Journal of Loss Prevention in The Process Industries最新文献

Conventional safety analyses in complex systems like air separation units (ASUs) often attributed accidents to linear, deterministic causes, such as operator error. However, acknowledging the intricate interdependence of process components necessitates a shift towards recognizing the complexity of incident causation. This study proposes a novel model that integrates Function Resonance Analysis Method (FRAM) and fuzzy logic analysis to address this growing need. The model facilitates the identification of emerging risks and assesses the impact of influential factors within a mixed qualitative and quantitative framework. The FRAM method is initially employed to identify emerging risks within the ASU. Subsequently, fuzzy multi-criteria decision-making methods are utilized to establish the relationships and weightage of influential factors. Data collection encompasses semi-structured interviews, direct observation, process workflow analysis, and the involvement of a panel of engineers and operators from the investigated ASU. Utilizing FMV software for FRAM analysis, functions associated with air compression, distribution, and storage exhibit high resonance. This signifies substantial variability and a heightened potential for incidents or deviations in these functions and higher-level tasks. Furthermore, Fuzzy TOPSIS analysis reveals that education and experience emerge as the most impactful factors governing newly emerging risk. This model demonstrates significant merit for risk assessment and incident investigation. Its non-linear and dynamic nature empowers the proactive identification and examination of processes, incidents, and emerging risks before deviations or accidents occur.

Medical and fire resources are scheduled to chemical industrial parks which have caused mass casualties due to accidents. However, most of models of emergency logistics do not account for pre-rescue before large-scale rescue which may increase the casualty rate because of the long emergency response time and distance. This paper presents a mathematical model proposed for optimal distribution of emergency resources for rescuing the trapped victims who are highly likely to be seriously injured or even killed before the arrival of ambulances and fire engines. Due to the different types and risks of accidents at various locations have different impacts on people, we consider the detailed characteristics of accident scenarios and maximum tolerance time for the trapped victims to determine the priority of rescue sites. In addition, this paper proposes two indices of pavement resistance coefficient and obstacle to reflect the environment after accidents, which are not involved in other models of emergency resources distribution. Based on these, a penalty cost objective function is established to maximize the rescue rate. The optimal delivery route which reflects the distribution process is planned for the robot that will save more casualties. Two simulations and a real accident case study were conducted by minimizing the objective function, and the numerical results showed the reliability and effectiveness of the presented model for making optimal decisions for emergency distribution to accidents in chemical industrial parks.

Historical data has shown that the natural gas pipeline network, as a critical urban lifeline system, is susceptible to disasters such as earthquakes resulting in leakage. Graph neural network modeling provides frontier rapid detection solutions for pipeline leakage; however, the challenges of collecting gas network anomaly data for training limit the precision and robustness of current model. This research proposes an unsupervised gas leakage detection and localization method based on a contained preprocessing process, with a graph deviation model that combines a structural learning approach with a graph neural network to model the spatial dependence of the sensors based on an attention mechanism, and variational inference models the posterior distributions of the hyper-parameters to optimize the model and improve the model precision. Meanwhile, in the preprocessing stage, the automatic optimization strategy of Northern Goshawk Optimization (NGO) for the best parameters K and ɑ in the Variable Mode Decomposition (VMD) efficiently extracts the valid signals and ensures that the model gives full play to the detection and localization effectiveness. The gas pipeline network dataset constructed by Pipeline Studio was used for comparing the performance of the model in this study with other frontier models. The results demonstrate that the model in this research has competitive detection Precision (93.31%), Recall (70.82%), and F1-score (0.81), and the posterior distribution of the model parameters strengthens the gas leakage localization precision, which provides a comprehensive solution for subsequent decision-making and reduces the hidden hazard of leakage effectively.

When the sour gas is transported through the pipeline, the active sulfur in it will corrode the inner wall of the pipeline, forming pyrophoric iron sulfides which will be attached to the pipe wall or move downstream with the transportation medium, and eventually spread throughout the whole pipeline transportation system. When the pipeline is corroded and perforated or in the state of pipeline shutdown and disassembly, if there is negative pressure inside the pipeline, the pyrophoric iron sulfides will contact the incoming air and be oxidized to spontaneous combustion. At this time, if there are substances with combustion or explosion tendency in the pipeline gathered around the pyrophoric iron sulfides that occur spontaneous combustion, major safety accidents such as fire or even explosion are easy to happen, which seriously threaten the safe operation of long-distance gas transmission system. Generally speaking, the greater the accumulation of corrodes inside the pipe, the higher the probability of spontaneous combustion will be due to their contact with oxygen. However, when pyrophoric iron sulfides occur oxidation to spontaneous combustion, it is difficult to be directly perceived from outside the pipe and can only be determined by indirect measurement based on the temperature change of the pipe wall. Therefore, in order to predict the accumulation of pyrophoric iron sulfides inside the pipeline and find out the temperature change of the pipe wall during the spontaneous combustion of pyrophoric iron sulfides inside the pipeline, based on theoretical analysis and computer numerical simulation method, this paper firstly used COMSOL Multiphysics software to build the corrosion model of pyrophoric iron sulfides inside the pipeline and the heat transfer model of pyrophoric iron sulfides inside the pipeline during spontaneous combustion and verify the feasibility of the model; Then, based on the actual operation condition of the long gas transmission pipeline, the formation process of the pyrophoric iron sulfides on the inner wall of the pipeline was simulated, and the heat transfer process of the pipe wall was simulated during oxidative spontaneous combustion of pyrophoric iron sulfides under different factors; after that, according to the simulation results, the corrosion law of the inner wall of the pipe and the heat transfer law of the pipe wall when the pyrophoric iron sulfides occur in oxidation spontaneous combustion were analyzed. The influence of different influencing factors on the heat transfer process of the pipe and their synergistic coupling effect was discussed. Thus, it provides a theoretical basis for early intervention in the oxidation and spontaneous combustion of iron sulfide corrosion products through abnormal temperature monitoring during the shutdown period of the pipeline.

High-pressure pipelines that transport sour natural gas contain high levels of hydrogen sulfide, which is poisonous and has irreparable effects on human health even in low concentrations. These pipes are break valve-assisted and buried underground to minimize gas leakage and protect people nearby. This study examines their leakage through a series of time-dependent three-dimensional CFD simulations. In contradiction of previous works that only considered the above-ground environment, here, for more realism, the computational domain includes the pipeline, trench, covering soil, and above-ground environment. The impact of hole size, leak location on the pipe, wind velocity, atmospheric stability class, time of occurrence (day or night), and the presence of break valves on the dispersion of leaked gas are comprehensively investigated. Results indicate that the effect of hole diameter on hydrogen sulfide concentration in the above-ground environment is dominant to other factors. In addition, the probability of fatality due to gas release and the intensity of the gas leak exposure crisis are studied by combining the dose-response model and CFD simulation results. In this line, LT₅₀, which measures how long it takes for 50% of people in different areas around the pipeline to die from exposure to hydrogen sulfide is calculated.

The effect of inertial vent covers on deflagrations of fast-burning gases, such as hydrogen, has received limited attention, and recommendations for their safe venting are unavailable. To this end, experiments on vented explosion of H₂/air mixtures, ignited from the center of a 1-m³ chamber with a top vent covered by hinged aluminum plates of various surface densities ($W_s$), were performed at initial temperatures and pressures of 290 K and 100 kPa to investigate the effects of $W_s$ on the flame evolution and pressure profile within and outside the vented vessel. Three pressure sensors (PS1-PS3) were used to record internal overpressure and another pressure sensor (PS4) was employed to monitor external overpressure. Current tests showed some unexpected results, which were inconsistent with previous research and available models. In this study, $P_{\max }$, $P_{red}$, and $P_{ext}$ are focused on; $P_{\max }$ refers to the maximum internal overpressure recorded by PS1-PS3, $P_{red}$ represents the highest $P_{\max }$ monitored by PS1-PS3 for a certain $W_s$, and $P_{ext}$ denotes the maximum external overpressure obtained by PS4. Experimental results reveal that for a given $W_s$ , the highest and lowest $P_{\max }$ are always observed at the bottom and the center of the chamber, respectively. With the increase of $W_s$ from 0 to 18.9, $P_{ext}$ first increases and then decreases, and it reaches its highest value when $W_s$ is increased to 8.1 kg/m². As $W_s$ increases from 0 to 18.9, $P_{red}$ first increases with $W_s$ and reaches its maximum of 93 kPa at