Reliability Engineering & System Safety最新文献_第2页

Team-centered IDAC: Modeling and simulation of operating crew in complex systems - Part 2: Simulation aspects and application 以团队为中心的 IDAC：复杂系统中操作人员的建模与仿真--第 2 部分：仿真方面与应用

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-24 DOI: 10.1016/j.ress.2024.110529

{"title":"Team-centered IDAC: Modeling and simulation of operating crew in complex systems - Part 2: Simulation aspects and application","authors":"","doi":"10.1016/j.ress.2024.110529","DOIUrl":"10.1016/j.ress.2024.110529","url":null,"abstract":"<div><div>Complex systems operations, such as Nuclear Power Plants (NPPs), generally require professional operating teams. Factors associated with teamwork, such as inappropriate communication and coordination, are important contributing factors to accidents and unsafe behavior. The impact of crew interactions on team effectiveness and, consequently, on the entire system, has yet to be fully and quantitatively explored in high-risk environments such as NPPs. Since a team is an interactive social system, team-specific issues must be studied and evaluated from a “team perspective”—based on team dynamics and processes. This paper is a part of a two-papers series that presents a simulation-based Team Model for NPP control room operations. Part 1 describes the theoretical fundaments of the model and details its elements. The current paper, Part 2, describes the simulation aspects and a full application of the method to an NPP four-steam generator feedwater system pipe break. It presents how to set up the simulation elements, such as hardware and humans within a team, using MATLAB Simulink. The method is demonstrated through a case study of an NPP four-steam generator feed water system pipe break. The results are discussed and assessed against theoretical and experimental findings.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Seismic risk estimates for reinforced concrete structures with incorporation of corrosion and aftershock 考虑腐蚀和余震因素的钢筋混凝土结构地震风险估算

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-24 DOI: 10.1016/j.ress.2024.110585

{"title":"Seismic risk estimates for reinforced concrete structures with incorporation of corrosion and aftershock","authors":"","doi":"10.1016/j.ress.2024.110585","DOIUrl":"10.1016/j.ress.2024.110585","url":null,"abstract":"<div><div>Numerous reinforced concrete (RC) structures are exposed to aggressive environments, such as chloride, mainshock and aftershock. These environmental and extreme loads have the potential to increase the seismic risks during structure's service life. This study introduces a practical probabilistic methodology to estimate the seismic risk of corroded RC frame subjected to mainshock-aftershock sequences. In this methodology, a time-variant modeling strategy is used to simulate the geometrical and mechanical properties of structural degraded materials. The Bayesian updating theorem is employed to calibrate the demand models, which are then used to estimate the fragilities and confidence intervals considering the model uncertainties. A Copula-based approach is conducted to generate joint probability of mainshock and aftershock intensities and the seismic hazard of the mainshock-aftershock scenario. Finally, the seismic risk and associated confidence intervals are estimated by integrating over all mainshock and aftershock intensities levels. A typical corroded RC frame structure is used to illustrate the proposed methodology. The results show that the contribution of corrosion and aftershock would lead a 10 times higher seismic risks compared to scenarios considering only mainshock damage. It is necessary to account for the influence of both corrosion and aftershock in seismic design.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sparse graph structure fusion convolutional network for machinery remaining useful life prediction 用于机械剩余使用寿命预测的稀疏图结构融合卷积网络

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-24 DOI: 10.1016/j.ress.2024.110592

{"title":"Sparse graph structure fusion convolutional network for machinery remaining useful life prediction","authors":"","doi":"10.1016/j.ress.2024.110592","DOIUrl":"10.1016/j.ress.2024.110592","url":null,"abstract":"<div><div>Effective prediction of machinery remaining useful life (RUL) is prominent to achieve intelligent preventive maintenance in manufacturing systems. In this paper, a sparse graph structure fusion convolutional network (SGSFCN) is proposed for more accurate end-to-end RUL prediction of machine. A novel node-level graph structure called time series shapelet distance graph (TSSDG) is designed to convert the time series to node feature. The SGSFCN model is proposed to learn degradation information from the graph structure. In SGSFCN, a sparse graph structure (SGS) layer and a fusion graph structure (FGS) layer preceding the graph convolutional network (GCN) are designed to learn the SGS from node representation and fuse the original graph structure, enabling the graph structure and node update iteratively in subsequent layers. Concurrently, a bidirectional long short-term memory network (BiLSTM) layer is integrated to capture the global temporal dependencies. The method is validated by two test rig data, and results demonstrate that the proposed method offers significantly higher prediction accuracy of RUL compared to several state-of-art methods.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel two-stage method via adversarial strategy for remaining useful life prediction of bearings under variable conditions 通过对抗策略预测轴承在不同条件下剩余使用寿命的两阶段新方法

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-24 DOI: 10.1016/j.ress.2024.110602

{"title":"A novel two-stage method via adversarial strategy for remaining useful life prediction of bearings under variable conditions","authors":"","doi":"10.1016/j.ress.2024.110602","DOIUrl":"10.1016/j.ress.2024.110602","url":null,"abstract":"<div><div>It is critical to accurately predict the remaining useful life (RUL) of rolling bearings to avoid severe accidents and financial losses in the industry. Nevertheless, accurately determining the initial prediction time (IPT) continues to pose a challenge, and significant differences in the data distribution of bearings under different operating conditions are frequently overlooked. To deal with these problems, we propose a novel two-stage method based on the adversarial strategy for RUL prediction of bearings under variable conditions. Firstly, we create reliable health indicators in an unsupervised manner by recording the coded characteristics of the bearing’s state of health. Secondly, an adaptive threshold method based on rate-of-change (ATMROC) is developed to perform accurate health state classification. Finally, we propose a RUL prediction network based on the attention depth-gated recurrent unit with domain invariance (DIADGRU) to handle the inconsistent distribution of degradation features under different operating conditions. Experiments of RUL prediction on PHM2012 and XITU-SY datasets are implemented, and the promising results validate the effectiveness of the proposed method.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Label-guided contrastive learning with weighted pseudo-labeling: A novel mechanical fault diagnosis method with insufficient annotated data 使用加权伪标签的标签引导对比学习：注释数据不足情况下的新型机械故障诊断方法

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-23 DOI: 10.1016/j.ress.2024.110597

{"title":"Label-guided contrastive learning with weighted pseudo-labeling: A novel mechanical fault diagnosis method with insufficient annotated data","authors":"","doi":"10.1016/j.ress.2024.110597","DOIUrl":"10.1016/j.ress.2024.110597","url":null,"abstract":"<div><div>Exploring fault diagnosis methods for mechanical equipment with weak dependency on annotated data is essential for industrial production. Contrastive learning (CL), capable of learning representations without labeling information, has achieved satisfactory performance in mechanical fault diagnosis. However, current CL-based approaches mainly encounter two limitations. First, the pre-training stage uses either unannotated or annotated samples exclusively while the fine-tuning stage solely relies on annotated ones, leading to inefficient sample utilization. Second, the representation learned by contrastive loss alone in the pretext task is sub-optimal for downstream diagnostic tasks. To address these issues, this paper proposed a novel diagnostic framework based on label-guided contrastive learning (LgCL) and weighted pseudo-labeling (WPL) strategy to improve fault diagnosis accuracy. In the pre-training stage, the proposed LgCL integrates two types of contrastive loss together with classification loss, enabling the encoder to learn discriminative representations that directly benefit the downstream diagnostic task. The devised hybrid fine-tuning strategy allows both labeled and unlabeled data to participate in fine-tuning via pseudo-labeling, enhancing model generalization. The pertinently designed WPL strategy mitigates the defect of noisy pseudo labels. Comparison and ablation experiments on two public datasets and one self-designed dataset validate the superiority of the proposed method for fault diagnosis with limited annotated data, with diagnostic accuracies improved by 25.30%, 5.47% and 10.02% over supervised, semi-supervised and contrastive learning methods, respectively.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On fractional moment estimation from polynomial chaos expansion 从多项式混沌展开论分数矩估计

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-22 DOI: 10.1016/j.ress.2024.110594

引用次数: 0

Maximum entropy-based modeling of community-level hazard responses for civil infrastructures 基于最大熵的民用基础设施社区级灾害响应建模

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-22 DOI: 10.1016/j.ress.2024.110589

{"title":"Maximum entropy-based modeling of community-level hazard responses for civil infrastructures","authors":"","doi":"10.1016/j.ress.2024.110589","DOIUrl":"10.1016/j.ress.2024.110589","url":null,"abstract":"<div><div>Perturbed by natural hazards, community-level infrastructure networks operate like many-body systems, with behaviors emerging from coupling individual component dynamics with group correlations and interactions. It follows that we can borrow methods from statistical physics to study the response of infrastructure systems to natural disasters. This study aims to construct a joint probability distribution model to describe the post-hazard state of infrastructure networks and propose an efficient surrogate model of the joint distribution for large-scale systems. Specifically, we present maximum entropy modeling of the regional impact of natural hazards on civil infrastructures. Provided with the current state of knowledge, the principle of maximum entropy yields the “most unbiased“ joint distribution model for the performances of infrastructures. In the general form, the model can handle multivariate performance states and higher-order correlations. In a particular yet typical scenario of binary performance state variables with knowledge of their mean and pairwise correlation, the joint distribution reduces to the Ising model in statistical physics. In this context, we propose using a dichotomized Gaussian model as an efficient surrogate for the maximum entropy model, facilitating the application to large systems. Using the proposed method, we investigate the seismic collective behavior of a large-scale road network (with 8,694 nodes and 26,964 links) in San Francisco, showcasing the non-trivial collective behaviors of infrastructure systems.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigation of essential parameters for the design of offshore wind turbine based on structural reliability 基于结构可靠性的海上风力涡轮机设计基本参数研究

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-20 DOI: 10.1016/j.ress.2024.110601

{"title":"Investigation of essential parameters for the design of offshore wind turbine based on structural reliability","authors":"","doi":"10.1016/j.ress.2024.110601","DOIUrl":"10.1016/j.ress.2024.110601","url":null,"abstract":"<div><div>The probabilistic-based design method is gradually gaining attention in the wind industry because it provides more accurate modeling of uncertainty variables than that of traditional methods. Unfortunately, the numerous uncertainty variables involved in structural design are major obstacles to the successful application of this method. Therefore, this study presents a sensitivity analysis (SA) of a benchmark monopile offshore wind turbine (OWT) to screen the top-ranking variables from the viewpoint of reliability. Primarily, a comprehensive reliability SA framework of OWT is proposed, in which a novel measurement of soil uncertainties is conducted using quantitative analysis from the perspective of soil structure interaction (SSI). Subsequently, a reliability SA is conducted to explore the crucial variables influencing the structural safety from the uncertain clusters. The results indicate that Young's modulus, structural geometry, and SSI have significant effects on the structural reliability of excessive vibration failure. The hydrodynamic and aerodynamic load variables exhibit the most prominent influence on excessive deflection failure. Additionally, the SSI uncertainties exhibit a non-negligible effect in affecting the structural reliability, i.e., the lateral bending stiffness shows more sensitivity to the normal operation cases, whereas the impact of joint stiffness is more remarkable in parked scenarios.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Damage-driven framework for reliability assessment of steam turbine rotors operating under flexible conditions 用于评估在柔性条件下运行的蒸汽轮机转子可靠性的损伤驱动框架

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-20 DOI: 10.1016/j.ress.2024.110578

{"title":"Damage-driven framework for reliability assessment of steam turbine rotors operating under flexible conditions","authors":"","doi":"10.1016/j.ress.2024.110578","DOIUrl":"10.1016/j.ress.2024.110578","url":null,"abstract":"<div><div>The high-temperature rotating structures (HTRS), e.g., steam turbine rotors, often operate in extremely harsh environments with a flexible load condition during peak shaving of power system. In this work, a damage-driven framework for reliability assessment is developed in terms of the cumulative damage-damage threshold interference (CD-DT) principle, in which the cumulative damage and damage threshold are regarded as two random parameters to address uncertainties. The CD-DT principle is founded on the engineering damage theory and incorporates physics-of-failure into the probabilistic modeling of high-temperature structural reliability. Probabilistic damage analysis, correlation analysis of weak sites, system-level reliability analysis, and sensitivity analysis have been encompassed in this framework. Three numerical examples are used to verify the effectiveness and applicability of the proposed framework. Application to steam turbine rotor involving multiple weak sites with multi-damage modes illustrate the implementation procedures of the framework. Results show that the reliability-based design life of rotor decreases with the increases of start-stop frequency, the implementation of a two-shift operation would pose a threat to meeting the safety requirement of a 30-year design life. Furthermore, sensitivity analysis highlights the critical influences of initial rotor temperature and speed rising rate on rotor reliability, providing insights for operational maintenance and reliability optimization.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reliability-constrained configuration optimization for integrated power and natural gas energy systems: A stochastic approach 综合电力和天然气能源系统的可靠性约束配置优化：随机方法

IF 9.4 1区工程技术

Reliability Engineering & System Safety Pub Date : 2024-10-19 DOI: 10.1016/j.ress.2024.110600

{"title":"Reliability-constrained configuration optimization for integrated power and natural gas energy systems: A stochastic approach","authors":"","doi":"10.1016/j.ress.2024.110600","DOIUrl":"10.1016/j.ress.2024.110600","url":null,"abstract":"<div><div>With the escalating dependence on electricity and natural gas infrastructure, ensuring both reliability and economic efficiency becomes paramount. It necessitates reliability centric measures to mitigate disruptions that could cascade between these interconnected systems. To address this challenges, this paper introduces a reliability-constrained two-stage stochastic model to optimize power-to-gas (P2 G) and gas-to-power (G2P) unit placement and sizing, aiming to enhance the reliability of both systems under stochastic scenarios. The proposed model, employing Sequential Monte Carlo (SMC) within its optimization framework, seeks to minimize investment, operation, and reliability costs. By addressing temporal uncertainties in component outages for both systems and considering uncertainties in power and gas system loads with a high temporal resolution and annual load growth, the model provides a comprehensive reliability perspective. Furthermore, sensitivity analysis is conducted to explore the impact of varying Values of Lost Load (VOLL) on the planning results. Numerical evaluation, using two integrated energy systems including IEEE 14-bus-10-gas node, and large-scale energy systems including IEEE 118-bus-85-gas node integrated power-gas system (IPGS), demonstrates a significant 12.53 % improvement in overall system reliability. Furthermore, a 2.81 % reduction in operation costs and a substantial 26.3 % reduction in reliability costs, validating the effectiveness of the proposed model.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":null,"pages":null},"PeriodicalIF":9.4,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0