80 citations · 133 across the 15 of their papers we have counts for
19 papers
Interpretable Data-driven Methods for Subgrid-scale Closure in LES for Transcritical LOX/GCH4 Combustion
Wai Tong Chung, Aashwin Ananda Mishra, Matthias Ihme
Many practical combustion systems such as those in rockets, gas turbines, and internal combustion engines operate under high pressures that surpass the thermodynamic critical limit…
Heat transfer augmentation by recombination reactions in turbulent reacting boundary layers at elevated pressures
Nikolaos Perakis, Oskar Haidn, Matthias Ihme
A study of a reacting boundary layer flow with heat transfer at conditions typical for configurations at elevated pressures has been performed using a set of direct numerical simul…
Requirements Towards Predictive Simulations of Turbulent Reacting Flows
Matthias Ihme
Significant progress has been made on the model development for simulating turbulent reacting flows. As a consequence, we are currently in a position where key-physical aspects of…
A General Drag Coefficient for Flow over a Sphere
Narendra Singh, Michael Kroells, Chenxi Li +4
A generalized physics-based expression for the drag coefficient of spherical particles moving in a fluid is derived. The proposed correlation incorporates essential rarefied physic…
Convolutional LSTM Neural Networks for Modeling Wildland Fire Dynamics
John Burge, Matthew Bonanni, Matthias Ihme +1
As the climate changes, the severity of wildland fires is expected to worsen. Models that accurately capture fire propagation dynamics greatly help efforts for understanding, respo…
Deep Learning Models for Predicting Wildfires from Historical Remote-Sensing Data
Fantine Huot, R. Lily Hu, Matthias Ihme +6
Identifying regions that have high likelihood for wildfires is a key component of land and forestry management and disaster preparedness. We create a data set by aggregating nearly…