1 citations · 3 across the 6 of their papers we have counts for
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Geometric and Topological Deep Learning for Predicting Thermo-mechanical Performance in Cold Spray Deposition Process Modeling
Akshansh Mishra
This study presents a geometric deep learning framework for predicting cold spray particle impact responses using finite element simulation data. A parametric dataset was generated…
Biomimetic Machine Learning approach for prediction of mechanical properties of Additive Friction Stir Deposited Aluminum alloys based walled structures
Akshansh Mishra
This study presents a novel approach to predicting mechanical properties of Additive Friction Stir Deposited (AFSD) aluminum alloy walled structures using biomimetic machine learni…
LatticeML: A data-driven application for predicting the effective Young Modulus of high temperature graph based architected materials
Akshansh Mishra
Architected materials with their unique topology and geometry offer the potential to modify physical and mechanical properties. Machine learning can accelerate the design and optim…
Transport Equation based Physics Informed Neural Network to predict the Yield Strength of Architected Materials
Akshansh Mishra
In this research, the application of the Physics-Informed Neural Network (PINN) model is explored to solve transport equation-based Partial Differential Equations (PDEs). The prima…