Ground influence on high-pressure methane jets: Practical tools for risk assessment

High-pressure gaseous methane release is a relevant safety-related problem mainly in the Oil and Gas industry. As well documented, the reason for these safety concerns is connected with the severe consequences of the domino effect subsequent to the possible ignition. In risk assessment activities, estimation of the damage area is of primary importance in order to draw up proper safety guidelines. To do this, loss prevention specialists use quick and well-established numerical tools (i.e., integral models) in their daily activities. However, the presence of an obstacle in the flow field of the jet (e.g., the ground) is a more probable situation to deal with. It is known that integral models fail in this kind of scenario, leading to unreliable predictions. Hence, the present work investigates how an industrial ground surface influences the LFL cloud size of a horizontal high-pressure methane jet. An innovative quick procedure is proposed allowing to determine the height below which the ground begins to influence the LFL cloud size and the extent of such influence. Therefore, this procedure allows practitioners to establish when integral models can be used and when not to use them, and also provides a simple and reliable alternative to their use. These analytical instruments are derived from an extensive computational fluid dynamics analysis performed with Ansys Fluent 19.0.     

Development of inherent safety and health index for formulated product design

The numerous formulated products which are introduced to the market consist of chemical ingredients that may cause various safety and health hazards to the consumers. Therefore, it is extremely important to practice a systematic methodology to formulate products with acceptable safety and health performances. This work presents an index-based methodology to assess the safety and health hazards of the ingredients during the early formulation stage of product design. Hence, new inherent safety and health sub-indexes are introduced to improve the current safety and health hazards that are needed in formulated product design. The inherent safety and health sub-indexes are assigned with scores based on the degree of potential hazards. A higher score indicates a higher safety risk or severe health effect, and vice versa. The proposed methodology will greatly assist the users to identify the adverse safety and health effects caused by the ingredients. Hence, it is pivotal to eliminate or reduce the safety and health impacts from product usage. A case study on common ingredients used in the formulation of paint is presented on this study to describe the proposed method.     

Unignited High-Pressure Methane Jet Impinging a Pipe Rack: Practical Tools for Risk Assessment

Although the diffusion of its storage and transport under liquefied conditions, nowadays it is common to have methane in gaseous form in several industrial applications. This leads to safety implications to be considered: hazards are linked to both the high-pressure at which the gas is kept and to its flammability. Scenarios where flammable jets impact an obstacle are of paramount importance because of their possible occurrence. Following a numerical approach, literature shows up that their assessment can be reliably performed by means of only Computational Fluid Dynamics tools. However, despite the improvements of computing power, Computational Fluid Dynamics costs still limit its use in daily risk analysts’ activities. Therefore, considering an accidental jet-obstacle scenario of industrial interest, the present work investigates how a pipe rack can influence the development of a high-pressure methane jet. Based on a Computational Fluid Dynamics analysis, main achievements of this work are a simple criterion able to identify the situations where the pipe rack does not influence the high-pressure methane jet behavior, therefore allowing to identify the scenarios where simpler models can be used (i.e., analytical correlations known for the free jet situation), and, if present, a simple analytical relationship that roughly predicts the influence of the pipe rack without the need of performing complex Computational Fluid Dynamics simulations.     

An improved grey wolf optimizer algorithm for identification and location of gas emission

Identification of the leakage of hazardous gases plays an important role in the environment protection, human health and safety of industry production. However, lots of current optimization algorithms, such as particle swarm optimization (PSO) and Grey Wolf Optimizer (GWO), suffer from poor global optimization capability and estimation accuracy. In this work, a hybrid differential evolutionary and GWO (DE-GWO) algorithm is proposed. Tested by simulation cases and Prairie Grass emission experimental data, DE-GWO shows higher estimation accuracy than GWO. Compared with the other four optimization algorithms, DE-GWO exhibits finer robust stability under different population sizes, fewer iterations, as well as higher estimation accuracy with fewer search agents. Importantly, simulation results demonstrate that DE-GWO is more suitable to apply in the scene with a small number of sensors. Therefore, the proposed in this paper outperforms other optimization algorithms for the gas emission inverse problem. DE-GWO can provide reliable estimation towards gas emission identification and positioning, which shows huge potential as the data analysis module of real-time monitoring and early warning system.     

Resilience-based approach to safety barrier performance assessment in process facilities

The performance assessment of safety barriers is essential to find vulnerable elements in a safety barrier system. Traditional performance assessment approaches mainly focus on using several static indicators for quantifying the performance of safety barriers. However, with the increasing complexity of the system, emerging hazards are highly uncertain, making it challenging for the static indicators to assess the performance of safety barriers. This paper proposes a resilience−based performance assessment method for safety barriers to overcome this problem. Safety barriers are classified according to their functions first. The dynamic Bayesian network (DBN) is then introduced to calculate the availability function under normal and disruption conditions. The ratio of the system's availability, when affected by the disruption, to the initial availability, is used to determine the absorption capacity of the system. The ratio of the quantity of availability recovery to the total quantity of system represents the adaptation and restoration capacity of the system. The system's resilience is represented by the sum of absorption, adaptation, and restoration capacities. The wax oil hydrogenation process is used to demonstrate the applicability of the proposed methodology.