Design of Multilayer Wideband Microwave Absorbers using Improved Grey Wolf Optimizer

Authors

  • Hao Nan Zhang College of Information Engineering, Yancheng Optical Fiber Sensing and Application Engineering Technology Research Center Yancheng Institute of Technology, Jiangsu Yancheng, 224051, China
  • Zhi Fei Zhang College of Information Engineering, Yancheng Optical Fiber Sensing and Application Engineering Technology Research Center Yancheng Institute of Technology, Jiangsu Yancheng, 224051, China
  • Yi Du College of Information Engineering, Yancheng Optical Fiber Sensing and Application Engineering Technology Research Center Yancheng Institute of Technology, Jiangsu Yancheng, 224051, China
  • Wei Bin Kong College of Information Engineering, Yancheng Optical Fiber Sensing and Application Engineering Technology Research Center Yancheng Institute of Technology, Jiangsu Yancheng, 224051, China
  • Xiao Fang Yang College of Information Engineering, Yancheng Optical Fiber Sensing and Application Engineering Technology Research Center Yancheng Institute of Technology, Jiangsu Yancheng, 224051, China
  • Zhong Qing Fang College of Information Engineering, Yancheng Optical Fiber Sensing and Application Engineering Technology Research Center Yancheng Institute of Technology, Jiangsu Yancheng, 224051, China

DOI:

https://doi.org/10.13052/2023.ACES.J.380913

Keywords:

absorbing material, GWO, multilayer microwave absorbers, reflection coefficient

Abstract

In this paper, an improved heuristic algorithm based on the disturbance and somersault foraging grey wolf optimizer (IDSFGWO) is proposed to optimize the design of multilayer wideband microwave absorbers for normal incidence. The multilayer absorber is designed to reduce maximum reflection coefficient by choosing suitable layers of materials from a predefined database. Three improvement strategies are given to enhance the performance of GWO, including tent map, nonlinear perturbation, and somersault foraging. The optimization results show that the reflection coefficients optimized by IDSFGWO are better than those of other algorithms for multilayer absorber design.

Downloads

Download data is not yet available.

Author Biographies

Hao Nan Zhang, College of Information Engineering, Yancheng Optical Fiber Sensing and Application Engineering Technology Research Center Yancheng Institute of Technology, Jiangsu Yancheng, 224051, China

Haonan Zhang received the B.S. degree from the Southeast University Chengxian College, Nanjing, China, in 2021, where he is currently pursuing the M.Eng. degree at Yancheng Institute of Technology. His current research interests include computational electromagnetics and wireless communications.

Zhi Fei Zhang, College of Information Engineering, Yancheng Optical Fiber Sensing and Application Engineering Technology Research Center Yancheng Institute of Technology, Jiangsu Yancheng, 224051, China

Zhifei Zhang received the B.S. degree in computer science and technology from Yancheng Institute of Techno-logy in 2022. He is currently pursuing the M.Eng. degree in mechanical engineering at Yancheng Institute of Technology. His main research interests focus on computational electromagnetics and artificial intelligence.

Yi Du, College of Information Engineering, Yancheng Optical Fiber Sensing and Application Engineering Technology Research Center Yancheng Institute of Technology, Jiangsu Yancheng, 224051, China

Yi Du received the B.S. degree in electrical information engineering from Suqian University, Suqian, China, in 2022. He is currently pursuing the M.Eng. degree in mechanical engineering at Yancheng Institute of Technology. His research interests include signal processing and artificial intelligence.

Wei Bin Kong, College of Information Engineering, Yancheng Optical Fiber Sensing and Application Engineering Technology Research Center Yancheng Institute of Technology, Jiangsu Yancheng, 224051, China

Weibin Kong received the B.S. degree in mathematics from Qufu Normal University, China, 2007, and the M.S. degree in mathematics from Southeast University, Nanjing, China, in 2010, and the Ph.D. degree in radio engineering from Southeast University, Nanjing, China, in 2015. Since 2020, he has been an associate professor with the College of Information Engineering, Yancheng Institute of Technology, Yancheng. His current research interests include computational electromagnetism, artificial intelligence, and wireless communication.

Xiao Fang Yang, College of Information Engineering, Yancheng Optical Fiber Sensing and Application Engineering Technology Research Center Yancheng Institute of Technology, Jiangsu Yancheng, 224051, China

Xiaofang Yang received the B.S. and M.S. degrees from Jiangsu Normal University, Xuzhou, China, in 2009 and 2012, respectively, and the Ph.D. degree from Fudan University, Shanghai, China, in 2016. Since 2016, she has been a lecturer with the Coll-ege of Information Engineering, Yancheng Institute of Technology, Yancheng, China. Her current research interests include fiber sensors, computational optics, and computational electromagnetics.

Zhong Qing Fang, College of Information Engineering, Yancheng Optical Fiber Sensing and Application Engineering Technology Research Center Yancheng Institute of Technology, Jiangsu Yancheng, 224051, China

Zhongqing Fang obtained the B.S degree in optical information science and technology from Anhui Uni-versity in 2014, and received his Ph.D. in optics from University of Science and Technology of China (USTC) in 2019. Since 2020, he has been a lecturer with the College of Information Engineering, Yancheng Institute of Technology, Yancheng. His current research interests focus on the fiber sensors and artificial intelligence.

References

R. Panwar, S. Puthucheri, D. Singh, and V. Agarwala, “Design of ferrite-graphene-based thin broadband radar wave absorber for stealth application,” IEEE Transactions on Magnetics, vol. 51, no. 11, pp. 1-4, Nov. 2015.

T. Peng, C. K. Zhu, T. Y. Zhou, B. Zhang, D. X. Ye, X. J. Li, and L. X. Ran, “A compact microwave imager integrated with a miniaturized dual-angle anechoic chamber,” IEEE Transactions on Microwave Theory and Techniques, vol. 69, no. 11, pp. 4831-4839, Nov. 2021.

R. Kumar, H. K. Choudhary, S. P. Pawar, S. Bose, and B. Sahoo, “Carbon encapsulated nanoscale iron/iron-carbide/graphite particles for EMI shielding and microwave absorption,” Physical Chemistry Chemical Physics, vol. 19, no. 34, pp. 23268-23279, Aug. 2017.

M. Cao, X. Wang, W. Cao, X. Fang, B. Wen, and J. Yuan, “Thermally driven transport and relaxation switching self-powered electromagnetic energy conversion,” Small, vol. 14, no. 29, pp. 1800987, July 2018.

R. Panwar, and J. R. Lee, “Recent advances in thin and broadband layered microwave absorbing and shielding structures for commercial and defense applications,” Functional Composites and Structures, vol. 1, no. 3, pp. 032022, July 2019.

P. Tar, B. Stágel, and I. Maros, “Parallel search paths for the simplex algorithm,” Central European Journal of Operations Research, vol. 25, no. 4, pp. 967-984, Dec. 2017.

N. Xiao, X. Liu, and Y. X. Yuan, “A class of smooth exact penalty function methods for optimization problems with orthogonality constraints,” Optimization Methods and Software, vol. 37, no. 4, pp. 1205-1241, Nov. 2020.

A. Toktas, D. Ustun, and M. Tekbas, “Multi-objective design of multi-layer radar absorber using surrogate-based optimization,” IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 8, pp. 3318-3329, Aug. 2019.

T. Alexandros, D. Georgios, “Nature inspired optimization algorithms related to physical phenomena and laws of science: A Survey,” International Journal on Artificial Intelligence Tools, vol. 26, no. 6, pp. 1750022.1-1750022.25, Dec. 2017.

X. S. Yang, S. Deb, S. Fong, X. He and Y. X. Zhao, “From swarm intelligence to metaheuristics: Nature-inspired optimization algorithms,” Computer, vol. 49, no. 9, pp. 52-59, Sep. 2016.

S. Roy, S. D. Roy, J. Tewary, A. Mahanti, and G. Mahanti, “Particle swarm optimization for optimal design of broadband multilayer microwave absorber for wide angle of incidence,” Progress in Electromagnetics Research B, vol. 62, pp. 121-135, 2015.

H. Mouna, V. Mekaladevi, and M. N. Devi, “Design of microwave absorbers using improvised particle swarm optimization algorithm,” Journal of Microwaves, Optoelectronics and Electromagnetic Applications, vol. 17, no. 2, pp. 188-200, June 2018.

X. Chen, X. X. Liu, X. J. Wang, and Y. Liu, “Optimized design for multi-layer absorbing materials based on genetic algorithm,” Advanced Materials Research, vol. 681, pp. 324-328, Apr.2013.

L. Xia, Y. Feng, and B. Zhao, “Intrinsic mechanism and multiphysics analysis of electromagnetic wave absorbing materials: New horizons and breakthrough,” Journal of Materials Science and Technology, vol. 130, no. 10, pp. 136-156, Dec. 2022.

T. Wang, G. Chen, J. H. Zhu, H. Gong, L. M. Zhang, and H. J. Wu, “Deep understanding of impedance matching and quarter wavelength theory in electromagnetic wave absorption,” Journal of Colloid and Interface Science, vol. 595, pp. 1-5, Aug. 2021.

S. Mirjalili, S. M. Mirjalili, and A. Lewis, “Grey wolf optimizer,” Advances in Engineering Software, vol. 69, pp. 46-61, Mar. 2014.

H. Faris, I. Aljarah, M. A. Al-Betar and S. Mirjalili, “Grey wolf optimizer: A review of recent variants and applications,” Neural Computing and Applications, vol. 30, pp. 413-435, Nov. 2017.

S. Mirjalili, S. Saremi, S. M. Mirjalili, “Multi-objective grey wolf optimizer: A novel algorithm for multi-criterion optimization,” Expert Systems with Applications, vol. 47, pp. 106-119, Apr.2016.

F. S. Gharehchopogh, I. Maleki, and Z. A. Dizaji, “Chaotic vortex search algorithm: Metaheuristic algorithm for feature selection,” Evolutionary Intelligence, vol. 15, no. 3, pp. 1777-1808, Sep.2022.

Y. C. Li, M. X. Han, and Q. L. Guo, “Modified whale optimization algorithm based on tent chaotic mapping and its application in structural optimization,” KSCE Journal of Civil Engineering, vol. 24, no. 12, pp. 3703-3713, Oct. 2020.

C. X. Zhang, K. Q. Zhou, S. Q. Ye, and A. M. Zain, “An improved cuckoo search algorithm utilizing nonlinear inertia weight and differential evolution for function optimization problem,” IEEE Access, vol. 9, pp. 161352-161373, Nov. 2021.

H. Hakli and M. S. Kiran, “An improved artifcial bee colony algorithm for balancing local and global search behaviors in continuous optimization,” International Journal of Machine Learning and Cybernetics, vol. 11, pp. 2051-2076, Feb.2020.

W. Zhao, Z. Zhang, and L. Wang, “Manta ray foraging optimization: An effective bio-inspired optimizer for engineering applications,” Engineering Applications of Artificial Intelligence, vol. 87, pp. 103300.1-103300.25, Jan. 2020.

E. Yigit and H. Duysak, “Determination of optimal layer sequence and thickness for broadband multilayer absorber design using double-stage artificial bee colony algorithm,” IEEE Transactions on Microwave Theory and Techniques, vol. 67, no. 8, pp. 3306-3317, Aug. 2019.

P. Ranjan, A. Choubey, and S. K. Mahto, “Wide-angle polarization independent multilayer microwave absorber using wind driven optimization technique,” International Journal of Applied Engineering Research, vol. 12, no. 19, pp. 8016-8025, 2017.

T. M. Shami, A. A. El-Saleh, M. Alswaitti, Q. Al-Tashi, M. A. Summakieh, and S. Mirjalili, “Particle swarm optimization:A comprehensive survey,” IEEE Access, vol. 10, pp. 10031-10061,2022.

S. Roy, S. D. Roy, J. Tewary, A. Mahanti, and G. Mahanti, “Particle swarm optimization for optimal design of broadband multilayer microwave absorber for wide angle of incidence,” Progress in Electromagnetic-s Research B, vol. 62, pp. 121-135, 2015.

S. Mirjalili and A. Lewis, “The whale optimization algorithm,” Advances in Engineering Software, vol. 95, pp. 51-67, May 2016.

F. S. Gharehchopogh and H. Gholizadeh, “A comprehensive survey: Whale optimization algorithm and its applications,” Swarm and Evolutionary Computation, vol. 48, pp. 1-24, Aug. 2019.

Downloads

Published

2024-02-18

How to Cite

[1]
H. N. . Zhang, Z. F. . Zhang, Y. . Du, W. B. . Kong, X. F. . Yang, and Z. Q. . Fang, “Design of Multilayer Wideband Microwave Absorbers using Improved Grey Wolf Optimizer”, ACES Journal, vol. 38, no. 09, pp. 725–733, Feb. 2024.

Issue

Section

Special Issue on ACES-China 2022 Conference

Categories