安全科学与韧性(英文)最新文献_第3页

Coupled effects of ammonia addition proportions and pipeline diameter on self-ignition in high-pressure hydrogen leakage 氨添加比例和管道直径对高压氢气泄漏自燃的耦合影响

IF 3.4 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-07-21 DOI: 10.1016/j.jnlssr.2025.100233

Qingzhao Li , Jialin Wu , Bo Chen , Jinghong Wang , Hongcheng Lu , Juncheng Jiang , Zhe Yang , Qiangling Duan

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.

氢的内在可燃性和爆炸性构成了严重的安全隐患。本文系统地研究了管道直径和氨添加比例对高压氢气泄漏自燃的耦合影响。利用计算流体动力学（CFD）技术，结合大涡流模拟（LES）和涡流耗散概念（EDC）燃烧模型，分析了氨添加比例（0% ~ 15%）对管道直径（5mm、10mm和15mm）范围内冲击波传播特性和临界自燃条件的影响。利用Chemkin-Pro中的等体积零维均匀绝热反应器模型，分析了H₂和O₂的生成速率和消耗率，以及相应的基本反应动力学。主要研究结果表明，增加氨混合比可显著降低H₂和O₂的生成和消耗率，抑制初等反应强度，提高自燃阈值。值得注意的是，温和的氨共混产生的抑制效果与管道直径膨胀相当。5%的nh3混合物将5mm管道的临界释放压力从1.61 MPa降低到1.42 MPa，相当于在纯空气条件下将管道增加到15mm的抑制效果。此外，氨的加入和直径结垢之间的化学-物理协同作用机制增强了着火抑制作用。在混合15% NH₃的15 mm管道中，氢气泄漏后的先导冲击波强度比5 mm纯空气管道降低了23.18%，而点火临界释放压力增加了2.57倍。本研究阐明了氨气与管道直径在缓解高压氢气泄漏自燃中的化学物理耦合机制，为氢能输送系统的安全设计和风险评估提供了理论依据。

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引用次数: 0

A resilience evolution model of urban lifeline systems during operation based on performance state transitions 基于性能状态转换的城市生命线系统运行弹性演化模型

IF 3.4 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-07-17 DOI: 10.1016/j.jnlssr.2025.100231

Dongyue Zhao , Qian Chen , Xiaolong Zhao , Yunhe Tong , Changkun Chen , Shijie Xia

To better understand the resilience evolution dynamics of urban lifeline systems over extended operational periods, this study introduces a model inspired by the susceptible-infected-recovered (SIR) model, which is traditionally used to simulate population health transitions. By analyzing the mechanisms governing the performance state evolution of urban lifeline systems under disaster scenarios, integrating a disaster scenario model with resilience assessment methodologies, and comprehensively considering three key resilience components—resistance, recovery, and adaptability—we develop a system dynamics resilience‒reliability (SDR-R) model. A hypothetical case study is conducted to validate the model’s applicability. The results indicate that the interplay of resistance, recovery, and adaptability influences the dynamic evolution of system performance across three states: disability performance, survivability performance, and recovery performance. The model reveals a cyclical pattern in resilience enhancement, with adaptability emerging as a critical determinant. Moreover, the SDR-R model not only simulates urban lifeline performance state evolution under single disaster scenarios but also captures resilience evolution trends over long-term system operations. The case study findings reveal that resilience decreases as disaster severity intensifies, yet positive feedback from adaptability fosters resilience improvement over time. The process of resilience evolution can be divided into four distinct phases: initial impact, adaptive priming, adaptive enhancement, and threshold effect. Notably, resilience dynamics vary significantly across disaster levels. While systems exhibit high resilience under low-level disasters, resilience gradually stabilizes at a high level in medium- and high-level disaster scenarios. However, extreme disasters introduce greater fluctuations in resilience, underscoring the necessity for targeted resilience-enhancing strategies. The insights derived from this study offer methodological guidance for understanding urban lifeline resilience evolution and developing strategies to enhance system robustness.

为了更好地理解城市生命线系统在长运行周期内的弹性演化动态，本研究引入了一个受易感-感染-恢复（SIR）模型启发的模型，该模型传统上用于模拟人口健康转变。通过分析灾害情景下城市生命线系统性能状态演变的控制机制，将灾害情景模型与弹性评估方法相结合，综合考虑弹性的三个关键组成部分——抵抗、恢复和适应性，建立了系统动力学弹性可靠性模型。通过一个假设的案例研究来验证模型的适用性。结果表明，抵抗、恢复和适应性的相互作用影响了系统性能在残疾性能、生存性能和恢复性能三种状态下的动态演化。该模型揭示了弹性增强的周期性模式，适应性成为关键决定因素。此外，SDR-R模型不仅模拟了单一灾害情景下的城市生命线性能状态演变，还捕捉了长期系统运行的弹性演变趋势。案例研究结果表明，随着灾害严重程度的加剧，恢复力会下降，但适应性的积极反馈会随着时间的推移促进恢复力的提高。弹性演化过程可分为初始冲击、自适应启动、自适应增强和阈值效应四个阶段。值得注意的是，不同灾害级别的恢复力动态差异很大。虽然系统在低级别灾害情景下表现出高弹性，但在中、高级别灾害情景下，弹性逐渐稳定在高水平。然而，极端灾害使复原力出现更大波动，强调有必要制定有针对性的增强复原力战略。本研究为理解城市生命线弹性演化和制定增强系统稳健性的策略提供了方法论指导。

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引用次数: 0

Awareness analysis via Weibo social media data of major fire disasters 通过微博社交媒体数据对重大火灾的认知分析

IF 3.4 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-07-16 DOI: 10.1016/j.jnlssr.2025.100230

Xiaoyu Sun , Yifei Ding , Zhichao He , Xinyan Huang

Fire, a globally significant hazard, has a detrimental impact on lives, property, and socio-economic development. Public attention to fires is crucial for building fire safety under the current disaster-driven regulation development. This study employs Chinese social media (Sina Weibo) data to analyze several major domestic and overseas fire incidents and explore the corresponding public awareness. Case studies analyze three groups, (1) building facade fire: the 2010 Shanghai Jing’an fire and the 2017 Grenfell Tower fire of London, (2) ancient building fire: the 2014 Shangri-La fire and the 2019 Notre-Dame de Paris fire, and (3) wildland-urban interface (WUI) fire: the 1987 Daxing’anling wildfire and the 2025 Southern California wildfire. The results show that these major fires attract varying levels of attention due to factors like fire location, losses, associated social issues, and subsequent developments. Comparison between fire events in China and overseas reveals that the Chinese internet pays more attention to overseas fire events. Compared to earthquakes and floods, major fire incidents generally receive less attention due to the scale of their influence and the intensity of media coverage. Social media data and analysis also suggest that measures such as publishing articles and conducting educational activities can increase public attention to past fires and pre-disaster fire safety awareness. This work helps understand the impact of major fire incidents on social media and the public’s evolving reactions and offers practical measures and suggestions for stakeholders to improve fire safety and mitigate fire losses.

火灾是一种全球性的重大灾害，对生命、财产和社会经济发展产生不利影响。在当前灾害驱动型监管发展的背景下，公众对火灾的关注对建筑消防安全至关重要。本研究采用中国社交媒体（新浪微博）数据分析国内外几起重大火灾事件，并探讨相应的公众意识。案例研究分析了三组：(1)建筑立面火灾：2010年上海静安火灾和2017年伦敦格伦费尔大厦火灾；(2)古建筑火灾：2014年香格里拉火灾和2019年巴黎圣母院火灾；(3)林地-城市界面（WUI）火灾：1987年大兴安岭野火和2025年南加州野火。结果表明，由于火灾地点、损失、相关社会问题和后续发展等因素，这些重大火灾引起了不同程度的关注。对比中国和海外的火灾事件可以发现，中国网民对海外的火灾事件更加关注。与地震和洪水相比，重大火灾事件由于其影响的规模和媒体报道的强度，通常受到的关注较少。社交媒体数据和分析也表明，发表文章和开展教育活动等措施可以提高公众对过去火灾的关注和灾前消防安全意识。这项工作有助于了解重大火灾事件对社交媒体的影响和公众反应的演变，并为利益相关者提供切实可行的措施和建议，以提高消防安全和减少火灾损失。

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引用次数: 0

A position-aware attention model based on double-level contrastive learning for hyper-relational knowledge graph representation in emergency management 基于双层次对比学习的位置感知注意模型在应急管理中的超关联知识图表示

IF 3.4 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-07-11 DOI: 10.1016/j.jnlssr.2025.100223

Xinzhi Wang , Weijian Zhu , Jiang Kai , Xiangfeng Luo , Jianqiang Huang

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.

有效的应急管理依赖于及时的风险识别和决策，其中自然语言处理起着至关重要的作用。超关系知识图（HKG）表示将实体及其复杂关系嵌入到潜在空间中，为支持应急响应提供了坚实的基础。现有的方法要么考虑实体之间的依赖，要么考虑事实之间的依赖，导致在未考虑的级别（事实级别或实体级别）丢失交互信息。为了解决上述问题，我们提出了一种基于双层次对比学习（PDCL）的位置感知注意模型。首先，使用不同的图卷积网络构造和编码完备图和共现图，生成实体和事实的不同嵌入视图；其次，设计实体级和事实级对比目标，以自我监督的方式加强两层之间的信息交流。最后，利用各元素序数信息对应的线性变换，将位置约束整合到HKG的表示中。三个基准数据集的实验结果表明，PDCL模型优于现有的最先进的方法。特别是，MRR和Hits@1值可分别提高1.8%和3.3%。

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引用次数: 0

Selecting vehicle dispatching plan for typhoon emergency evacuation based on fault-tolerance analysis 基于容错分析的台风应急疏散车辆调度方案选择

IF 3.7 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-07-11 DOI: 10.1016/j.jnlssr.2025.01.005

Zhao-ge Liu , Xiang-yang Li

Unexpected scenarios often occur during typhoon response, which is likely to cause the failure of evacuation vehicle dispatching and other preparedness plans. To solve this problem, a vehicle dispatching plan selecting method based on fault-tolerance analysis is proposed, which considers the bounded rationality of emergency decision-makers. The method improves the capability of responding to unexpected scenarios by increasing backup resources. First, under the expected scenarios, a bi-level programming model for arranging the quantities of each type of vehicle and their routes is established, with the goal of minimizing the expected total evacuation time. A corresponding solving algorithm is designed. Second, possible unexpected scenarios are preset by integrating local and non-local historical experiences, and the scenario influences on vehicle dispatching constraints are analyzed. Third, under unexpected scenarios, a fault-tolerance plan set is established considering the failure risk of vehicle dispatching and fault-tolerant cost. The optimal plan is selected by calculating and ranking fault-tolerant rates. Finally, a case study in Shenzhen, China is provided to verify the reasonability and effectiveness of the method. The results show that the proposed method can help discover and address the ‘fault’ of vehicle dispatching plans during emergency preparedness and thus improve evacuation capabilities in emergency response. The proposed method can be used to develop evacuation vehicle dispatching planning methods with comprehensive scenario adaptability and a precisely improved capability.

在台风应对过程中，经常会出现意想不到的情况，这很可能导致疏散车辆调度和其他准备计划的失败。针对这一问题，提出了一种考虑应急决策者有限理性的基于容错分析的车辆调度方案选择方法。该方法通过增加备份资源，提高了对突发场景的响应能力。首先，在预期场景下，以期望总疏散时间最小为目标，建立了规划各类车辆数量和路径的双层规划模型。设计了相应的求解算法。其次，结合本地和非本地历史经验，预设可能出现的意外场景，分析场景对车辆调度约束的影响；第三，在突发情况下，考虑车辆调度的故障风险和容错成本，建立容错计划集。通过对容错率的计算和排序，选择最优方案。最后，以中国深圳市为例，验证了该方法的合理性和有效性。结果表明，该方法有助于发现和解决应急准备过程中车辆调度计划的“故障”，从而提高应急响应中的疏散能力。该方法可用于开发具有综合场景适应性和精确改进能力的疏散车辆调度规划方法。

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引用次数: 0

National resilience: Development and validation of a new four-dimensional model for disaster preparedness assessment 国家复原力：开发和验证用于备灾评估的新的四维模型

IF 3.4 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-07-09 DOI: 10.1016/j.jnlssr.2025.100228

Avi Zigdon , Osnat Lavenda , Eyal Lewin

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 (N = 748) and Study 2 in 2020 (N = 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 (α = 0.860), Political Trust (α = 0.783), Perceived Internal Threats (α = 0.768), and Perceived External Threats (α = 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.

本文描述的研究旨在开发并从经验上验证一个更准确和可靠的模型，用于评估国家恢复力，强调其对减少灾害风险和备灾的重要性。在以色列进行了两项大规模调查-研究1于2019年（N = 748）和研究2于2020年(N = 1198) -在COVID-19大流行的早期阶段。在探索性因子分析和验证性因子分析的基础上，编制了一份13项量表，分别对爱国主义（α = 0.860）、政治信任（α = 0.783）、感知内部威胁（α = 0.768）和感知外部威胁（α = 0.787）四个维度进行了测评。这四个因素加在一起解释了总方差的61.69%。验证性因子分析（CFA）证实，四因素结构是最佳拟合模型（GFI = 0.916; CFI = 0.867; RMSEA = 0.095），优于一因素和三因素替代模型。该模型被证明在不同的人口群体和不同的社会背景下是一致的。研究结果为评估国家复原力的社会心理维度提供了一个有效的、可扩展的工具。通过捕捉公民的情感参与、对机构的信任以及对内部和外部威胁的感知，该模型为评估一个国家的适应能力提供了一个基于证据的框架。它使政策制定者和灾害管理专家能够长期监测人口的复原力，确定社会凝聚力或机构信心方面的弱点，并制定有针对性的干预措施，以加强面对复杂和不断演变的危机的国家准备工作。

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引用次数: 0

A fuzzy multi-criteria decision framework for community isolation center site selection to enhance public health resilience 社区隔离中心选址的模糊多准则决策框架以增强公共卫生弹性

IF 3.4 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-07-05 DOI: 10.1016/j.jnlssr.2025.100227

Chawis Boonmee , Nannaphat Tanpruttianunt

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.

传染病爆发需要有效的应急准备战略，包括迅速部署社区隔离中心。然而，为这些设施选择合适的地点是一个复杂的决策问题，涉及多个标准和重大的不确定性，特别是在公众接受和基础设施准备方面。本研究提出了一个模糊多准则决策框架，以支持既提高运营效率又提高社区弹性的选址。该框架不仅将社区复原力定义为从健康冲击中恢复的能力，而且还定义为参与、支持和接受地方公共卫生干预措施的能力。该模型将模糊层次分析法与理想解相似性排序的模糊技术相结合，利用梯形模糊数更好地表达专家判断中的不确定性和社区反馈中的模糊性。一项来自泰国清迈的真实案例研究基于可达性、环境影响、社区同意和应急准备等标准对六个候选地点进行了评估。结果表明，该模型能够支持上下文敏感、透明和有弹性的公共卫生决策。这种方法提供了一种可重复的、计算效率高的决策支持工具，改善了卫生基础设施的选址，从而促进了安全科学。它强调技术和社会层面的一体化，以支持脆弱社区的应急准备和长期复原力。

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引用次数: 0

Knowledge and practice of earthquake management among apartment dwellers: A case study of Jakarta City, Indonesia 公寓居民的地震管理知识与实践：以印尼雅加达市为例

IF 3.4 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-07-04 DOI: 10.1016/j.jnlssr.2025.100225

Fatmah , Irene Sondang Fitrinitia , Sumiaty Ambran

Urban city apartments and flat dwellers face increasing threats from earthquakes, and the current understanding and implementation of earthquake risk reduction techniques in high-rise housing communities remain lacking. Therefore, this study examined the relationships between earthquake management practices and demographic characteristics, vertical housing features, earthquake management knowledge, and emergency response plans. The research employed a cross-sectional study design and included 215 participants from 14 selected apartments. The findings indicated that (1) earthquake management practices vary among individuals aged 35–54, types of dwelling units, dwelling sizes, numbers of rooms, those who have resided in an apartment for 3–5 years, emergency response plans, and knowledge regarding earthquake management (before, during, and after); (2) earthquake management knowledge levels (including mitigation and self-rescue knowledge during an earthquake) are low; (3) emergency response and earthquake management practices are insufficient; and (4) apartment dwellers with moderate knowledge levels of earthquake self-rescue are 12.2 times more likely to have moderate earthquake management practices than those without (OR = 12.2, p = 0.000). The study recommends that the National Disaster Management Authority and the Jakarta City Disaster Risk Reduction Forum collaborate with building managers to develop an annual earthquake mitigation programme to enhance knowledge levels regarding earthquake risk reduction.

城市公寓和公寓居民面临着越来越多的地震威胁，目前高层住宅社区对地震风险降低技术的理解和实施仍然缺乏。因此，本研究考察了地震管理实践与人口特征、垂直房屋特征、地震管理知识和应急响应计划之间的关系。该研究采用了横断面研究设计，包括来自14个选定公寓的215名参与者。结果表明：(1)35 ~ 54岁、住宅单元类型、住宅面积、房间数、居住年限3 ~ 5年、应急预案、地震管理知识（地震前、地震中、地震后）等方面的地震管理实践存在差异；(2)地震管理知识水平（包括地震减灾和自救知识）较低；(3)应急响应和地震管理实践不足；(4)具有中等地震自救知识水平的公寓居民具有中等地震自救知识水平的可能性是无地震自救知识水平的公寓居民的12.2倍（OR = 12.2, p = 0.000）。该研究建议国家灾害管理局和雅加达市减少灾害风险论坛与建筑物管理人员合作，制定一个年度地震减灾方案，以提高有关减少地震风险的知识水平。

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引用次数: 0

Advancing hazardous materials transport safety: Systematic insights on risks, challenges, and research gaps 推进危险材料运输安全：对风险、挑战和研究差距的系统见解

IF 3.4 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-06-28 DOI: 10.1016/j.jnlssr.2025.100226

Kamran Gholamizadeh , Chia Rostami , Esmaeil Zarei , Mohammad Yazdi , Sarbast Moslem

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.

危险材料（Hazmat）的运输对供应链至关重要，但也带来了重大的安全风险，导致严重的人类、环境和财务影响。本研究系统回顾了1970年至2022年的2078份出版物，重点关注危险物品运输安全的趋势、挑战和研究差距。通过文献计量学和系统审查方法，确定了调查的关键领域，如风险管理、安全路线和应急响应。建立了一个强有力的国际合作网络，特别强调风险管理。然而，关键的主题，如人为因素、弹性工程和安全性，被发现没有得到充分的探索。尽管在风险评估方面取得了进展，但在处理动态风险和使用真实世界数据改进模型验证方面仍然存在重要差距。此外，得出的结论是，未来的研究应在加强现有方法的同时解决这些差距。这篇综述对当前的研究现状进行了全面的分析，突出了需要进一步探索的领域，并为提高危险品运输系统的安全性和可持续性提供了有价值的见解。研究结果预计将指导未来的研究工作并为政策制定提供信息，最终有助于减少与危险物品运输相关的风险，并在这一重要部门推进更安全的做法。

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引用次数: 0

High-performance fire detection framework based on feature enhancement and multimodal fusion 基于特征增强和多模态融合的高性能火灾探测框架

IF 3.4 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

安全科学与韧性(英文)

Pub Date : 2025-06-26 DOI: 10.1016/j.jnlssr.2025.03.004

Zekun Zhou , Hongyang Zhao , Xingdong Li , Yi Liu , Tao Jiang , Jing Jin , Yanan Guo

Fire detection technology has become increasingly critical in the context of rising global fire threats and extreme weather conditions. Traditional methods rely on single-modal sensors and conventional image processing techniques and often struggle with complex environmental variations and background interference. This study proposes an innovative multimodal fire detection framework that integrates advanced deep learning techniques to address these limitations. By leveraging a comprehensive approach that combines YOLOv8-based object detection, HSV color space enhancement, completed local binary pattern (CLBP) texture analysis, and a novel dynamic feature enhancement module (DFEM), the proposed method significantly improves fire detection accuracy and robustness. This research introduces a sophisticated multimodal fusion strategy that systematically processes fire-related features across multiple domains. A key innovation is the cross-modality fusion Mamba (CMFM) module, which employs efficient channel attention (ECA) and an efficient 2D-selective scan module (E2DSM) to dynamically integrate and refine features from different modalities. Experimental validation was conducted on a dataset that we collected, which was supplemented by data collected via real-world robotic image acquisition in diverse environments, including forests, corridors, and outdoor settings. The proposed method demonstrated exceptional performance, with a precision of 96.4%, a recall of 95.7%, and an overall accuracy of 95.8%, outperforming state-of-the-art models such as VGG16, ResNet50, YOLOv5, and YOLOv8. Ablation studies further validated the contribution of each module and highlighted the framework’s robust feature enhancement and fusion capabilities.

在全球火灾威胁和极端天气条件不断上升的背景下，火灾探测技术变得越来越重要。传统的方法依赖于单模态传感器和传统的图像处理技术，并且经常与复杂的环境变化和背景干扰作斗争。本研究提出了一种创新的多模态火灾探测框架，该框架集成了先进的深度学习技术来解决这些限制。该方法将基于yolov8的目标检测、HSV色彩空间增强、完整局部二值模式（CLBP）纹理分析和新型动态特征增强模块（DFEM）相结合，显著提高了火灾检测精度和鲁棒性。本研究引入了一种复杂的多模态融合策略，系统地处理跨多个领域的火灾相关特征。一个关键的创新是跨模态融合曼巴（CMFM）模块，它采用有效的通道注意（ECA）和有效的2d选择扫描模块（E2DSM）来动态集成和细化来自不同模态的特征。我们在收集的数据集上进行了实验验证，并辅以在不同环境（包括森林、走廊和室外环境）中通过真实机器人图像采集收集的数据。该方法的准确率为96.4%，召回率为95.7%，总体准确率为95.8%，优于VGG16、ResNet50、YOLOv5和YOLOv8等最先进的模型。消融研究进一步验证了每个模块的贡献，并强调了框架强大的特征增强和融合能力。

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