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Using global variance-based sensitivity analysis, influence of nonlinear modelling approaches on uncertainty propagation is studied.
A variance-based sensitivity analysis method is used to validate the results of parameters' effects.
Using global variance-based sensitivity analysis, uncertainties in material properties, geometrical properties and mechanical properties are studied.
In the past several years there has been considerable commercial and academic interest in methods for variance-based sensitivity analysis.
A variance-based sensitivity analysis was performed in order to define the most effective design and operating parameters.
Nowadays, utilizing the Monte Carlo estimators for variance-based sensitivity analysis has gained sufficient popularity in many research fields.
Similar(42)
In the present work, we propose a set of variance-based sensitivity indices to perform sensitivity analysis of models with dependent inputs.
Firstly, variance-based sensitivity analyses are conducted to investigate the interaction of loss predictions with different inputs to the calculations.
A new set of variance-based sensitivity indices, called W-indices, is proposed.
A kind of Monte Carlo simulation was used to calculate the variance-based sensitivity indices.
Among all approximation methods, polynomial chaos expansion is one of the most efficient to calculate variance-based sensitivity indices.
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