A machine learning-based surrogate model for optimization of truss structures with geometrically nonlinear behavior

Design optimization of geometrically nonlinear structures is well known as a computationally expensive problem by using incremental-iterative solution techniques. To handle the problem effectively the optimization algorithm needs to ensure that the trade-off between the computational time and the qu...

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