization techniques, including genetic algorithm (GA), simulated annealing (SA), and a highly nonlinear design problem—the optimal design of automotive magnetorheological brake (MRB). Unlike the conventional brakes, an MRB employs the interaction between a magnetorheological fluid and an applied magnetic field to generate the retarding braking torque. The SEUMRE design optimization algorithm was used to maximize the braking torque and minimize the weight of the brake structure. The computation time and optimized design parameters illustrated SEUMRE’s capability to converge to an accurate result faster than the conventional global optimization methods. However, SA provided significantly better optimization results than GA and SEUMRE in terms of the cost function.
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References
An J, Kwon D (2003) Modeling of a magnetorheological actuator including magnetic hysteresis. J Intell Mater Syst Struct 14(9):541–550
Baritompa B, Hendrix EMT (2005) On the investigation of stochastic global optimization algorithms. J Glob Optim 31(4):567–578
Carlson JD (2001) Magnetorheological brake with integrated flywheel. US Patent No. 6186290 B1. United States Patent Office; 13 February 2001
Carlson JD, LeRoy DF, Holzheimer JC, Prindle DR, Marjoram RH (1998) Controllable brake. US Patent No. 5842547. United States Patent Office; 1 December 1998
Cressie N (1988) Spatial prediction and ordinary Kriging. Math Geol 20(4):405–421
Dorigo M, Maniezzo V, Colorni A (1996) Ant system: optimization by a colony of cooperating agents. IEEE Trans Syst Man Cybern Part B Cybern 26(1):29–41
Gill PE, Murray E, Wright MH (1981) Practical optimization. Academic, New York
Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison Wesley, New York
Hendrix EMT (1998) Global optimization at work. Ph.D. Dissertation, Wageningen Agricultural University
Huang D, Allen T, Notz W, Zeng N (2006) Global optimization of stochastic black-box system via sequential Kriging meta-models. J Glob Optim 34:441–466
Jones DR, Schonlau M, Welch WJ (1998) Efficient global optimization of expensive black-box functions. J Glob Optim 13(4):455–492
Karakoc K, Park E, Suleman A (2008) Design consideration for an automotive magnetorheological brake. Mechatronics 18:434–447
Kaymaz I, McMathon CA (2005) A response surface method based on weighted regression for structural reliability analysis. Probab Eng Mech 20:11–17
Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks, pp 1942–1948
Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220:671–680
Kordonsky W (1993) Elements and devices based on magnetorheological effect. J Intell Mater Syst Struct 4(1):65–69
Liu B, Li WH, Kosasih PB, Zhang XZ (2006) Development of an MR brake based haptic device. Smart Mater Struct 15:1960–1966
Lord Corporation Material Division (2003) MR Brake product bulletin, 2107-3. Lord Corporation, Cary
McKay M, Bechman R, Conver W (1997) A comparison of three methods for selecting values of input variables in the analysis techniques for computer codes. Technometrics 21(2):239–245
Michalewicz Z (1996) Genetic algorithms + data structures = evolution programs. Springer, New York
Park EJ, Stoikov D, Falcao da Luz L, Suleman A (2006) A performance evaluation of an automotive magnetorheological brake design with a sliding mode controller. Mechatronics 16:405–416
Phillips RW (1969) Engineering applications of fluids with a variable yield stress. Ph.D. Thesis, University of California, Berkeley, CA
Shan S, Wang G (2004) Space exploration and global optimization for computationally intensive design problems: a rough set based approach. Struct Multidisc Optim 28:427–441
Simpson TW, Mauery TM, Korte JJ, Mistree F (2001) Kriging models for global approximation in simulation-based multidisciplinary design optimization. AIAA J 39(12):2233–2241
Wang G, Shan S (2004) Design space reduction for multi-objective optimization and robust design optimization problems. SAE International, Warrendale
Wang G, Dong Z, Aitchison P (2001) Adaptive response surface method—a global optimization scheme for approximation- based design problems. J Mech Eng 33:707–733
Wang L, Shan S, Wang G (2004) Mode-pursuing sampling method for global optimization on expensive black-box functions. Eng Optim 36(4):419–438
Webb G (1998) Exercise apparatus and associated method including rheological fluid brake. US Patent 5749807
Weise T (2009) Global optimization algorithms, theory and applications. Accessed at: www.it-weise.de/projects/book.pdf
Weiss KD, Carlson JD, Nixon DA (1994) Viscoelastic properties of magneto- and electrorheological fuids. J Intell Mater Syst Struct 5(11):772–775
Younis A, Dong Z (2009a) Metamodeling and search using space exploration and unimodal region elimination in computation intensive design optimization. J Eng Optimiz 42(6):517–533
Younis A, Dong Z (2009b) Global optimization using mixed surrogate models for computation intensive designs. In: 2nd International Symposium on Computational Mechanics (ISCM II), 12th international conference on Enhancement and Promotion of Computational Methods in Engineering and Science (EPMESC XII). Hong Kong—Macau
Younis A, Xu R, Dong Z (2009) Approximated unimodal region elimination based global optimization method for engineering design. Intl J Prod Dev 9(1/2/3):164–187
Zabinsky ZB, Smith RL (1992) Pure adaptive search in global optimization. Math Program 53:323–338
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Appendices
Appendix 1: Sample of test results of SEUMRE method
Appendix 2: Comparison of the resulting optimum design parameters and computational efficiency for different number of disks and weight coefficients
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Younis, A., Karakoc, K., Dong, Z. et al. Application of SEUMRE global optimization algorithm in automotive magnetorheological brake design. Struct Multidisc Optim 44, 761–772 (2011). https://doi.org/10.1007/s00158-011-0661-8
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DOI: https://doi.org/10.1007/s00158-011-0661-8