Pub Date : 2025-09-27DOI: 10.1016/j.jnlssr.2025.100266
Zeng Long , Cong Su , Chang Liu , Fazheng Chong , Fan Tong , Fengju Shang , Jiaqing Zhang , Jiansong Wu
The cross-floor spread of fire smoke in a two-story building hinders personal evacuation and leads to casualties. To address this issue, sufficient wind pressure needs to be applied at the stair to prevent smoke from entering the upper space, and the critical velocity is an important parameter worthy of attention. By conducting a series of model experiments and numerical simulations in this study, the critical velocity below the ceiling screen at the stair is investigated, considering the factors of heat release rate (HRR), fire source location, ceiling screen depth and number of stairs. The results show that the critical velocity is proportional to one-third of the HRR, and the proportional coefficient decreases as the fire source is farther from the stair and the ceiling screen depth increases. The prediction models for the critical velocity under fire sources located in front and back of the stairs are proposed, respectively, and the proposed model is validated under three stairs. Additionally, the proposed prediction model is compared with the velocity value required by the relevant standard, and some dangerous situations are identified that require further strengthened ventilation. This study can provide theoretical guidance for ventilation design and emergency response in actual engineering with similar structures.
{"title":"Predicting models for critical velocity at the stair entrance under a two-story building fire","authors":"Zeng Long , Cong Su , Chang Liu , Fazheng Chong , Fan Tong , Fengju Shang , Jiaqing Zhang , Jiansong Wu","doi":"10.1016/j.jnlssr.2025.100266","DOIUrl":"10.1016/j.jnlssr.2025.100266","url":null,"abstract":"<div><div>The cross-floor spread of fire smoke in a two-story building hinders personal evacuation and leads to casualties. To address this issue, sufficient wind pressure needs to be applied at the stair to prevent smoke from entering the upper space, and the critical velocity is an important parameter worthy of attention. By conducting a series of model experiments and numerical simulations in this study, the critical velocity below the ceiling screen at the stair is investigated, considering the factors of heat release rate (HRR), fire source location, ceiling screen depth and number of stairs. The results show that the critical velocity is proportional to one-third of the HRR, and the proportional coefficient decreases as the fire source is farther from the stair and the ceiling screen depth increases. The prediction models for the critical velocity under fire sources located in front and back of the stairs are proposed, respectively, and the proposed model is validated under three stairs. Additionally, the proposed prediction model is compared with the velocity value required by the relevant standard, and some dangerous situations are identified that require further strengthened ventilation. This study can provide theoretical guidance for ventilation design and emergency response in actual engineering with similar structures.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 2","pages":"Article 100266"},"PeriodicalIF":3.4,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145326926","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}
Pub Date : 2025-09-11DOI: 10.1016/j.jnlssr.2025.100265
Qian Yang, Feiyue Wang, Zihuan Wang, Bo Ma, Jiajie Lu, Leiwei Li
After a disaster, due to transportation constraints, transportation priority setting, emergency resource shortage and imprecise assessment of emergency resources, it is easy to cause an inaccurate match between the types of supply and demand for emergency resources. It aggravates the psychological pain of the victims. To address this gap, combining descriptive analysis, correlation analysis, and regression analysis, the mechanisms and internal pathways of imprecise emergency material supply-demand type on psychological pain were comprehensively examined. Based on Maslow's hierarchy of needs theory, four priority levels for emergency material types are proposed. A survey questionnaire was designed using the Numerical Rating Scale (NRS), which included 12 scenarios. Nine typical waterlogging sites in Changsha, Hunan Province, China, were selected as field survey sites, and 162 valid samples were collected through face-to-face interviews. The results show that: (1) Emergency material types have a significant impact on psychological pain, and this impact is related to the priority level of the material types. (2) The impact of the matching degree of emergency material supply-demand types on psychological pain is moderated by the priority level of the demanded material types, exhibiting a reverse compensation effect. (3) The impact of demographic factors on the degree of psychological pain experienced by victims shows complex differences. Most surprisingly, the higher the monthly income is, the more difficult it is to accept the inaccurate supply-demand of emergency supplies. Because high-income people have higher expectations for quality of life, their psychological pain is more obvious.
{"title":"The impact of inaccurate supply-demand types for emergency supplies on the psychological pain of victims: Data from flood disasters in China","authors":"Qian Yang, Feiyue Wang, Zihuan Wang, Bo Ma, Jiajie Lu, Leiwei Li","doi":"10.1016/j.jnlssr.2025.100265","DOIUrl":"10.1016/j.jnlssr.2025.100265","url":null,"abstract":"<div><div>After a disaster, due to transportation constraints, transportation priority setting, emergency resource shortage and imprecise assessment of emergency resources, it is easy to cause an inaccurate match between the types of supply and demand for emergency resources. It aggravates the psychological pain of the victims. To address this gap, combining descriptive analysis, correlation analysis, and regression analysis, the mechanisms and internal pathways of imprecise emergency material supply-demand type on psychological pain were comprehensively examined. Based on Maslow's hierarchy of needs theory, four priority levels for emergency material types are proposed. A survey questionnaire was designed using the Numerical Rating Scale (NRS), which included 12 scenarios. Nine typical waterlogging sites in Changsha, Hunan Province, China, were selected as field survey sites, and 162 valid samples were collected through face-to-face interviews. The results show that: (1) Emergency material types have a significant impact on psychological pain, and this impact is related to the priority level of the material types. (2) The impact of the matching degree of emergency material supply-demand types on psychological pain is moderated by the priority level of the demanded material types, exhibiting a reverse compensation effect. (3) The impact of demographic factors on the degree of psychological pain experienced by victims shows complex differences. Most surprisingly, the higher the monthly income is, the more difficult it is to accept the inaccurate supply-demand of emergency supplies. Because high-income people have higher expectations for quality of life, their psychological pain is more obvious.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 2","pages":"Article 100265"},"PeriodicalIF":3.4,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789664","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}
Pub Date : 2025-09-06DOI: 10.1016/j.jnlssr.2025.100252
Ao Zheng , Rui Ba , Wenyu Jiang , Zijun Chen , Menghao He , Yuansheng Hua , Song Zhu , Jiasong Zhu , Guochao Liu , Zhuojie Zhu , Xinyi Han
Wildfire prevention and control, especially within complex Wildland-Urban Interface (WUI), face escalating challenges due to the synergistic impacts of climate change and expanding urban frontiers. While advanced wildfire spread prediction models are essential for developing disaster-resilient emergency systems, the increasing complexities of WUI wildfire scenarios highlight critical limitations in current modeling approaches. These complexities include the dynamic interactions between vegetation and built environments, the demands of multi-scale spatiotemporal forecasting, and the challenges of cross-platform integration. To better understand and address these challenges, this paper establishes a novel tripartite analytical framework through a systematic review of peer-reviewed studies from the Scopus and Web of Science databases: (1) fire combustion characterization, (2) fire dynamics mechanism, and (3) fire management system. Our critical analysis identifies three persistent research challenges, including modeling fire behaviors in heterogeneous WUI scenarios; balancing fire dynamics with computational speed, accuracy, and resolution; and managing and applying models in highly integrated systems. This study concludes with actionable priorities for subsequent research, providing methodological guidelines for model developers and evidence-based integration pathways for emergency management systems, particularly in addressing critical infrastructure protection in rapidly urbanizing, fire-prone regions.
由于气候变化和城市边界扩大的协同影响,野火防控,特别是复杂的野火-城市界面(WUI)的野火防控面临着日益严峻的挑战。虽然先进的野火蔓延预测模型对于开发抗灾应急系统至关重要,但WUI野火场景的日益复杂性突出了当前建模方法的关键局限性。这些复杂性包括植被与建筑环境之间的动态相互作用、多尺度时空预测的需求以及跨平台集成的挑战。为了更好地理解和应对这些挑战,本文通过系统回顾来自Scopus和Web of Science数据库的同行评议研究,建立了一个新的三方分析框架:(1)火灾燃烧特性,(2)火灾动力学机制,(3)火灾管理系统。我们的批判性分析确定了三个持续存在的研究挑战,包括在异构WUI场景中模拟火灾行为;平衡火动力学与计算速度,准确性和分辨率;以及在高度集成的系统中管理和应用模型。本研究总结了后续研究的可操作优先事项,为模型开发者提供了方法指南,并为应急管理系统提供了基于证据的整合途径,特别是在快速城市化、火灾易发地区解决关键基础设施保护问题。
{"title":"Intelligent fire modeling in wildland-urban interface: A comprehensive review of current progress, challenges, and future perspectives","authors":"Ao Zheng , Rui Ba , Wenyu Jiang , Zijun Chen , Menghao He , Yuansheng Hua , Song Zhu , Jiasong Zhu , Guochao Liu , Zhuojie Zhu , Xinyi Han","doi":"10.1016/j.jnlssr.2025.100252","DOIUrl":"10.1016/j.jnlssr.2025.100252","url":null,"abstract":"<div><div>Wildfire prevention and control, especially within complex Wildland-Urban Interface (WUI), face escalating challenges due to the synergistic impacts of climate change and expanding urban frontiers. While advanced wildfire spread prediction models are essential for developing disaster-resilient emergency systems, the increasing complexities of WUI wildfire scenarios highlight critical limitations in current modeling approaches. These complexities include the dynamic interactions between vegetation and built environments, the demands of multi-scale spatiotemporal forecasting, and the challenges of cross-platform integration. To better understand and address these challenges, this paper establishes a novel tripartite analytical framework through a systematic review of peer-reviewed studies from the Scopus and Web of Science databases: (1) fire combustion characterization, (2) fire dynamics mechanism, and (3) fire management system. Our critical analysis identifies three persistent research challenges, including modeling fire behaviors in heterogeneous WUI scenarios; balancing fire dynamics with computational speed, accuracy, and resolution; and managing and applying models in highly integrated systems. This study concludes with actionable priorities for subsequent research, providing methodological guidelines for model developers and evidence-based integration pathways for emergency management systems, particularly in addressing critical infrastructure protection in rapidly urbanizing, fire-prone regions.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 2","pages":"Article 100252"},"PeriodicalIF":3.4,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789662","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}
Pub Date : 2025-09-06DOI: 10.1016/j.jnlssr.2025.100255
Tong Xu , Xiaole Dai , Kai Wang , Fazheng Chong , Fengju Shang , Chang Liu
A series of experiments was conducted to explore the influence of cable spacing on combustion characteristics in real cable installation, considering various external radiation intensities (30, 50 kW/m2) and cable spacings (0, 2.5, 5 cm). A comparative analysis of the combustion characteristics (such as heat release rate (HRR), combustion gas, and mass loss) was conducted, and the HRR calculation for cables that were not fully filled in the sample tray was revised as well. It could be found that with the increasing radiation intensities, the peak concentrations of CO and CO₂ increased (O₂ concentration decreased), and the interval between the two peaks shortened. The HRR curves of cables with different spacings all presented two peaks under two radiation intensities. The max-peak HRR occurs at Dd = 2.5 cm, and the double max-peak HRRs are 582 kW/m2 and 407 kW/m2 under radiation intensities of 50 kW/m2 and 35 kW/m2, respectively. This is because when Dd = 0 cm, the thermal feedback effect between cables is relatively enhanced, while the air entrainment between the cables is weakened. When Dd = 5 cm, the thermal feedback effect is weakened. When Dd = 2.5 cm, both the air entrainment and the thermal feedback are strengthened, and the peak HRR occurs. The above results could provide data to support fire safety design and the emergency response to cable laying.
{"title":"Study on combustion characteristics of cables with spacing arrangement under different external radiation conditions","authors":"Tong Xu , Xiaole Dai , Kai Wang , Fazheng Chong , Fengju Shang , Chang Liu","doi":"10.1016/j.jnlssr.2025.100255","DOIUrl":"10.1016/j.jnlssr.2025.100255","url":null,"abstract":"<div><div>A series of experiments was conducted to explore the influence of cable spacing on combustion characteristics in real cable installation, considering various external radiation intensities (30, 50 kW/m<sup>2</sup>) and cable spacings (0, 2.5, 5 cm). A comparative analysis of the combustion characteristics (such as heat release rate (HRR), combustion gas, and mass loss) was conducted, and the HRR calculation for cables that were not fully filled in the sample tray was revised as well. It could be found that with the increasing radiation intensities, the peak concentrations of CO and CO₂ increased (O₂ concentration decreased), and the interval between the two peaks shortened. The HRR curves of cables with different spacings all presented two peaks under two radiation intensities. The max-peak HRR occurs at <em>D<sub>d</sub></em> = 2.5 cm, and the double max-peak HRRs are 582 kW/m<sup>2</sup> and 407 kW/m<sup>2</sup> under radiation intensities of 50 kW/m<sup>2</sup> and 35 kW/m<sup>2</sup>, respectively. This is because when <em>D<sub>d</sub></em> = 0 cm, the thermal feedback effect between cables is relatively enhanced, while the air entrainment between the cables is weakened. When <em>D<sub>d</sub></em> = 5 cm, the thermal feedback effect is weakened. When <em>D<sub>d</sub></em> = 2.5 cm, both the air entrainment and the thermal feedback are strengthened, and the peak HRR occurs. The above results could provide data to support fire safety design and the emergency response to cable laying.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 2","pages":"Article 100255"},"PeriodicalIF":3.4,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145789663","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}
Pub Date : 2025-09-05DOI: 10.1016/j.jnlssr.2025.100254
Jingshuo Yu , Qian Chen
The urgent need for advanced fire detection methods stems from the increased intensity of fire incidents, which cause massive property loss and irreversible damage. To overcome the limitations of traditional fire detection methods, such as those of smoke detectors, fire detection based on computer vision (CV) algorithms has been adopted to improve detection accuracy. Compared to single-modal fire detection, multi-modal fire detection has gained attention because it leverages the richer information present in both RGB and thermal images. However, prevalent multi-modal fire detection methods significantly increase model complexity by requiring two separate streams in the backbone to process RGB and thermal images independently. To address this issue, this paper proposes a four-channel single-stream fire detection method based on YOLOv5, which concatenates RGB and thermal images to form the required four-channel input. Comparison experiments with dual-stream YOLOv5 models using add fusion and transformer fusion demonstrate that the four-channel single-stream model reduces model complexity while improving detection accuracy. To further enhance detection accuracy and reduce model complexity, this study redesigned YOLOv5’s C3 module by integrating the convolutional block attention module (CBAM) to form the C3CBAM module and introduced the SCYLLA-Intersection over Union (SIoU) loss function. By comparing its performance with that of state-of-the-art (SOTA) models in multi-modal object detection, such as the YOLOv5-based dual-stream model, this study shows that the proposed approach improves detection in the diverse conditions presented in the selected dataset.
由于火灾事故的频繁发生,造成了巨大的财产损失和不可逆转的损失,迫切需要先进的火灾探测方法。为了克服传统火灾探测方法(如烟雾探测器)的局限性,采用基于计算机视觉(CV)算法的火灾探测来提高探测精度。与单模态火灾探测相比,多模态火灾探测受到了人们的关注,因为它利用了RGB和热图像中更丰富的信息。然而,流行的多模态火灾探测方法需要在主干中两个独立的流来独立处理RGB和热图像,从而显著增加了模型的复杂性。针对这一问题,本文提出了一种基于YOLOv5的四通道单流火灾检测方法,该方法将RGB图像和热图像拼接成所需的四通道输入。采用添加融合和变压器融合的双流YOLOv5模型对比实验表明,四通道单流模型在降低模型复杂度的同时提高了检测精度。为了进一步提高检测精度,降低模型复杂度,本研究对YOLOv5的C3模块进行了重新设计,将卷积块注意模块(CBAM)集成为C3CBAM模块,并引入了SCYLLA-Intersection over Union (SIoU)损失函数。通过将该方法与基于yolov5的双流模型等最先进的SOTA模型在多模态目标检测中的性能进行比较,本研究表明,该方法可以提高所选数据集中不同条件下的检测效果。
{"title":"A lightweight four-channel multi-modal model to improve computational performance of automated fire detection","authors":"Jingshuo Yu , Qian Chen","doi":"10.1016/j.jnlssr.2025.100254","DOIUrl":"10.1016/j.jnlssr.2025.100254","url":null,"abstract":"<div><div>The urgent need for advanced fire detection methods stems from the increased intensity of fire incidents, which cause massive property loss and irreversible damage. To overcome the limitations of traditional fire detection methods, such as those of smoke detectors, fire detection based on computer vision (CV) algorithms has been adopted to improve detection accuracy. Compared to single-modal fire detection, multi-modal fire detection has gained attention because it leverages the richer information present in both RGB and thermal images. However, prevalent multi-modal fire detection methods significantly increase model complexity by requiring two separate streams in the backbone to process RGB and thermal images independently. To address this issue, this paper proposes a four-channel single-stream fire detection method based on YOLOv5, which concatenates RGB and thermal images to form the required four-channel input. Comparison experiments with dual-stream YOLOv5 models using add fusion and transformer fusion demonstrate that the four-channel single-stream model reduces model complexity while improving detection accuracy. To further enhance detection accuracy and reduce model complexity, this study redesigned YOLOv5’s C3 module by integrating the convolutional block attention module (CBAM) to form the C3CBAM module and introduced the SCYLLA-Intersection over Union (SIoU) loss function. By comparing its performance with that of state-of-the-art (SOTA) models in multi-modal object detection, such as the YOLOv5-based dual-stream model, this study shows that the proposed approach improves detection in the diverse conditions presented in the selected dataset.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 2","pages":"Article 100254"},"PeriodicalIF":3.4,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736496","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}
Pub Date : 2025-09-04DOI: 10.1016/j.jnlssr.2025.100253
Lin Zhang , Qichen Wang , Yanjun Guo , Xiangliang Tian , Lin Qi
This study proposes an emergency rescue collaboration knowledge graph construction method for urban agglomeration in earthquake disasters. Based on the collection of 22 earthquake disaster emergency plans published on the official websites of multiple cities in the Chengdu-Chongqing urban agglomeration in China, earthquake disaster emergency rescue data from the Red Cross Society of Sichuan Province and Chongqing City, and historical rescue information from the China Blue Sky rescue team, this study defines and extracts six types of entities including rescue entities, policy documents, rescue actions, rescue information, rescue supplies, and emergency response levels. A knowledge graph pattern layer is established using a hybrid approach of top-down and bottom-up, including concept layer, relationship layer, rule layer, and instance layer. This study extracts earthquake disaster emergency rescue collaboration knowledge information from collected data sources, and YEDDA software is used for knowledge fusion, thus constructing a knowledge graph data layer. The data is stored in the Neo4j graph database as triplets (entity-relation-entity). Visual representation and retrieval are used to achieve the query, association, and inference of emergency rescue collaboration information for urban agglomeration in earthquake disasters. The 2022 Luding earthquake disaster in Ganzi Tibetan Autonomous Prefecture, China is selected as a typical case, and verified the effectiveness and reliability by inputting the case into the emergency rescue collaboration knowledge graph which was constructed in this study. The results indicate that the constructed knowledge graph provides intelligent decision support for earthquake disaster emergency rescue collaboration in urban agglomeration, effectively improves the performance of earthquake disaster emergency rescue, and provides new ideas and methods for earthquake disaster rescue and reduction.
{"title":"Construction and application of knowledge graph for urban agglomeration emergency rescue collaboration in earthquake disasters","authors":"Lin Zhang , Qichen Wang , Yanjun Guo , Xiangliang Tian , Lin Qi","doi":"10.1016/j.jnlssr.2025.100253","DOIUrl":"10.1016/j.jnlssr.2025.100253","url":null,"abstract":"<div><div>This study proposes an emergency rescue collaboration knowledge graph construction method for urban agglomeration in earthquake disasters. Based on the collection of 22 earthquake disaster emergency plans published on the official websites of multiple cities in the Chengdu-Chongqing urban agglomeration in China, earthquake disaster emergency rescue data from the Red Cross Society of Sichuan Province and Chongqing City, and historical rescue information from the China Blue Sky rescue team, this study defines and extracts six types of entities including rescue entities, policy documents, rescue actions, rescue information, rescue supplies, and emergency response levels. A knowledge graph pattern layer is established using a hybrid approach of top-down and bottom-up, including concept layer, relationship layer, rule layer, and instance layer. This study extracts earthquake disaster emergency rescue collaboration knowledge information from collected data sources, and YEDDA software is used for knowledge fusion, thus constructing a knowledge graph data layer. The data is stored in the Neo4j graph database as triplets (entity-relation-entity). Visual representation and retrieval are used to achieve the query, association, and inference of emergency rescue collaboration information for urban agglomeration in earthquake disasters. The 2022 Luding earthquake disaster in Ganzi Tibetan Autonomous Prefecture, China is selected as a typical case, and verified the effectiveness and reliability by inputting the case into the emergency rescue collaboration knowledge graph which was constructed in this study. The results indicate that the constructed knowledge graph provides intelligent decision support for earthquake disaster emergency rescue collaboration in urban agglomeration, effectively improves the performance of earthquake disaster emergency rescue, and provides new ideas and methods for earthquake disaster rescue and reduction.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 1","pages":"Article 100253"},"PeriodicalIF":3.4,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145362247","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}
Pub Date : 2025-09-02DOI: 10.1016/j.jnlssr.2025.100251
Wencong Ye , Jinjiang Wang , Zhenqiang Wei , Zheng Wang , Laibin Zhang
The growing imperative for safe and intelligent operation of long-distance oil and gas pipeline systems has led to increased deployment of interlock systems at processing stations, but their reliability and compliance are difficult to guarantee. To achieve process hazard analysis (PHA) and safety integrity level (SIL) assessment in complex hazardous scenarios of oil and gas stations, this paper presents a safety instrumented system (SIS) SIL assessment method based on a combination of system theory, process analysis and the Bow-tie model (STPA-Bow-tie). First, the boundary of the station process system is determined, and unsafe control actions (UCAs) and their key causes are identified based on the hierarchical control structure model of the oil and gas stations. Then, the element mapping relationship among STPA, layers of protection analysis (LOPA), and Bow-tie is proposed, and the Bow-tie model based on Simulink is constructed to realize LOPA, so as to quantify the required risk reduction factor (RRF) and determine the target SIL level of the safety instrument function (SIF). Finally, a Markov model verifies the safety integrity of the interlock circuit. Taking the SIL assessment of an SIS system in a certain oil transfer station as an example, the proposed method demonstrates equivalent SIL determination accuracy to the traditional HAZOP-LOPA method while providing 24 % higher analytical precision and superior visualization of multi-cause/consequence coupling in complex hazard scenarios.
{"title":"SIL assessment of safety instrumented systems in oil and gas stations based on STPA-Bow-tie","authors":"Wencong Ye , Jinjiang Wang , Zhenqiang Wei , Zheng Wang , Laibin Zhang","doi":"10.1016/j.jnlssr.2025.100251","DOIUrl":"10.1016/j.jnlssr.2025.100251","url":null,"abstract":"<div><div>The growing imperative for safe and intelligent operation of long-distance oil and gas pipeline systems has led to increased deployment of interlock systems at processing stations, but their reliability and compliance are difficult to guarantee. To achieve process hazard analysis (PHA) and safety integrity level (SIL) assessment in complex hazardous scenarios of oil and gas stations, this paper presents a safety instrumented system (SIS) SIL assessment method based on a combination of system theory, process analysis and the Bow-tie model (STPA-Bow-tie). First, the boundary of the station process system is determined, and unsafe control actions (UCAs) and their key causes are identified based on the hierarchical control structure model of the oil and gas stations. Then, the element mapping relationship among STPA, layers of protection analysis (LOPA), and Bow-tie is proposed, and the Bow-tie model based on Simulink is constructed to realize LOPA, so as to quantify the required risk reduction factor (RRF) and determine the target SIL level of the safety instrument function (SIF). Finally, a Markov model verifies the safety integrity of the interlock circuit. Taking the SIL assessment of an SIS system in a certain oil transfer station as an example, the proposed method demonstrates equivalent SIL determination accuracy to the traditional HAZOP-LOPA method while providing 24 % higher analytical precision and superior visualization of multi-cause/consequence coupling in complex hazard scenarios.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 2","pages":"Article 100251"},"PeriodicalIF":3.4,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145520269","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}
Machine learning (ML) drives progress in occupational accident prevention across diverse sectors. However, significant challenges persist in aligning these tools with practical safety needs, including accurate risk assessment, incident prediction, and targeted prevention strategies. While prior reviews focused narrowly on specific industries or data types, this study presents a comprehensive analysis of ML models in accident analysis, categorizing them by accident type, industry application, and modeling methodology. This study addresses critical challenges in ML model development—such as data quality, hyperparameter tuning, and managing class imbalances—and examines less-discussed topics, including explanatory variable selection and strategies for mitigating overfitting. This review thoroughly assesses the current state of ML-based accident prediction, highlighting critical gaps, methodological limitations, and potential research directions. By analyzing 504 studies across three perspectives—Accident Type, Industry Application, and Modeling Methodology—this review identifies pressing challenges, including (1) limitations in data quality and availability, especially for real-time sources; (2) inadequate model interpretability across applications; (3) difficulties in handling imbalanced accident datasets; and (4) the lack of an integrated framework for incorporating proactive data and industry-specific risk factors. The findings outline a roadmap for advancing ML in occupational safety by enhancing model robustness, improving interpretability, and expanding data sources. This review aims to better align ML applications with safety objectives, promoting data-driven approaches for effective accident analysis and prevention across industries.
{"title":"Machine learning for occupational accident analysis: Applications, challenges, and future directions","authors":"Izuchukwu Chukwuma Obasi, Pericles Cheng, Cleo Varianou-Mikellidou, Christos Dimopoulos, Georgios Boustras","doi":"10.1016/j.jnlssr.2025.100250","DOIUrl":"10.1016/j.jnlssr.2025.100250","url":null,"abstract":"<div><div>Machine learning (ML) drives progress in occupational accident prevention across diverse sectors. However, significant challenges persist in aligning these tools with practical safety needs, including accurate risk assessment, incident prediction, and targeted prevention strategies. While prior reviews focused narrowly on specific industries or data types, this study presents a comprehensive analysis of ML models in accident analysis, categorizing them by accident type, industry application, and modeling methodology. This study addresses critical challenges in ML model development—such as data quality, hyperparameter tuning, and managing class imbalances—and examines less-discussed topics, including explanatory variable selection and strategies for mitigating overfitting. This review thoroughly assesses the current state of ML-based accident prediction, highlighting critical gaps, methodological limitations, and potential research directions. By analyzing 504 studies across three perspectives—Accident Type, Industry Application, and Modeling Methodology—this review identifies pressing challenges, including (1) limitations in data quality and availability, especially for real-time sources; (2) inadequate model interpretability across applications; (3) difficulties in handling imbalanced accident datasets; and (4) the lack of an integrated framework for incorporating proactive data and industry-specific risk factors. The findings outline a roadmap for advancing ML in occupational safety by enhancing model robustness, improving interpretability, and expanding data sources. This review aims to better align ML applications with safety objectives, promoting data-driven approaches for effective accident analysis and prevention across industries.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 1","pages":"Article 100250"},"PeriodicalIF":3.4,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048450","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}
Pub Date : 2025-08-24DOI: 10.1016/j.jnlssr.2025.100249
Elizabeth Amorkor Okine , Esmaeil Zarei , Brian J. Roggow , Naser Dehghan
Despite the multitude of research endeavors dedicated to Human Factors (HF) in aviation safety, a comprehensive review remains conspicuously scarce. Accordingly, this study presents the first in-depth systematic review and bibliometric analysis of the vital role played by HF in enhancing the safety and reliability of air transportation. Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline, we scrutinized the Scopus dataset spanning from 1937 to late 2023. A rigorous screening process was applied to identify relevant documents, ultimately subjecting critical analyses of 1663 documents to address four foundational research questions within HF associated with aviation safety. First, our analysis delves into the identification of key areas of emphasis that have characterized HF in the aviation industry since 1937. By tracing the trajectory of research over time, the study aims to discern the evolution of HF within the aviation context. Furthermore, an exploration of primary challenges and knowledge gaps crucial to research is highlighted, with proposed pathways for future investigations to maximize their impact on air transportation safety. Finally, the study extends its inquiry to compare the existing landscape of human reliability research within the aviation sector with that of Nuclear Power Plants (NPPs) and the Chemical Process Industry (CPI). This holistic approach to understanding HF not only contributes valuable insights into aviation safety but also contextualizes these findings within broader industrial frameworks, revealing the key gaps that exist in human reliability within the aviation industry. The outcomes of this study underscore the indispensable role of HF in establishing and advancing safer and more resilient air transportation systems.
{"title":"Evolution of human factors research in aviation safety: A systematic review and bibliometric analysis of the intellectual structure","authors":"Elizabeth Amorkor Okine , Esmaeil Zarei , Brian J. Roggow , Naser Dehghan","doi":"10.1016/j.jnlssr.2025.100249","DOIUrl":"10.1016/j.jnlssr.2025.100249","url":null,"abstract":"<div><div>Despite the multitude of research endeavors dedicated to Human Factors (HF) in aviation safety, a comprehensive review remains conspicuously scarce. Accordingly, this study presents the first in-depth systematic review and bibliometric analysis of the vital role played by HF in enhancing the safety and reliability of air transportation. Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline, we scrutinized the Scopus dataset spanning from 1937 to late 2023. A rigorous screening process was applied to identify relevant documents, ultimately subjecting critical analyses of 1663 documents to address four foundational research questions within HF associated with aviation safety. First, our analysis delves into the identification of key areas of emphasis that have characterized HF in the aviation industry since 1937. By tracing the trajectory of research over time, the study aims to discern the evolution of HF within the aviation context. Furthermore, an exploration of primary challenges and knowledge gaps crucial to research is highlighted, with proposed pathways for future investigations to maximize their impact on air transportation safety. Finally, the study extends its inquiry to compare the existing landscape of human reliability research within the aviation sector with that of Nuclear Power Plants (NPPs) and the Chemical Process Industry (CPI). This holistic approach to understanding HF not only contributes valuable insights into aviation safety but also contextualizes these findings within broader industrial frameworks, revealing the key gaps that exist in human reliability within the aviation industry. The outcomes of this study underscore the indispensable role of HF in establishing and advancing safer and more resilient air transportation systems.</div></div>","PeriodicalId":62710,"journal":{"name":"安全科学与韧性(英文)","volume":"7 1","pages":"Article 100249"},"PeriodicalIF":3.4,"publicationDate":"2025-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095496","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}
Pub Date : 2025-08-08DOI: 10.1016/j.jnlssr.2025.100247
J. Afonso-Fernandes , J. Barbosa , P. Arezes , C. Pardo-Ferreira , J.C. Rubio-Romero , M.A. Rodrigues
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.
{"title":"Assessing resilience potentials in management of occupational safety and health in hospitals: Development and validation of a tool","authors":"J. Afonso-Fernandes , J. Barbosa , P. Arezes , C. Pardo-Ferreira , J.C. Rubio-Romero , 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":"2025-08-08","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}