When dealing with timber structures, the characteristic strength and stiffness of the material are made highly variable and uncertain by the unavoidable, yet hardly predictable, presence of knots and other defects. In this work, we apply the sparse grids stochastic collocation method to perform uncertainty quantification for structural engineering in the scenario described above. Sparse grids have been developed by the mathematical community in the last decades, and their theoretical background has been rigorously and extensively studied. The document proposes a brief practice-oriented introduction with minimal theoretical background, provides detailed instructions for the use of the off-the-shelf Sparse Grid Matlab kit (freely available online and straightforward to use) and discusses two preliminary examples inspired from timber engineering problems that highlight how sparse grids exhibit superior performances compared to the plain Monte Carlo method.

Uncertainty quantification in timber-like beams using sparse grids: theory and examples with off-the-shelf software utilization

F. Bonizzoni;L. Tamellini
2023-01-01

Abstract

When dealing with timber structures, the characteristic strength and stiffness of the material are made highly variable and uncertain by the unavoidable, yet hardly predictable, presence of knots and other defects. In this work, we apply the sparse grids stochastic collocation method to perform uncertainty quantification for structural engineering in the scenario described above. Sparse grids have been developed by the mathematical community in the last decades, and their theoretical background has been rigorously and extensively studied. The document proposes a brief practice-oriented introduction with minimal theoretical background, provides detailed instructions for the use of the off-the-shelf Sparse Grid Matlab kit (freely available online and straightforward to use) and discusses two preliminary examples inspired from timber engineering problems that highlight how sparse grids exhibit superior performances compared to the plain Monte Carlo method.
2023
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1225219
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