2012-08-23
On the Design and Reliability Analysis of Electromagnetic Absorbers Using Real-Coded Genetic Algorithm and Monte Carlo Simulation
By
Progress In Electromagnetics Research B, Vol. 43, 169-187, 2012
Abstract
In this paper, we propose an approach for designing and quantitatively assessing the performance of the multilayered radar-absorbing structure. In our proposed approach, a five layered radarabsorbing materials design is optimized from the predefined materials database. But to determine the optimal choice of the material and thickness of each layer, a combined binary and real-coded genetic algorithm (GA) is used to handle the integer and real variables involved in such designs. Further, the proposed approach employs the Latin hypercube sampling with Monte Carlo Simulation to carry out the performance based reliability analysis of the design. Absorber synthesized results are compared with the published work using other algorithms. The outcomes of our approach show that the combined GA works quite well, and most prominently the reliability analysis provides the decision maker a means to select among the several design alternatives available before him.
Citation
Heeralal Gargama, Sanjay Kumar Chaturvedi, and Awalendra K. Thakur, "On the Design and Reliability Analysis of Electromagnetic Absorbers Using Real-Coded Genetic Algorithm and Monte Carlo Simulation," Progress In Electromagnetics Research B, Vol. 43, 169-187, 2012.
doi:10.2528/PIERB12061107
References

1. Chung, D. D. L., "Materials for electromagnetic interference shielding," Journal of Material Engineering and Performance, Vol. 9, 350-354, 2000.
doi:10.1361/105994900770346042        Google Scholar

2. Paul, C. R., Introduction to Electromagnetic Compatibility, 2nd Ed., John Wiley & Sons, Inc., 2006.

3. Morgan, D. A., Handbook for EMC Testing and Measurement, The Institution of Engineering and Technology, 2007.

4. Hoang, N. H., J. L. Wojkiewicz, J. L. Miane, and R. S. Biscarro, "Lightweight electromagnetic shields using optimised polyaniline composites in the microwave band," Polymers for Advanced Technologies, Vol. 18, 257-262, 2007.
doi:10.1002/pat.829        Google Scholar

5. Gargama, H., S. K. Chaturvedi, and A. K. Thakur, "Design and optimization of multilayered electromagnetic shield using a real-coded genetic algorithm," Progress In Electromagnetics Research B, Vol. 39, 241-266, 2012.
doi:10.2528/PIERB12011902        Google Scholar

6. IEEE Standard 299-1997 (Revision of IEEE Standard 299-1991) IEEE Standard Method for Measuring the Effectiveness of Electromagnetic Shielding Enclosures, The Institute of Electrical and Electronics Engineers, Inc., 1998.

7. Micheli, D., C. Apollo, R. Pastore, et al. "Optimization of multilayer shields made of composite nanostructured materials," IEEE Transactions on Electromagnetic Compatibility, Vol. 54, No. 1, 60-69, 2012.
doi:10.1109/TEMC.2011.2171688        Google Scholar

8. Markham, D., "Shielding: Quantifying the shielding requirements for portable electronic design and providing new solutions by using a combination of materials and design," Materials and Design, Vol. 21, No. 1, 45-50, 2000.
doi:10.1016/S0261-3069(99)00049-7        Google Scholar

9. Michielssen, E., J.-M. Sajer, S. Ranjithan, et al. "Design of lightweight, broad-band microwave absorbers using genetic algorithms," IEEE Transactions on Microwave Theory and Techniques, Vol. 41, No. 6-7, 1024-1030, 1993.
doi:10.1109/22.238519        Google Scholar

10. Cui, S. and D. S. Weile, "Robust design of absorbers using genetic algorithms and the finite element-boundary integral method," IEEE Transactions on Antennas and Propagation, Vol. 51, No. 12, 3249-3258, 2003.
doi:10.1109/TAP.2003.820971        Google Scholar

11. Jie, Y., G. Xiao, and M.-S. Cao, "A novel method of computation and optimization for multi-layered radar absorbing coatings using open source software," Materials and Design, Vol. 27, 45-52, 2006.
doi:10.1016/j.matdes.2004.09.009        Google Scholar

12. Micheli, D., R. Pastore, C. Apollo, et al. "Broadband electromagnetic absorbers using carbon nanostructure-based composites," IEEE Transactions on Microwave Theory and Techniques, Vol. 59, No. 10, 2633-2646, 2011.
doi:10.1109/TMTT.2011.2160198        Google Scholar

13. Goudos, S. K., "A versatile software tool for microwave planar radar absorbing materials design using global optimization algorithms," Materials and Design, Vol. 28, 2585-2895, 2007.
doi:10.1016/j.matdes.2006.10.016        Google Scholar

14. Goudos, S. K., "Design of microwave broadband absorbers using a self-adaptive differential evolution algorithm," International Journal of RF and Microwave Computer-aided Engineering, Vol. 19, No. 3, 364-372, 2009.
doi:10.1002/mmce.20357        Google Scholar

15. Dib, N., M. Asi, A, and Sabbah, "International Journal of RF and Microwave Computer-aided Engineering," Progress In Electromagnetics Research C, Vol. 13, 171-185, 2010.
doi:10.2528/PIERC10041310        Google Scholar

16. Asi, M. J. and N. I. Dib, "Design of multilayer microwave broadband absorbers using central force optimization," Progress In Electromagnetics Research B, Vol. 26, 101-113, 2010.
doi:10.2528/PIERB10090103        Google Scholar

17. Deb, K. and R. B. Agrawal, "Simulated binary crossover for continuous search space," Complex Systems, Vol. 9, 115-148, 1995.        Google Scholar

18. Deb, K. and M. Goyal, "A combined genetic adaptive search (Gene AS) for engineering design," Computer Science and Informatics, Vol. 26, No. 4, 30-45, 1996.        Google Scholar

19. Deb, K., "An efficient constraint handling method for the genetic algorithm," Computer Methods in Applied Mechanics and Engineering, Vol. 186, 311-338, 2000.
doi:10.1016/S0045-7825(99)00389-8        Google Scholar

20. Zhang, J. Y., S. Y. Liang, J. Yao, et al. "Evolutionary optimization of machining processes," Journal of Intelligent Manufacturing, Vol. 17, 203-215, 2006.
doi:10.1007/s10845-005-6637-z        Google Scholar

21. Deep, K., K. P. Singh, and M. L. Kansal, "A real coded genetic algorithm for solving integer and mixed integer optimization problems," Applied Mathematics and Computation, Vol. 212, 505-518, 2009.
doi:10.1016/j.amc.2009.02.044        Google Scholar

22. Gargama, H., S. K. Chaturvedi, and A. K. Thakur, "Electromagnetic interference shielding design using real-coded genetic algorithm and reliability evaluation in X-band," Proceedings of the International Conference on SocProS 2011, Advances in Intelligent and Soft Computing, Vol. 131, 331-342, 2012.        Google Scholar

23. Haldar, A. and S. Mahadevan, Reliability Assessment Using Stochastic Finite Element Analysis, John Wiley & Sons Inc., New York, 2000.

24. Páez, E., M. A. Azpúrua, C. Tremolo, and R. C. Callarotti, "Uncertainty estimation in complex permittivity measurements by shielded dielectric resonator technique using the Monte Carlo method," Progress In Electromagnetics Research B, Vol. 41, 101-119, 2012.        Google Scholar

25. Azpúrua, M., C. Tremolo, and E. Páez, "Comparison of the gum and Monte Carlo methods for the uncertainty estimation in electromagnetic compatibility testing," Progress In Electromagnetics Research B, Vol. 34, 125-144, 2011.        Google Scholar

26. Helton, J. C. and F. J. Davis, "Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems," Reliability Engineering and System Safety, Vol. 81, 23-69, 2003.
doi:10.1016/S0951-8320(03)00058-9        Google Scholar

27. Chew, W. C., Waves and Fields in Inhomogeneous Media, Reprinted by IEEE Press, Van Nostrand Reinhold, 1995.

28. Kapur, K. C. and L. R. Lamberson, Reliability in Engineering Design, Reprint, Wiley India Pvt. Ltd., 2009.

29. Foschi, R. O., H. Li, and J. Zhang, "Reliability and performance-based design: A computational approach and applications," Structural Safety, Vol. 24, 205-218, 2002.
doi:10.1016/S0167-4730(02)00025-5        Google Scholar

30. Singh, D., A. Kumar, S. Meena, and V. Agarwala, "Analysis of frequency selective surfaces for radar absorbing materials," Progress In Electromagnetics Research B, Vol. 38, 297-314, 2012.        Google Scholar

31. Schucany, W. R., "Kernel smoothers: An overview of curve estimators for the first graduate course in nonparametric statistics," Statistical Science, Vol. 19, No. 4, 663-675, 2004.
doi:10.1214/088342304000000756        Google Scholar