Expedient evaluation of capacitance and conductance matrices of thermal reduced order models of heated structures with temperature-dependent properties

Raghavendra Murthy, Marc Mignolet

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The focus of the present investigation is on the development of an efficient estimation strategy of the temperature dependent capacitance and conductance matrices of the heat conduction problem expressed in a projection reduced order model. This problem arises in particular in the context of hypersonic vehicles where reduced order and surrogate modeling methods are particularly desirable to dramatically reduce the computational effort. The approach presented here recognizes that the structure undergoes a temperature rise which is not uniform but exhibits only relatively small variations around a uniform distribution. This expected property is used in a Taylor series format to permit a direct evaluation of the temperature dependent capacitance and conductance matrices which does not require the rebuilding of the thermal full finite element model. The accuracy of the proposed approach is evaluated, and found excellent, on a well-known baseline problem.

Original languageEnglish (US)
Title of host publicationAIAA Scitech 2019 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105784
DOIs
StatePublished - 2019
EventAIAA Scitech Forum, 2019 - San Diego, United States
Duration: Jan 7 2019Jan 11 2019

Publication series

NameAIAA Scitech 2019 Forum

Conference

ConferenceAIAA Scitech Forum, 2019
CountryUnited States
CitySan Diego
Period1/7/191/11/19

ASJC Scopus subject areas

  • Aerospace Engineering

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    Murthy, R., & Mignolet, M. (2019). Expedient evaluation of capacitance and conductance matrices of thermal reduced order models of heated structures with temperature-dependent properties. In AIAA Scitech 2019 Forum (AIAA Scitech 2019 Forum). American Institute of Aeronautics and Astronautics Inc, AIAA. https://doi.org/10.2514/6.2019-1528