Realization of a Framework for Simulation-Based Large-Scale Shape Optimization Using Vertex Morphing

Aditya Ghantasala (), Reza Najian Asl (), Armin Geiser (), Andrew Brodie (), Efthymios Papoutsis () and Kai-Uwe Bletzinger ()
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Aditya Ghantasala: Technische Universität München
Reza Najian Asl: Technische Universität München
Armin Geiser: Technische Universität München
Andrew Brodie: BMW Group
Efthymios Papoutsis: BMW Group
Kai-Uwe Bletzinger: Technische Universität München

Journal of Optimization Theory and Applications, 2021, vol. 189, issue 1, No 8, 164-189

Abstract: Abstract There is a significant tendency in the industry for automation of the engineering design process. This requires the capability of analyzing an existing design and proposing or ideally generating an optimal design using numerical optimization. In this context, efficient and robust realization of such a framework for numerical shape optimization is of prime importance. Another requirement of such a framework is modularity, such that the shape optimization can involve different physics. This requires that different physics solvers should be handled in black-box nature. The current contribution discusses the conceptualization and applications of a general framework for numerical shape optimization using the vertex morphing parametrization technique. We deal with both 2D and 3D shape optimization problems, of which 3D problems usually tend to be expensive and are candidates for special attention in terms of efficient and high-performance computing. The paper demonstrates the different aspects of the framework, together with the challenges in realizing them. Several numerical examples involving different physics and constraints are presented to show the flexibility and extendability of the framework.

Keywords: Shape optimization; Vertex morphing; Geometric constraints; Multi-physics optimization; Additive manufacturing (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10957-021-01826-x

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