Correlation-Guided Coarse-Mesh Selection for Automated Space Mapping Optimization of Microwave Components

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Abstract
Mesh morphing-based coarse- and fine-mesh space mapping (CFM-SM) is a prevalent surrogate-based optimization technique for fast electromagnetic (EM) design. This letter proposes a correlation-guided coarse-mesh selection method for automated space mapping (SM) optimization to address inappropriate coarse-mesh invocation in existing CFM-SM. A composite correlation coefficient comprising the Spearman’s rank correlation coefficient and feature coefficient is introduced to select an adequate coarse mesh by quantifying response similarity. The proposed automated CFM-SM optimization method embeds an adaptive coarse-mesh updating mechanism to reconstruct the coarse mesh when deformation becomes invalid at inferior design points, which prevents error accumulation in the iterative process. The proposed method enhances overall efficiency by balancing training and calculation time, avoiding optimization failure caused by mesh degradation. The effectiveness of the proposed technique is verified through two waveguide examples.
Funding Information
  • Science and Technology Program of Suzhou (242G0201Z)
  • China Postdoctoral Science Foundation (2020M680883)