Abstract
This paper introduces an approach to level-set topology optimization that can handle multiple constraints and simultaneously optimize non-level-set design variables. The key features of the new method are discretized boundary integrals to estimate function changes and the formulation of an optimization sub-problem to attain the velocity function. The sub-problem is solved using sequential linear programming (SLP) and the new method is called the SLP level-set method. The new approach is developed in the context of the Hamilton-Jacobi type level-set method, where shape derivatives are employed to optimize a structure represented by an implicit level-set function. This approach is sometimes referred to as the conventional level-set method. The SLP level-set method is demonstrated via a range of problems that include volume, compliance, eigenvalue and displacement constraints and simultaneous optimization of non-level-set design variables.
Original language | English |
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Pages (from-to) | 631-643 |
Number of pages | 13 |
Journal | Structural and multidisciplinary optimization |
Volume | 51 |
Early online date | 30 Sept 2014 |
DOIs | |
Publication status | Published - Mar 2015 |
Bibliographical note
The authors would like to thank Numerical AnalysisGroup at the Rutherford Appleton Laboratory for their FORTRAN
HSL packages (HSL, a collection of Fortran codes for large-scale scientific
computation. See http://www.hsl.rl.ac.uk/). Dr H Alicia Kim
acknowledges the support from Engineering and Physical Sciences
Research Council, grant number EP/M002322/1
Keywords
- Level-set method
- Topology optimization
- Constraints
- Sequential linear programming
- structural topology
- sensitivity-analysis
- shape optimization
- design
- FEM