Applying uncertainty quantification to structural systems: Parameter reduction for evaluating model complexity

Keyphrases

• Mathematical Model 100%
• Structural System 100%
• System Parameters 100%
• Model Complexity 100%
• Evaluation Model 100%
• Uncertainty Quantification 100%
• Output Response 100%
• Parameter Reduction 100%
• Sensitivity Analysis 66%
• Numerical Model 66%
• Truss 66%
• Two-degree-of-freedom 66%
• Subject System 66%
• Operating Conditions 33%
• Uncertainty Levels 33%
• Dynamic Behavior 33%
• Material Properties 33%
• Numerical Solution 33%
• Single Component 33%
• Gaussian Process Model 33%
• Failure Risk 33%
• Model Selection 33%
• Model Sensitivity Analysis 33%
• Simulation Analysis 33%
• System Integration 33%
• R2 Value 33%
• Low Sensitivity 33%
• Physical Systems 33%
• Computational Efficiency 33%
• Variation Analysis 33%
• Bayesian Inference 33%
• Fundamental Physics 33%
• Number of Parameters 33%
• Functional Relationship 33%
• Coefficient of Determination 33%
• Increasing Complexity 33%
• Parameter Sensitivity 33%
• Model Form 33%
• System Dynamic Behavior 33%
• Metropolis-Hastings Algorithm 33%
• Mass-spring-damper 33%
• Model Adequacy 33%
• Solution Form 33%
• Response Features 33%
• Global Sensitivity 33%

Engineering

• System Parameter 100%
• Input Parameter 100%
• Structural System 100%
• Uncertainty Quantification 100%
• Output Response 100%
• Dynamic Behavior 66%
• Numerical Model 66%
• Two Degree of Freedom 66%
• Gaussians 33%
• Experimental Measurement 33%
• Numerical Solution 33%
• Systems Dynamics 33%
• Physical System 33%
• Functional Relationship 33%
• Acceptable Level 33%
• Computational Efficiency 33%
• Operational Condition 33%
• Single Component 33%
• Sensitivity Parameter 33%
• Model Form 33%
• Damper System 33%