Machine Learning Techniques for Data Reduction of CFD Applications

arXiv:2404.18063v1 Announce Type: new
Abstract: We present an approach called guaranteed block autoencoder that leverages Tensor Correlations (GBATC) for reducing the spatiotemporal data generated by computational fluid dynamics (CFD) and other scientific applications. It uses a multidimensional block of tensors (spanning in space and time) for both input and output, capturing the spatiotemporal and interspecies relationship within a tensor. The tensor consists of species that represent different elements in a CFD simulation. To guarantee the error bound of the reconstructed …

abstract applications arxiv autoencoder block cfd computational correlations cs.lg data data reduction dynamics fluid dynamics generated machine machine learning machine learning techniques multidimensional scientific space space and time tensor type