Journal of Loss Prevention in The Process Industries最新文献

{"title":"Uncertainty quantification of flammable gas dispersion numerical models driven by hybrid variational inference deep learning","authors":"Weikang Xie ,&nbsp;Qing Wang ,&nbsp;Jiyuan Li ,&nbsp;Zonghao Xie ,&nbsp;Jihao Shi ,&nbsp;Xinyan Huang ,&nbsp;Asif Usmani","doi":"10.1016/j.jlp.2025.105758","DOIUrl":"10.1016/j.jlp.2025.105758","url":null,"abstract":"<div><div>Accurate modeling of flammable gas dispersion is essential for fire and explosion risk assessment. However, CFD models that rely on fixed hyperparameters preclude uncertainty quantification, leading to overconfidence prediction. This work proposed a hybrid deep learning framework with variational Bayesian inference to inversely solve distributions of numerical model parameters. The gas dispersion database under different Froude numbers <em>Fr</em> is developed, which contains repetitive experimental data and corresponding numerical simulation values. CNN-AM architecture is developed to capture nonlinear relationship between model parameters and concentration outputs. Using experimental data, ADVI is employed to derive posterior distributions of the optimal model parameters. The results indicate that the parameter-optimized model obviously improves prediction accuracy for 80 % scenarios, with overall error below 5 %. Furthermore, spatial distribution characteristics of plumes are characterized probabilistically. Near leakage nozzles, local concentration fluctuations peak when gravity and initial momentum jointly dominate plume dynamics at <em>Fr</em> = 74.38. In terms of plume morphology, variability in horizontal extent increases monotonically with <em>Fr</em>, while uncertainty in vertical drop attains a maximum at 0.060 when <em>Fr</em> = 55.79. These findings demonstrate the robustness of the proposed method for uncertainty quantification in gas distribution modelling, thereby enhancing risk evaluation in industries.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"98 ","pages":"Article 105758"},"PeriodicalIF":4.2,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144893281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of ventilation air methane explosion in regenerative thermal oxidation based on hyperparameter-optimized random forest algorithm","authors":"Jing Luo ,&nbsp;Li Wang ,&nbsp;Wei Gao ,&nbsp;Haipeng Jiang","doi":"10.1016/j.jlp.2025.105757","DOIUrl":"10.1016/j.jlp.2025.105757","url":null,"abstract":"<div><div>Regenerative Thermal Oxidation (RTO) is a key technology for utilizing Ventilation Air Methane (VAM), with safety assessments depending on accurate explosion predictions. This study develops a predictive model using a particle swarm optimization-random forest (PSO-RF) algorithm to determine whether methane will explode under various conditions in regenerative thermal oxidation. Experimental data were collected to determine the critical transition from oxidation to explosion. By integrating the ultra-lean methane oxidation kinetics model (GRTO) with Grey Relational Analysis (GRA), ambient temperature and methane concentration were identified as critical input features. The RF model's hyperparameters were optimized via the improved PSO algorithm to improve accuracy and computational efficiency. The dataset was randomly split into a training set and a testing set in a 7:3 ratio. The PSO-RF model was subsequently compared with Support Vector Machine (SVM), Decision Tree (DT), and Neural Network (NN) models. Results indicate that the PSO-RF model outperforms other models in key classification metrics on the test set, effectively predicting explosion risks under complex conditions.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"98 ","pages":"Article 105757"},"PeriodicalIF":4.2,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144865226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The bi-objective emergency system location-allocation approach based on the improved risk assessment in petrochemical industrial zone","authors":"Zixian Chen ,&nbsp;Junhao Jiang ,&nbsp;Jiahong Zhao ,&nbsp;Jianwei Peng ,&nbsp;Xiaochun Zhang","doi":"10.1016/j.jlp.2025.105759","DOIUrl":"10.1016/j.jlp.2025.105759","url":null,"abstract":"<div><div>Petrochemical industrial zones pose significant risks due to the inherent properties of their products and the potential domino effect. This paper focuses on optimizing the emergency system in the petrochemical industrial zone. An improved quantitative risk assessment method considering the domino effect following fire and explosion incidents has been proposed, utilizing the regional gridding method and Monte Carlo simulation. On this basis, a bi-objective emergency system location-allocation model was established to minimize the total cost of emergency facility construction and maximize the total risk reduction covered by emergency facilities. To address the bi-objective problem, the weighted linear combination method and the augmented ε-constraint solution technique were introduced and compared. Tests indicated that the AEC method was more competitive in obtaining the optimal solution. Moreover, the proposed model was applied to the Daya Bay petrochemical industrial zone in China to verify its effectiveness. Compared to the recommended location-allocation plan based on the traditional risk model, the proposed method increased individual risk coverage by 68.13 % and accident area coverage by 50 %, incurring only a modest increase in total cost. This paper serves as a supplement to the theory of risk assessment and management in the petrochemical industrial zone.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"98 ","pages":"Article 105759"},"PeriodicalIF":4.2,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144889888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of incident data reveals critical process safety issues and opportunities for improvement in the Indonesian oil and gas industry","authors":"Muchammad Ali Lukman ,&nbsp;Ibnu Maulana Hidayatullah ,&nbsp;Habiburrahman Zulfikri","doi":"10.1016/j.jlp.2025.105756","DOIUrl":"10.1016/j.jlp.2025.105756","url":null,"abstract":"<div><div>The present work examines the critical issue of process safety incidents in the Indonesian oil and gas sector, with the aim of improving process safety implementation and decreasing the occurrence of process safety incidents. Despite the implementation of process safety management systems, the industry remains plagued by major process safety incidents raising questions about the adequacy of existing protocols. Publicly accessible incident investigation reports were examined to identify the underlying causes of these incidents. Descriptive statistical methods were employed to pinpoint trends in process safety incident scenarios, their causes, and the correlations with different elements of process safety management systems. The findings indicate key problems associated with process safety management systems in Indonesia, notably the elements of hazard identification and risk analysis, asset integrity and reliability, and process safety culture. In addition, the discussion highlights opportunities for enhancing regulatory frameworks and their enforcement, and the need for a comprehensive approach to process safety management in Indonesia's oil and gas industry. Enhancements to process safety programs and amendments to process safety regulations are among the suggested recommendations. Addressing these problems would enable Indonesia's oil and gas industry to effectively manage the risks linked to process safety incidents.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"98 ","pages":"Article 105756"},"PeriodicalIF":4.2,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Black swans to gray rhinos: Robust decision making for Natech scenarios caused by floods","authors":"Xiangyang Hu,&nbsp;Angbin Yang,&nbsp;Shaohui Wu,&nbsp;Ruipeng Tong","doi":"10.1016/j.jlp.2025.105755","DOIUrl":"10.1016/j.jlp.2025.105755","url":null,"abstract":"<div><div>Industrial facilities and critical infrastructure are affected by natural disasters with increasing probability, potentially resulting in serious health impacts, environmental pollution, and economic losses. Deep uncertainty about future scenarios leads to under-adaptation due to the inability of existing knowledge to cope with ambiguity and complexity. With scientific constraints, particularly in model limitations and scenario scarcity, estimating the likelihood of risk events and possible implications is challenging and error-prone. Using systems thinking to guide scenario planning, a Pressure-State-Response (PSR) model of Natech risk was developed to outline the uncertainty involved in the full course of the Natech event in this paper. Taking the flood-triggered Natech risks as an example, a robust decision-making (RDM) framework was adopted to analyze the impacts of future extreme rainfall scenarios on the city. Obtaining future rainfall scenarios through screening and quantitative analysis of uncertainties and their intervals of variability under the impact of climate change. By evaluating urban disaster curves that may be triggered in the future, an interpretive structural model (ISM) of the future urban response to the Natech accident scenario was constructed, and prioritized adaptation paths were selected to enhance urban resilience.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"98 ","pages":"Article 105755"},"PeriodicalIF":4.2,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144842279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intelligent countermeasures analysis in oil and gas projects utilizing topic modeling","authors":"Ehab Elhosary ,&nbsp;Osama Moselhi","doi":"10.1016/j.jlp.2025.105751","DOIUrl":"10.1016/j.jlp.2025.105751","url":null,"abstract":"<div><div>The oil and gas industry is inherently complex and high-risk, with potential fires, explosions, and releases of hazardous substances posing significant safety challenges. Despite robust safety management systems, accidents persist, highlighting the importance of learning from past incidents and hazard reports. Historical Hazard and Operability (HAZOP) reports generate valuable countermeasures—safeguards and recommendations—that inform the design of protection systems to enhance safety management. However, the sheer volume of countermeasures produced makes addressing each one prohibitively expensive and time-consuming. Additionally, current HAZOP literature and software tools lack automation of these countermeasures, impeding the efficient dissemination of information to the appropriate departments for detailed design. This paper introduces categorizing countermeasures utilizing the BERTopic algorithm in natural language processing (NLP). The methodology comprises data preprocessing, SBERT (a modification of the Bidirectional Encoder Representations from Transformers) for generating embeddings, Uniform manifold approximation and projection (UMAP) for dimensionality reduction, hierarchical density-based spatial clustering of applications with noise (HDBSCAN) for clustering, and KeyBERT for topic representation. Applied to 1574 records from a HAZOP report of an oil pump station, the BERTopic model achieved 84.6 % coherence score and 90.7 % topic diversity score, resulting in 15 final topics, outperforming Latent Dirichlet Allocation (LDA) (45.3 % and 84.7 %) and Latent Semantic Analysis (LSA) (53 % and 96 %). The study identified included and excluded topics for each node and the most frequent topics by risk rate. The generated safety systems (SS) were validated against API RP 750 and RP 752 standards and the Countermeasures Breakdown Structure (CBS) was introduced to organize safety systems hierarchically. The developed model was tested on another dataset of an oil and gas production facility, comprising 512 records and 21 nodes, achieving 85.29 % coherence and 98.33 % topic diversity, confirming its robustness and consistency. This research benefits HAZOP participants by improving hazard identification, emphasizing key preventative actions, and assigning them to relevant departments for design-stage deployment.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"98 ","pages":"Article 105751"},"PeriodicalIF":4.2,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144813966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of process safety management system sustainability in industrial organizations with regards to organization and personnel elements","authors":"Ozgul Yildirim ,&nbsp;Saliha Cetinyokus ,&nbsp;Tahsin Cetinyokus","doi":"10.1016/j.jlp.2025.105750","DOIUrl":"10.1016/j.jlp.2025.105750","url":null,"abstract":"<div><div>The organization and personnel element is critical to the sustainability of the Process Safety Management System (PSMS). This element reflects the commitment of personnel to the safety culture and procedures, the effectiveness of training and development programs, and the alignment of management systems with corporate objectives. In this study, it was aimed to analyze the sustainability of the process safety management system in industrial organizations, especially in terms of organization and personnel elements. For this purpose, a methodology based on benchmarking including the planning, data collection, analysis and adaptation stages was proposed. A case study was also performed on sample organizations (Organization A and Organization B). In the planning, the team was determined and the workflows of the sample organizations were explained. Data collection was carried out with a descriptive survey. Analyses were conducted using descriptive analysis and <em>t</em>-test. In the adaptation, targets for sustainability were determined and an action plan was developed. It was seen that Organization A and Organization B did not differ significantly in terms of personnel element (t = −1.258, p = 0.209, 95 % CI = −.192 – .042, 99 % CI = −.229 – .079). In terms of organization element, Organization B was found to be more positive than Organization A (t = −7.096, p &lt; 0.05, 95 % CI = −.775 to −.439, 99 % CI = −.829 to −.386). The action plan for Organization A focused on key issues such as a critical assessment of current procedures, establishing effective communication, strengthening safety training, establishing a safety culture, and improving emergency management. It is envisaged that the proposed methodology can be used as a practical tool in the sustainability benchmarking of organizations, specific to the relevant element.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"98 ","pages":"Article 105750"},"PeriodicalIF":4.2,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144770661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing a Petri-net approach for emergency response modeling and time analysis of process accidents considering the execution characteristics of emergency tasks","authors":"Jianfeng Zhou ,&nbsp;Genserik Reniers","doi":"10.1016/j.jlp.2025.105753","DOIUrl":"10.1016/j.jlp.2025.105753","url":null,"abstract":"<div><div>In the process industry, hazardous chemical accidents can easily cause heavy loss, and emergency response is an important approach to reduce it. In the process of emergency response, many emergency tasks have different characteristics in their execution. This study analyzes the impact of the dynamic changes of emergency response personnel on the emergency tasks, and deduces the relationship between the execution time of an emergency task and the number of people with the time they join the task. Aiming to model the emergency response process under the possible dynamic change of the emergency task execution time, the dynamic timed Petri-net (DTPN) is proposed by improving the timed Petri-net (TPN) on the basis of the execution mechanism of transition, and the corresponding models are established according to several basic execution characteristics of the emergency tasks. The proposed approach is used to model the emergency response of on-site responders to a fire in a storage tank, and the time analysis is carried out. The results show that the approach can well solve the problem of modeling and analysis of emergency tasks with dynamic execution characteristics.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"98 ","pages":"Article 105753"},"PeriodicalIF":4.2,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144780612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on the blast-resistant performance of concrete walls coated with explosion-proof materials under hydrogen explosion conditions","authors":"Fei Liu ,&nbsp;Yujiang Qian ,&nbsp;Xiting Long ,&nbsp;Zhirong Wang ,&nbsp;Pingfeng Li ,&nbsp;Xiaojun Niu ,&nbsp;Jie Xiao","doi":"10.1016/j.jlp.2025.105749","DOIUrl":"10.1016/j.jlp.2025.105749","url":null,"abstract":"<div><div>Hydrogen energy boasts a multitude of benefits and is poised to become a pivotal component of the future energy infrastructure. Despite its promise, the high energy density and inherent flammability and explosiveness of hydrogen pose significant challenges to its widespread adoption and application. In the event of a hydrogen leak and subsequent ignition during utilization, an efficient explosion-proof coating on structural components could be instrumental in mitigating potential losses to both personnel and property. Hydrogen energy's promise is counterbalanced by explosion risks during leaks. In this study, the test of 15 mm thick blocks (front-coated with 3 mm polyurea) to hydrogen-air explosions (15 % H₂) generated in a Ø 600 mm spherical device were conducted. The findings revealed that (1) coated blocks sustained localized center damage (peak horizontal strain ∼9000 με) with back cracking, while uncoated blocks fragmented entirely; (2) coating reduced front vertical strain by 83 %; (3) backside vertical strain exceeded limits (&gt;32768 με) in all tests, confirming tensile failure dominance. Results validate polyurea's viability for retrofit protection in hydrogen infrastructure and averting large-scale disasters.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"98 ","pages":"Article 105749"},"PeriodicalIF":4.2,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144770660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HFACS-OGP:An analysis framework for oil and gas pipeline accident causation","authors":"Yunhua Gong ,&nbsp;Yi Xiong","doi":"10.1016/j.jlp.2025.105747","DOIUrl":"10.1016/j.jlp.2025.105747","url":null,"abstract":"<div><div>Pipelines serve as the primary means for transporting oil and gas globally. Despite their perceived safety, accidents continue to occur in modern operations. The operating environment of oil and gas pipelines necessitates that the prevention of accidents should take into account not only the internal management of pipeline operators, but also external factors such as national regulatory oversight and third-party damage. Existing Human Factors Analysis and Classification System (HFACS) frameworks, originally developed for aviation, are inadequate for analyzing regulatory gaps and emerging challenges (e.g., third-party damage) in the oil and gas pipeline industry. To address this, a novel HFACS named the Human Factors Analysis and Classification System for the Oil and Gas Pipeline industry (HFACS-OGP) is proposed. Eighty accident reports primarily sourced from the US National Transportation Safety Board (NTSB) and Canadian Transportation Safety Board (TSB) were analyzed to develop HFACS-OGP based on grounded theory. Three levels: third-party factors, administration oversight and design gaps, and legislation gaps, were incorporated into the original framework of HFACS. The frequency of each contributing factor in the 80 accidents was analyzed. HFACS-OGP adapts the original HFACS structure to industry-specific contexts and offers a customized framework for investigating and preventing oil and gas pipeline accidents.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"98 ","pages":"Article 105747"},"PeriodicalIF":3.6,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}