Multiobjective Topology Optimization of Energy Absorbing Materials

Abstract

A method for the multiobjective optimization of local-scale material topology is presented. The topology optimization scheme is based on a constructive solid geometry-like representation, in which convex polygons---defined as the convex hull of arbitrary-length lists of points---are combined using an overlapping function. This data structure is tree-shaped and so genetic programming is used as the optimizer. The forward problem is solved with a multiscale finite element method with automatic cohesive zone insertion to model damage. As a multiscale method, loads and boundary conditions are applied and objective functions measured at a global scale, while the local scale material structure is optimized. The global scale geometry is assumed fixed. Pareto optimal designs are generated, representing optimal tradeoffs between conflicting goals: quasi-static displacement and dynamic strain energy. Results demonstrate the efficacy of the proposed algorithm.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2015
Accession Number
ADA623814

Entities

People

  • George A. Gazonas
  • Raymond A. Wildman

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Boundaries
  • Composite Materials
  • Computer Programming
  • Displacement
  • Evolutionary Algorithms
  • Finite Element Analysis
  • Genetic Algorithms
  • Geometry
  • Heuristic Methods
  • Materials
  • Military Research
  • Multiobjective Optimization
  • Optimization
  • Topology
  • Topology Optimization

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Fluid Dynamics (CFD)
  • Graph Algorithms and Convex Optimization.

Technology Areas

  • Biotechnology