367 citations · 409 across the 13 of their papers we have counts for
5 papers · 1 filter
Model-Agnostic Hybrid Numerical Weather Prediction and Machine Learning Paradigm for Solar Forecasting in the Tropics
Nigel Yuan Yun Ng, Harish Gopalan, Venugopalan S. G. Raghavan +1
Numerical weather prediction (NWP) and machine learning (ML) methods are popular for solar forecasting. However, NWP models have multiple possible physical parameterizations, which…
CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method
Pao-Hsiung Chiu, Jian Cheng Wong, Chinchun Ooi +2
In this study, novel physics-informed neural network (PINN) methods for coupling neighboring support points and their derivative terms which are obtained by automatic differentiati…
U-Net-Based Surrogate Model For Evaluation of Microfluidic Channels
Quang Tuyen Le, Pao-Hsiung Chiu, Chin Chun Ooi
Microfluidics have shown great promise in multiple applications, especially in biomedical diagnostics and separations. While the flow properties of these microfluidic devices can b…
Surrogate Modeling of Fluid Dynamics with a Multigrid Inspired Neural Network Architecture
Quang Tuyen Le, Chin Chun Ooi
Algebraic or geometric multigrid methods are commonly used in numerical solvers as they are a multi-resolution method able to handle problems with multiple scales. In this work, we…
Improved Surrogate Modeling of Fluid Dynamics with Physics-Informed Neural Networks
Jian Cheng Wong, Chinchun Ooi, Pao-Hsiung Chiu +1
Physics-Informed Neural Networks (PINNs) have recently shown great promise as a way of incorporating physics-based domain knowledge, including fundamental governing equations, into…