Abstract
This work investigates the application of Model Order Reduction (MOR) to the case of a non-linear heat transfer simulation, which pertains to Selective Laser Melting (SLM). A hyper-reduction strategy, relying on the Energy Conserving Sampling and Weighting (ECSW) method, is presented before being implemented within an adaptative POD-Greedy algorithm to build a more general reduced order base composed of versatile thermal modes. To this end, an a-posteriori error estimator is used alongside Ordinary Kriging to evaluate the degree of error committed during the parametrized-MOR process. The approach introduces a novel scheme called parametric Energy Conserving Sampling and Weighting (pECSW), which extends the applicability of the sparse selection of finite elements for larger parametric ranges than what is possible with the regular ECSW approach. Hence, the generic property of the final layout avoids launching an optimization strategy for new model analysis.
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Acknowledgements
The work leading to this publication has been funded by the project “PROCSIMA”, which fits in the MacroModelMat(M3) research program, coordinated by Siemens (Siemens Digital Industries Software, Belgium) and funded by SIM (Strategic Initiative Materials in Flanders) and VLAIO (Flanders Innovation & Entrepreneurship Agency), as well as the KU Leuven research fund. The VSC (Flemish Supercomputer Center), funded by the research Foundation - Flanders (FWO) and the Flemish Government - department EWI.
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Ben Yahmed, M.A., Naets, F. Parametric energy conserving sampling and weighting for the thermal analysis of Selective Laser Melting. Comput Mech (2023). https://doi.org/10.1007/s00466-023-02416-6
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DOI: https://doi.org/10.1007/s00466-023-02416-6