Global sensitivity analysis of structural seismic demand based on information entropy

To improve the computational efficiency of global sensitivity analysis (GSA) for complex structures, this study proposed a new importance analysis method (IE) based on the low deviation sequences and orthogonal polynomials to study the influence of parameters' uncertainty on three structural seismic demands. A comparative investigation utilizing nonlinear time history analysis for these seismic demands was conducted using OpenSEES. The variance-based importance analysis method and the Tornado graphic sensitivity analysis method were employed to validate the accuracy of the proposed approach. The results regarding the order of importance are nearly consistent across methods, demonstrating the effectiveness of our proposed method. Notably, the sample size required by this new method is only 1024 to achieve reliable results, which is significantly lower than existing sampling methods that necessitate thousands of samples for effective importance analysis; thus, enhancing overall efficiency. Furthermore, the findings indicate that the influence of representative value of gravity load (M<sub>s</sub>) on seismic demands is relatively substantial, whereas the influence of modulus of elasticity of concrete (E<sub>c</sub>) is comparatively minor.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-03-11
DOI
https://doi.org/10.1038/s41598-025-93150-x
Citations
3
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
2.86
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Global sensitivity analysis of structural seismic demand based on information entropy

Zhaoxia Xu, Chuanzhi Sun, Xiuzhen Wang
3 citations
Scientific Reports
Structural Health Monitoring Techniques
2.86
article

Global sensitivity analysis of structural seismic demand based on information entropy

Zhaoxia Xu, Chuanzhi Sun, Xiuzhen Wang
article en
3 citations

Abstract

To improve the computational efficiency of global sensitivity analysis (GSA) for complex structures, this study proposed a new importance analysis method (IE) based on the low deviation sequences and orthogonal polynomials to study the influence of parameters' uncertainty on three structural seismic demands. A comparative investigation utilizing nonlinear time history analysis for these seismic demands was conducted using OpenSEES. The variance-based importance analysis method and the Tornado graphic sensitivity analysis method were employed to validate the accuracy of the proposed approach. The results regarding the order of importance are nearly consistent across methods, demonstrating the effectiveness of our proposed method. Notably, the sample size required by this new method is only 1024 to achieve reliable results, which is significantly lower than existing sampling methods that necessitate thousands of samples for effective importance analysis; thus, enhancing overall efficiency. Furthermore, the findings indicate that the influence of representative value of gravity load (M<sub>s</sub>) on seismic demands is relatively substantial, whereas the influence of modulus of elasticity of concrete (E<sub>c</sub>) is comparatively minor.

Scientific ReportsVol. 15(1)
Suqian University
Climate action
Openalex Percentile: Top 11%
Structural Health Monitoring Techniques
2.86
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.