Tracking the information about your manuscript
Communicate with the editorial office
Query manuscript payment status Reviewer LoginOnline Review
Online Communication with the Editorial Department Author LoginCollecting, editing, reviewing and other affairs offices
Managing manuscripts
Managing author information and external review Expert Information
Downloads
Page Views
Page visits today: 28
About the Journal
Superintended by：China North Industries Group Corporation Limited
Sponsoredy：Beijing Institute of Technology, Chinese Scoiety for Environmental Sciences, China Occupational Safety and Health Association
Edited & Published by: Editorial Department of Journal of Safety and Environment
Issues per year: 12
ISSN 1009-6094
CN 11-4537/X
Functional resonance model of ship operation safety risks based on complex networks
HU Shenping;WANG Shengjun;XI Xiuting;CHEN Yan;This study presents a methodology for modeling ship operation safety risks using a data-driven complex network approach. The process begins with an analysis of Port State Control(PSC) defect data, utilizing the Apriori algorithm to mine frequent itemsets and identify association rules among various risk factors. This step quantifies the non-linear interactive effects between system components. The support, confidence, and lift metrics derived from these rules are then synthesized to create an interaction strength matrix. This matrix serves as the adjacency matrix for developing a Functional Resonance Analysis Method(FRAM) model, which represents the ship's operational safety system as a complex network, where nodes correspond to system components and weighted edges indicate their interaction strength. A Graph Convolutional Network(GCN) is subsequently applied to learn the latent features of this network structure. By processing both the node features and the adjacency matrix, the GCN identifies key nodes with high centrality and influence, effectively restructuring the interaction network to emphasize the most critical components. Subsequently, the Depth-First Search(DFS) algorithm is employed on the refined graph to systematically trace critical risk propagation paths, simulating how initial failures can resonate and cascade through the system. The influence of each component factor is calculated based on its position and connections within these identified paths. Simulation results derived from the PSC data confirm that a ship's unsafe state arises from the coupled interaction of both internal and external factors. The model successfully identifies several critical resonance paths where risks are significantly amplified. Notably, the interaction path between the firefighting system and the ship's structural integrity emerged as a critical resonance loop, indicating that a deficiency in one can severely compromise the other and escalate overall risk. The study demonstrates the model's sensitivity, as it dynamically generates distinct risk path dependencies when provided with varying data inputs. This validates its effectiveness in simulating risk emergence in systems characterized by uncertain structural interactions.
Analysis of safety risk factor correlations in aircraft maintenance
CHEN Yonggang;LIU Taiwei;LIU Dongling;LIU Kangni;WANG Shuai;LONG Yike;DONG Qin;To thoroughly investigate the correlation between risk factors in aircraft maintenance safety information, we propose a method that integrates theme modeling with an improved Frequent Pattern Growth(FP-Growth) algorithm for correlation analysis. In this study, we analyze safety information provided by airlines, develop a custom vocabulary tailored to the aircraft maintenance industry, and utilize the Jieba package for preprocessing the text data. Additionally, we apply the Biterm Topic Model(BTM) to perform thematic clustering of the aircraft maintenance risk text. To address the issue of traditional association rule mining generating a large number of redundant rules, we employ an improved FP-Growth algorithm to filter out these redundancies and enhance the quality of the association rules. This approach facilitates the exploration of potential correlations between prominent risk issues at various locations and the influencing factors associated with different risk themes. Using the dependency syntax analysis and semantic role annotation capabilities of the Language Technology Platform(LTP), we extracted the “subject-predicate-object” knowledge triads of strongly related risk information. Additionally, we constructed a knowledge graph of the core risk factors in aircraft maintenance using the Neo4j platform. The results indicate that 14 core risks, including de-icing specifications and video record management, were identified using the Biterm Topic Model(BTM). Additionally, prominent maintenance risk issues such as work record specifications, maintenance tool management, and avionics maintenance in areas B1, B2, and B3 were revealed, along with the key influencing factors associated with each risk theme. Compared to traditional Apriori and FP-Growth algorithms, the improved FP-Growth algorithm effectively eliminates redundant association rules and enhances computational accuracy to over 0.92. Furthermore, the constructed semantic knowledge graph enables dynamic visual analysis of core aircraft service risk factors, providing efficient and accurate decision support for the risk control efforts of the aircraft maintenance management department.
Safety evaluation of special equipment for explosives and propellants using AHP-fuzzy comprehensive evaluation methodology
YANG Dehua;LUO Yunjun;YUE Chunhui;MAO Changyong;SONG Kaixu;HE Xiaojun;LENG Chunfeng;HUANG Lixiang;Currently, safety accidents are prevalent in the explosives and propellants industry, highlighting a critical need for improved work safety measures. Conducting safety assessments on specialized equipment used for explosives and propellants can significantly mitigate the risk of such accidents. To quantitatively assess the safety level of this specialized equipment, this study proposes a safety evaluation model that integrates the Analytic Hierarchy Process(AHP) with fuzzy comprehensive evaluation methods, tailored to the specific characteristics of explosives and propellants. A comprehensive scientific evaluation system is constructed to facilitate this assessment. First, a safety evaluation system for specialized equipment used in explosives and propellants was developed, based on six primary indicators: equipment structure, industrial control, equipment usage, equipment maintenance and repair, safety regulations, and fire extinguishing equipment. This system also includes 25 secondary indicators, such as the structural safety of components and their safety design. Subsequently, the AHP was employed to determine the weights for each level of indicators within this evaluation framework. The weighting of the indicators revealed that the three key factors—equipment structure, industrial control, and equipment usage—have a substantial influence on the safety evaluation of specialized equipment for explosives and propellants, accounting for 79.71% of the total weight. Notably, equipment structure alone contributed a significant 41.89%. Following this analysis, a typical piece of specialized equipment from the factory was selected as the evaluation subject for practical application. Twenty personnel from the factory, specializing in equipment, safety, processes, and operations, were invited to perform grade evaluations for each assessment index. Using the fuzzy comprehensive evaluation model, a safety assessment was conducted. The results indicated that the total score for the fuzzy comprehensive evaluation of this typical specialized equipment was Z=81.209 1, categorizing it as a good rating. However, the comprehensive score for the first-level index related to equipment structure was the lowest at 79.518, placing it in the general category. This finding suggests that further improvements and optimizations are needed regarding the equipment structure. The comprehensive score for the first-level index related to fire extinguishing equipment was the highest at 90.645, indicating that the configuration and management of the fire extinguishing equipment are excellent, aligning well with the actual situation. These research results offer valuable insights and guidance for enterprises seeking to enhance the safety management of specialized equipment used in the explosives and propellants industry.
Quantitative risk assessment for high-pressure hydrogen supply system operations
PAN Jun;HE Binbin;ZHUO Yu;CHEN Aijun;PAN Xufang;Due to the inherent safety challenges linked to hydrogen production, storage, and transportation, the incidence of hydrogen-related fires and explosions has been increasing globally in recent years. To tackle these issues, this study examines a representative high-pressure hydrogen supply system commonly utilized in refueling stations. A detailed three-dimensional layout of the station was created using FLACS software to simulate gas dispersion, flame propagation, thermal radiation attenuation, and explosion reflections in realistic scenarios. Using this model, a Quantitative Risk Assessment(QRA) was performed, analyzing 320 representative fire and explosion scenarios. The study systematically evaluates the consequences, occurrence frequencies, and risks of personnel injury associated with critical equipment under typical hydrogen leakage conditions. Results indicate that the overall system risk, when assessed against various international risk acceptance criteria, remains within acceptable limits. The highest individual fatality frequency due to thermal radiation from fire reaches 6.3×10-6 a-1, approaching but not exceeding the ISO 19880-1 limit for vulnerable offsite populations. Notably, the compressor area stands out as the most risk-concentrated zone, exhibiting thermal radiation fatality frequencies significantly higher than those in other regions. This underscores the urgent need to enhance fire separation distances, improve real-time leak detection systems, and implement inherently safe design principles. While explosion consequences can be severe—particularly in proximity to high-pressure storage units—the associated fatal overpressure frequency remains extremely low, with a maximum of 1.0×10-8 a-1, primarily due to effective station ventilation. In contrast, jet fires represent a more realistic and widespread hazard, owing to their extensive thermal radiation impact. As such, they constitute a critical focus in safety design and mitigation strategies. Overall, the 3DQRA approach demonstrates clear advantages over traditional 2D methods by accurately capturing physical realism, enabling the identification of high-risk areas, and supporting risk-informed optimization of equipment layouts. Future enhancements should prioritize improving fire control capabilities and refining the design of working environments to further minimize the potential for severe injuries.
Vulnerability assessment of security protection systems in overseas industrial parks based on combined weighting-cloud model
ZANG Na;MIAO Tianhao;To tackle the challenges related to identifying assessment indicators and hierarchical classifications, this study proposes a comprehensive evaluation methodology for assessing the vulnerability of security protection systems in overseas industrial parks along the Belt and Road. Initially, through an in-depth analysis of vulnerabilities within these overseas industrial parks and employing a dual approach that combines literature review with expert consultation, a systematic framework comprising 16 vulnerability assessment indicators is established. Subsequently, an innovative weighting strategy is developed that incorporates both subjective and objective perspectives. Subjective weights are established using the Best-Worst Method(BWM), while objective weights are derived from an enhanced Criteria Importance Through Inter-criteria Correlation(CRITIC) method. To reconcile these distinct weighting schemes and derive optimal combined weights, game theory is employed, balancing expert judgment with data-driven insights. The implementation of the framework utilizes a cloud model-based evaluation mechanism, enabling the conversion of qualitative assessments into quantitative analyses through cloud digital characteristics. Finally, a case study of the China-Belarus Industrial Park validates the practical implementation of this methodology. The calculated comprehensive cloud digital characteristics for the vulnerability of the security protection system are(0.4813, 0.0607, 0.0085). Visual interpretation of the synthesized cloud model indicates a ‘Medium' vulnerability classification, aligning closely with empirical observations and operational conditions. The results demonstrate a validated indicator system for assessing security vulnerabilities in transnational industrial parks. Conflicts between subjective and objective weighting are reconciled through the novel integration of game theory with combined weighting. The implementation of the cloud model offers an innovative solution for managing assessment uncertainties and achieving qualitative-quantitative conversions in complex evaluation scenarios. These findings empirically validate the methodology while providing theoretical frameworks and technical benchmarks for enhancing security in overseas industrial parks. Future research will aim to extend the applicability of indicators across diverse geographic contexts and optimize dynamic assessment mechanisms to address evolving security threats.
