5 papers
Droplet-LNO: Physics-Informed Laplace Neural Operators for Accurate Prediction of Droplet Spreading Dynamics on Complex Surfaces
Ganesh Sahadeo Meshram, Partha Pratim Chakrabarti, Suman Chakraborty
Spreading of liquid droplets on solid substrates constitutes a classic multiphysics problem with widespread applications ranging from inkjet printing, spray cooling, to biomedical…
Lattice-Boltzmann-Driven Physics-Informed Neural Networks for Droplet Wettability on Rough Surfaces
Ganesh Sahadeo Meshram, Partha Pratim Chakrabarti, Suman Chakraborty
We introduce a Lattice-Boltzmann-driven kinetic physics-informed neural network (K-PINN) for predictive modeling of droplet dynamics on structured surfaces, in which the discrete B…
-FlowNet: A Deep Learning Approach for Mapping Flow Fields in Irregular Microchannels Using an Attention-based U-Net Encoder-Decoder Architecture
Ganesh Sahadeo Meshram, Suman Chakraborty, Nishant Sinha +1
In the complex domain of microfluidics systems, analysing fluid flow patterns through random-shaped circular microchannels is significantly challenging task. Conventional approach…
Amalgamation of Physics-Informed Neural Network and LBM for the Prediction of Unsteady Fluid Flows in Fractal-Rough Microchannels
Ganesh Sahadeo Meshram, Partha Pratim Chakrabarti, Suman Chakraborty
One of the biggest challenges in the optimization of micro-scale fluid transport phenomena is the prediction of unsteady fluid flow in the presence of rough channel walls. Even tho…
Extending deep learning U-Net architecture for predicting unsteady fluid flows in textured microchannels
Ganesh Sahadeo Meshram, Partha Pratim Chakrabarti, Suman Chakraborty
In this study, we have explored an application of deep learning architecture of the U-Net model, originally designed for biomedical image segmentation, in a regression analysis aim…