Purpose

The fabrication of electromagnetic (EM) components may induce randomness in several design parameters. In such cases, an uncertainty assessment is of high importance, as simulating the performance of those devices via deterministic approaches may lead to a misinterpretation of the extracted outcomes. This paper aims to present a novel heuristic for the sparse representation of the polynomial chaos (PC) expansion of the output of interest, aiming at calculating the involved coefficients with a small computational cost.

Design/methodology/approach

This paper presents a novel heuristic that aims to develop a sparse PC technique based on anisotropic index sets. Specifically, this study’s approach generates those indices by using the mean elementary effect of each input. Accurate outcomes are extracted in low computational times, by constructing design of experiments (DoE) which satisfy the D-optimality criterion.

Findings

The method proposed in this study is tested on three test problems; the first one involves a transmission line that exhibits several random dielectrics, while the second and the third cases examine the effects of various random design parameters to the transmission coefficient of microwave filters. Comparisons with the Monte Carlo technique and other PC approaches prove that accurate outcomes are obtained in a smaller computational cost, thus the efficiency of the PC scheme is enhanced.

Originality/value

This paper introduces a new sparse PC technique based on anisotropic indices. The proposed method manages to accurately extract the expansion coefficients by locating D-optimal DoE.

中文翻译：

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基于各向异性指数的自适应稀疏多项式混沌技术

目的

电磁（EM）组件的制造可能会在几个设计参数中引起随机性。在这种情况下，不确定性评估非常重要，因为通过确定性方法模拟那些设备的性能可能会导致对提取结果的误解。本文旨在提出一种新颖的启发式方法，以稀疏表示感兴趣的输出的多项式混沌（PC）展开，旨在以较小的计算成本来计算所涉及的系数。

设计/方法/方法

本文提出了一种新颖的启发式方法，旨在开发基于各向异性索引集的稀疏PC技术。具体而言，本研究的方法通过使用每个输入的平均基本效应来生成那些指数。通过构建满足D优化准则的实验设计（DoE），可以在较低的计算时间内提取出准确的结果。

发现

本研究提出的方法是针对三个测试问题进行测试的。第一种情况涉及一条传输线，该传输线具有几种随机的电介质，而第二种和第三种情况则考察了各种随机设计参数对微波滤波器的传输系数的影响。与蒙特卡洛技术和其他PC方法的比较证明，可以以较小的计算成本获得准确的结果，从而提高了PC方案的效率。

创意/价值

本文介绍了一种基于各向异性指标的稀疏PC技术。所提出的方法通过定位D最佳DoE来设法准确地提取膨胀系数。