Reliability-based topology optimization using stochastic gradients
نویسندگان
چکیده
This paper addresses the computational challenges in reliability-based topology optimization (RBTO) of structures associated with estimation statistics objective and constraints using standard sampling methods. The aim is to overcome accuracy issues traditional methods that rely on approximating limit-state function. Herein, we present a stochastic gradient-based approach, where estimate probability failure at every few iterations an efficient strategy. To gradients respect design parameters, apply Bayes’ rule wherein assume parametric exponential model for density function parameters conditioned failure. this are updated gradient descent approach requiring only small, e.g., $${\mathcal {O}}(1)$$ , number random samples per iteration, thus, leading considerable reduction cost as compared RBTO techniques. We illustrate proposed benchmark example has analytical solution well two widely used problems structural optimization. These examples efficacy producing reliable designs.
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ژورنال
عنوان ژورنال: Structural and Multidisciplinary Optimization
سال: 2021
ISSN: ['1615-1488', '1615-147X']
DOI: https://doi.org/10.1007/s00158-021-03023-w