246 citations · 301 across the 5 of their papers we have counts for
6 papers
Virtual Foundry Graphnet for Metal Sintering Deformation Prediction
Rachel, Chen, Juheon Lee +4
Metal Sintering is a necessary step for Metal Injection Molded parts and binder jet such as HP's metal 3D printer. The metal sintering process introduces large deformation varying…
DMIS: Dynamic Mesh-based Importance Sampling for Training Physics-Informed Neural Networks
Zijiang Yang, Zhongwei Qiu, Dongmei Fu
Modeling dynamics in the form of partial differential equations (PDEs) is an effectual way to understand real-world physics processes. For complex physics systems, analytical solut…
A General Framework Combining Generative Adversarial Networks and Mixture Density Networks for Inverse Modeling in Microstructural Materials Design
Zijiang Yang, Dipendra Jha, Arindam Paul +3
Microstructural materials design is one of the most important applications of inverse modeling in materials science. Generally speaking, there are two broad modeling paradigms in s…
A real-time iterative machine learning approach for temperature profile prediction in additive manufacturing processes
Arindam Paul, Mojtaba Mozaffar, Zijiang Yang +4
Additive Manufacturing (AM) is a manufacturing paradigm that builds three-dimensional objects from a computer-aided design model by successively adding material layer by layer. AM…
IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery
Dipendra Jha, Logan Ward, Zijiang Yang +5
Materials discovery is crucial for making scientific advances in many domains. Collections of data from experiments and first-principle computations have spurred interest in applyi…
Microstructural Materials Design via Deep Adversarial Learning Methodology
Zijiang Yang, Xiaolin Li, L. Catherine Brinson +3
Identifying the key microstructure representations is crucial for Computational Materials Design (CMD). However, existing microstructure characterization and reconstruction (MCR) t…