Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4967166 | Journal of Computational Physics | 2017 | 26 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Lester O. Hedges, H. Alicia Kim, Robert L. Jack,