28 citations · 46 across the 4 of their papers we have counts for
5 papers
Demystifying the Data Need of ML-surrogates for CFD Simulations
Tongtao Zhang, Biswadip Dey, Krishna Veeraraghavan +2
Computational fluid dynamics (CFD) simulations, a critical tool in various engineering applications, often require significant time and compute power to predict flow properties. Th…
Frequency-compensated PINNs for Fluid-dynamic Design Problems
Tongtao Zhang, Biswadip Dey, Pratik Kakkar +2
Incompressible fluid flow around a cylinder is one of the classical problems in fluid-dynamics with strong relevance with many real-world engineering problems, for example, design…
Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning
Yaofeng Desmond Zhong, Biswadip Dey, Amit Chakraborty
In this work, we introduce Dissipative SymODEN, a deep learning architecture which can infer the dynamics of a physical system with dissipation from observed state trajectories. To…
A Conditional Generative Model for Predicting Material Microstructures from Processing Methods
Akshay Iyer, Biswadip Dey, Arindam Dasgupta +2
Microstructures of a material form the bridge linking processing conditions - which can be controlled, to the material property - which is the primary interest in engineering appli…
InverseNet: Solving Inverse Problems with Splitting Networks
Kai Fan, Qi Wei, Wenlin Wang +2
We propose a new method that uses deep learning techniques to solve the inverse problems. The inverse problem is cast in the form of learning an end-to-end mapping from observed da…