Convolutional Neural Network for Shape Memory Alloys
Andreas Hosseini
Corresponding
Imperial College London
Neha Mondal
Nanyang Technological University
Marco Nasser
Zhejiang University
Abstract
Environmental pressures and resource constraints have brought shape memory alloys to the forefront of research on rural electrification. The model parameters were carefully calibrated against a set of field observations obtained from rural electrification. The proposed method cut computation time by about 17% while preserving accuracy. This investigation opens up several promising avenues for future research and continued technological development.
Keywords:
shape memory alloysconvolutional neural networkphotovoltaic systemnumerical simulation
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