Journal of Loss Prevention in The Process Industries最新文献

{"title":"Explosion parameters of aviation kerosene/nano aluminum mixture at initial high temperature and pressure","authors":"Yue Wang ,&nbsp;Zhiguo Chang ,&nbsp;Qi Zhang","doi":"10.1016/j.jlp.2026.105919","DOIUrl":"10.1016/j.jlp.2026.105919","url":null,"abstract":"<div><div>JP10 (95(w)%) and nm aluminum (5(w)%) in air mist, as a special fuel used in underground mining of coalbed methane, the explosion hazard is the basis of safety design. In this study, the explosion pressure, the maximum rate of explosion pressure rise and the lower limit of the explosion concentration of aviation kerosene JP10 (95(w)%) and nm-aluminum powder (5(w)%) mist under different initial pressures and initial temperatures were observed by using a 20 L mist explosion experimental device. Change laws of the experimental peak explosion pressures of the JP10 (95(w)%) and nm aluminum (5(w)%) in air mist with concentration, with initial pressure and initial temperature have been found respectively. The experimental peak explosion pressures of the JP10 (95(w)%) and nm aluminum (5(w)%) in air mist at the concentration 500 g/m³ increase with the initial pressure and decrease as the initial temperature increases. The experimental lower explosion concentration limits of the fuel (JP10, 95(w)% nm aluminum, 5(w)% in air) mist decrease as the initial temperature increases within the initial temperature range from 30 °C to 80 °C.The lower explosion limit of the fuel-air mixture JP10 (95w%) and nm AL powder (5w%) decreases as the initial pressure increases from 0.1 MPa to 0.3 MPa.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105919"},"PeriodicalIF":4.2,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977008","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 fire behavior of steel welding single disk internal floating roof with the large-scale fire experiment: structural defect and its optimizing strategy in fire","authors":"Wei Liu ,&nbsp;Hang Ye ,&nbsp;Shuang Wang ,&nbsp;Zejiang Zhang ,&nbsp;Ji Xiao","doi":"10.1016/j.jlp.2026.105913","DOIUrl":"10.1016/j.jlp.2026.105913","url":null,"abstract":"<div><div>In this study, steel welding single disk IFR arranged with the penetrating damage to the body and partial loss in the rim seal system has been designed as the experimental model at the diameter of 4.7 m according to API Pub 2021A-1998 and API 653, in order to simulate its most adverse situation in the real fire. The large-scale fire experiment has been conducted for the model, so as to investigate the fire development and burning behavior of the IFR, and further determine its structural defect and the optimizing strategy in fire. Fire process and temperature rise of the IFR model have been recorded and monitored as a function of time. Influence of the corrective measures on the fire behavior of IFR has been also analyzed and discussed here. Para-full surface fire has been first discovered and proposed to describe the characteristic burning behavior of this IFR. The results indicate that the traditional model exhibits para-full surface fire in the tank after 20min with the highest maximum temperature rise of 958 °C at 1050s, while the modified model with the corrective measures could prohibit the occurrence of para-full surface fire, restrict the temperature rise of the body and its surroundings below 900 °C, and stop the spread of fire in the storage tank for a period of 2 h, which is 6.0 times higher than the traditional model. And the related optimizing strategy has been proposed for the traditional steel welding single disk IFR in design and use.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105913"},"PeriodicalIF":4.2,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938637","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":"A machine learning-based approach for broadband sound recognition: A case study on investigating potential fire hazards of grinding machines","authors":"Shengli Kong ,&nbsp;Qianyu Tan ,&nbsp;Kai Zhou ,&nbsp;Wei Wang ,&nbsp;Ting Wang","doi":"10.1016/j.jlp.2026.105918","DOIUrl":"10.1016/j.jlp.2026.105918","url":null,"abstract":"<div><div>Fire investigations often rely on visual evidence, which may be compromised by surveillance failures, occlusion, or image loss. Broadband acoustic signals, with strong penetration and temporal resolution, provide complementary clues about equipment conditions, explosions, and structural failures. Yet their non-stationary and overlapping characteristics hinder analysis using conventional methods. This study presents a machine learning-based broadband sound recognition approach, using grinding machines as representative fire hazards. Mel-frequency cepstral coefficients (MFCCs) and spectrogram gray-level co-occurrence matrix (GLCM) features were extracted to capture spectral and texture information, then fused for classification with XGBoost. Bayesian optimization was applied to adapt hyperparameters and improve robustness. The proposed model initially achieved 94.2 % accuracy and 91.5 % recall in multi-condition recognition using default hyperparameters. After applying Bayesian optimization to adapt hyperparameters and improve robustness, the model achieved 96.7 % accuracy and 93.3 % recall, outperforming support vector machines, random forests, and backpropagation neural networks. These results demonstrate the potential of broadband acoustic data to support fire investigations and provide a practical pathway for scene reconstruction and evidence enhancement.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105918"},"PeriodicalIF":4.2,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938720","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":"Quantifying reliability and uncertainty in hydrogen infrastructure through integrated incident analysis","authors":"Saksham Timalsina,&nbsp;Chengyi Zhang,&nbsp;Uttam Kumar Pal","doi":"10.1016/j.jlp.2026.105921","DOIUrl":"10.1016/j.jlp.2026.105921","url":null,"abstract":"<div><div>Hydrogen infrastructure introduces complex safety and reliability challenges due to its unique physicochemical properties, which tightly connect technical, human, and operational elements involved. Addressing these challenges requires methods that incorporate real system behavior and quantify uncertainty rather than relying solely on theoretical hazard models. This study analyzes incidents from the H2Tools database and develops an integrated framework for reliability and probabilistic safety assessment of hydrogen systems. Root causes are categorized using an Ishikawa diagram, after which a risk-impact matrix evaluates the relative contribution of each failure mechanism. A Monte-Carlo uncertainty analysis improves assessment by characterizing uncertainty in risk severity and highlighting causes that may escalate under unfavorable conditions. Results show that human errors, procedural deficiencies, and technical failures dominate risk profiles, exhibiting significant uncertainty ranges that affect system-level reliability. To support practical safety engineering, the study compiles targeted engineering controls, operational standards, maintenance considerations, and training measures linked directly to the identified failure modes. The proposed framework transforms empirical incident data into a structured, reliability-oriented decision-support tool, offering actionable guidance for enhancing safety, resilience, and operational assurance in hydrogen energy systems.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105921"},"PeriodicalIF":4.2,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938722","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":"A Safety-II theory based method for human reliability assessment to prevent fire and explosion during shipping LNG offloading","authors":"Renyou Zhang ,&nbsp;Mengjie Shi ,&nbsp;Rabiul Islam ,&nbsp;Shanguang Chen ,&nbsp;Shaowen Ding ,&nbsp;Zhen Liao ,&nbsp;Zhan Dou","doi":"10.1016/j.jlp.2026.105920","DOIUrl":"10.1016/j.jlp.2026.105920","url":null,"abstract":"<div><div>Human factors constitute the important element in ensuring operational safety in high-risk industries. Particularly in complex operations such as shipping Liquefied Natural Gas (LNG) offloading, even minor operational errors can cause disastrous consequences such as fire and explosion. Traditional accident causation theories often focus excessively on specific and localized causes, overlooking the intricate interconnections among components involved in complex tasks. This oversight can result in an inaccurate safety analysis model and questionable quantitative outcomes. Therefore, this study adopts the Safety-II theoretical framework, providing a perspective for understanding dynamic human-factor interactions in complex systems. Firstly, this study employs the Functional Resonance Analysis Method and Minimum Spanning Tree (FRAM-MST) algorithm to identify the critical functional coupling. Building upon this framework, the Cognitive Reliability and Error Analysis Method (CREAM) and Bayesian network (BN) are introduced to perform a quantitative risk analysis of unsafe behavior, assessing them from a probability perspective and calculating the Human Error Probability (HEP). The findings indicate that HEP for the LNG offloading operation is 1.52 × 10⁻⁴. This outcome provides operators with a clearer understanding of the risks associated with the operations, enabling the development of targeted explosion-proof measures.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105920"},"PeriodicalIF":4.2,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938635","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":"Definition of a simplified risk assessment methodology for NaTech scenarios triggered by tornado","authors":"Fabrizio Santamato ,&nbsp;Clara Iannantuoni ,&nbsp;Valentina Busini","doi":"10.1016/j.jlp.2026.105915","DOIUrl":"10.1016/j.jlp.2026.105915","url":null,"abstract":"<div><div>Natural catastrophic events affecting technological systems may lead to the release of hazardous materials, giving rise to so-called “NaTech” events. The increasing number of NaTech events observed over recent years, possibly related to climate change, has reinforced interest in and the need to investigate the risk of exposure to natural hazards affecting the process industry. In the literature, most attention has been devoted to accidents triggered by floods and earthquakes, whereas no specific analysis protocols aimed at assessing the risk posed by tornadoes and severe wind gusts on production facilities are currently available. Consequently, the objective of this paper is to fill a gap in NaTech risk assessment by proposing a qualitative methodology for assessing the risk related to tornadoes and severe wind gusts. The proposed approach provides a basis for an objective, although simplified, comparison of both the risk posed by different plants potentially exposed to extreme wind events and the identification of the most critical equipment within a single plant. The analysis, partly based on existing qualitative methods, requires limited resources and data and relies on index-based evaluations.</div><div>A screening phase is first carried out by assessing the statistical incidence of the natural event using a European database, followed by the application of a qualitative method for evaluating equipment vulnerability and the consequences of their failure. Although the methodology was initially developed using data from the Italian territory, it can be applied to other countries, as demonstrated by the location sensitivity analysis performed at the end of the case study. The application of the methodology to a real case study showed that vertically developed and exposed assets, such as flare stacks, process columns, and gasoline storage tanks, represent the most critical equipment, consistently associated with medium to high risk levels. The sensitivity analysis, performed by relocating the same plant into different geographical areas, confirmed the robustness of the approach, as highly vulnerable assets remained critical across all locations, while less vulnerable equipment (e.g., pumps and phase separators) exhibited risk levels strongly dependent on local wind hazard conditions. These results demonstrate the capability of the methodology to effectively discriminate among territorial risk levels and to support the identification of installations requiring more detailed quantitative analyses.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105915"},"PeriodicalIF":4.2,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938638","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":"Comparative evaluation of chemical segregation methods based on chemical compatibility assessment in chemical laboratories","authors":"Uiam Lee ,&nbsp;Dal Jae Park","doi":"10.1016/j.jlp.2026.105916","DOIUrl":"10.1016/j.jlp.2026.105916","url":null,"abstract":"<div><div>Chemical laboratories storing diverse chemicals in limited spaces face significant risks from incompatible chemical storage, which can lead to fires, explosions, and toxic gas releases during accidental spills or leaks. Although various institutions have developed their own segregation guidelines, no standardized method exists for quantitatively comparing these approaches or systematically optimizing storage under space constraints. This study develops the Chemical incompatibility Hazard Index (C.H.I.), a novel quantitative metric for evaluating mixed storage risks, and applies it to compare seven international segregation methods.</div><div>Using the CAMEO (Computer-Aided Management of Emergency Operations) Chemicals database, 52 chemicals from a Korean quantum dot synthesis laboratory were classified according to each method. The seven methods evaluated include the existing Korean regulatory-based approach, systems from Stanford University, Harvard University, Imperial College London, and Fred Hutchinson Cancer Research Center, the Merck classification system, and the National Oceanic and Atmospheric Administration (NOAA) reactive groups. Compatibility charts were generated for each method, and C.H.I. values were calculated based on the proportion of incompatible, caution, and compatible pairwise reactions within each storage group.</div><div>Among the seven methods, the NOAA reactive group-based approach yielded the lowest average C.H.I. (22.68), significantly outperforming the existing laboratory method (47.78). Subsequent optimization through consolidation of compatible groups to reduce storage locations and selective isolation of six high-reactivity chemicals (11.5 % of inventory) achieved a 71.6 % reduction in average C.H.I. (from 47.78 to 13.56) and a 55.4 % reduction in maximum C.H.I. (from 80.00 to 35.71).</div><div>This study establishes the first quantitative framework for comparing and optimizing chemical segregation methods. The C.H.I. methodology provides a reproducible approach applicable to diverse laboratory environments, particularly benefiting space-constrained research facilities seeking maximum safety improvement with minimal intervention.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105916"},"PeriodicalIF":4.2,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938634","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":"Public risk perception and behavioral responses to flood-triggered Natech Events: A field investigation in industrial areas of Luzhou, China","authors":"Xiao Tang ,&nbsp;Xiaolong Luo ,&nbsp;Baofeng Di ,&nbsp;Bingwei Tian","doi":"10.1016/j.jlp.2026.105914","DOIUrl":"10.1016/j.jlp.2026.105914","url":null,"abstract":"<div><div>Natural hazard triggered technological accidents, known as Natech events, are becoming increasingly frequent with the intensification of extreme weather, posing significant challenges to the risk management and response of such complex disasters. Therefore, the risk management and response to complex disasters represented by Natech events have become crucial components of contemporary risk management. In light of these challenges, this study conducted a field investigation on public perception of flood-triggered Natech events in the industrial areas of Luzhou, China. Guided by the Risk Information Seeking and Processing (RISP) model, the field investigation employed semi-structured street interviews (n = 33) to explore patterns of public risk perception and behavioral responses in Natech scenarios. The findings reveal that Individuals with dual identities (the workers at chemical and distillery factories and residents) tend to have a higher Natech risk perception. In addition, behavioral responses are influenced by risk perception, while decision-making is shaped by perceived barriers and response evaluations. Moreover, insufficient Natech risk information drives risk communication only when individuals are willing to reduce Natech risk but lack the information for effective responses. Lastly, a social expectation bias exists between actual Natech risk perception and behavioral responses and the intentions expressed in interviews. Within this sample, we identified several gaps in public Natech risk perception and response preparedness. Based on these gaps, several targeted recommendations are proposed. These measures will enable researchers to formulate more effective Natech risk communication strategies targeting public risk perception and behavioral responses.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105914"},"PeriodicalIF":4.2,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938636","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":"Artificial intelligence in process safety: A review of opportunities, challenges, and future directions for the chemical process industries","authors":"D. Christopher Selvam ,&nbsp;T. Raja ,&nbsp;Divyesh Rameshbhai Vaghela ,&nbsp;Mansingh Meena ,&nbsp;Sasmeeta Tripathy ,&nbsp;Bhavan Kumar ,&nbsp;Honganur Raju Manjunath ,&nbsp;Kulmani Mehar ,&nbsp;Yuvarajan Devarajan","doi":"10.1016/j.jlp.2026.105917","DOIUrl":"10.1016/j.jlp.2026.105917","url":null,"abstract":"<div><div>The Chemical Process Industries (CPIs) are undergoing a data-driven transformation, as artificial intelligence (AI), the Industrial Internet of Things (IIoT), and advanced analytics are redefining critical safety operations. This review consolidates recent applications of AI for hazard identification, dynamic risk assessment, early incident detection, and proactive barrier management in refineries and petrochemical facilities, emphasizing reported enhancements of 30–60 % in anomaly detection and near-miss classification compared to traditional methodologies. Ongoing challenges include sparse and biased incident datasets, limited interpretability, difficulties in validating algorithms under actual plant conditions, and regulatory ambiguities that limit widespread deployment. To mitigate these deficiencies, the paper proposes a multilayered framework that aligns AI functions with process safety management (PSM) elements, including asset integrity, alarm management, and emergency response. Future research priorities include the development of explainable, certifiable artificial intelligence, digital-twin-driven predictive risk assessment, and the integration of functional safety and risk governance standards, such as International Electrotechnical Commission (IEC) 61511 and ISO 31000. The review delineates pathways to establish safer, cleaner, and more resilient chemical and energy systems globally.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105917"},"PeriodicalIF":4.2,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977010","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":"Fire risk analysis of working items during nuclear power plant decommissioning in Taiwan","authors":"Yu-Hsiang Huang ,&nbsp;Tzu-Sheng Shen ,&nbsp;Ming-Yu Kuo ,&nbsp;Chi-Min Shu","doi":"10.1016/j.jlp.2025.105911","DOIUrl":"10.1016/j.jlp.2025.105911","url":null,"abstract":"<div><div>This research comprehensively analysed domestic and foreign laws and regulations, case studies, and site surveys of Unit One of the First Nuclear Power Plant in Taiwan to conduct a risk analysis of fire prevention in the decommissioning task. It initially proposed and summarised the following principles of fire protection for relevant authorities during the decommissioning process. At the end of this study, six recommendations in Tabble 5 are summarised as follows: (1) Safety of combustibles management, (2) Safety of ventilation and dust collection equipment, (3) Electrical safety, (4) Fire safety, (5) Construction safety, and (6) Personnel safety.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105911"},"PeriodicalIF":4.2,"publicationDate":"2026-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977009","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}