Abstract
We present a new method for stochastic shape optimisation of engineering structures. The method generalises an existing deterministic scheme, in which the structure is represented and evolved by a level-set method coupled with mathematical programming. The stochastic element of the algorithm is built on the methods of statistical mechanics and is designed so that the system explores a Boltzmann–Gibbs distribution of structures. In non-convex optimisation problems, the deterministic algorithm can get trapped in local optima: the stochastic generalisation enables sampling of multiple local optima, which aids the search for the globally-optimal structure. The method is demonstrated for several simple geometrical problems, and a proof-of-principle calculation is shown for a simple engineering structure.
Original language | English |
---|---|
Pages (from-to) | 82-107 |
Number of pages | 26 |
Journal | Journal of Computational Physics |
Volume | 348 |
DOIs | |
Publication status | Published - 1 Nov 2017 |
Keywords
- Level-set method
- Stochastic motion of shape boundaries
- Topology optimisation
ASJC Scopus subject areas
- Physics and Astronomy (miscellaneous)
- Computer Science Applications