Abstract Fuming nitric acid and fuming sulfuric acid, as critical industrial chemicals, can exhibit high reactivity with metals, posing significant thermal safety risks. This study systematically evaluated the thermal stability of fuming nitric acid, fuming sulfuric acid, and their mixed acid, alongside their chemical compatibility with common structural metals. Utilizing differential scanning calorimetry with custom glass crucibles effectively prevented side reactions with the container, allowing for precise characterization of thermal behavior. Findings revealed that while none of the three acids exhibited exothermic decomposition, their thermal stability varied. Metal compatibility results were distinct: gold was inert across all systems; titanium demonstrated good compatibility only with fuming nitric acid, reacting exothermically with the others; both aluminum and copper triggered vigorous exothermic reactions in all acids, indicating a high thermal runaway risk—the copper/mixed acid system further displayed autocatalytic behavior; the stainless steels showed complex, composition‐dependent reactivity.

Abstract Gas chromatography–mass spectrometry (GC–MS) is a powerful tool in process safety, widely applied to identify and monitor hazardous chemicals in industrial environments. Its ability to separate complex mixtures and unambiguously characterize components makes it essential for detecting leaks, monitoring volatile organic compound emissions, analyzing contaminants, and ensuring regulatory compliance. This paper highlights GC–MS applications in fire risk assessment, chemical hazard evaluation, and transportation safety. Key studies include compositional analysis of flammable gases emitted during battery thermal runaway, following UL 9540A to inform fire and explosion protection standards (NFPA 855, IFC 608, UL 9540). GC–MS has also been used to quantify flammable gases from expandable polymeric beads and molding compounds, supporting safe handling and transport decisions under UN Test U.1 for UN 2211 and UN 3314 classifications. In fire investigations, GC–MS identifies ignitable liquid residues using ASTM E1618, enhancing understanding of fire origin, fuel load, and incendiary characteristics. Additional applications include verifying refrigerant blends for safety classification (ASHRAE Standard 34) and coupling GC–MS with calorimetric tools such as ARC, VSP2, and RC‐1. This integration provides complementary chemical, physical, and kinetic data, enabling deeper insight into reaction mechanisms, dynamic hazard mitigation, and accident prevention during scale‐up processes.

Abstract This study investigated the diffusion of leaked liquefied petroleum gas (LPG) and analyzed the load distribution characteristics of a petrochemical control room under a vapor cloud explosion (VCE) flow field based on the ANSYS/Fluent software. The results showed that the leaked LPG tended to accumulate near the ground. High wind speed accelerated the propagation of the leaked LPG cloud along the leaked direction and accelerated the dilution of the leaked LPG in the side direction. Besides, the existence of obstacles can significantly increase the gas cloud concentration near the obstacles. The nonuniform concentration field generated by leakage accidents can initiate detonation with relatively low ignition energy. In sparsely obstructed environments, the explosive behavior followed the classic open‐space gas cloud explosion pattern, where peak overpressure decreased with distance. The peak overpressure during explosions increased markedly with more obstacles, demonstrating that complex obstructions substantially elevated the risk of explosion accidents. The load distribution across control room walls exhibits significant nonuniformity in both temporal and spatial dimensions. The statistical analysis on historical maximum load distributions at different wall positions was conducted, employing bivariate quadratic polynomial fitting to derive a simplified calculation formula, which can be applied to analyze load distribution patterns across control room walls.

Abstract Heavy Fuel Oil (HFO) handling in power plants poses significant safety and environmental risks, yet conventional risk assessment tools lack real‐time applicability. This study addresses this gap by integrating Hazard and Operability (HAZOP) analysis, computational simulations, and machine learning (ML) to predict HFO leakage consequences at the HUBCO Power Plant, Narowal. A HAZOP study identified 13 critical deviations, with tank leakage as the most severe hazard due to its potential for toxic exposure, environmental contamination, and operational disruptions. Quantitative simulations using the Process Hazard Analysis Software Tool (PHAST) modeled 2757 scenarios, revealing that large leaks (≥500 mm diameter) under elevated temperatures (40–50°C) and moderate wind speeds (4–6 m/s) generated toxic vapor concentrations exceeding 500 ppm at 60 m. To enable real‐time prediction, an Artificial Neural Network (ANN) surrogate model was trained on PHAST data, achieving high accuracy ( R 2 = 0.9667–0.9670) in estimating vapor dispersion at 60 m and 200 m distances. The ANN reduced computational latency from 5 to 15 min (PHAST) to 3–5 ms, indicating scalability for dynamic risk assessment. While slight heteroscedasticity was observed in high‐concentration predictions, the model exhibited robust generalization, particularly at 200 m. This hybrid framework bridges the gap between physical modeling and rapid decision‐making, presenting a proactive strategy for industrial safety. The study underscores the transformative potential of ML in enhancing hazard prediction, operational resilience, and environmental stewardship in HFO‐dependent facilities.

Abstract Process safety is intrinsic across industries, especially in complex sectors like Oil and Gas, where managing safety barriers is essential but challenging. This paper presents a dynamic safety barrier management system for midstream facilities, integrating the Bowtie (BT) method with corporate and automation data. Unlike static systems, it continuously monitors the integrity and effectiveness of preventive and mitigative barriers in real‐time, adapting to changing operational conditions. The methodology follows ANSI Z10, ISO 45001, and ISO 45002 standards. Hazards are assessed using a 5 × 5 risk matrix, assigning a 1–25 risk score that is adjusted based on existing control protections. A Web‐based platform enables users to build BT diagrams, perform protection analyses, and visualize asset safety status. Its back‐end algorithm collects real‐time data on alarms, performance indicators, and checklists, updating risk scores accordingly. By aggregating data from various facility areas, the system ensures proactive risk management and aligns with international standards. The BT diagrams provide clear risk visualizations, linking incident causes to consequences and controls. Results show enhanced operational safety, improved resource allocation, and strengthened safety culture, ultimately reducing incidents and promoting continuous process safety improvements.

Abstract Gas‐Based Combined Cycle Power Plants (GBCCPPs) play a pivotal role in modern energy systems by combining high‐thermal efficiency with reduced emissions. However, their operation carries significant hazards, including fires, explosions, and toxic gas releases, potentially leading to loss of life, environmental damage, and substantial disruptions. Nonetheless, safety management systems at many facilities rely predominantly on qualitative methods, resulting in limited incorporation of quantified risk metrics in emergency‐response planning. In this work, we present a comprehensive Quantitative Risk Assessment framework tailored to GBCCPPs. We employ failure‐frequency analysis alongside consequence modeling to estimate the likelihood and severity of potential accident scenarios. Consequence analysis is conducted using Areal Locations of Hazardous Atmospheres software, facilitating high‐resolution dispersion modeling of hazardous releases. This framework yields probabilistic risk contours that delineate zones of varying harm potential and support the identification of dominant hazard contributors. Application of the framework to a representative GBCCPP demonstrates its capability to quantify catastrophic release scenarios and reveal critical operational vulnerabilities. The results provide actionable insights for plant operators, enabling evidence‐based prioritization of mitigation measures and optimization of safety protocols. This study bridges the gap between qualitative methods and data‐driven risk management in GBCCPPs, thereby enhancing both operational safety and regulatory compliance.

Abstract NFPA 660, Standard for Combustible Dusts and Particulate Solids , became effective on December 6, 2024. This standard is the product of an effort, extending over a decade, to make the National Fire Protection Association (NFPA) requirements for the safe handling of combustible dust, easier for the user to understand and apply. This effort began in March 2011 and was complete in the fall of 2024, with the publishing of NFPA 660. The result, NFPA 660, is organized into chapters establishing requirements fundamental to all combustible dusts, followed by individual chapters providing additional requirements specific to each industry or commodity. In this article, the authors draw on their experiences working on multiple NFPA committees, conversations with committee members, and reviews of the NFPA 660 with multiple stakeholders, to describe the organization of the standard, provide a high‐level summary of the requirements, and share major updates and changes from previous combustible dust standards. Readers will gain an understanding of the requirements, learn what changes will need to be made to existing programs already in compliance with previous standards, and know how to navigate the standard to find the information they need to ensure safe operation of facilities processing and handling combustible dusts.

Abstract Currently, well integrity management in the hydrocarbon industry is highly relevant due to past incidents and process safety events caused by inadequate monitoring and control of asset integrity. In 2020, a high‐risk integrity condition was identified in a well in the Colombian Foothills, involving sustained pressure in two annulars from an external source and failure of the tubing hanger's secondary seals. The primary barrier was deemed ineffective, and the secondary barrier partially effective, posing a high risk of gas communication with annulars A and B, and potential external communication, risking fire and explosion. A remediation intervention was deemed necessary. A workover operation restored the barrier envelope status, using remedial cementing to isolate the annuli pressure source and a double production packing system to isolate open perforations. The well was successfully recompleted, restoring integrity at both surface and downhole levels, with tested secondary barriers. The operation restored well integrity as a gas injector, providing pressure support and recovery benefits to nearby wells, minimized risk conditions, and prevented containment loss and process safety incidents. Currently, primary and secondary seals are optimal, and annular pressure remains below operational limits.