Global sensitivity analysis of structural seismic demand based on information entropy.

Area of Science:

• Structural Engineering
• Computational Mechanics
• Seismic Analysis

Background:

• Global sensitivity analysis (GSA) is crucial for understanding parameter uncertainty in complex structural models.
• Existing GSA methods often require extensive computational resources, limiting their application.
• Efficiently quantifying the impact of various parameters on structural performance under seismic loads is a key challenge.

Purpose of the Study:

• To develop a computationally efficient global sensitivity analysis (GSA) method for complex structures.
• To assess the influence of parameter uncertainty on structural seismic demands.
• To validate the proposed method against established GSA techniques.

Main Methods:

• Proposed a novel importance analysis (IE) method utilizing low deviation sequences and orthogonal polynomials.
• Conducted nonlinear time history analysis using OpenSEES for seismic demand assessment.
• Employed variance-based and Tornado graphic sensitivity analysis for comparative validation.

Main Results:

• The proposed IE method achieved reliable results with a significantly reduced sample size (1024 samples).
• The order of parameter importance determined by the IE method closely matched established methods.
• Identified the representative value of gravity load (Ms) as having a substantial influence on seismic demands.
• Determined the modulus of elasticity of concrete (Ec) has a minor influence on seismic demands.

Conclusions:

• The new IE method offers a computationally efficient and accurate alternative for GSA in complex structural engineering.
• The method effectively identifies key parameters influencing structural response to seismic events.
• Findings provide valuable insights for prioritizing design parameters and reducing uncertainty in seismic risk assessments.