A multidisciplinary model coupling Lattice-Boltzmann-based CFD and a Social Force Model for the simulation of pollutant dispersion in evacuation situations

Marlow, Felix; Jacob, Jérôme; Sagaut, Pierre

doi:10.1016/j.buildenv.2021.108212

Cited by 23 publications

(6 citation statements)

References 35 publications

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“…Based on the research of domestic and foreign methods for model networking [14,33,34], the cruise ship was networked with different functional areas on the cruise ship, which was used to provide an application environment for the evacuation model. All the areas were cut according to the concave and convex shapes, and then a central node was set for all the cut areas to judge whether different areas were interconnected.…”

Section: Cruise Ship Model Networkingmentioning

confidence: 99%

Optimal Emergency Evacuation Route Planning Model Based on Fire Prediction Data

Deng

Zhang

et al. 2022

Mathematics

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For the emergency evacuation of cruise ships in case of sudden fire, this research proposes a dynamic route optimization method based on the improved A* algorithm for real-time information, in order to obtain the real-time optimal evacuation route. Initially, a basic network topology diagram is established according to the internal structure of the cruise ship. Before the occurrence of the accident, the A* algorithm can be applied to obtain an a priori evacuation network consisting of all the optimal routes from each node to the exit. At the time of the accident, the dynamic diffusion of fire can be simulated using Fire Dynamics Simulator (FDS) based on the preliminary information of the fire, so as to estimate the impact of the fire domain on each node of the network. Then, according to the fire dynamic diffusion data, the evacuation route planning is carried out by the improved A* algorithm applying the breadth-first search strategy, so as to determine the optimal route from the current node to the safety exit and to reduce the possibility of casualties due to the uncertainty of the fire during the evacuation. This model allows for both people’s safety and evacuation time to dynamically avoid fire-affected nodes and helps people to reach the safe area as soon as possible. Finally, the evacuation model is established according to the open-source cruise ship structure, and the evacuation process of people under the dynamic spread of cruise ship fire is simulated. The results show that the route planning method proposed in this research works out well in evacuating mass people, which can effectively reduce the evacuation time and improve the safety of the evacuation process.

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Section: Cruise Ship Model Networkingmentioning

confidence: 99%

Optimal Emergency Evacuation Route Planning Model Based on Fire Prediction Data

Deng

Zhang

et al. 2022

Mathematics

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“…The Social Force Model, first proposed by Helbing in 1995 and continuously developed in the future, is a pedestrian dynamic model recognized by most scholars [7][8][9][10][11][12][13][14]. Helbing [15][16] believes that "social force" is composed of three forces: self-driving force, others' force and boundary force, whose expression is as follows:…”

Section: The Social Force Modementioning

confidence: 99%

Review on Microscopic Model of Continuous Pedestrian Flow

Huang

Liu²

2022

JERR

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Continuous pedestrian flow micro model is an important method to study pedestrian flow at present. Compared with macro model and discrete model, continuous pedestrian flow micro model can better simulate pedestrian flow phenomenon. This paper summarizes the research significance and achievements of the continuous pedestrian flow micro model. The research contents and corresponding modeling methods of relevant models are mainly introduced, and the future development of pedestrian flow micro models is prospected.

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“…Unlike building environments, the internal space of large public transportation vehicles is narrow, and there are many obstacles, characterizing it as a special environment with a high personnel density, more obstacles, and stronger obstruction [4,[17][18][19][20][21][22]. When using social forces to drive high-density crowds to evacuate between obstacles in such an environment, it is difficult to simulate real crowd flow, bottleneck evolution, and frequent interaction conflicts and avoidance behaviors among personnel in multiple areas [23].…”

Section: Introductionmentioning

confidence: 99%

Research on Passenger Evacuation Behavior in Civil Aircraft Demonstration Experiments Based on Neural Networks and Modeling

Feng,

You,

Chen

et al. 2024

Aerospace

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Evacuation simulation is an important method for studying and evaluating the safety of passenger evacuation, and the key lies in whether it can accurately predict personnel evacuation behavior in different environments. The existing models have good adaptability in building environments but have weaker adaptability to personnel evacuation in civil aircraft cabins with more obstacles and stronger hindrances. We target the narrow seat aisle environment on airplanes and use a BP neural network to establish a continuous displacement model for personnel evacuation. We compare the simulation accuracy of evacuation time with the social force model based on continuous displacement and further compare the similarity of personnel evacuation process behavior. The results show that both models were close to the experimental values in simulating evacuation time, while our BP neural network evacuation model based on experimental data was more accurate in predicting the personnel evacuation process, showing more realistic details such as the probability of conflicts and bottleneck evolution in the cross aisle.

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A multidisciplinary model coupling Lattice-Boltzmann-based CFD and a Social Force Model for the simulation of pollutant dispersion in evacuation situations

Cited by 23 publications

References 35 publications

Optimal Emergency Evacuation Route Planning Model Based on Fire Prediction Data

Optimal Emergency Evacuation Route Planning Model Based on Fire Prediction Data

Review on Microscopic Model of Continuous Pedestrian Flow

Research on Passenger Evacuation Behavior in Civil Aircraft Demonstration Experiments Based on Neural Networks and Modeling

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