To this end, a Progressive Latin Hypercube Sampling (PLHS) method was developed to derive the minimum samples for UA. The required sample size is calculated based on the convergence of the UA results. Therefore, UA is achieved by a variable sample size Design of Experiments (DOE). This ...
In order to reduce variance within SAA, Latin Hypercube Sampling (LHS) may be used instead of uniform sampling. Performance comparisons of LHS and uniform sampling, within SAA scheme, are analyzed in Ahmed and Shapiro (2002). The resulting SAA problem \(Min_{x \in X} \{ \hat{g}_{N}...
Feasibility study of progressive Latin hypercube sampling and quasi-Monte Carlo simulation for probabilistic risk assessmentSeung-Seop JinGungyu KimShinyoung KwagSeunghyun Eem
Using Latin Hypercube sampling of both random structure variables and external loads, random realizations of structures are generated and progressive collapse analysis is carried out using pseudo-static pushdown method. The proposed framework is applied to study the vulnerability of composite floor. ...
Validation through a dataset generated via Latin hypercube sampling (LHS) and simulation affirms the efficacy, demonstrating fast and accurate simulation. The results underscore its potential for collaborative optimization. In summary, the proposed method has obvious advantages and can be extended to ...
In this study, a comprehensive database was established by data collection, Latin hypercube sampling and structural design, and was used to train the mathematical model for quantifying progressive collapse resistance of reinforced concrete (RC) beam-column substructures under middle column removal ...
Thirdly, design of experiment (DOE) has been carried out using optimal Latin hypercube sampling method. The surrogate model has been established based on the DOE process and elliptical basis functions (EBF). Sensitivity analysis of mass, peak moment of folding, torsional failure angle, and peak ...
With incremental Latin Hypercube sampling of both random cohesive properties and external loads, the model is used to investigate the probabilistic collapse behavior of a two-dimensional 30 story RC structural frame under different column removal scenarios, where the occurrence probabilities of various ...
Therefore, it requires efficient techniques to perform the stochastic PFA compared to random sampling techniques such as Monte Carlo or Latin Hypercube Sampling (LHS) simulations. To this end, an efficient technique called Polynomial Chaos Expansion (PCE) has been implemented to minimize the ...
Thirdly, design of experiment (DOE) has been carried out using optimal Latin hypercube sampling method. The surrogate model has been established based on the DOE process and elliptical basis functions (EBF). Sensitivity analysis of mass, peak moment of folding, torsional failure angle, and peak ...