CORDIS
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Emergency Decision Support System of Offshore Platform Fires

Emergency Decision Support System of Offshore Platform Fires

Objective

In this project, fire accidents on offshore oil and gas platform will be analysed to identify the typical fire scenarios, followed by numerical simulation on the temporal and spatial evolution of the fires. Secondly, the coupling mechanism between human behavior and fire development will be investigated to quantitatively characterize the impact of fire on people and other assets. Thereafter, based on fire numerical simulation and multi-agent theory, an evacuation simulation model of offshore platform fires will be proposed. Thirdly, the dynamic risk of offshore platform fire evacuation will be evaluated by considering both failure consequences and their probabilities. A risk warning model of offshore platform fire evacuation will be built based on the Wavelet Genetic Neural Network. Finally, a dynamic decision-making support system for fire emergency evacuation will be designed by integrating Computation Fluid Dynamic (CFD), multi-agent theory and the Virtual Reality (VR) technology.
This project covers a wide range of disciplines including CFD, multi-agent-based evacuation simulations, probabilistic inference (Bayesian inference and system dynamic model) and the VR technology. This Individual Fellowship will significantly accelerate the development of interdisciplinary knowledge, innovative research skills and new career of the nominated Fellow.
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Coordinator

LIVERPOOL JOHN MOORES UNIVERSITY

Address

Rodney Street 2 Egerton Court
L3 5ux Liverpool

United Kingdom

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 224 933,76

Project information

Grant agreement ID: 840425

Status

Grant agreement signed

  • Start date

    20 December 2019

  • End date

    19 December 2021

Funded under:

H2020-EU.1.3.2.

  • Overall budget:

    € 224 933,76

  • EU contribution

    € 224 933,76

Coordinated by:

LIVERPOOL JOHN MOORES UNIVERSITY

United Kingdom