Back to Search Start Over

vFirelib: A GPU-based fire simulation and visualization tool

Authors :
Rui Wu
Connor Scully-Allison
Chase Carthen
Andy Garcia
Roger Hoang
Christopher Lewis
Ronn Siedrik Quijada
Jessica Smith
Sergiu M. Dascalu
Frederick C. Harris, Jr.
Source :
SoftwareX, Vol 23, Iss , Pp 101411- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Wildfires are a common and devastating event that impacts ecosystems and communities yearly. Fire experts rely on simulations to better understand how to mitigate the damage they cause and respond to live threats. Many available fire simulation tools and libraries do not produce simulation results fast enough to be used with multiple parameter sets during an active fire and are difficult to integrate with other applications. To address this gap, we propose a GPU-based fire simulation and visualization tool: vFirelib. Using a GPGPU (General Purpose Graphics Processing Unit) framework, we can parallelize the fire spread computations and achieve a 20X computation speedup over a sequential implementation of a fire spread using a widely used fire spread model. To facilitate the integration with other applications, we implemented a wrapper including RESTful APIs to provide fire simulation as a service. In this paper, two examples are illustrated how to simulate wildfire scenarios and visualize results: a web-based application, and a 3D virtual reality application.

Details

Language :
English
ISSN :
23527110
Volume :
23
Issue :
101411-
Database :
Directory of Open Access Journals
Journal :
SoftwareX
Publication Type :
Academic Journal
Accession number :
edsdoj.062ba4bdde3a4c09b333255ad73e374c
Document Type :
article
Full Text :
https://doi.org/10.1016/j.softx.2023.101411