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

Submission Deadline: 30 June 2022
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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


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
  • Dynamic Meta-Modeling Method to Assess Stochastic Flutter Behavior in Turbomachinery
  • Abstract With increasing design demands of turbomachinery, stochastic flutter behavior has become more prominent and even appears a hazard to reliability and safety. Stochastic flutter assessment is an effective measure to quantify the failure risk and improve aeroelastic stability. However, for complex turbomachinery with multiple dynamic influencing factors (i.e., aeroengine compressor with time-variant loads), the stochastic flutter assessment is hard to be achieved effectively, since large deviations and inefficient computing will be incurred no matter considering influencing factors at a certain instant or the whole time domain. To improve the assessing efficiency and accuracy of stochastic flutter behavior, a dynamic meta-modeling… More
  •   Views:911       Downloads:332        Download PDF

  • RBMDO Using Gaussian Mixture Model-Based Second-Order Mean-Value Saddlepoint Approximation
  • Abstract Actual engineering systems will be inevitably affected by uncertain factors. Thus, the Reliability-Based Multidisciplinary Design Optimization (RBMDO) has become a hotspot for recent research and application in complex engineering system design. The Second-Order/First-Order Mean-Value Saddlepoint Approximate (SOMVSA/FOMVSA) are two popular reliability analysis strategies that are widely used in RBMDO. However, the SOMVSA method can only be used efficiently when the distribution of input variables is Gaussian distribution, which significantly limits its application. In this study, the Gaussian Mixture Model-based Second-Order Mean-Value Saddlepoint Approximation (GMM-SOMVSA) is introduced to tackle above problem. It is integrated with the Collaborative Optimization (CO) method to… More
  •   Views:73       Downloads:48        Download PDF

  • Handling Uncertainty in Human Cognitive Reliability Method for Safety Assessment Based on DSET
  • Abstract Human Reliability Analysis (HRA) is an important part in safety assessment of a large complex system. Human Cognitive Reliability (HCR) model is a method of evaluating the probability that operators fail to complete during diagnostic decision making within a limited time, which is widely used in HRA. In the application of this method, cognitive patterns of humans are required to be considered and classified, and this process often relies on the evaluation opinions of experts which is highly subjective and uncertain. How to effectively express and process this uncertain and subjective information plays a critical role in improving the accuracy… More
  •   Views:160       Downloads:112        Download PDF

  • Modeling and Experimental Study for Automotive Dry Clutch Sliding Noise
  • Abstract Automotive dry clutches have been found to produce a low frequency sliding noise in many applications, which challenges the ride comfort of vehicles. In order to study this clutch sliding noise, a detailed finite element model including both a pressure plate assembly and a driven plate assembly was developed. Based on this model, a complex eigenvalue analysis is performed in this research. The effect of several major factors on the clutch sliding noise, such as the coefficient of friction, the clamping force, the geometric imperfection of the friction plate, and the thermal deformation of the pressure plate, were investigated numerically.… More
  •   Views:916       Downloads:393        Download PDF

  • Time-Variant Reliability-Based Multi-Objective Fuzzy Design Optimization for Anti-Roll Torsion Bar of EMU
  • Abstract Although various types of anti-roll torsion bars have been developed to inhibit excessive roll angle of the electric multiple unit (EMU) car body, it is critical to ensure the reliability of structural design due to the complexity of the problems involving time and uncertainties. To address this issue, a multi-objective fuzzy design optimization model is constructed considering time-variant stiffness and strength reliability constraints for the anti-roll torsion bar. A hybrid optimization strategy combining the design of experiment (DoE) sampling and non-linear programming by quadratic lagrangian (NLPQL) is presented to deal with the design optimization model. To characterize the effect of… More
  •   Views:405       Downloads:326        Download PDF

  • Dynamic Fatigue Reliability Analysis of Transmission Gear Considering Failure Dependence
  • Abstract Multiple failure modes and strength degradation are usually inherent in the gear transmission system, which brings new challenges for conducting fatigue reliability analysis and design. This paper proposes a novel dynamic fatigue reliability analysis method for failure dependence and strength degradation based on the combination of the Copula function and Gamma process. Firstly, the dynamic simulation model of the gear transmission system is established to obtain the dynamic stress-time history. The Gamma process is then used to describe the strength degradation to establish the dynamic stress-strength interference model. The marginal distribution functions of tooth contact fatigue and dedendum bending fatigue… More
  •   Views:567       Downloads:457        Download PDF

  • Fault Analysis of Wind Power Rolling Bearing Based on EMD Feature Extraction
  • Abstract In a wind turbine, the rolling bearing is the critical component. However, it has a high failure rate. Therefore, the failure analysis and fault diagnosis of wind power rolling bearings are very important to ensure the high reliability and safety of wind power equipment. In this study, the failure form and the corresponding reason for the failure are discussed firstly. Then, the natural frequency and the characteristic frequency are analyzed. The Empirical Mode Decomposition (EMD) algorithm is used to extract the characteristics of the vibration signal of the rolling bearing. Moreover, the eigenmode function is obtained and then filtered by… More
  •   Views:700       Downloads:568       Cited by:2        Download PDF

  • 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
  •   Views:691       Downloads:572        Download PDF

  • 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
  •   Views:690       Downloads:574        Download PDF

  • 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:825       Downloads:634        Download PDF