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Department of Mechanical Engineering
Student sits at workstation and looks at laptop. © Aliona Kardash​/​TU Dortmund

CRE participates at GAMM 2025 in Poznań

© CRE
Dr. Peipei Li, Dr. Marcos Valdebenito and Dr. Xuan-Yi Zhang presented their research at GAMM 2025 conference

From April 7–11, 2025, members of the Chair for Reliability Engineering (CRE) participated in the 95th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM 2025), held in Poznań, Poland.  Representing CRE, Dr. Peipei Li, Dr. Marcos Valdebenito and Dr. Xuan-Yi Zhang presented their latest findings in structural reliability under uncertainty and sensitivity analysis of stochastic computational models.

Dr. Peipei Li’s Research:

Reliability analysis of structures with correlated random variables considering uncertain distribution parameters

Abstract:

This study presents a reliability evaluation method that considers the correlated random variables with uncertain distribution parameters. First, the limit state function involving correlated random variables is transformed into standard normal space based on the orthogonal normal transformation. Then, the sparse grid quadrature is employed to compute the first three moments of the conditional reliability index, facilitating the derivation of its distribution.  Based on this distribution, an explicit expression for the quantile values of the conditional failure probability can be obtained. The effectiveness and accuracy of the proposed method are validated through two illustrative examples.

Dr. Marcos Valdebenito’s Research:

Augmented First-Order Reliability Method for Estimation of Imprecise Failure Probabilities

Abstract:

This work presents an approach for coping with aleatory and epistemic uncertainty when assessing structural reliability. The approach is based on the concept of an augmented reliability problem, where the epistemic distribution parameters are artificially regarded as aleatory. The augmented reliability problem is solved using the First-Order Reliability Method (FORM). The functional dependence of the failure probability with respect to the distribution parameters can be calculated explicitly based on the FORM assumption. This allows determining the bounds of the failure probability in closed form once the design point associated with the augmented reliability problem has been located.

Dr. Xuan-Yi Zhang’s Research:

Sensitivity Estimation of Failure Probability with Respect to Input Distribution Parameters in Stochastic Computational Models

Abstract:

This research addresses a vital aspect of computational modeling—understanding how variations in input distribution parameters influence the uncertainty of model outputs. Departing from traditional sensitivity estimation approaches that analyze input values directly, this study introduces a framework focused on the hyperparameters of input distributions. By formulating new sensitivity indices based on the moments and cumulative distribution function of outputs, the proposed methodology allows for efficient evaluation during post-processing without requiring additional model simulations. Demonstrated through three case studies including nonlinear models and finite element analyses, the approach proves robust and scalable, offering a deeper grasp of uncertainty propagation and its implications for decision-making in complex systems.

 

As CRE continues its mission to bridge theoretical innovation with practical impact, we are proud of our team’s contributions at GAMM 2025. The conference provided a valuable platform for showcasing our latest research, exchanging ideas, and fostering collaborations to advance resilient and reliable engineering systems globally.

Conference details sourced from: GAMM 2025 Official Website

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