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Description

Reliability is a key aspect of safety-critical structures and systems such as bridges, aircrafts, dams, and nuclear structural facilities. For this reason, the performance of such structures and systems needs to be assessed via reliability analysis, to ensure they operate safely and, in turn, protect lives.

Given that reliability analysis is data-driven in nature, a significant challenge is the limited information availability, such as: 1) component reliability data; and 2) model-form certainty over the structure/system. These introduce uncertainty in the analysis, which is present in real-world engineering problems. Hence, the reliability analysis is often accompanied by an uncertainty analysis, which can be performed via the Bayesian approach.

The Special Collection builds on the previous efforts looking at uncertainty quantification in engineering, with the objective of creating a collection of state-of-the-art Bayesian methodologies, and cutting-edge research results in the context of reliability analysis of safety-critical structures and systems under limited data

Topics

We welcome submissions covering a wide range of topics related to Bayesian approaches for reliability analysis of safety-critical structures under uncertainty, including but not limited to:

A) Methods:

  • Bayesian model updating for system performance monitoring and prediction
  • Bayesian network analysis for accident and event dependence modelling
  • Markov chain Monte Carlo strategies for posterior estimates
  • Model-form selection via Bayesian statistics under model-form uncertainty
  • Online Bayesian approaches for real-time structural health monitoring

B) Applications:

  • Bayesian-based prognostics health management for predictive maintenance scheduling
  • Bayesian-based reliability updating under different sources of uncertainty
  • Bayesian approaches to optimal sensor placement for reliability analysis under limited data
  • Bayesian methodologies for characterizing environmental and anthropogenic actions on safety-critical systems

Note that all contributions should explicitly acknowledge the presence of uncertainties.

Special Issue Publication Dates

Paper submission deadline: April 31, 2026

Initial review completed: July 31, 2026

Publication date: December 2026

Guest Editors

  • Adolphus Lye , Singapore Nuclear Research and Safety Institute, National University of Singapore
  • Pengfei Wei , School of Power and Energy, Northwestern Polytechnical University, China
  • Danko Jerez , Departamento de Obras Civiles, Universidad Tecnica Federico Santa María, Chile
  • Marcos Valdebenito , Chair for Reliability Engineering, TU Dortmund University, Germany

Submission Guidelines

Authors should submit manuscripts electronically through the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering Editorial Manager website.

Authors should prepare their manuscripts according to guidelines found in the ASCE Author Center .

When submitting, authors should indicate in the submission questions that the paper is being submitted in response to this call for papers Advances in Bayesian Approaches for Reliability Updating of Safety-Critical Structures Under Limited Data.

Please note that this is an invitation to submit papers for peer review and does not imply acceptance for publication. Acceptance of submitted papers depends on the results of the normal refereed peer review process of the journal.

All accepted papers submitted through this solicitation will be published in regular issues of the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering as they are accepted. They will also be added to the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering Special Collections (similar to a print version of a special issue) page and indexed for citations like other regular journal papers.