3 papers
physics.comp-ph2026
Machine Learning-Driven Chemical Reactor Network Modeling of the Sandia-D Flame
Nicolas J. Tricard, Benjamin C. Koenig, Sili Deng
Turbulent combustion simulations are crucial for many scientific and engineering systems. However, the high cost to fully resolve the complex multiscale and multiphysics behavior m…
cs.CV2026
3-D Representations for Hyperspectral Flame Tomography
Nicolas Tricard, Zituo Chen, Sili Deng
Flame tomography is a compelling approach for extracting large amounts of data from experiments via 3-D thermochemical reconstruction. Recent efforts employing neural-network flame…
cs.LG2026
GLU: Global-Local-Uncertainty Fusion for Scalable Spatiotemporal Reconstruction and Forecasting
Linzheng Wang, Jason Chen, Nicolas Tricard +2
Digital twins of complex physical systems are expected to infer unobserved states from sparse measurements and predict their evolution in time, yet these two functions are typicall…