[HTML][HTML] Physics-aware recurrent convolutional neural networks for modeling multiphase compressible flows
Multiphase compressible flow systems can exhibit unsteady and fast-transient dynamics,
marked by sharp gradients and discontinuities, and material boundaries that interact with the …
marked by sharp gradients and discontinuities, and material boundaries that interact with the …
[HTML][HTML] SAG's Overload Forecasting Using a CNN Physical Informed Approach
The overload problem in semi-autogenous grinding (SAG) mills is critical in the mining
industry, impacting the extraction of valuable metals and overall productivity. Overloads can …
industry, impacting the extraction of valuable metals and overall productivity. Overloads can …
FLRNet: A Deep Learning Method for Regressive Reconstruction of Flow Field From Limited Sensor Measurements
Many applications in computational and experimental fluid mechanics require effective
methods for reconstructing the flow fields from limited sensor data. However, this task …
methods for reconstructing the flow fields from limited sensor data. However, this task …