Abstract

Abstract This paper presents topology optimization of nonlinear heat conduction problems with multiple domains and multiple constraints, including regional temperature and material volume for reducing temperature. Maximum approximation temperatures in the constraint regions are accurately and dynamically calculated, though temperature and temperature-dependent thermal conductivity change with the update of material distribution. A temperature measure with constant error to approximate regional maximum temperature is adaptive to different temperature ranges. A strategy of hole nucleation generation combined with the regional temperature constraints is presented for the level set-based topology optimization. The solid isotropic material with penalization (SIMP) and parametrized level set methods are compared for the temperature-constrained topology optimization. Finally, several numerical examples are solved by the SIMP and parametrized level set methods. The results demonstrate that the proposed approach can obtain intricate topological details and reduce regional temperatures for the nonlinear heat conduction problems.

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