Article
Licensed
Unlicensed Requires Authentication

The Henry gas solubility optimization algorithm for optimum structural design of automobile brake components

  • , , , , and
Published/Copyright: February 25, 2020
Become an author with De Gruyter Brill

Abstract

As a result of the requirements imposed by international organizations and governments on fuel emissions, there is a growing interest in the design of lightweight vehicles with low-fuel emissions. Metaheuristic methods have been widely used for the optimum design of vehicle components in recent years for which successful results have been reported. Encouraged by such results obtained from the methods mentioned, the Henry gas solubility optimization algorithm (HGSO), a recently developed optimization method, is used to solve the shape optimization of a vehicle brake pedal to prove how HGSO can be used for solving shape optimization problems. This paper is the first application of the HGSO in connection with real-world optimization problems in the literature. The results show HGSO's ability to design better optimal components in the automotive industry.


Correspondence Address, Prof. Dr. Ali Rıza Yıldız, Department of Automotive Engineering, Bursa Uludağ University, Görükle, Bursa, Turkey, E-mail:

Dr. Betül Sultan Yıldız completed her BSc and MSc degrees at Uludağ University, Bursa, Turkey and received her PhD in Mechanical Engineering from Bursa Technical University, Turkey. Her research interests are optimal design, shape optimization, topology optimization, topography optimization, structural optimization methods and meta-heuristic optimization algorithms as well as applications to industrial problems.

Dr. Ali Rıza Yıldız is a Professor in the Department of Automotive Engineering, Bursa Uludağ University, Bursa, Turkey. His research interests are the finite element analysis of automobile components, lightweight design, composite materials, vehicle design, vehicle crashworthiness, shape and topology optimization of vehicle components, metaheuristic optimization techniques, and sheet metal forming. He has been serving as an Associate Editor for the Journal of Expert Systems, Wiley.

Nantiwat Pholdee received his BEng degree (Second Class Honors) in Mechanical Engineering in 2008 and his PhD degree in Mechanical Engineering in 2013 from Khon Kaen University, Khon Kaen, Thailand. His research interests include multidisciplinary design optimization, aircraft design, flight control, evolutionary computation and finite-element analysis.

Dr. Sujin Bureerat received his BEng degree in Mechanical Engineering from Khon Kaen University, Khon Kaen, Thailand, in 1992, and his PhD degree in Engineering from Manchester University, Manchester, UK, in 2001. Currently, he is a Professor with the Department of Mechanical Engineering, Khon Kaen University. His research interests include multidisciplinary design optimization, evolutionary computation, aircraft design, finite-element analysis, agricultural machinery, mechanism synthesis, and mechanical vibration.

Dr. Sadiq M. Sait received his Bachelor's degree in Electronics Engineering from Bangalore University, India, in 1981, and his Master's and Ph.D. degrees in Electrical Engineering from the King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, in 1983 and 1987, respectively. He is currently a Professor of Computer Engineering and Director of the Center for Communications and IT Research, KFUPM, Dhahran, Saudi Arabia. He is a Senior Member of the IEEE. In 1981, he received the Best Electronic Engineer Award from the Indian Institute of Electrical Engineers, Bengaluru.

Dr. Vivek K. Patel received Ph.D in the area of thermal system optimization from SVNIT. He has had more than 12 years of teaching experience. His research area focuses on the development of metaheuristic algorithms for the design and optimization of real life engineering applications and energy systems. He is currently working as an Assistant Professor in Mechanical Engineering Dept. of Pandit Deendayal Petroleum University, Gandhinagar.


References

1 B. S. Yildiz , A. R.Yildiz: Comparison of grey wolf, whale, water cycle, ant lion and sine-cosine algorithms for the optimization of a vehicle engine connecting rod, Materials Testing60 (2018), No. 3, pp. 311315 DOI: 10.3139/120.111153Search in Google Scholar

2 A. R. Yildiz , H.Abderazek, S.Mirjalili: A Comparative Study of Recent Non-traditional Methods for Mechanical Design Optimization, Archives of Computational Methods in Engineering (2019) DOI: 10.1007/s11831-019-09343-x (in print)Search in Google Scholar

3 A. R. Yildiz , B. S.Yildiz, S. M.Sait, X. Y.Li: The Harris hawks, grasshopper and multi-verse optimization algorithms for the selection of optimal machining parameters in manufacturing operations, Materials Testing61 (2019), pp. 725733 DOI: 10.3139/120.111377Search in Google Scholar

4 A. R. Yildiz , B. S.Yildiz, S. M.Sait, S.Bureerat, N.Pholdee: A new hybrid Harris hawks Nelder-Mead optimization algorithm for solving design and manufacturing problems, Materials Testing61 (2019); No. 8, pp. 735743 DOI: 10.3139/120.111378Search in Google Scholar

5 B. S. Yildiz , A. R.Yildiz: The Harris hawks optimization algorithm, salp swarm optimization algorithm, grasshopper optimization algorithm and dragonfly algorithm for structural design optimization of vehicle components, Materials Testing61 (2019), No. 8, pp. 744748 DOI: 10.3139/120.111379Search in Google Scholar

6 T. Kunakote , S.Bureerat: Multi-objective topology optimization using evolutionary algorithms, Engineering Optimization43 (2011), No. 5, pp. 541557 DOI: 10.1080/0305215X.2010.502935Search in Google Scholar

7 B. S. Yildiz , A. R.Yildiz: Moth-flame optimization algorithm to determine optimal machining parameters in manufacturing processes, Materials Testing59 (2017), No. 5, pp. 425429 DOI: 10.3139/120.111024Search in Google Scholar

8 A. R. Yildiz : A comparative study of population-based optimization algorithms for turning operations, Information Sciences210 (2012), pp. 8188 DOI: 10.1016/j.ins.2012.03.005Search in Google Scholar

9 A. R. Yildiz : An effective hybrid immune-hill climbing optimization approach for solving design and manufacturing optimization problems in industry, Journal of Materials Processing Technology209 (2009), No. 6, pp. 27732780 DOI: 10.1016/j.jmatprotec.2008.06.028Search in Google Scholar

10 A. R. Yildiz : A new hybrid bee colony optimization approach for robust optimal design and manufacturing, Applied Soft Computing13 (2013), No. 5, pp. 29062912 DOI: 10.1016/j.asoc.2012.04.013Search in Google Scholar

11 A. R. Yildiz : A new hybrid differential evolution algorithm for the selection of optimal machining parameters in milling operations, Applied Soft Computing13 (2013), No. 3, pp. 15611566 DOI: 10.1016/j.asoc.2011.12.016Search in Google Scholar

12 A. R. Yildiz : Hybrid Taguchi-differential evolution algorithm for optimization of multi-pass turning operations, Applied Soft Computing13 (2013), No. 3, pp. 14331439 DOI: 10.1016/j.asoc.2012.01.012Search in Google Scholar

13 A. R. Yildiz , K.Solanki: Multi-objective optimization of vehicle crashworthiness using new particle swarm based approach, International Journal of Advanced Manufacturing Technology59 (2012), No. 1–4, pp. 367376 DOI: 10.1007/s00170-011-3496-ySearch in Google Scholar

14 A. R. Yildiz : Hybrid immune-simulated annealing algorithm for optimal design and manufacturing, International Journal of Materials and Product Technology34 (2009), No. 3, pp. 217226 DOI: 10.1504/IJMPT.2009.024655Search in Google Scholar

15 T. Güler , A.Demirci, A. R.Yıldız, U.Yavuz: Lightweight design of an automobile hinge component using glass fiber polyamide composites, Materials Testing60(2018), No. 3, pp. 306310Search in Google Scholar

16 B. S. Yildiz , H.Lekesiz: Fatigue-based structural optimisation of vehicle components, International Journal of Vehicle Design73 (2017), pp. 5462 DOI: 10.1504/IJVD.2017.10003398Search in Google Scholar

17 F. Hamza , H.Abderazek, S.Lakhdar, D.Ferhat, A. R.Yildiz: Optimum design of cam-roller follower mechanism using a new evolutionary algorithm, The International Journal of Advanced Manufacturing Technology99 (2018), No. 5–8, pp. 12611282 DOI: 10.1007/s00170-018-2543-3Search in Google Scholar

18 N. Pholdee , S.Bureerat, A. R.Yildiz: Hybrid real-code population-based incremental learning and differential evolution for many-objective optimisation of an automotive floor-frame, International Journal of Vehicle Design73 (2017), No. 1–3, pp. 2053 DOI: 10.1504/IJVD.2017.082578Search in Google Scholar

19 S. Karagöz , A. R.Yildiz: A comparison of recent metaheuristic algorithms for crashworthiness optimisation of vehicle thin-walled tubes considering sheet metal forming effects, International Journal of Vehicle Design73 (2017), No. 1–3, pp. 179188 DOI: 10.1504/IJVD.2017.082593Search in Google Scholar

20 A. R. Yildiz , E.Kurtuluş, E.Demirci, B. S.Yildiz, S.Karagöz: Optimization of thin-wall structures using hybrid gravitational search and Nelder-Mead algorithm, Materials Testing58 (2016), No. 1, pp. 7578 DOI: 10.3139/120.110823Search in Google Scholar

21 B. S. Yildiz : A comparative investigation of eight recent population-based optimisation algorithms for mechanical and structural design problems, International Journal of Vehicle Design73 (2017), No. 1–3, pp. 208218 DOI: 10.1504/IJVD.2017.082603Search in Google Scholar

22 M. Kiani , A. R.Yildiz: A comparative study of non-traditional methods for vehicle crashworthiness and NVH optimization, Archives of Computational Methods in Engineering23 (2016), No. 4, pp. 723734 DOI: 10.1007/s11831-015-9155-ySearch in Google Scholar

23 B. S. Yildiz , H.Lekesiz, A. R.Yildiz: Structural design of vehicle components using gravitational search and charged system search algorithms, Materials Testing58 (2016), No. 1, pp. 7981 DOI: 10.3139/120.110819Search in Google Scholar

24 A. R. Yildiz : Comparison of evolutionary based optimization algorithms for structural design optimization, Engineering Applications of Artificial Intelligence26 (2013), No. 1, pp. 327333 DOI: 10.1016/j.engappai.2012.05.014Search in Google Scholar

25 A. R. Yildiz , K.Saitou: Topology synthesis of multi-component structural assemblies in continuum domains, Transactions of ASME, Journal of Mechanical Design133 (2011), No. 1, 011008-9 DOI: 10.1115/1.4003038Search in Google Scholar

26 A. R. Yıldız , U. A.Kılıçarpa, E.Demirci: Topography and topology optimization of diesel engine components for light-weight design in the automotive industry, Materials Testing61 (2019), No. 1, pp. 2734 DOI: 10.3139/120.111277Search in Google Scholar

27 E. Demirci , A. R.Yıldız: An experimental and numerical investigation of the effects of geometry and spot welds on the crashworthiness of vehicle thin-walled structures, Materials Testing60 (2018), No. 6, pp. 553561 DOI: 10.3139/120.111187Search in Google Scholar

28 E. Demirci , A. R.Yıldız: An investigation of the crash performance of magnesium, aluminum and advanced high strength steels and different cross-sections for vehicle thin-walled energy absorbers, Materials Testing60 (2018), No. 7–8, pp. 661668 DOI: 10.3139/120.111201Search in Google Scholar

29 A. R. Yildiz : A new hybrid particle swarm optimization approach for structural design optimization in automotive industry, Journal of Automobile Engineering226 (2012), No. 10, pp. 13401351 DOI: 10.1177/0954407012443636Search in Google Scholar

30 B. S. Yildiz : Natural frequency optimization of vehicle components using the interior search algorithm, Materials Testing59 (2017), No. 5, pp. 456458 DOI: 10.3139/120.111018Search in Google Scholar

31 E. Demirci , A. R.Yıldız: A new hybrid approach for reliability-based design optimization of structural components, Materials Testing61 (2019), No. 2, pp. 111119 DOI: 10.3139/120.111291Search in Google Scholar

32 A. R. Yıldız , U. A.Kılıçarpa, E.Demirci: Topography and topology optimization of diesel engine components for light-weight design in the automotive industry, Materials Testing61 (2019), No. 1, pp. 2734Search in Google Scholar

33 A. Askarzadeh : A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm, Computers & Structure169 (2016), pp. 112 DOI: 10.1016/j.compstruc.2016.03.001Search in Google Scholar

34 A. R. Yildiz : A novel hybrid whale nelder mead algorithm for optimization of design and manufacturing problems, International Journal of Advanced Manufacturing Technology (2019) DOI: 10.1007/s00170-019-04532-1 (in print)Search in Google Scholar

35 H. Abderazek , A. R.Yildiz, S.Mirjalili: Comparison of recent optimization algorithms for design optimization of a cam-follower mechanism, Knowledge-Based Systems (2019) DOI: 10.1016/j.knosys.2019.105237 (in print)Search in Google Scholar

36 A. R. Yildiz : Designing of optimum vehicle components using new generation optimization methods, Journal of Polytechnic20 (2017), No. 2, pp. 319323 DOI: 10.2339/2017.20.2.325-332Search in Google Scholar

37 A. R. Yildiz , F.Ozturk: Hybrid enhanced genetic algorithm to select optimal machining parameters in turning operation, Proc. Instn. Mech. Engrs, Part B, Journal of Engineering Manufacture220 (2006), No. 12, pp. 20412053 DOI: 10.1243/09544054JEM570Search in Google Scholar

38 A. R. Yildiz : A New Design Optimization Framework based on immune Algorithm and Taguchi Method, Computers in Industry60 (2009), pp. 613620 DOI: 10.1016/j.compind.2009.05.016Search in Google Scholar

39 S. Bureerat , N.Pholdee: Inverse problem based differential evolution for efficient structural health monitoring of trusses, Applied Soft Computing66 (2018), pp. 462472 DOI: 10.1016/j.asoc.2018.02.046Search in Google Scholar

40 O. F. Sonmez : Shape optimization of 2D structures using simulated annealing, Computer Methods in Applied Mechanics and Engineering, 196(2007), pp. 32793299 DOI: 10.1016/j.cma.2007.01.019Search in Google Scholar

41 A. R. Yildiz , N.Öztürk, N.Kaya, F.Öztürk: Hybrid multi-objective shape design optimization using Taguchi's method and genetic algorithm, Structural and Multidisciplinary Optimization34 (2007), No. 4, pp. 317332 DOI: 10.1007/s00158-006-0079-xSearch in Google Scholar

42 A. R. Yildiz , N.Öztürk, N.Kaya, F.Öztürk: Integrated optimal topology design and shape optimization using neural networks, Structural and Multidisciplinary Optimization25 (2003), No. 4, pp. 251260 DOI: 10.1007/s00158-003-0300-0 13Search in Google Scholar

43 N. Öztürk , A. R.Yildiz, N.Kaya, F.Öztürk: Neuro-genetic design optimization framework to support the integrated robust design optimization process in CE, 14 (2006), No. 1, pp. 516 DOI: 10.1177/1063293X06063314Search in Google Scholar

44 F. A. Hashim , E. H.Houssein, M. S.Mabrouk, W.Al-Atabany, S.Mirjalili: Henry gas solubility optimization: A novel physics-based algorithm, Future Generation Computer Systems, 101(2019), pp. 646667 DOI: 10.1016/j.future.2019.07.015Search in Google Scholar

Published Online: 2020-02-25
Published in Print: 2020-03-02

© 2020, Carl Hanser Verlag, München

Downloaded on 12.4.2026 from https://www.degruyterbrill.com/document/doi/10.3139/120.111479/html
Scroll to top button