Physical-informed random field technique for virtual modelling based building probabilistic vulnerability assessment
Year: 2025
Type: article
Abstract: • PIRF considers spatiotemporally variable rural environments in bushfire simulation. • The virtual modelling facilitates the quick prediction of large-scale bushfire. • The transportation infrastructure is considered in the vulnerability assessment. • A probabilistic vulnerability assessment is developed for bushfire-safety buildings. Developing a probabilistic vulnerability assessment framework for bushfire-prone buildings is a critical measure to reduce bushfire-induced risks to life safety and economic losses to an acceptable level. A reliable assessment approach should include multiple probability-based macro indicators by considering their inherent uncertainties. These macro indicators can incorporate the efficiency of bushfire-damaged transportation network at specified moments, the geographical position of buildings, among others. A Physics-Informed Random Field-Virtual Modelling (PIRF-VM) framework for probabilistic vulnerability assessment of bushfire-prone buildings in large-scale bushfire incidents is proposed. The PIRF generates a random field-based, multi-physical information-fusion model for the simulation of bushfire spread in a large-scale approximate natural environment. The integrated physical information includes the spatially varying vegetation characteristics, the Digital Elevation Model (DEM)-based terrain, the terrain-shaped time-dependent wind field, the geographical coordinates of roads and buildings. To mitigate the computational burden posed by stochastic bushfire simulations in PIRF, the VM is introduced. It can establish an explicit functional relationship between input physical information and output responses of interest, such as the remaining time for bushfire reaching a specified location. As a result, for any new input physical information, the output responses can be directly predicted without time-consuming simulations. Benefiting from the efficient predictions of the PIRF-VM, several probability-based macro indicators are simultaneously considered when assessing the probabilistic vulnerability for bushfire-prone buildings in large-scale bushfire incidents. The Australian community of Cowan serves as an example to illustrate the practical application of the proposed scheme, demonstrating potential in constructing more bushfire-resilient communities in the face of bushfire hazards.
Source: Structural Safety
Authors: Zhiyi Shi, Yuan Feng, Mark G. Stewart, Wei Gao
Institutions: UNSW Sydney, University of Technology Sydney
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $4,430
Awards: Topological Design of Mechanical Meta-Structures, ARC Industry Transformation Research Hub for Resilient and Intelligent Infrastructure Systems (RIIS) in Urban, Resources and Energy Sectors, ARC Research Hub for Transformation of Reclaimed Waste Resources to Engineered Materials and Solutions for a Circular Economy, Experiment-numerical-virtual Generative Design for Nondeterministic Impacts
OpenAlex ID: W4408566629