
doi: 10.1002/nme.5797
SummaryThis paper develops a new reliability‐based topology optimization framework considering spatially varying geometric uncertainties. Geometric imperfections arising from manufacturing errors are modeled with a random threshold model. The projection threshold is represented by a memoryless transformation of a Gaussian random field, which is then discretized by means of the expansion optimal linear estimation. The structural response and their sensitivities are evaluated with the polynomial chaos expansion, and the accuracy of the proposed method is verified by Monte Carlo simulations. The performance measure approach is adopted to tackle the reliability constraints in the reliability‐based topology optimization problem. The optimized designs obtained with the present method are compared with the deterministic solutions and the reliability‐based design considering random variables. Numerical examples demonstrate the efficiency of the proposed method.
polynomial chaos expansion, random threshold model, Topological methods for optimization problems in solid mechanics, Reliability and life testing, geometric uncertainty, reliability, Reliability, availability, maintenance, inspection in operations research, random field, General theory of stochastic processes, topology optimization
polynomial chaos expansion, random threshold model, Topological methods for optimization problems in solid mechanics, Reliability and life testing, geometric uncertainty, reliability, Reliability, availability, maintenance, inspection in operations research, random field, General theory of stochastic processes, topology optimization
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