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Civil-Comp Conferences
ISSN 2753-3239
CCC: 5
PROCEEDINGS OF THE SIXTH INTERNATIONAL CONFERENCE ON SOFT COMPUTING, MACHINE LEARNING AND OPTIMISATION IN CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING
Edited by: P. Iványi, J. Logo and B.H.V. Topping
Paper 1.8

On design-dependent loads in a NURBS-density-based topology optimisation method

E. Urso, S. Zerrouq and M. Montemurro

Universite de Bordeaux, Arts et Metiers Institute of Technology, CNRS, INRA, Bordeaux INP, HESAM Universite, I2M UMR 5295, Talence, France

Full Bibliographic Reference for this paper
E. Urso, S. Zerrouq, M. Montemurro, "On design-dependent loads in a NURBS-density-based topology optimisation method", in P. Iványi, J. Logo, B.H.V. Topping, (Editors), "Proceedings of the Sixth International Conference on Soft Computing, Machine Learning and Optimisation in Civil, Structural and Environmental Engineering", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 5, Paper 1.8, 2023, doi:10.4203/ccc.5.1.8
Keywords: topology optimisation, NURBS surfaces, design-dependent loads, density-based algorithm, inertial loads, penalisation schemes.

Abstract
This paper deals with topology optimisation (TO) problem with design-dependent loads. Specifically, the problem is formulated in the context of a special density-based TO algorithm wherein a non uniform rational basis spline (NURBS) entity is used to represent the topological descriptor, i.e., the pseudo-density field. In this context, TO problems involving design-dependent loads are addressed, in the most general case of inhomogeneous Neumann-Dirichlet boundary conditions. A study of the penalty function of the design-dependent loads is carried out to investigate its effect on the optimised topologies and overcome the singularity effect related to the zones characterised by low values of the pseudo-density field. Finally, the combination of both design-dependent loads and inhomogeneous Neumann-Dirichlet boundary conditions is investigated and the effectiveness of the method is proven on a 2D benchmark problems.

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