Prediction of wildland-urban interface fires using a digital twin
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The feasibility of using a digital twin for the prediction of the wildland-urban interface fires was studied. The wildfire ignition and spread were investigated for a cultural site (Lecture Hall of Sosu Confucian Academy in Youngju, South Korea) using the Wildland-Urban Interface Fire Dynamics Simulator (WFDS). The vegetation and building information were obtained using aerial LiDAR imaging. The ground and aerial photographs validated the captured fuel and building information in terms of their sizes and distributions. The validated fuel and building information were conveyed to a digital twin domain for computational fluid dynamics calculation. A parametric study was performed for various ignition locations, atmospheric conditions (wind speed, direction, humidity), and moisture contents. Based on the prediction results, fuel treatments were suggested to prevent the ignition of the buildings by wildfire. The study showed that using a digital twin could provide a reasonable prediction for the wildfire spread at the wildland-urban interface, and the prediction results could serve as guidelines for wildfire spread prevention activities. The use of a digital twin for wildfire spread prediction will be further investigated for more test sites and fuel conditions.
Keywords: Climate change, Research
ID: 3617379