5 papers
Scalable Physics-Informed Neural Differential Equations and Data-Driven Algorithms for HVAC Systems
Hanfeng Zhai, Hongtao Qiao, Hassan Mansour +1
We present a scalable, data-driven simulation framework for large-scale heating, ventilation, and air conditioning (HVAC) systems that couples physics-informed neural ordinary diff…
Learning Interatomic Force Coefficients from X-ray Thermal Diffuse Scattering Data
Klara Suchan, Shaswat Mohanty, Hanfeng Zhai +1
We present a fully automated framework for extracting interatomic force constants (IFCs) directly from X-ray thermal diffuse scattering (TDS) data. By formulating scattering intens…
Atomistic and data-driven insights into the local slip resistances in random refractory multi-principal element alloys
Wu-Rong Jian, Arjun S. Kulathuvayal, Hanfeng Zhai +5
Refractory multi-principal element alloys (RMPEAs) have attracted growing interest for their exceptional high-temperature strength, yet their complex compositions hinder a mechanis…
Link Statistics of Dislocation Network during Strain Hardening
Sh. Akhondzadeh, Hanfeng Zhai, Wurong Jian +3
Dislocations are line defects in crystals that multiply and self-organize into a complex network during strain hardening. The length of dislocation links, connecting neighboring no…
Stress Predictions in Polycrystal Plasticity using Graph Neural Networks with Subgraph Training
Hanfeng Zhai
Numerical modeling of polycrystal plasticity is computationally intensive. We employ Graph Neural Networks (GNN) to predict stresses on complex geometries for polycrystal plasticit…