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Matlab latin hypercube sampling gumbel distribution
Matlab latin hypercube sampling gumbel distribution












matlab latin hypercube sampling gumbel distribution matlab latin hypercube sampling gumbel distribution

When assessing bridge safety, the lack of information causes high uncertainties when representing the loads and material properties. The presented methodology and derived fragility curves can be used to assess bridge performance under a flood event, thus providing useful information for bridge management and monitoring. The results show the failure mechanism of the masonry arch bridges when subjected to scour-induced settlements and the influence of soil density on the failure probability obtained for different flow discharge values and angles of attack. Moreover, a stochastic parametric analysis based on the geotechnical properties of the soil components of masonry arch bridges located in Portugal was performed. Surrogate models were implemented to ease the computational cost of the probabilistic analysis. The objective of the present work is to present consistent tools that may allow us to obtain the failure probability of a masonry arch bridge under a flood event, leading to local scour. Therefore, the assessment of bridges exposed to these events is of paramount importance to identify possible mitigation needs. Natural disasters are unavoidable and can cause serious damage to bridges, which may lead to catastrophic losses, both human and economic.














Matlab latin hypercube sampling gumbel distribution