Journal of Loss Prevention in The Process Industries最新文献

{"title":"Investigating the effect of random packing on flame quenching and explosion pressure suppression","authors":"Shoutao Ma ,&nbsp;Rusong Shang ,&nbsp;Hongwei Zhu ,&nbsp;Wei Xu ,&nbsp;Bing Sun","doi":"10.1016/j.jlp.2025.105710","DOIUrl":"10.1016/j.jlp.2025.105710","url":null,"abstract":"<div><div>Gas-phase oxidation processes are crucial chemical reaction processes widely utilized in the production of various raw materials, intermediates, and products in several industries. Due to the fact that the raw materials in these reactions primarily consist of flammable gases, the presence of a certain concentration of oxygen in the reactant leads to the formation of a combustible system. In such cases, ignition sources can cause explosions, posing serious safety risks to personnel and equipment. In this study, the use of porous inert random packing to quench propylene-air flame was innovatively proposed, and the performance of various types of porous inert packing in extinguishing flames and reducing the maximum explosion pressure was also investigated by self-made detonation tube. The results show that the flame of 8 % C₃H₆-92 % air premixed gas can be effectively quenched within 20 cm by filling the random packing in a pipe with a diameter of 20 mm at the pressure of 110 kPa and 160 kPa. Raschig ring packing can control the flame quenching distance within 5 cm. When the initial pressure of premixed gas is 110 kPa, implementation of Dixon ring packing achieves a 13.3 % reduction in maximum explosion overpressure relative to the empty chamber configuration. In addition, the effects of hydrogen on flame quenching distance and explosion pressure rise were also performed, and the flame quenching distance and explosion are all increased compared with the system of C₃H₆-9air premixed gas. Furthermore, the random packing of Pall rings cannot quench the flame of premixed gas with hydrogen addition because of its large porosity which leads to poor wall efficiency. These experimental findings provide theoretical support and guidance for the development of new types of intrinsically safe gas-solid phase reactors and offer a strategy for conducting gas-phase oxidation reactions within the explosive limit range.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"97 ","pages":"Article 105710"},"PeriodicalIF":3.6,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271124","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":"Modeling CO2 leak and dispersion from injection wells and surface facilities using machine learning","authors":"Mohamed Abdalla ,&nbsp;Mohammed Alrasheed ,&nbsp;Qingsheng Wang","doi":"10.1016/j.jlp.2025.105709","DOIUrl":"10.1016/j.jlp.2025.105709","url":null,"abstract":"<div><div>This study presents a novel machine learning–based approach for real-time predictions of CO₂ leak and dispersion from injection wells and surface facilities. A comprehensive dataset was generated using PHAST simulations under worst-case scenarios, specifically targeting two critical CO₂ concentration thresholds, 30,000 ppm (ACGIH STEL) and 40,000 ppm (IDLH). Key operational parameters, including operating temperature (0–100 °C), operating pressure (1–250 bar), and leak diameter (1–12 inches), were systematically varied while maintaining other parameters fixed at conservative values, and considering two atmospheric stability classes (F and D) with corresponding surface wind speeds (1.5 m s⁻¹ and 5 m s⁻¹) respectively. Multiple machine learning models were trained on this high-fidelity dataset, and the model performances were evaluated. The Artificial Neural Network (ANN) model emerged as the top performer, achieving high predictive accuracy (R² ≈ 0.9996 on test data) with minimal error. Extensive diagnostic analyses, including residual, cumulative error, and leverage evaluations, confirmed the model's robustness and generalizability. The final predictive model was integrated into an interactive application, enabling rapid hazard assessment, and offering a significant reduction in computational cost compared to traditional Computational Fluid Dynamics (CFD) methods. This work provides a scalable framework for enhancing emergency response and process safety in CO₂-intensive industrial environments.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"97 ","pages":"Article 105709"},"PeriodicalIF":3.6,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144298204","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 simplified model for rainout estimation for two phase releases of alternative liquified fuels","authors":"Raymond Quek ,&nbsp;Vinh-Tan Nguyen ,&nbsp;Venugopalan Raghavan ,&nbsp;Chang Wei Kang ,&nbsp;He Zhimin ,&nbsp;Lim Boon How","doi":"10.1016/j.jlp.2025.105693","DOIUrl":"10.1016/j.jlp.2025.105693","url":null,"abstract":"<div><div>The adoption of alternative fuels in the energy and transport sectors is strategically important for achieving decarbonization goals. However, managing the risks associated with accidental leakages from storage and transfer of these fuels – such as LNG, ammonia, and methanol – is essential for their safe handling and usage. These leakages can lead to complex release dynamics due to phase changes when the fuel transitions from high-pressure storage to ambient conditions, resulting in a mixture of liquid and gas phases. Quantifying the liquid content after such leaks, referred to as rainout, is particularly challenging. This work presents an approach to estimate the rainout fraction from accidental liquid fuel releases using simplified equations for flow dynamics and two-phase physics. A relative time scale parameter is derived to determine rainout occurrence, and the resulting model is calibrated with our recent field experiments via a simple regression technique. The model is validated with historical experimental data and compared with existing models, demonstrating reliable order-of-magnitude predictions of rainout fractions across various substances and storage conditions. This simplified model provides a rapid estimation tool for rainout fraction as an input into subsequent dispersion analysis.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"97 ","pages":"Article 105693"},"PeriodicalIF":3.6,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144290815","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":"Knowledge graph-based alarm management in petrochemical enterprises: A study on fusion and analysis of multi-source heterogeneous information","authors":"Xiaomiao Song ,&nbsp;Fabo Yin ,&nbsp;Dongfeng Zhao","doi":"10.1016/j.jlp.2025.105706","DOIUrl":"10.1016/j.jlp.2025.105706","url":null,"abstract":"<div><div>In response to the increasing emphasis on alarm management in the petrochemical industry, there has been an explosive growth in relevant information. However, this information is often scattered across different systems and databases, stored in various forms such as documents, tables, and images, making it challenging to uniformly store, share, and utilize multi-source heterogeneous information. This commonly leads to the problem of “Information Islands.” In order to effectively leverage knowledge in the field of alarm management in the petrochemical industry and overcome the challenge of non-interoperable information, a method for fusing multi-source heterogeneous information in petrochemical enterprise alarm management based on knowledge graph is proposed. This method aims to standardize the management of alarm-related information and achieve information fusion. Initially, the approach utilizes data from petrochemical enterprises and publicly available data in the field of alarm management to establish both local and global ontologies. Subsequently, mapping algorithms are designed to achieve a more accurate construction of the hybrid ontology. Based on this foundation, a knowledge graph for alarm management in the petrochemical industry is established. Additionally, corresponding modules for information storage and retrieval are developed. Through the application demonstration using real alarm management information from a petrochemical enterprise, the results indicate that the proposed method for fusing multi-source heterogeneous information in petrochemical enterprise alarm management can effectively achieve information fusion.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"97 ","pages":"Article 105706"},"PeriodicalIF":3.6,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271262","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":"Quantitative evaluation of occupational hazards caused by dust in Sanxin Gold and Copper Mine","authors":"Xiaohong Gui,&nbsp;Zhenrong Li,&nbsp;Mengzhen Xu,&nbsp;Jingya Zheng,&nbsp;Shiqing Xing","doi":"10.1016/j.jlp.2025.105705","DOIUrl":"10.1016/j.jlp.2025.105705","url":null,"abstract":"<div><div>The occupational pneumoconiosis is a serious threat to the health of mine workers. In order to quantitatively evaluate the degree of dust hazards in the production chain, the dust health hazard evaluation model was established based on the USEPA (US Environmental Protection Agency) health risk evaluation method. The DALY (Disability Adjusted Life Year) value was introduced to quantitatively express the damage of dust to workers. By calculating the health risks and DALY values of different work types in different working faces, the key control points of dust hazards are identified as wind drilling workers, transportation workers, forklift drivers, and crushing positions. A probabilistic hazard quantification model was constructed by combining the health hazard evaluation model with Monte Carlo method to simulate the distribution of dust hazards at different working surfaces and analyze the sensitivity of exposure parameters. The results show that the mining workshop of this mine is exposed to the greatest dust hazard, with a worker DALY value of 1.15 × 10⁻¹a. In addition, the dust concentration (C), average exposure time (AT), exposure duration (ED) and exposure frequency (EF) have the most significant effects on dust health hazards.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"97 ","pages":"Article 105705"},"PeriodicalIF":3.6,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271125","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":"Study on key causal factors and pathways of fire and explosion accidents in hazardous chemical storage tank area","authors":"Wei Jiang,&nbsp;Shengxiang Ma,&nbsp;Zhuoye Zhang,&nbsp;Yuan Xu","doi":"10.1016/j.jlp.2025.105704","DOIUrl":"10.1016/j.jlp.2025.105704","url":null,"abstract":"<div><div>Accidents occurred in hazardous chemical storage areas often have significant impacts and serious consequences. To ensure the safety and health of employees and prevent accidents in hazardous chemical storage areas, it is necessary to explore the key causal factors and critical paths of accidents through certain technical means. Therefore, this paper proposes a research method that combines text mining, association rule mining, and Bayesian networks to conduct in-depth mining and analysis of textual data from cases of hazardous chemical storage tank area fire and explosion accidents (HCSTAFEAs), thereby effectively identifying the causal factors of such accidents and exploring the degree of interaction, importance, and critical paths of the causal factors. First, this paper improved the text mining process by using methods such as grounded theory, text processing, and Chinese word segmentation to mine 60 collected reports, resulting in 68 primary causal factors, 17 secondary causal factors, and 6 tertiary causal factors. Second, the grey relational method was used to analyze the impact of the causal factors, quantitatively determining the importance of each causal factor and further refining them. The Apriori algorithm was subsequently employed to obtain the frequent itemsets and strong association rules of the accident causal factors, and a Bayesian network model was constructed. Through sensitivity analysis and critical path analysis, the key causal factors and critical paths of HCSTAFEAs were identified. The study indicates that five high-sensitivity causal factors—equipment and operation status control defects, equipment maintenance and management defects, unsafe acts, safety management systems and implementation defects, and safety training defects—are the key causal factors of HCSTAFEAs. In addition, three key paths that trigger accidents were obtained: safety management systems and implementation defects → safety training defects → internal supervision defects → operational program defects → unsafe acts; safety management systems and implementation defects → safety training defects → equipment maintenance and management defects → equipment and operation status control defects; and safety management systems and implementation defects → safety training defects → internal supervision defects → operational program defects → equipment and operation status control defects. This paper provides insights into the effective mining and extraction of unstructured accident investigation report textual information and offers a perspective for research on the identification of causal factors and critical paths of accidents in hazardous chemical storage areas based on data-driven thinking.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"97 ","pages":"Article 105704"},"PeriodicalIF":3.6,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144241616","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":"Effect of substrate thermal properties on evaporating liquid hydrogen and ammonia spills","authors":"Martin Spillum Grønli,&nbsp;Hans Langva Skarsvåg,&nbsp;Svend Tollak Munkejord","doi":"10.1016/j.jlp.2025.105685","DOIUrl":"10.1016/j.jlp.2025.105685","url":null,"abstract":"<div><div>To decarbonize the energy, transport and industrial sectors, liquid hydrogen and ammonia are likely to be more widely employed. During an accidental release, these cryogens quickly spread and evaporate, producing explosive (<span><math><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>) or toxic (<span><math><msub><mrow><mi>NH</mi></mrow><mrow><mn>3</mn></mrow></msub></math></span>) clouds. Assessing the risks associated with storage and transport therefore requires tools that can simulate these spill processes, accounting for both the spill source, geometry and substrate thermal properties. In this work we have developed a flexible tool that takes the details of the spill, geometry and substrate as input. The parameters include initial spill velocity, ground topography, obstructions, and details regarding the thermal properties of the substrate. The latter includes temperature-dependent thermal properties, porosity and potential freeze out of trapped water. We validate this model against experimental data and apply it to relevant <span><math><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> and <span><math><msub><mrow><mi>NH</mi></mrow><mrow><mn>3</mn></mrow></msub></math></span> spill cases. Evaporation rates were found to vary significantly with substrate characteristics, and this is expected to have a large impact on safety distances.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"97 ","pages":"Article 105685"},"PeriodicalIF":3.6,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144280099","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":"Application of one point clustering algorithms to develop a defect comparison model for differential time inspection of chemical pipelines","authors":"Yen-Ju Lu,&nbsp;Chen-Hua Wang","doi":"10.1016/j.jlp.2025.105701","DOIUrl":"10.1016/j.jlp.2025.105701","url":null,"abstract":"<div><div>This study addresses the challenges of defect comparison in differential time inspection of industrial long-distance pipelines by proposing a clustering algorithm-based defect comparison model. The research focuses on the safety management needs of underground pipelines in the petrochemical industry, particularly on accurately matching defect distribution and features after multiple in-line inspections (ILI). A data-driven automated comparison procedure employing clustering analysis is developed, effectively identifying defect similarities and distribution patterns, thereby significantly improving comparison efficiency and accuracy. Notably, this work pioneers the integration of data preprocessing techniques, such as mileage calibration and weld seam alignment, with weighted feature clustering to enhance both the reliability and sensitivity of defect matching. Validation through Unity Plot analysis confirmed that the proposed method reduced manual matching errors to zero and improved comparison efficiency by 76 %. The findings demonstrate that the model not only enhances the reliability of defect matching but also provides robust technical support for the safe operation and maintenance strategies of underground pipelines, with potential extensions to multi-source data integration and predictive maintenance applications.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"97 ","pages":"Article 105701"},"PeriodicalIF":3.6,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144229772","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":"Study of the magnesium dust cloud hot surface ignition characteristics in the Godbert-Greenwald furnace","authors":"Tengfei Chen ,&nbsp;Xiaoxing Zhong ,&nbsp;Jo Van Caneghem ,&nbsp;Yansen Lu ,&nbsp;Qiu Zhong ,&nbsp;Zhenzhen Zhao ,&nbsp;Maarten Vanierschot","doi":"10.1016/j.jlp.2025.105702","DOIUrl":"10.1016/j.jlp.2025.105702","url":null,"abstract":"<div><div>Magnesium dust cloud hot surface ignition characteristics in the Godbert-Greenwald (G-G) furnace are simulated. CFD models and algorithms selected for the simulation are validated through comparison between simulated dust cloud critical ignition temperature (<em>CIT</em>) results and experimental dust cloud minimum ignition temperature (<em>MIT</em>) data. The magnesium dust cloud ignition process in the G-G furnace mainly characterizes three stages: dust dispersion and cloud formation, dust cloud deposition and heat accumulation, and dust cloud thermal runaway. Particle size increase shortens particle residence time in the furnace and lifts the particle-gas thermal resistance, leading to more significant delays between particle ignition and gas flame formation for larger particle sizes over 100 μm. Under the marginal super-critical ignition state as the furnace heating temperature just reaches the <em>CIT</em> level, if the <em>CIT</em> of a specific particle sized dust cloud is higher than the <em>MIT</em> of the same sized single magnesium particle (<em>MITP</em>), the dust cloud ignition mainly characterizes an individual particle ignition driven mode, otherwise governed by a collective particle heating driven mode. The simulated magnesium dust cloud <em>CIT</em> stays rather stable under lower dust dispersion pressures (<em>P</em>_<em>dis</em>) below 2 kPa, but shows a clearer increasing trend as <em>P</em>_<em>dis</em> further rises.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"97 ","pages":"Article 105702"},"PeriodicalIF":3.6,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144241617","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 effect of water on the explosion characteristics of pure and diluted light alcohols","authors":"Rafal Porowski ,&nbsp;Gianmaria Pio ,&nbsp;Tomasz Gorzelnik ,&nbsp;Benedetta De Liso ,&nbsp;Ernesto Salzano","doi":"10.1016/j.jlp.2025.105699","DOIUrl":"10.1016/j.jlp.2025.105699","url":null,"abstract":"<div><div>Light alcohols (methanol, ethanol, 1-propanol and 2-propanol) and their water-diluted mixtures were studied in a 20 L spherical explosion vessel at 323.15 K and 1 bar to quantify explosion parameters: explosion pressure (P_ex), maximum pressure rise rate ((dP/dt)_max) and explosion delay time (t_del). Pure samples at an equivalence ratio ϕ = 0.3 yielded P_ex = 6.88 bar and (dP/dt)_max = 365.29 bar/s for methanol, and P_ex = 6.70 bar with (dP/dt)_max ≈ 260.05 bar/s for ethanol (t_del ≈ 79 ms).</div><div>Addition of 10 vol% water to ϕ = 0.3 samples reduced P_ex by only 5–10 % but increased (dP/dt)_max by up to 15 % and shortened t_del by ≈ 20 ms, indicating enhanced flame propagation due to improved mixing. In contrast, water contents of 40–60 vol% caused P_ex to drop by 50–70 % (e.g., ϕ = 0.3 methanol P_ex &lt; 1 bar at 40 % H₂O) and (dP/dt)_max to decrease by 60–80 %, while t_del increased by up to 50 %, reflecting strong thermal dilution and kinetic inhibition.</div><div>Comparative analysis across alcohols showed that methanol mixtures consistently exhibit the highest P_ex and (dP/dt)_max at low water dilution, followed by ethanol and propanol isomers, with 1-propanol and 2-propanol displaying similar trends but slightly lower reactivity (peak P_ex differences ≤10 %). These quantitative findings provide clear design guidelines: moderate water addition (10–30 vol%) can enhance safety without severe performance penalties, whereas high dilution (&gt;40 vol%) effectively inertizes light-alcohol flames, offering a robust mitigation strategy in industrial settings.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"97 ","pages":"Article 105699"},"PeriodicalIF":3.6,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271123","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}