Quantile-based versus Sobol sensitivity analysis in limit state design

Abstract

In limit state design, the reliability of building constructions is generally verified using design quantiles. The design resistance of a structure is explicitly expressed as a low quantile of the cumulative distribution function of resistance. The aim of this article is to show the connections and differences between quantile-oriented sensitivity analysis subordinated to a contrast and classic Sobol sensitivity analysis. Changing the fixed input variable causes synchronous change in the quantile and mean value, but how do the results of these two sensitivity analyses differ? The question is whether or not the changes around the design quantile (measured by contrast indices) are similar to the changes around the mean value, which are measured using Sobol’s indices. Comparison is performed on a case study, where the resistance of the structure is expressed by a non-linear function, the inputs of which are random material and geometric characteristics of the structure. The non-dimensional slenderness is a deterministic parameter, which changes the influence of input variables on the resistance as the model output. It was concluded upon comparing the results of both sensitivity analyses that the rank of the most important variables is the same for both low and high slenderness and is similar for intermediate slenderness. However, the interaction effects are very different. The identification of insignificant variables is the same. Other significant similarities and differences between both types of sensitivity analyses are presented in the article.

In limit state design, the reliability of building constructions is generally verified using design quantiles. The design resistance of a structure is explicitly expressed as a low quantile of the cumulative distribution function of resistance. The aim of this article is to show the connections and differences between quantile-oriented sensitivity analysis subordinated to a contrast and classic Sobol sensitivity analysis. Changing the fixed input variable causes synchronous change in the quantile and mean value, but how do the results of these two sensitivity analyses differ? The question is whether or not the changes around the design quantile (measured by contrast indices) are similar to the changes around the mean value, which are measured using Sobol’s indices. Comparison is performed on a case study, where the resistance of the structure is expressed by a non-linear function, the inputs of which are random material and geometric characteristics of the structure. The non-dimensional slenderness is a deterministic parameter, which changes the influence of input variables on the resistance as the model output. It was concluded upon comparing the results of both sensitivity analyses that the rank of the most important variables is the same for both low and high slenderness and is similar for intermediate slenderness. However, the interaction effects are very different. The identification of insignificant variables is the same. Other significant similarities and differences between both types of sensitivity analyses are presented in the article.