A Stochastic Radial Point Interpolation Method for Uncertainty Analysis in Geometry

Kiran, R and Vinoy, KJ (2023) A Stochastic Radial Point Interpolation Method for Uncertainty Analysis in Geometry. In: 2023 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2023, 28-30 June 2023, Winnipeg, MB, Canada, pp. 184-186.

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Abstract

A time domain method for quantitative analysis of geometrical uncertainty is introduced here by combining polynomial chaos expansion (PCE) with the radial point interpolation method (RPIM). The shape function matrix of RPIM is represented in a stochastic framework. The proposed method is validated in a two dimensional problem and its accuracy is compared with Monte-Carlo (MC) simulation using Kolmogorov Smirnov (KS) test. Time complexity of the proposed method is remarkably better than MC. Since RPIM is an unstructured node based approach, this method can be well adapted for complex curved geometries. © 2023 IEEE.

Item Type:	Conference Paper
Publication:	2023 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization, NEMO 2023
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to the Institute of Electrical and Electronics Engineers Inc.
Keywords:	Computational complexity; Interpolation; Monte Carlo methods; Stochastic systems; Time domain analysis; Uncertainty analysis, Chaos expansions; Geometric stochastic radial point interpolation method; Geometrical uncertainty; Polynomial chaos; Polynomial chaos expansion; Radial point interpolation method; Stochastics; Time domain electromagnetic methods; Time-domain methods; Uncertainty quantifications, Geometry
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	07 Nov 2023 03:56
Last Modified:	07 Nov 2023 03:57
URI:	https://eprints.iisc.ac.in/id/eprint/83079

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