研究目的
To propose an alternative optimisation approach for designing complex metamaterial structures by exploiting the Kriging methodology in conjunction with an adaptive sampling plan to simultaneously optimise multiple conflicting objectives.
研究成果
The proposed optimisation approach effectively balances the real and imaginary components of the refractive index, providing a uniform spread of optimal trade-off designs. This method overcomes the limitations of conventional approaches, significantly reducing simulation times and enabling the design of complex and inhomogeneous metamaterial structures.
研究不足
The computational cost associated with running multiple expensive high-fidelity full-wave simulations and the underlying numerical noise that can adversely affect the simulation-driven optimisation cycle.
1：Experimental Design and Method Selection:
The approach combines Kriging methodology with an adaptive sampling plan (LOLA-Voronoi) and Multi-Objective Constrained Expected Improvement (MOCEI) for optimisation.
2：Sample Selection and Data Sources:
Utilises a 3D full-wave numerical solver suite and a robust retrieval of effective constitutive parameters technique.
3：List of Experimental Equipment and Materials:
CST Microwave Studio for simulations, Duroid 5880 substrate, copper layers.
4：Experimental Procedures and Operational Workflow:
Starts with an initial design of experiment (DOE) sample data set, uses LOLA-Voronoi for adaptive sampling, and MOCEI for in-fill criteria.
5：Data Analysis Methods:
Kriging predications and correlation coefficients are used to assess model accuracy.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
