Development of a model to generate a risk map in a building fire

Chu, Ying; Zhang, Hui; Shen, Shifei; Yang, Rui; Qiao, Lifeng

doi:10.1007/s11431-010-4063-8

Cited by 13 publications

(5 citation statements)

References 10 publications

(6 reference statements)

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“…via mobile device or dynamic signposts) [8][9][10]. This evacuation planner accounts for the location of hazards and produces evacuation routes that minimize evacuation time and exposure to the hazard.…”

Section: Route Allocationmentioning

confidence: 99%

Problem Decomposition for Evacuation Simulation Using Network Flow

Murphy

Brown

Sreenan

2012

2012 IEEE/ACM 16th International Symposium on Distributed Simulation and Real Time Applications

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Abstract. Simulation of building evacuations can be a powerful tool for predicting evacuation outcomes, but for this prediction to be useful it must be produced in a timely manner. The building evacuation outcomes are dependent on the movement decisions of the occupants, but simulating all possible combinations of occupant decisions is infeasible. Our contribution is a novel technique using building structure knowledge in the form of a Network Flow Graph to determine where and when occupants might interact with one another. We decompose the problem into non-interacting groups, to be simulated separately, which leads to a significant simulation workload reduction.Keywords: evacuation monitoring, multi-agent simulation, distributed simulation, network flow graph, problem decomposition IntroductionSimulation of building evacuation during emergencies is a powerful tool for evaluating building safety and prediction of evacuation outcomes [1]. Simulating the movement of evacuating pedestrians can provide useful information to building designers and to fire safety officials, including evacuation time estimates and locations at risk of traffic congestion or evacuee injury [1][2][3][4][5][6][7]. We make use of a 2D vector-space pedestrian simulator to simulate the individual movements of pedestrians in the building. This simulator provides a realistic model of pedestrian movement but is computationally intensive compared to simpler models such as Cellular Automata [2,4,10] or Graph-based simulations [5]. The usefulness of any prediction information is contingent on both the timeliness and the accuracy of the simulation that generated it. Since a real evacuation involves autonomous human actors and uncertain hazard spread, to ensure that the simulations cover likely scenarios we must run many different scenarios. The more we can reduce the simulation time, the more scenarios we can consider, and the more useful the results will be. In this paper, we investigate the problem of how to cover a wide range of scenarios without an excessive increase in computation time.We assume that clusters of individuals in an evacuation will behave as a group, and once they have formed a group all members will follow the same route out of the building. We reduce the amount of simulation by limiting our attention to the most likely routes for each initial group. However, different groups may meet during the evacuation and cause congestion, and may form into larger groups to continue the evacuation. Since congestion slows down the evacuation, and puts the participants at risk, we must investigate the interaction of the different groups. Even for small numbers of likely routes, this group interaction quickly produces an excessively large simulation space. We reduce the complexity of the problem by quickly generating possible group interactions using Network-Flow Graph analysis, identifying groups and routes which do not interact, distributing the simulation of those local scenarios to different processors, and then combining the results to pro...

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Section: Route Allocationmentioning

confidence: 99%

Problem Decomposition for Evacuation Simulation Using Network Flow

Murphy

Brown

Sreenan

2012

2012 IEEE/ACM 16th International Symposium on Distributed Simulation and Real Time Applications

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“…In order to implement the modeling method, an H = \l\, P 2 , P 3 , P 4 , P 5 } is defined as a set of composable IA, which is used to describe the control-oriented abstraction [29] model of the safety protocols. P u P 5 are used to describe the safety service users of the two sides of communication respectively.…”

Section: Modeling the Safety Protocols Using Iamentioning

confidence: 99%

“…If cycles can be found not to have this property, the verifier can declare the existence of a nonprogress loop, corresponding to possible starvation. 4 Case study: verification of a safety protocol…”

Section: Properties Verificationmentioning

confidence: 99%

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Formal verification of safety protocol in train control system

Zhang

Tang

et al. 2011

Sci. China Technol. Sci.

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In order to satisfy the safety-critical requirements, the train control system (TCS) often employs a layered safety communication protocol to provide reliable services. However, both description and verification of the safety protocols may be formidable due to the system complexity. In this paper, interface autómata (IA) are used to describe the safety service interface behaviors of safety communication protocol. A formal verification method is proposed to describe the safety communication protocols using IA and transíate IA model into PROMELA model so that the protocols can be verified by the model checker SPIN. A case study of using this method to describe and verify a safety communication protocol is included. The verification results illustrate that the proposed method is effective to describe the safety protocols and verify deadlocks, hvelocks and several mandatory consistency properties. A prototype of safety protocols is also developed based on the presented formally verifying method.train control system, safety communication protocol, interface autómata, verification Citation:Zhang Y, Tang T, Li K P, et al. Formal verification of safety protocol in train control system.

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“…To assess management platform is vulnerable or not, and improve the risk assessment about the software and hardware. [4] First, the study combines the business information systems and related inventory data of Ching Yun University. Second, the important meetings of competent department confirm the priority order aim on the important system or data analysis.…”

Section: Risk Factors Calculationmentioning

confidence: 99%

The Database of Facilities Asset Management Application in the Disaster Reduction – Case Study of Ching Yun Building in Ching Yun University

Shiu

Sung²,

Lin

et al. 2011

AMR

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The study analysis the disaster risk using the asset management database of Ching Yun University. The study proposed the risk factors of calculation and process in different disaster. Disaster of highest frequency in history of Ching Yun University is fire disaster and artificial mistake. The risk value was been calculated from the facilities and personnel on each floor. The risk analysis results show that the badly need of improvement floors is 3F, 6F and 8F. There is the highest risk value of personnel and facilities in 3F. This study proposes four improving options to reduce the casualties of the two dangerous situations occurrence. The analysis method of risk assessment used in this study is suitable for the general building to use to plan escape routes but the database should be set first.

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Development of a model to generate a risk map in a building fire

Cited by 13 publications

References 10 publications

Problem Decomposition for Evacuation Simulation Using Network Flow

Problem Decomposition for Evacuation Simulation Using Network Flow

Formal verification of safety protocol in train control system

The Database of Facilities Asset Management Application in the Disaster Reduction – Case Study of Ching Yun Building in Ching Yun University

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