安全科学与韧性(英文)最新文献

{"title":"Advancing hazardous materials transport safety: Systematic insights on risks, challenges, and research gaps","authors":"Kamran Gholamizadeh ,&nbsp;Chia Rostami ,&nbsp;Esmaeil Zarei ,&nbsp;Mohammad Yazdi ,&nbsp;Sarbast Moslem","doi":"10.1016/j.jnlssr.2025.100226","DOIUrl":"10.1016/j.jnlssr.2025.100226","url":null,"abstract":"<div><div>The transportation of hazardous materials (Hazmat) has been essential to supply chains but has posed significant safety risks, resulting in severe human, environmental, and financial impacts. This study systematically reviewed 2078 publications from 1970 to 2022, focusing on trends, challenges, and research gaps in Hazmat transportation safety. Through bibliometric and systematic review methodologies, key areas of investigation, such as risk management, safety routing, and emergency response, were identified. A strong international collaborative network was revealed, with significant emphasis on managing risks. However, critical topics such as human factors, resilience engineering, and security were found to be underexplored. Despite advancements in risk assessment, important gaps remained in addressing dynamic risks and improving model validation using real-world data. Furthermore, it was concluded that future research should address these gaps while enhancing existing methodologies. This review provided a comprehensive analysis of the current research landscape, highlighting areas requiring further exploration and offering valuable insights into improving the safety and sustainability of Hazmat transportation systems. The findings are expected to guide future research efforts and inform policy development, ultimately contributing to the reduction of risks associated with Hazmat transport and advancing safer practices in this essential sector.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 1","pages":"Article 100226"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guidance for estimating the blast load from vapour cloud explosions in traffic environments using the multi-energy method","authors":"Fabio Lozano ,&nbsp;Morgan Johansson ,&nbsp;Joosef Leppänen ,&nbsp;Mario Plos","doi":"10.1016/j.jnlssr.2025.100222","DOIUrl":"10.1016/j.jnlssr.2025.100222","url":null,"abstract":"<div><div>The accidental release of a flammable gas on a road can result in a vapour cloud explosion (VCE). Such VCEs generate a blast wave that propagates away from the explosion, potentially damaging nearby structures. The TNO Multi-Energy Method is commonly used for a simplified estimate of the blast load resulting from a VCE. The method characterises the severity and duration of the blast wave using a case-specific strength class and combustion energy (which the method relates to the gas volume of the equivalent blast source). However, no specific guidelines for estimating the strength class in urban roads or related settings (such as carparks) are currently available in the literature. This makes implementing the method in such scenarios challenging and imprecise. The authors’ work used computational fluid dynamics (CFD) to evaluate multiple gas explosion scenarios and proposed recommendations for determining the strength class and gas volume at the blast source. These scenarios comprised a group of vehicles engulfed by a stoichiometric propane-air cloud. It was concluded that the strength class could be reasonably estimated based on the number of vehicles in the transverse direction. Furthermore, the guidance for estimating the gas volume at the equivalent blast source was based on the critical gas volume, after which no further enhancement of overpressure was obtained. The recommendations were implemented in several scenarios and compared with corresponding CFD analyses. The results showed very good agreement for predicting impulse. Predicting overpressure was affected by the inherent asymmetry of the scenarios, although it was possible to achieve acceptable and conservative results.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 1","pages":"Article 100222"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A position-aware attention model based on double-level contrastive learning for hyper-relational knowledge graph representation in emergency management","authors":"Xinzhi Wang ,&nbsp;Weijian Zhu ,&nbsp;Jiang Kai ,&nbsp;Xiangfeng Luo ,&nbsp;Jianqiang Huang","doi":"10.1016/j.jnlssr.2025.100223","DOIUrl":"10.1016/j.jnlssr.2025.100223","url":null,"abstract":"<div><div>Effective emergency management relies on timely risk identification and decision-making, wherein natural language processing plays a vital role. Hyper-relational knowledge graph (HKG) representation, which embeds entities and their complex relations into latent space, provides a strong foundation for supporting emergency responses. Existing methods consider either inter-entity or inter-fact dependencies, leading to the loss of interaction information at the unconsidered level (fact level or entity level). To address the above issue, we propose a position-aware attention model based on dual-level contrastive learning (PDCL) for HKG representation. First, the complete and co-occurrence graphs were constructed and encoded using different graph convolutional networks, generating different embedding views for entities and facts. Second, entity-level and fact-level contrastive objectives were designed to enhance information exchange between the two levels in a self-supervised manner. Finally, a linear transformation corresponding to the ordinal information of each element was used to integrate positional constraints into the representation of the HKG. Experimental results for three benchmark datasets showed that the PDCL model outperformed existing state-of-the-art methods. Especially, MRR and Hits@1 values could be improved by up to 1.8% and 3.3%, respectively.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 1","pages":"Article 100223"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145026458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing resilience potentials in management of occupational safety and health in hospitals: Development and validation of a tool","authors":"J. Afonso-Fernandes ,&nbsp;J. Barbosa ,&nbsp;P. Arezes ,&nbsp;C. Pardo-Ferreira ,&nbsp;J.C. Rubio-Romero ,&nbsp;M.A. Rodrigues","doi":"10.1016/j.jnlssr.2025.100247","DOIUrl":"10.1016/j.jnlssr.2025.100247","url":null,"abstract":"<div><div>A resilient Occupational Safety and Health (OSH) management system is crucial for effectively addressing potential future public emergencies, ensuring the continuous protection of workers' safety and health. Therefore, it is essential for organizations, particularly hospitals, to assess their resilient performance and employ tools that are appropriate and tailored to their specific context. This study aims to enhance the understanding of resilience potentials in OSH management within hospital settings. To this end, an assessment tool was developed based on the Resilience Assessment Grid (RAG). A Delphi study involving subject matter experts was conducted to refine the tailored RAG tool. Following this, a pilot test was administered to 404 healthcare professionals across three public hospitals, with subsequent psychometric analysis. Exploratory Factor Analysis (EFA) identified a four-dimensional structure. Goodness-of-fit indices demonstrated acceptable values, confirming the adequacy of the measurement model. Reliability testing indicated that the 29 item assessment tool is both valid and reliable. The tailored RAG tool was successfully validated, enabling the identification of strengths and weaknesses in OSH management.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 1","pages":"Article 100247"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"National resilience: Development and validation of a new four-dimensional model for disaster preparedness assessment","authors":"Avi Zigdon ,&nbsp;Osnat Lavenda ,&nbsp;Eyal Lewin","doi":"10.1016/j.jnlssr.2025.100228","DOIUrl":"10.1016/j.jnlssr.2025.100228","url":null,"abstract":"<div><div>The studies described here aim to develop and empirically validate a more accurate and reliable model for assessing national resilience, emphasizing its importance for disaster risk reduction and disaster preparedness. Two large-scale surveys were conducted in Israel—Study 1 in 2019 (<em>N</em> = 748) and Study 2 in 2020 (<em>N</em> = 1198)—during the early phase of the COVID-19 pandemic. Based on exploratory and confirmatory factor analyses, a 13-item scale was developed to assess four dimensions of national resilience: Patriotism (<em>α</em> = 0.860), Political Trust (<em>α</em> = 0.783), Perceived Internal Threats (<em>α</em> = 0.768), and Perceived External Threats (<em>α</em> = 0.787). Together, these four factors explained 61.69 % of the total variance. Confirmatory factor analysis (CFA) confirmed the four-factor structure as the best-fitting model (GFI = 0.916; CFI = 0.867; RMSEA = 0.095), outperforming both the one- and three-factor alternatives. The model proved to be consistent across different demographic groups and in different social contexts. The results provide a validated and scalable tool for assessing the socio-psychological dimensions of national resilience. By capturing citizens’ emotional engagement, trust in institutions, and perceptions of internal and external threats, the model provides an evidence-based framework for assessing a nation's adaptive capacity. It enables policymakers and disaster management experts to monitor the resilience of the population over time, identify weaknesses in social cohesion or institutional confidence, and develop targeted interventions to strengthen national preparedness in the face of complex and evolving crises.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 1","pages":"Article 100228"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145018431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Skeleton-based detection of anomalous personal protective equipment doffing behaviors among healthcare workers","authors":"Qiang Zhang,&nbsp;Lixin Yang,&nbsp;Ying Qi,&nbsp;Teng Wan,&nbsp;Qiushi Li,&nbsp;Renwen Miao","doi":"10.1016/j.jnlssr.2025.100229","DOIUrl":"10.1016/j.jnlssr.2025.100229","url":null,"abstract":"<div><div>Identification of doffing behaviors of personal protective equipment (PPE) plays a crucial role in ensuring the safety of healthcare workers. With the continuous emergence of new infectious diseases, accurate detection of anomalous behaviors during PPE doffing procedures has become increasingly critical. In complex medical environments, conventional visual methods have demonstrated limited capability in accurately capturing the subtle movements involved in the multistep PPE doffing process. To address the challenges of low motion heterogeneity and minimal amplitude variations in PPE doffing procedures, this study presents a skeleton keypoint-based anomaly detection model. The proposed model innovatively integrates spatiotemporal embedding modules and adaptive attention mechanisms, allowing the precise detection of subtle changes in localized hand movements. In contrast to the limitations of conventional methods in characterizing fine-grained feature differences, this model demonstrates significantly enhanced capability in identifying anomalous PPE doffing behaviors. Extensive experimental results indicate that the model outperforms existing methods in key metrics, including precision and recall, providing novel technical support for the management of standardized PPE in medical settings.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 1","pages":"Article 100229"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coupled effects of ammonia addition proportions and pipeline diameter on self-ignition in high-pressure hydrogen leakage","authors":"Qingzhao Li ,&nbsp;Jialin Wu ,&nbsp;Bo Chen ,&nbsp;Jinghong Wang ,&nbsp;Hongcheng Lu ,&nbsp;Juncheng Jiang ,&nbsp;Zhe Yang ,&nbsp;Qiangling Duan","doi":"10.1016/j.jnlssr.2025.100233","DOIUrl":"10.1016/j.jnlssr.2025.100233","url":null,"abstract":"<div><div>Hydrogen's intrinsic flammability and explosiveness pose serious safety hazards. This study systematically investigates the coupled effects of pipe diameter and ammonia addition proportions on self-ignition during high-pressure hydrogen leaks. Utilizing computational fluid dynamics (CFD) techniques integrated with the Large Eddy Simulation (LES) and the Eddy Dissipation Concept (EDC) combustion model, the effects of ammonia addition proportions (0 %∼15 %) on shockwave propagation characteristics and critical self-ignition conditions are analyzed for a range of pipeline diameters (5 mm, 10 mm, and 15 mm). A constant volume zero-dimensional homogeneous adiabatic reactor model in Chemkin-Pro was utilized to analyze the generation and consumption rates of H₂ and O₂, together with the corresponding elementary reaction kinetics. Principal findings indicate that increasing the ammonia mixing ratio significantly reduces the generation and consumption rates of H₂ and O₂, suppresses elementary reaction intensities, and elevates the threshold for self-ignition. Notably, mild ammonia blending produces suppression effects comparable to pipeline diameter expansion. A 5 % NH₃ mixture decreases the critical release pressure for a 5 mm pipeline from 1.61 MPa to 1.42 MPa, equivalent to the suppression efficacy of increasing the pipeline to 15 mm in pure air conditions. Furthermore, the combined chemical-physical synergistic mechanism between ammonia addition and diameter scaling amplifies ignition inhibition. In a 15 mm pipeline with 15 % NH₃ blending, the intensity of the leading shockwave after hydrogen leakage decreases by 23.18 % compared to a 5 mm pure-air pipeline, while the critical release pressure for ignition increases by a factor of 2.57. This study clarifies the chemical-physical coupling mechanisms of ammonia and pipeline diameter in mitigating self-ignition caused by high-pressure hydrogen leakage, providing theoretical foundations for the safety design and risk assessment of hydrogen energy transport systems.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 1","pages":"Article 100233"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145323704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CO-Mode with AV-CRM: A novel paradigm towards human–machine collaboration in intelligent vehicle safety","authors":"Jiayi Lu ,&nbsp;Bin Sun ,&nbsp;Boao Zhang,&nbsp;Zhaowen Pang,&nbsp;Zhaoxia Peng,&nbsp;Shichun Yang,&nbsp;Yaoguang Cao","doi":"10.1016/j.jnlssr.2025.04.002","DOIUrl":"10.1016/j.jnlssr.2025.04.002","url":null,"abstract":"<div><div>With the continuous advancement in vehicle intelligence, enhancing safety has emerged as a key priority in intelligent vehicle research and development. Intelligent vehicles are currently limited in supporting autonomous or human-driven modes. This limitation becomes apparent in complex driving scenarios, where vehicle risk response capabilities are inadequate. This paper suggests that shifting from a single decision maker to a human–machine collaboration approach is a potential solution. However, current research on human–machine collaboration in intelligent vehicles primarily focuses on intelligent systems that assist the driver, rather than treating the driver and the system as equals. This approach overlooks the role of the driver in helping the system, lacks effective communication, and diminishes the sense of collaborative cooperation, all of which hinder the promotion of efficient, safe, and stable driving. Inspired by the aviation approach to risk management through Crew Resource Management (CRM), this study introduces the Collaborative Operation Mode (CO-Mode) for intelligent vehicles. Based on CO-Mode’s requirements for human–machine collaborative perception, decision making, and control, the Autonomous Vehicle Collaborative Resource Management (AV-CRM) is proposed. In addition, challenges and future perspectives are explored by analyzing the abilities and limitations of relevant technologies. The proposed AV-CRM redefines the relationship between drivers and intelligent systems, offering new insights into the safety of intelligent vehicles and their technological evolution.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 1","pages":"Article 100209"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144890529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A fuzzy multi-criteria decision framework for community isolation center site selection to enhance public health resilience","authors":"Chawis Boonmee ,&nbsp;Nannaphat Tanpruttianunt","doi":"10.1016/j.jnlssr.2025.100227","DOIUrl":"10.1016/j.jnlssr.2025.100227","url":null,"abstract":"<div><div>Infectious disease outbreaks require effective emergency preparedness strategies, including the rapid deployment of community isolation centers. However, selecting suitable locations for these facilities is a complex decision-making problem involving multiple criteria and significant uncertainty, especially regarding public acceptance and infrastructure readiness. This research proposes a fuzzy multi-criteria decision-making framework to support location selection that enhances both operational efficiency and community resilience. The framework defines community resilience not only as the ability to recover from health shocks but also as the capacity to engage with, support, and accept local public health interventions. The model integrates the fuzzy analytic hierarchy process and the fuzzy technique for order preference by similarity to the ideal solution using trapezoidal fuzzy numbers to better represent uncertainty in expert judgments and ambiguity in community feedback. A real-world case study from Chiang Mai, Thailand, evaluates six candidate sites based on criteria such as accessibility, environmental impact, community consent, and emergency readiness. The results demonstrate the model’s capacity to support context-sensitive, transparent, and resilient public health decision-making. This approach contributes to safety science by offering a reproducible and computationally efficient decision-support tool that improves the siting of health infrastructure in response to pandemics. It emphasizes the integration of technical and social dimensions to support emergency preparedness and long-term resilience in vulnerable communities.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 1","pages":"Article 100227"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving fire resistance of data monitoring equipment in wildland and wildland-urban interface fires","authors":"A.I. Filkov ,&nbsp;M. Mohamed ,&nbsp;S. Carracher ,&nbsp;J. Simkin","doi":"10.1016/j.jnlssr.2025.100224","DOIUrl":"10.1016/j.jnlssr.2025.100224","url":null,"abstract":"<div><div>The 2019–2020 Black Summer fire season highlighted the vulnerability of water monitoring sites, causing damage, data loss, and negatively affecting water management during massive wildfires. It becomes crucial to reduce the impact of wildfires on them. The current study aims to improve the fire resistance of monitoring equipment. Internal thermal insulation was designed for the instrumentation cabinets and tested under different wildfire conditions to evaluate the performance of various materials and equipment designs. The results demonstrated that the new design of the instrumentation cabinet managed to significantly reduce the effect of thermal exposure and kept the temperatures inside the cabinet below the critical threshold of 70 °C for electronics components. Recommendations of insulation and alternative designs are provided for construction in wildland and wildland-urban interface areas.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 1","pages":"Article 100224"},"PeriodicalIF":3.4,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}