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Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges
The computerized simulations of physical and socio-economic systems have proliferated in
the past decade, at the same time, the capability to develop high-fidelity system predictive …
the past decade, at the same time, the capability to develop high-fidelity system predictive …
Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches
The risk assessment process performs an important role in maintenance decision making,
through structuring the process of identifying, prioritizing, and thereafter formulating effective …
through structuring the process of identifying, prioritizing, and thereafter formulating effective …
[HTML][HTML] Efficient reliability analysis of complex systems in consideration of imprecision
In this work, the reliability of complex systems under consideration of imprecision is
addressed. By joining two methods coming from different fields, namely, structural reliability …
addressed. By joining two methods coming from different fields, namely, structural reliability …
Reliability assessment of a hierarchical system subjected to inconsistent priors and multilevel data
The reliability assessment for a system with multiple prior information can be challenging. In
this paper, we propose a novel Bayesian melding (BM) approach to combine the …
this paper, we propose a novel Bayesian melding (BM) approach to combine the …
On the performance evaluation of a hierarchical-structure prototype product using inconsistent prior information and limited test data
Performance evaluation or parameter estimation for a hierarchical structure prototype
product is an imperative yet difficult task. The challenge comes from both inaccurate prior …
product is an imperative yet difficult task. The challenge comes from both inaccurate prior …