Koziel Slawomir, Pietrenko-Dabrowska Anna, Ullah Ubaid
Engineering Optimization and Modeling Center, Reykjavik University, 102, Reykjavík, Iceland.
Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80-233, Gdańsk, Poland.
Sci Rep. 2023 Oct 28;13(1):18509. doi: 10.1038/s41598-023-45890-x.
Development of modern microwave devices largely exploits full-wave electromagnetic (EM) simulations. Yet, simulation-driven design may be problematic due to the incurred CPU expenses. Addressing the high-cost issues stimulated the development of surrogate modeling methods. Among them, data-driven techniques seem to be the most widespread owing to their flexibility and accessibility. Nonetheless, applicability of approximation-based modeling for real-world microwave components is hindered by a high nonlinearity of the system characteristics, dimensionality issues, and broad ranges of operating parameters the model should cover to make it practically useful. Performance-driven modeling frameworks deliver a partial mitigation of these problems through appropriate spatial orientation of the metamodel domain, which only encapsulates high-quality designs and not the entire space. Unfortunately, the initial model setup cost is high, as defining the domain requires database designs that need to be a priori acquired. This paper introduces a novel approach, where the database designs are replaced by random observables, and dimensionality of the domain is reduced using spectral analysis thereof. The major contributions of the work include implementation of the explicit dimensionality reduction of the confined surrogate model domain and introducing this concept into a complete cost-efficient framework for modeling of microwave components. Comprehensive benchmarking demonstrates excellent performance of the introduced framework, both in terms of predictive power of the rendered surrogates, their scalability properties, as well as low computational overhead associated with the model setup.
现代微波器件的发展在很大程度上依赖于全波电磁（EM）仿真。然而，由于产生的CPU开销，仿真驱动设计可能存在问题。解决高成本问题推动了代理建模方法的发展。其中，数据驱动技术因其灵活性和可及性似乎最为广泛。尽管如此，基于近似的建模在实际微波组件中的适用性受到系统特性的高度非线性、维度问题以及模型为实用而应涵盖的广泛操作参数范围的阻碍。性能驱动建模框架通过元模型域的适当空间定位部分缓解了这些问题，该元模型域仅封装高质量设计而非整个空间。不幸的是，初始模型设置成本很高，因为定义域需要先验获取的数据库设计。本文介绍了一种新颖的方法，其中数据库设计被随机观测值取代，并使用其频谱分析降低域的维度。这项工作的主要贡献包括实现受限代理模型域的显式降维，并将这一概念引入一个完整的、具有成本效益的微波组件建模框架。全面的基准测试表明，所引入的框架具有出色的性能，无论是在渲染代理的预测能力、其可扩展性属性方面，还是在与模型设置相关的低计算开销方面。
