Using exact particular solutions and modal reduction in topology optimization of transient thermo-mechanical problems

Conference Paper (2017)
Author(s)

Max van der Kolk (TU Delft - Computational Design and Mechanics)

E.C. Hooijkamp (TU Delft - Computational Design and Mechanics)

Matthijs Langelaar (TU Delft - Computational Design and Mechanics)

Fred van Keulen (TU Delft - Computational Design and Mechanics)

Research Group
Computational Design and Mechanics
DOI related publication
https://doi.org/10.1007/978-3-319-67988-4_78
More Info
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Publication Year
2017
Language
English
Research Group
Computational Design and Mechanics
Pages (from-to)
1027-1041
ISBN (print)
978-3-319-67987-7
ISBN (electronic)
978-3-319-67988-4

Abstract

Design of transient thermo-mechanical systems is a challenging task often encountered during the design of high precision machines and instrumentation. Topology optimization can provide valuable insight during the design process, however, for large scale problems the backward time integration required to obtain adjoint sensitivity information is undesired. Previous work has illustrated how the introduction of a reduced modal basis allows to eliminate the backward time integration to obtain the adjoint variables. In order to reduce computational effort further, additional reduction approaches are considered. The focus is specifically on design cases where the relevant heat loads can be expressed or approximated analytically by combinations of harmonic, polynomial or exponential functions of time. Using the method of undetermined coefficients, an exact particular solution is obtained using the full system. Then, the corresponding homogenous solution is expressed using a reduced modal basis, for which a relatively small set of modes is required to obtain an accurate approximation. For the cases where the time component of the heat loads are expressed by the considered analytical functions, the backward time integration is eliminated from the calculation of the design sensitivities, while the forward integration is handled by convolutions.

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