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Dealing with Uncertainty in Modeling of Structures
6. April 2020 @ 14:00 - 15:30
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Applications to Model Validation and Design Optimization
Dr. Subhayan De University of Colorado, Boulder
Abstract In simulation-based engineering, models, often in the form of discretized differential equations, are used for purposes such as design space exploration, response prediction, health monitoring, and design optimization. For effective usage, these models must incorporate the ubiquitous presence of uncertainties in material properties and geometry of a structure. However, the number of models and model classes available to the modeler to represent a physical phenomenon can be very large. This poses a significant problem of identifying valid models to be used for further studies because retaining all available models throughout a study can be computationally burdensome. In this talk, a probabilistic hybrid framework for validating models by intertwining the concepts of model falsification and Bayesian model selection will be discussed. In another application, namely, the design optimization of complex engineering systems, uncertainties and their influences on the modelling of the underlying physical phenomena need to be considered in order to achieve a robust design. To achieve this, a novel approach of using stochastic gradients for topology optimization under uncertainty, along with the use of low- and high-fidelity models of the structure, will also be discussed. Examples will consider the uncertainties in material properties both in macro and microscale and in geometry.