Safety barrier performance assessment by integrating computational fluid dynamics and evacuation modeling for toxic gas leakage scenarios
نویسندگان
چکیده
Toxic gas leakage represents a type of major process accident scenario threatening human life. Technical and non-technical safety barriers are employed to prevent toxic accidents or mitigate the possible catastrophic consequences. Evacuation must be executed in severe release scenarios. The performance assessment technical evacuations these scenarios, although very important, has never been investigated previous studies. This paper proposes an approach integrating event tree analysis (ETA), computational fluid dynamics (CFD) simulation, evacuation modeling (EM), for risk chemical plants. In proposed approach, spatiotemporal distribution is predicted by CFD simulations. A dynamic determined cellular automaton (CA)-based model. Synergistic interventions resulting from considered assessment. Considering barrier failures analysis, individual fatality risks due scenarios calculated. For illustrative purposes, method applied case ammonia leakage. results show that worse would ignored without considering failure probabilities barriers, which can cause underestimated risks. Timely detection & alarm potential expedite starting time thus may shorten evacuees stay toxicity area reduce
منابع مشابه
Computational fluid dynamics simulation of the flow patterns and performance of conventional and dual-cone gas-particle cyclones
One of the main concerns of researchers is the separation of suspended particles in a fluid. Accordingly, the current study numerically investigated the effects of a conical section on the flow pattern of a Stairmand cyclone by simulating single-cone and dual-cone cyclones. A turbulence model was used to analyze incompressible gas-particle flow in the cyclone models, and the Eulerian–Lagrangian...
متن کاملComputational fluid dynamics simulations for investigation of parameters affecting goaf gas distribution
It is necessary to obtain a fundamental understanding of the goaf gas flow patterns in longwall mine in order to develop optimum goaf gas drainage and spontaneous combustion (sponcom) management strategies. The best ventilation layout for a longwall underground mine should assist in goaf gas drainage and further reduce the risk of sponcom in the goaf. Further, in the longwall panel, regulators ...
متن کاملSensing Performance of Sc-doped B12N12 Nanocage for Detecting Toxic Cyanogen Gas: A Computational Study
Adsorption of cyanogen molecule on the surface of pristine and Sc-doped B12N12 nanocage is scrutinized using at DFT calculations to investigating its potential as chemical nanosensors. The results show that cyanogen is weakly adsorbed on the pristine B12N12 and consequently its electrical properties are changed insignificantly. In order to improve the...
متن کاملHydrodynamic Improvement of underwater glider by Computational Fluid Dynamics method
Gliders are new marine vehicles which have research and military uses and they move by sequent diving and climbing. Suitable design of its main body and wings are important for the most advance velocity. hydrodynamic design variables are main body form, wings (cross section, dimensions, shape, longitudinal and vertical position) and hydrostatic parameters (static trim angle, amount of added for...
متن کاملCombining Computational Fluid Dynamics and Agent-Based Modeling: A New Approach to Evacuation Planning
We introduce a novel hybrid of two fields-Computational Fluid Dynamics (CFD) and Agent-Based Modeling (ABM)-as a powerful new technique for urban evacuation planning. CFD is a predominant technique for modeling airborne transport of contaminants, while ABM is a powerful approach for modeling social dynamics in populations of adaptive individuals. The hybrid CFD-ABM method is capable of simulati...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Reliability Engineering & System Safety
سال: 2022
ISSN: ['1879-0836', '0951-8320']
DOI: https://doi.org/10.1016/j.ress.2022.108719