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Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures

Submission Deadline: 31 December 2023 (closed)

Guest Editors

Prof. Debiao Meng, University of Electronic Science and Technology of China (UESTC), China

Prof. Abílio Manuel Pinho de Jesus, University of Porto (FEUP), Portugal

Prof. Zeng Meng, Hefei University of Technology, China

Summary

With the progress of science and technology, more and more complex engineering structures are serving in extreme environments. In the service life of these engineering structures, multi-source mixed uncertainty factors exist widely, which can affect safety and reliability significantly. Thus, how to ensure the high reliability and long service life of complex engineering structures is a research hotspot in the field of engineering design. Computer-aided uncertainty modeling and reliability evaluation for complex engineering structures are powerful tools to tackle the above challenges.

 

With the continuous advancement of the computer field, different advanced computational technologies have been introduced into computer-aided uncertainty modeling and reliability evaluation, such as artificial neural networks, surrogate models, metaheuristic algorithms, information entropy, fuzzy logic, convex model, multifidelity model, physics-informed neural network, deep learning, etc. However, each of these methods has its own merits and disadvantage. Facing a complex and changing variable environment, it is difficult to say which single technical means is the best. Meanwhile, the continuing development of engineering structures makes the existing methods difficult to deal with all new problems efficiently. Therefore, novel uncertainty modeling and reliability evaluation methods based on these advanced computational technologies are needed to be developed to provide more accurate and efficient estimations of the safety levels for the complex engineering structures of today.

 

This special issue would aim to establish an academic exchange platform between experts and scholars, also, 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 methods necessary to performing uncertainty modeling and reliability analysis for complex engineering structure. Potential topics include, but are not limited to:

• Uncertainty modeling

• Reliability evaluation and risk assessment

• Structural safety

• Fuzzy logic

• Interval and fuzzy mathematics

• Uncertainty quantification and propagation

• Machine learning

• Structural integrity

• Metaheuristic algorithm

• Information fusion

• Fault diagnosis

• Probabilistic Physics of Failure

• Surrogate models

• Uncertainty-based design optimization

• Signal processing

• Performance degradation modeling and analysis

• Durability and damage tolerance

• Risk analysis and safety of materials and structural mechanics

• Analytical and numerical simulation of materials and structures

• Experimental methods applied to structural integrity


Keywords

Uncertainty modeling, Reliability evaluation and risk assessment, Machine learning, Structural integrity, Surrogate models

Published Papers


  • Open Access

    ARTICLE

    A Planning Method for Operational Test of UAV Swarm Based on Mission Reliability

    Jingyu Wang, Ping Jiang, Jianjun Qi
    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1889-1918, 2024, DOI:10.32604/cmes.2024.049813
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract The unmanned aerial vehicle (UAV) swarm plays an increasingly important role in the modern battlefield, and the UAV swarm operational test is a vital means to validate the combat effectiveness of the UAV swarm. Due to the high cost and long duration of operational tests, it is essential to plan the test in advance. To solve the problem of planning UAV swarm operational test, this study considers the multi-stage feature of a UAV swarm mission, composed of launch, flight and combat stages, and proposes a method to find test plans that can maximize mission reliability. Therefore, a multi-stage mission reliability… More >

  • Open Access

    ARTICLE

    Constitutive Behavior of the Interface between UHPC and Steel Plate without Shear Connector: From Experimental to Numerical Study

    Zihan Wang, Boshan Zhang, Hui Wang, Qing Ai, Xingchun Huang
    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1863-1888, 2024, DOI:10.32604/cmes.2024.048217
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract The application of ultra-high performance concrete (UHPC) as a covering layer for steel bridge decks has gained widespread popularity. By employing a connection without a shear connector between the steel plate and UHPC, namely, the sandblasted interface and the epoxy adhesive with sprinkled basalt aggregate interface, the installation cannot only be simplified but also the stress concentration resulting from the welded shear connectors can be eliminated. This study develops constitutive models for these two interfaces without shear connectors, based on the interfacial pull-off and push-out tests. For validation, three-point bending tests on the steel-UHPC composite plates are conducted. The results… More >

  • Open Access

    ARTICLE

    Application of the CatBoost Model for Stirred Reactor State Monitoring Based on Vibration Signals

    Xukai Ren, Huanwei Yu, Xianfeng Chen, Yantong Tang, Guobiao Wang, Xiyong Du
    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 647-663, 2024, DOI:10.32604/cmes.2024.048782
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract Stirred reactors are key equipment in production, and unpredictable failures will result in significant economic losses and safety issues. Therefore, it is necessary to monitor its health state. To achieve this goal, in this study, five states of the stirred reactor were firstly preset: normal, shaft bending, blade eccentricity, bearing wear, and bolt looseness. Vibration signals along x, y and z axes were collected and analyzed in both the time domain and frequency domain. Secondly, 93 statistical features were extracted and evaluated by ReliefF, Maximal Information Coefficient (MIC) and XGBoost. The above evaluation results were then fused by D-S evidence… More >

  • Open Access

    ARTICLE

    Random Forest-Based Fatigue Reliability-Based Design Optimization for Aeroengine Structures

    Xue-Qin Li, Lu-Kai Song
    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 665-684, 2024, DOI:10.32604/cmes.2024.048445
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function, leading to the traditional direct Monte Claro and surrogate methods prone to unacceptable computing efficiency and accuracy. In this case, by fusing the random subspace strategy and weight allocation technology into bagging ensemble theory, a random forest (RF) model is presented to enhance the computing efficiency of reliability degree; moreover, by embedding the RF model into multilevel optimization model, an efficient RF-assisted fatigue reliability-based design optimization framework is developed. Regarding the low-cycle fatigue reliability-based design optimization of… More >

  • Open Access

    ARTICLE

    Contact Stress Reliability Analysis Model for Cylindrical Gear with Circular Arc Tooth Trace Based on an Improved Metamodel

    Qi Zhang, Zhixin Chen, Yang Wu, Guoqi Xiang, Guang Wen, Xuegang Zhang, Yongchun Xie, Guangchun Yang
    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 593-619, 2024, DOI:10.32604/cmes.2023.046319
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract Although there is currently no unified standard theoretical formula for calculating the contact stress of cylindrical gears with a circular arc tooth trace (referred to as CATT gear), a mathematical model for determining the contact stress of CATT gear is essential for studying how parameters affect its contact stress and building the contact stress limit state equation for contact stress reliability analysis. In this study, a mathematical relationship between design parameters and contact stress is formulated using the Kriging Metamodel. To enhance the model’s accuracy, we propose a new hybrid algorithm that merges the genetic algorithm with the Quantum Particle… More >

  • Open Access

    ARTICLE

    Modularized and Parametric Modeling Technology for Finite Element Simulations of Underground Engineering under Complicated Geological Conditions

    Jiaqi Wu, Li Zhuo, Jianliang Pei, Yao Li, Hongqiang Xie, Jiaming Wu, Huaizhong Liu
    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 621-645, 2024, DOI:10.32604/cmes.2024.046398
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract The surrounding geological conditions and supporting structures of underground engineering are often updated during construction, and these updates require repeated numerical modeling. To improve the numerical modeling efficiency of underground engineering, a modularized and parametric modeling cloud server is developed by using Python codes. The basic framework of the cloud server is as follows: input the modeling parameters into the web platform, implement Rhino software and FLAC3D software to model and run simulations in the cloud server, and return the simulation results to the web platform. The modeling program can automatically generate instructions that can run the modeling process in… More >

  • Open Access

    REVIEW

    Saddlepoint Approximation Method in Reliability Analysis: A Review

    Debiao Meng, Yipeng Guo, Yihe Xu, Shiyuan Yang, Yongqiang Guo, Lidong Pan, Xinkai Guo
    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2329-2359, 2024, DOI:10.32604/cmes.2024.047507
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract The escalating need for reliability analysis (RA) and reliability-based design optimization (RBDO) within engineering challenges has prompted the advancement of saddlepoint approximation methods (SAM) tailored for such problems. This article offers a detailed overview of the general SAM and summarizes the method characteristics first. Subsequently, recent enhancements in the SAM theoretical framework are assessed. Notably, the mean value first-order saddlepoint approximation (MVFOSA) bears resemblance to the conceptual framework of the mean value second-order saddlepoint approximation (MVSOSA); the latter serves as an auxiliary approach to the former. Their distinction is rooted in the varying expansion orders of the performance function as… More >

  • Open Access

    ARTICLE

    Research on Optimal Preload Method of Controllable Rolling Bearing Based on Multisensor Fusion

    Kuosheng Jiang, Chengrui Han, Yasheng Chang
    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3329-3352, 2024, DOI:10.32604/cmes.2024.046729
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract Angular contact ball bearings have been widely used in machine tool spindles, and the bearing preload plays an important role in the performance of the spindle. In order to solve the problems of the traditional optimal preload prediction method limited by actual conditions and uncertainties, a roller bearing preload test method based on the improved D-S evidence theory multi-sensor fusion method was proposed. First, a novel controllable preload system is proposed and evaluated. Subsequently, multiple sensors are employed to collect data on the bearing parameters during preload application. Finally, a multisensor fusion algorithm is used to make predictions, and a… More >

  • Open Access

    REVIEW

    A Review of the Tuned Mass Damper Inerter (TMDI) in Energy Harvesting and Vibration Control: Designs, Analysis and Applications

    Xiaofang Kang, Qiwen Huang, Zongqin Wu, Jianjun Tang, Xueqin Jiang, Shancheng Lei
    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2361-2398, 2024, DOI:10.32604/cmes.2023.043936
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract Tuned mass damper inerter (TMDI) is a device that couples traditional tuned mass dampers (TMD) with an inertial device. The inertial device produces resistance proportional to the relative acceleration at its two ends through its “inertial” constant. Due to its unique mechanical properties, TMDI has received widespread attention and application in the past twenty years. As different configurations are required in different practical situations, TMDI is still active in the research on vibration control and energy harvesting in structures. This paper provides a comprehensive review of the research status of TMDI. This work first examines the generation and important vibration… More >

  • Open Access

    ARTICLE

    An Efficient Reliability-Based Optimization Method Utilizing High-Dimensional Model Representation and Weight-Point Estimation Method

    Xiaoyi Wang, Xinyue Chang, Wenxuan Wang, Zijie Qiao, Feng Zhang
    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1775-1796, 2024, DOI:10.32604/cmes.2023.043913
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract The objective of reliability-based design optimization (RBDO) is to minimize the optimization objective while satisfying the corresponding reliability requirements. However, the nested loop characteristic reduces the efficiency of RBDO algorithm, which hinders their application to high-dimensional engineering problems. To address these issues, this paper proposes an efficient decoupled RBDO method combining high dimensional model representation (HDMR) and the weight-point estimation method (WPEM). First, we decouple the RBDO model using HDMR and WPEM. Second, Lagrange interpolation is used to approximate a univariate function. Finally, based on the results of the first two steps, the original nested loop reliability optimization model is… More >

  • Open Access

    ARTICLE

    Comparative Analysis of ARIMA and LSTM Model-Based Anomaly Detection for Unannotated Structural Health Monitoring Data in an Immersed Tunnel

    Qing Ai, Hao Tian, Hui Wang, Qing Lang, Xingchun Huang, Xinghong Jiang, Qiang Jing
    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1797-1827, 2024, DOI:10.32604/cmes.2023.045251
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract Structural Health Monitoring (SHM) systems have become a crucial tool for the operational management of long tunnels. For immersed tunnels exposed to both traffic loads and the effects of the marine environment, efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge. This study proposed a model-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel. Firstly, a dynamic predictive model-based anomaly detection method is proposed, which utilizes a rolling time window for modeling to achieve dynamic prediction. Leveraging the assumption… More >

  • Open Access

    ARTICLE

    An Improved CREAM Model Based on DS Evidence Theory and DEMATEL

    Zhihui Xu, Shuwen Shang, Yuntong Pu, Xiaoyan Su, Hong Qian, Xiaolei Pan
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2597-2617, 2024, DOI:10.32604/cmes.2023.031247
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract Cognitive Reliability and Error Analysis Method (CREAM) is widely used in human reliability analysis (HRA). It defines nine common performance conditions (CPCs), which represent the factors that may affect human reliability and are used to modify the cognitive failure probability (CFP). However, the levels of CPCs are usually determined by domain experts, which may be subjective and uncertain. What’s more, the classic CREAM assumes that the CPCs are independent, which is unrealistic. Ignoring the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability evaluation. To address the issue… More >

    Graphic Abstract

    An Improved CREAM Model Based on DS Evidence Theory and DEMATEL

  • Open Access

    ARTICLE

    Bearing Fault Diagnosis Based on Deep Discriminative Adversarial Domain Adaptation Neural Networks

    Jinxi Guo, Kai Chen, Jiehui Liu, Yuhao Ma, Jie Wu, Yaochun Wu, Xiaofeng Xue, Jianshen Li
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2619-2640, 2024, DOI:10.32604/cmes.2023.031360
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract Intelligent diagnosis driven by big data for mechanical fault is an important means to ensure the safe operation of equipment. In these methods, deep learning-based machinery fault diagnosis approaches have received increasing attention and achieved some results. It might lead to insufficient performance for using transfer learning alone and cause misclassification of target samples for domain bias when building deep models to learn domain-invariant features. To address the above problems, a deep discriminative adversarial domain adaptation neural network for the bearing fault diagnosis model is proposed (DDADAN). In this method, the raw vibration data are firstly converted into frequency domain… More >

  • Open Access

    ARTICLE

    Multidomain Correlation-Based Multidimensional CSI Tensor Generation for Device-Free Wi-Fi Sensing

    Liufeng Du, Shaoru Shang, Linghua Zhang, Chong Li, Jianing Yang, Xiyan Tian
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1749-1767, 2024, DOI:10.32604/cmes.2023.030144
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract Due to the fine-grained communication scenarios characterization and stability, Wi-Fi channel state information (CSI) has been increasingly applied to indoor sensing tasks recently. Although spatial variations are explicitly reflected in CSI measurements, the representation differences caused by small contextual changes are easily submerged in the fluctuations of multipath effects, especially in device-free Wi-Fi sensing. Most existing data solutions cannot fully exploit the temporal, spatial, and frequency information carried by CSI, which results in insufficient sensing resolution for indoor scenario changes. As a result, the well-liked machine learning (ML)-based CSI sensing models still struggling with stable performance. This paper formulates a… More >

  • Open Access

    ARTICLE

    System Reliability Analysis Method Based on T-S FTA and HE-BN

    Qing Xia, Yonghua Li, Dongxu Zhang, Yufeng Wang
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1769-1794, 2024, DOI:10.32604/cmes.2023.030724
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract For high-reliability systems in military, aerospace, and railway fields, the challenges of reliability analysis lie in dealing with unclear failure mechanisms, complex fault relationships, lack of fault data, and uncertainty of fault states. To overcome these problems, this paper proposes a reliability analysis method based on T-S fault tree analysis (T-S FTA) and Hyper-ellipsoidal Bayesian network (HE-BN). The method describes the connection between the various system fault events by T-S fuzzy gates and translates them into a Bayesian network (BN) model. Combining the advantages of T-S fault tree modeling with the advantages of Bayesian network computation, a reliability modeling method… More >

  • Open Access

    ARTICLE

    Adaptive H Filtering Algorithm for Train Positioning Based on Prior Combination Constraints

    Xiuhui Diao, Pengfei Wang, Weidong Li, Xianwu Chu, Yunming Wang
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1795-1812, 2024, DOI:10.32604/cmes.2023.030008
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract To solve the problem of data fusion for prior information such as track information and train status in train positioning, an adaptive H filtering algorithm with combination constraint is proposed, which fuses prior information with other sensor information in the form of constraints. Firstly, the train precise track constraint method of the train is proposed, and the plane position constraint and train motion state constraints are analysed. A model for combining prior information with constraints is established. Then an adaptive H filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor. Finally, the positioning… More >

  • Open Access

    ARTICLE

    Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

    Xiaoyan Su, Shuwen Shang, Zhihui Xu, Hong Qian, Xiaolei Pan
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1813-1826, 2024, DOI:10.32604/cmes.2023.030957
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract With the improvement of equipment reliability, human factors have become the most uncertain part in the system. The standardized Plant Analysis of Risk-Human Reliability Analysis (SPAR-H) method is a reliable method in the field of human reliability analysis (HRA) to evaluate human reliability and assess risk in large complex systems. However, the classical SPAR-H method does not consider the dependencies among performance shaping factors (PSFs), which may cause overestimation or underestimation of the risk of the actual situation. To address this issue, this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the… More >

    Graphic Abstract

    Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

  • Open Access

    ARTICLE

    Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-Speed Wire Rod Finishing Mills

    Cunsong Wang, Ningze Tang, Quanling Zhang, Lixin Gao, Haichen Yin, Hao Peng
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1827-1847, 2024, DOI:10.32604/cmes.2023.030970
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise. As complex system-level equipment, it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring. To solve the above problems, an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper. First, based on its mechanical structure, time and frequency domain analysis are improved in fault feature extraction. The approach of combining virtual value, peak value with kurtosis value index, is adopted in time domain analysis. Speed adjustment and side… More >

  • Open Access

    ARTICLE

    A Stroke-Limitation AMD Control System with Variable Gain and Limited Area for High-Rise Buildings

    Zuo-Hua Li, Qing-Gui Wu, Jun Teng, Chao-Jun Chen
    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 865-884, 2024, DOI:10.32604/cmes.2023.029927
    (This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
    Abstract Collisions between a moving mass and an anti-collision device increase structural responses and threaten structural safety. An active mass damper (AMD) with stroke limitations is often used to avoid collisions. However, a stroke-limited AMD control system with a fixed limited area shortens the available AMD stroke and leads to significant control power. To solve this problem, the design approach with variable gain and limited area (VGLA) is proposed in this study. First, the boundary of variable-limited areas is calculated based on the real-time status of the moving mass. The variable gain (VG) expression at the variable limited area is deduced… More >

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