Application of Artificial Intelligence-Based Technique in Electric Motors: A Review
Electric motors find widespread application across various industrial fields. The pursuit of
enhanced comprehensive electric motors performance has consistently drawn significant …
enhanced comprehensive electric motors performance has consistently drawn significant …
Deep neural network modeling for CFD simulations: Benchmarking the Fourier neural operator on the lid-driven cavity case
In this work we present the development, testing and comparison of three different physics-
informed deep learning paradigms, namely the ConvLSTM, CNN-LSTM and a novel Fourier …
informed deep learning paradigms, namely the ConvLSTM, CNN-LSTM and a novel Fourier …
PIX-GAN: Enhance Physics-Informed Estimation via Generative Adversarial Network
Worldwide urbanization requires control systems to accommodate uncertain sources, eg,
wind and solar generations in the energy sector. This uncertainty poses significant …
wind and solar generations in the energy sector. This uncertainty poses significant …
Physics Informed Neural Network for thermal modeling of an Electric Motor
J Stensson, K Svantesson - 2023 - odr.chalmers.se
Artificial intelligence and machine learning are becoming increasingly significant, and the
need to investigate the potential for different areas arises. This project investigated the …
need to investigate the potential for different areas arises. This project investigated the …
Data-Driven Methods for Design and Analysis of Electromagnetic Devices
Electromagnetic devices, such as electrical drive systems for electric vehicles, have been
widely employed in domestic and industrial equipment. In the context of Industry 4.0, their …
widely employed in domestic and industrial equipment. In the context of Industry 4.0, their …