238 citations · 1.9k across the 126 of their papers we have counts for
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Graph Convolutional Neural Networks for Body Force Prediction
Francis Ogoke, Kazem Meidani, Amirreza Hashemi +1
Many scientific and engineering processes produce spatially unstructured data. However, most data-driven models require a feature matrix that enforces both a set number and order o…
Data-driven Identification of 2D Partial Differential Equations using extracted physical features
Kazem Meidani, Amir Barati Farimani
Many scientific phenomena are modeled by Partial Differential Equations (PDEs). The development of data gathering tools along with the advances in machine learning (ML) techniques…
Deep Learning for Efficient Reconstruction of High-Resolution Turbulent DNS Data
Pranshu Pant, Amir Barati Farimani
Within the domain of Computational Fluid Dynamics, Direct Numerical Simulation (DNS) is used to obtain highly accurate numerical solutions for fluid flows. However, this approach f…
FaultNet: A Deep Convolutional Neural Network for bearing fault classification
Rishikesh Magar, Lalit Ghule, Junhan Li +2
The increased presence of advanced sensors on the production floors has led to the collection of datasets that can provide significant insights into machine health. An important an…
Orbital Graph Convolutional Neural Network for Material Property Prediction
Mohammadreza Karamad, Rishikesh Magar, Yuting Shi +3
Material representations that are compatible with machine learning models play a key role in developing models that exhibit high accuracy for property prediction. Atomic orbital in…
Reduced Thermal Conductivity of Supported and Encased Monolayer and Bilayer MoS
Alexander J. Gabourie, Saurabh V. Suryavanshi, Amir Barati Farimani +1
Electrical and thermal properties of atomically thin two-dimensional (2D) materials are affected by their environment, e.g. through remote phonon scattering or dielectric screening…