Special Issue "Computer-Aided Structural Integrity and Safety Assessment"

Submission Deadline: 31 December 2021
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Guest Editors
Prof. Shun-Peng Zhu, University of Electronic Science and Technology of China, China
Prof. José A.F.O. Correia, University of Porto, Portugal
Prof. Grzegorz Lesiuk, Wroclaw University of Science and Technology, Poland

Summary

As the demand on the reliability of engineering systems such as aircraft engines, steam turbines, nuclear reactors and high-speed trains increases, computer-aided structural integrity and safety of these systems have been becoming extremely significant. With the help of advanced monitoring/testing techniques and mathematical approaches/tools, currently increasing interests are being paid on new techniques to discover and understand the integrity and safety of engineering systems, from materials to components. Current design of engineering systems aims to operate in extreme loading environments, which need to consider the unexpected ageing related degradations/damaging and integrity.

 

As the advances in the computational methods, structural integrity and safety assessment of engineering systems and their improvement have been feasible through the accurate failure mechanism modeling with the combination of either deterministic or probabilistic analyses by using computer methods, including artificial intelligence, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, intelligent and adaptive systems, knowledge discovery and engineering, machine learning, neural network computing etc. Using model-based and data-driven-based approaches, studies on integrity and performance degradation assessment should be conducted to maximize lifetime and optimize inspection and maintenance policy of engineering systems. Specifically, failure occurs under influences of multi-sources of uncertainty, including load variations in usage, material properties, geometry variations within tolerances, and other uncontrolled variations. Thus, advanced methods and applications for theoretical, numerical, and experimental contributions that address these issues on structural integrity and safety assessment of engineering systems are desired and expected, which attempts to prevent over-design and unnecessary inspection and provide tools to enable a balance between safety and economy to be achieved.

 

The aim would be to establish a common understanding about the state of the field and draw a road map on where the research is heading, highlight the issues and discuss the possible solutions, and provide the data, models and tools necessary to performing statistically safety and integrity assessment by computer methods. It is also available to concerned review/regular articles that will support and stimulate the continuing efforts to understand the research and development of model-based and data-driven-based approaches for structural integrity, safety and field applications. Potential topics include, but are not limited to: 

 

 Artificial intelligence

 Fuzzy logic and genetic algorithms

 Machine learning

 Neural network computing

 Structural integrity

 Structural reliability

 Structural health monitoring

 Computational mechanics

 Structural design methodology

 Prognostics and health management

 Probabilistic Physics of Failure

 Reliability-based design

 Durability and damage tolerance

 Uncertainty quantification and propagation

 Performance degradation modeling and analysis

 Non-destructive testing and evaluation for structural integrity

 Risk analysis and safety of materials and structural mechanics

 Analytical and numerical simulation of materials and structures

 Experimental methods applied to structural integrity


Published Papers
  • Fusion Fault Diagnosis Approach to Rolling Bearing with Vibrational and Acoustic Emission Signals
  • Abstract As the key component in aeroengine rotor systems, the health status of rolling bearings directly influences the reliability and safety of aeroengine rotor systems. In order to monitor rolling bearing conditions, a fusion fault diagnosis method, namely empirical mode decomposition (EMD)-Mahalanobis distance (E2MD) and improved wavelet threshold (IWT) (E2MD-IWT) for vibrational signals and acoustic emission (AE) signals is developed to improve the diagnostic accuracy of rolling bearings. The IWT method is proposed with a hard wavelet threshold and a soft wavelet threshold. Moreover, it is shown to be effective through numerical simulation. EMD is utilized to process the original AE… More
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  • Novel Kriging-Based Decomposed-Coordinated Approach for Estimating the Clearance Reliability of Assembled Structures
  • Abstract Turbine blisks are assembled using blades, disks and casings. They can endure complex loads at a high temperature, high pressure and high speed. The safe operation of assembled structures depends on the reliability of each component. Monte Carlo (MC) simulation is commonly used to analyze structural reliability, but this method needs to run thousands of computations. In order to assess the clearance reliability of assembled structures in an efficient and precise manner, the novel Kriging-based decomposed-coordinated (DC) (DCNK) approach is proposed by integrating the DC strategy, the Kriging model and the importance sampling-based Markov chain (MCIS) technique. In this method,… More
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  • Reliability Modeling and Evaluation of Complex Multi-State System Based on Bayesian Networks Considering Fuzzy Dynamic of Faults
  • Abstract In the traditional reliability evaluation based on the Bayesian method, the failure probability of nodes is usually expressed by the average failure rate within a period of time. Aiming at the shortcomings of traditional Bayesian network reliability evaluation methods, this paper proposes a Bayesian network reliability evaluation method considering dynamics and fuzziness. The fuzzy theory and the dynamic of component failure probability are introduced to construct the dynamic fuzzy set function. Based on the solving characteristics of the dynamic fuzzy set and Bayesian network, the fuzzy dynamic probability and fuzzy dynamic importance degree of the fault state of leaf nodes… More
  •   Views:86       Downloads:69        Download PDF