3 papers
A geometry-aligned multi-fidelity framework for uncertainty quantification of wildfire spread
Konstantinos Vogiatzoglou, Costas Papadimitriou, Vasilis Bontozoglou +2
Forward propagation of input uncertainties in physics-based wildfire models is computationally prohibitive, limiting the use of high-fidelity simulators in risk assessment workflow…
Physics-informed neural networks for parameter learning of wildfire spreading
Konstantinos Vogiatzoglou, Costas Papadimitriou, Vasilis Bontozoglou +1
Wildland fires pose a terrifying natural hazard, underscoring the urgent need to develop data-driven and physics-informed digital twins for wildfire prevention, monitoring, interve…
An interpretable wildfire spreading model for real-time predictions
Konstantinos Vogiatzoglou, Costas Papadimitriou, Konstantinos Ampountolas +3
Forest fires pose a natural threat with devastating social, environmental, and economic implications. The rapid and highly uncertain rate of spread of wildfires necessitates a trus…