Large-Scale H2 Optimization for Thermo-Mechanical Reliability of Electronics

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Optimization of transient models is required in several domains related to thermo-mechanical reliability of electronics, such as Prognostic Health Monitoring (PHM) and design optimization. A novel framework for efficient (local) parameter optimization of transient models in the H2 norm is proposed. The optimization is feasible for large-scale transient models because it approximates the gradient using physics-based model order reduction (MOR), in contrast to existing approaches that typically use data-driven surrogate models such as neural networks. To demonstrate the framework an optimal fixed-order virtual sensor for PHM of a Ball Grid Array (BGA) is numerically determined.

Original languageEnglish
Title of host publicationScientific Computing in Electrical Engineering
Subtitle of host publicationSCEE 2022, Amsterdam, The Netherlands, July 2022
EditorsMartijn van Beurden, Neil V. Budko, Gabriela Ciuprina, Wil Schilders, Harshit Bansal, Ruxandra Barbulescu
Place of PublicationCham
PublisherSpringer
Pages144-151
Number of pages8
ISBN (Electronic)978-3-031-54517-7
ISBN (Print)978-3-031-54516-0
DOIs
Publication statusPublished - 1 Mar 2024
EventScientific Computing in Electrical Engineering, SCEE 2022 - Amsterdam, Netherlands
Duration: 11 Jul 202214 Jul 2022
https://www.scee-conferences.org/

Publication series

NameMathematics in Industry
Volume43
ISSN (Print)1612-3956
ISSN (Electronic)2198-3283

Conference

ConferenceScientific Computing in Electrical Engineering, SCEE 2022
Abbreviated titleSCEE 2022
Country/TerritoryNetherlands
CityAmsterdam
Period11/07/2214/07/22
Internet address

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