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

Frequency-domain approach to automated and efficient multivariate kernel density estimation for probabilistic modeling 用于概率建模的多变量核密度估计的频域方法

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-02-04 DOI: 10.1016/j.ress.2026.112351

Futai Zhang , Jun Xu , Dan Wang

{"title":"Frequency-domain approach to automated and efficient multivariate kernel density estimation for probabilistic modeling","authors":"Futai Zhang , Jun Xu , Dan Wang","doi":"10.1016/j.ress.2026.112351","DOIUrl":"10.1016/j.ress.2026.112351","url":null,"abstract":"<div><div>Accurate estimation of probability density functions is essential for probabilistic modeling but remains a major challenge, particularly for large-scale, multidimensional datasets. Kernel Density Estimation (KDE), one of the most widely used nonparametric methods, has been extensively studied. However, for such datasets, KDE is limited by high computational cost, suboptimal bandwidth selection, and density leakage. To address these limitations, we propose a method that reformulates bandwidth selection as a gradient-based optimization task in the frequency domain, thereby simultaneously resolving these three shortcomings. In this framework, the data are discretized and transformed using the discrete cosine transform, which decouples computational complexity from dataset size. We then construct a differentiable objective function that integrates a frequency-domain fidelity loss with a regularization penalty and stabilize it with a normalization scheme. The optimal bandwidth vector is obtained by minimizing this function with the Adam optimizer and its analytical gradient. This approach outperforms classical and transformation-based estimators, as well as Copula models, in both efficiency and accuracy, while achieving results comparable to specialized asymmetric product kernels at a much lower computational cost. Overall, the proposed method provides a reliable solution for one to multi-dimensional data-driven density estimation.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112351"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174758","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 pressure-chlorine driven approach to design effective district metered areas (DMA) configurations in water distribution systems 一种压力-氯驱动的方法来设计供水系统中有效的区域计量区域（DMA）配置

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-02-09 DOI: 10.1016/j.ress.2026.112382

Pedram Jazayeri, Ramtin Moeini

{"title":"A pressure-chlorine driven approach to design effective district metered areas (DMA) configurations in water distribution systems","authors":"Pedram Jazayeri, Ramtin Moeini","doi":"10.1016/j.ress.2026.112382","DOIUrl":"10.1016/j.ress.2026.112382","url":null,"abstract":"<div><div>To address the limitations of conventional Graph Theory (<em>GT</em>) techniques, in this study, an effective approach, named the Graph Theory-based Pressure and Chlorine Quantities (GT-PCQ) method, is proposed inspired by Girvan–Newman (<em>GN</em>) algorithm. Here, the nodal pressure and chlorine concentration values are directly integrated into the network partitioning process. Three performance indices—Hydraulic Reliability Index (<em>HRI</em>), Quality Reliability Index (<em>QRI</em>), and Hydraulic–Quality Reliability Index (<em>HQRI</em>)—are employed to evaluate the performance of the resulting configurations. The GT-PCQ method is applied to a large-scale, real-world Water Distribution System (WDS) in Najaf Abad, Isfahan, Iran, using a 24-hour Extended Period Simulation (EPS) combined with Pressure-Dependent Analysis (PDA) modeling for both hot and cold day scenarios. Three models are developed to assess the influence of system quantities, including (i) simultaneous consideration of pressure and chlorine concentration, (ii) pressure-only, and (iii) chlorine-only. Results indicate that, compared to the GN algorithm, the GT-PCQ method substantially reduces computational time (<em>CT</em>) and improves average network pressure (<em>P̅</em>) and chlorine concentration (<span><math><mover><mrow><mi>C</mi><mi>L</mi></mrow><mo>‾</mo></mover></math></span>), ultimately leading to improved reliability across all indices.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112382"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174990","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

Dynamic coupling reliability assessment of smart wind-photovoltaic-storage cyber-physical systems under multi-source uncertain information 多源不确定信息下智能风-光-储网络物理系统动态耦合可靠性评估

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-02-06 DOI: 10.1016/j.ress.2026.112368

Hongyan Dui , Rukun Wang , Wanyun Xia , Liudong Xing

{"title":"Dynamic coupling reliability assessment of smart wind-photovoltaic-storage cyber-physical systems under multi-source uncertain information","authors":"Hongyan Dui , Rukun Wang , Wanyun Xia , Liudong Xing","doi":"10.1016/j.ress.2026.112368","DOIUrl":"10.1016/j.ress.2026.112368","url":null,"abstract":"<div><div>With the increasing integration of wind, photovoltaic (PV), and energy storage systems, modern distributed energy systems rely on sensing, communication, and control infrastructures, evolving into smart cyber-physical systems. Under multi-source uncertainties including renewable variability, load fluctuations, communication degradation, and cyber attacks, existing methods struggle to capture coupled power–information dynamics and their joint reliability impacts. This study proposes a dynamic coupling reliability assessment framework for Wind-PV-Storage Cyber-Physical Systems (WPS-CPSs). A heterogeneous directed network is constructed to model structural relationships among generation, load, storage, and cyber components. Based on this model, a Power Flow Reliability Index (PFRI) and an Information Flow Reliability Index (IFRI) are developed to characterize physical-layer and cyber-layer performance, respectively. These indices are integrated via a coupling penalty mechanism to form the Dynamic Coupling Reliability Index (DCRI), enabling evaluation of cross-layer interactions. The framework is validated on a benchmark integrating a modified IEEE 14-bus system with engineering data from the Yancheng National Renewable Energy Demonstration Base. Results indicate that energy storage improves the lower reliability bound, Denial-of-Service and False Data Injection attacks cause distinct IFRI degradation, and DCRI captures coupling-penalty variations revealing both the benefits and risks of cyber-physical integration, offering guidance for resilient renewable-rich microgrids.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112368"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174952","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

Research on risk prevention and control of coal mine gas explosion using bayesian network and system dynamics: An optimization model for safety investment decision-making 基于贝叶斯网络和系统动力学的煤矿瓦斯爆炸风险防控研究——安全投资决策的优化模型

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-01-26 DOI: 10.1016/j.ress.2026.112298

Zhijun Lin , Shengwu Qin , Shan He , Shiliang Shi , Tingwei Chen , Baijian Zhu

{"title":"Research on risk prevention and control of coal mine gas explosion using bayesian network and system dynamics: An optimization model for safety investment decision-making","authors":"Zhijun Lin , Shengwu Qin , Shan He , Shiliang Shi , Tingwei Chen , Baijian Zhu","doi":"10.1016/j.ress.2026.112298","DOIUrl":"10.1016/j.ress.2026.112298","url":null,"abstract":"<div><div>To mitigate catastrophic coal mine gas explosion (CMGE) accidents, enhance overall safety performance, and achieve an efficient allocation of safety-related resources, this study proposes an optimization framework for safety investment decision-making by integrating System Dynamics (SD) with Bayesian Network (BN). First, based on a sensitivity analysis of 298 major CMGE accidents that occurred between 2000 and 2022, the key causal factors are identified. Second, an optimal safety investment portfolio is formulated to maximize safety outcomes under limited investment resources. The simulation results indicate that the shorter the expected time required to achieve a given safety level, the higher the minimum initial total safety investment needed. Safety management has the most significant influence on coal mine safety, followed sequentially by safety technology, training, and facilities, emphasizing the priority areas for allocating resources. Finally, a case study validated the proposed model, demonstrating its practical applicability and potential for real-world implementation.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112298"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174932","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

Temporal causal graph-based attention gated recurrent unit for interpretable fault diagnosis in nuclear power plants 基于时间因果图的核电厂可解释故障诊断注意门控循环单元

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-01-31 DOI: 10.1016/j.ress.2026.112332

Jie Liu , Kai Pan , Enrico Zio , Yuantao Yao

{"title":"Temporal causal graph-based attention gated recurrent unit for interpretable fault diagnosis in nuclear power plants","authors":"Jie Liu , Kai Pan , Enrico Zio , Yuantao Yao","doi":"10.1016/j.ress.2026.112332","DOIUrl":"10.1016/j.ress.2026.112332","url":null,"abstract":"<div><div>Intelligent fault diagnosis is crucial for safe operation of nuclear power plants (NPPs), yet challenges remain due to complex architectures and dynamic time-series data. Besides, the black-box nature of conventional data-driven models also hinders their practical deployment in fault diagnosis scenarios. To address these issues, this paper proposes a novel temporal causal graph-based gated recurrent unit with cell-level graph attention (GraphAttGRU-Cell) network for interpretable and efficient system-level fault diagnosis in NPPs. A temporal causal discovery method integrating domain expertise with data is first adopted to learn stable and credible temporal causal graph that incorporate both instantaneous and lagged dependencies from multivariate sensor data. The proposed GraphAttGRU-Cell Network is designed from the bottom up at the cell level, in which the attention and gated mechanisms can capture spatial and temporal features within the graph. The proposed method is validated by a simulated Gen-IV NPP simulation accident dataset. Experimental results demonstrate that the proposed method significantly outperforms state-of-the-art baselines in accuracy and interpretability, offering a robust and explainable tool for NPP maintenance decision-making.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112332"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175035","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 multimodal full-cycle risk perception and early warning model for mine water inrush disasters 矿井突水灾害多模式全周期风险感知与预警模型

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-02-04 DOI: 10.1016/j.ress.2026.112362

Junwei Shi , Ziyan Zhang , Liangning Li

{"title":"A multimodal full-cycle risk perception and early warning model for mine water inrush disasters","authors":"Junwei Shi , Ziyan Zhang , Liangning Li","doi":"10.1016/j.ress.2026.112362","DOIUrl":"10.1016/j.ress.2026.112362","url":null,"abstract":"<div><div>Mine water inrush is highly nonlinear and sudden; failure to perceive and warn of its risk in time may lead to severe safety accidents. Existing early-warning methods often rely on single hydrological or geological parameters, making it difficult to capture the full-process dynamic evolution of inrush events and leading to delayed or false alarms. To address this issue, this study proposes a multi-modal full-cycle risk perception and early-warning model. In the early perception stage, a rock seepage expansion visual detection network (VDRS-Net) and an abnormal fissure flow acoustic network (AFG-Net) are established to capture multi-source precursor signals. In the mid-to-late stage, a multi-modal time-series prediction model (MTWNet) integrating WOA, VMD, and LSTM-Attention is developed for adaptive optimization, feature decomposition, and long-range dependency modeling. Field validation in typical coal mines of Qitaihe City shows that VDRS-Net and AFG-Net achieve accuracies of 95.3% and 92.7%, improving recognition by 21.4% in early perception; the model achieves over 91% overall prediction accuracy, with RMSE and MAE reduced by 30∼50% and the false-alarm rate lowered from 18.7% to 1.2%, the warning response time is advanced by 63 minutes, which demonstrates its high reliability, precision, and engineering adaptability for disaster prevention.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112362"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174762","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

Empirical reliability enhancement in series elastic actuators using fractional-order finite-time robust control 基于分数阶有限时间鲁棒控制的串联弹性执行器可靠性经验增强

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-01-30 DOI: 10.1016/j.ress.2026.112330

Seyed Ali Moafi , Ebrahim Abbaszadeh , Seyed Hossein Rouhani , Saleh Mobayen , Farid Najafi

{"title":"Empirical reliability enhancement in series elastic actuators using fractional-order finite-time robust control","authors":"Seyed Ali Moafi , Ebrahim Abbaszadeh , Seyed Hossein Rouhani , Saleh Mobayen , Farid Najafi","doi":"10.1016/j.ress.2026.112330","DOIUrl":"10.1016/j.ress.2026.112330","url":null,"abstract":"<div><div>This paper presents a novel fractional-order control strategy aimed at enhancing the reliability, safety, and efficiency of the series elastic actuators in robotic systems, with practical reliability approximated through empirical metrics such as failure probability and mean time to failure. The proposed method optimizes control signal constraints, thereby improving the performance and reliability of series elastic actuator-driven robots in assistive human-robot interaction tasks. Leveraging fractional calculus, the proposed approach provides a more accurate model of dynamic interactions between robots and flexible environments, addressing these complexities more precisely than traditional integer-order models. The proposed strategy accounts for controller effort saturation, offering robust finite-time convergence and ensuring superior resilience to disturbances and uncertainties, critical for mission success in real-world applications. The adaptive capability of the system in low- and high-stiffness environments further enhances its versatility and maintainability in diverse operational scenarios. Various experiments demonstrate the superior performance of the method compared to integer-order terminal sliding mode techniques, particularly in accurately modeling failure dynamics and enhancing system safety. The findings underscore the potential of fractional-order control to substantially improve the reliability of series elastic actuator-driven robots, advancing the development of safe, human-centric robotic systems for deployment in unpredictable and dynamic environments.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112330"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174765","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

Deep transfer learning based on cross-domain subsequence alignment and feature contribution interpretation for remaining useful life prediction 基于跨域子序列比对和特征贡献解释的深度迁移学习剩余使用寿命预测

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-02-05 DOI: 10.1016/j.ress.2026.112370

Tongshan Liu, Yiming Li, Zhihao Hu, Congjie Fu, Guiqiu Song

{"title":"Deep transfer learning based on cross-domain subsequence alignment and feature contribution interpretation for remaining useful life prediction","authors":"Tongshan Liu, Yiming Li, Zhihao Hu, Congjie Fu, Guiqiu Song","doi":"10.1016/j.ress.2026.112370","DOIUrl":"10.1016/j.ress.2026.112370","url":null,"abstract":"<div><div>Deep transfer learning enables the transfer of knowledge learned from a source domain to a target domain, thereby alleviating the few-shot problem in remaining useful life (RUL) prediction tasks. However, due to differences in operating conditions and working scenarios, a significant domain shift commonly exists between the source and target domains. Existing cross-domain transfer learning still faces the following challenges: difficulties in cross-domain subsequence alignment, insufficient robustness under few-shot conditions, and limited interpretability of model decisions, which collectively degrade the stability and reliability of prediction results. To address these issues, this paper proposes a RUL transfer prediction method based on cross-domain subsequence alignment and feature contribution interpretation to optimize the cross-domain transfer process. First, a multi-scale subsequence alignment strategy is developed to select the most informative source domain subsequences, thereby reducing the risk of negative transfer. Second, an interpretable cross-domain transfer learning model is constructed by embedding a self-attention mechanism and a Bayesian linear layer into the domain adaptation framework, which enhances robustness in cross-domain prediction and mitigates overfitting under few-shot conditions in the target domain. Finally, a lightweight analysis method for identifying critical time steps and feature contributions is established to further improve the interpretability of the decision-making process. Experimental results on the IEEE PHM 2012 bearing dataset and the XJTU-SY bearing dataset demonstrate the effectiveness of the proposed method, achieving an RMSE of 0.06, an MAE of 0.05, and an R² of 0.96.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112370"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174767","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

An advanced petri-net modelling approach for risk asset management of reinforced concrete ageing transportation infrastructure under climate change effects 气候变化影响下钢筋混凝土老化交通基础设施风险资产管理的先进petri-net建模方法

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-01-21 DOI: 10.1016/j.ress.2026.112253

F. Pugliese , D.R. Prescott , J. Andrews , G. Calvert

{"title":"An advanced petri-net modelling approach for risk asset management of reinforced concrete ageing transportation infrastructure under climate change effects","authors":"F. Pugliese , D.R. Prescott , J. Andrews , G. Calvert","doi":"10.1016/j.ress.2026.112253","DOIUrl":"10.1016/j.ress.2026.112253","url":null,"abstract":"<div><div>This paper presents an advanced Petri Net (PN) modelling framework for the risk-based management of ageing reinforced concrete (RC) transportation infrastructure under climate change. The proposed framework introduces a modular PN architecture that decomposes infrastructure systems into interconnected submodules encompassing deterioration mechanisms, inspection policies, and maintenance strategies. These submodules are integrated into component, system and network-level PN modules, enabling holistic simulation and optimisation of asset-level decisions. A probabilistic degradation process is embedded within each submodule, incorporating climate-dependent parameters and allowing seamless integration of regional/national climate projections. Additionally, a multivariate statistical formulation is employed to capture interdependencies between component deterioration rates, enabling system-level reliability assessment.</div><div>To demonstrate the framework’s application, the model is implemented for a case-study RC bridge using the UKCP18 climate projection dataset, which includes 28 distinct climate scenarios. Monte Carlo simulations are conducted for three environmental trajectories: baseline ageing, expected and pessimistic climate change. Results indicate that climate change accelerates corrosion-induced deterioration, highlighting the need for adaptive inspection and maintenance strategies.</div><div>The proposed PN framework provides a generalised, data-driven tool for long-term infrastructure durability and life-cycle risk management under uncertainty.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112253"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174834","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 review of hospital seismic resilience enhancement strategies and technologies: State of the art, challenges, and future 医院增强地震恢复力的策略和技术综述：现状、挑战和未来

IF 11 1区工程技术

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-01-24 DOI: 10.1016/j.ress.2026.112285

Jin Liu , Zhuoru Song , Changhai Zhai , Junnan Ding

{"title":"A review of hospital seismic resilience enhancement strategies and technologies: State of the art, challenges, and future","authors":"Jin Liu , Zhuoru Song , Changhai Zhai , Junnan Ding","doi":"10.1016/j.ress.2026.112285","DOIUrl":"10.1016/j.ress.2026.112285","url":null,"abstract":"<div><div>Hospitals, as the backbone of post-earthquake emergency response systems, exhibit functional complexity and critical importance far beyond that of typical buildings and must demonstrate superior operational continuity and reliability. While developing resilient cities has become a strategic imperative for societal stability and sustainable development, and preliminary frameworks for assessing hospital seismic resilience have been proposed, there is still a lack of clearly defined, scientifically grounded technical pathways for enhancing hospital seismic resilience. This study summarizes the functional characteristics, seismic damage, and function quantification of hospital buildings, reviews past research on seismic retrofit technologies applied in hospital buildings, and proposes an enhancement-oriented framework integrating structural, nonstructural, and organizational strategies. The functions of hospitals are categorized as physical dimension, clinical dimension, and organizational dimension in this paper. Based on the concept of seismic resilience, hospital seismic resilience enhancement should consider the comprehensive demands of “resource-service-management” and integrates mechanism-based technology selection, rapid prediction models, multi-objective optimization balancing cost-effectiveness and operational functionality, and adaptive management strategies. This study advances the field from passive assessment toward proactive enhancement, bridging the information and coordination gaps among governments, users, and practitioners, and providing a technically actionable foundation for future hospital seismic resilience research and application.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"273 ","pages":"Article 112285"},"PeriodicalIF":11.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146174838","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