The paper “Dynamic analysis for prediction of flow patterns in an oscillatory baffled reactor using machine learning,” published by Professor Matsumoto’s group at Tokyo University of Science, reports analyses conducted using Multi-Sigma®.
The study analyzes spatiotemporal data of flow fields. Because CFD prediction of unsteady flows is computationally demanding, the authors employed a neural network model to perform the analysis within a practical computation time. Multi-Sigma® was used to build the neural network model and analyze data.
For details, please refer to the paper below.
[Paper Information]
Title: Dynamic analysis for prediction of flow patterns in an oscillatory baffled reactor using machine learning.
Authors: Hideyuki Matsumoto et al.
Journal: Systems and Control Transactions (2025): 394-398.
Year: 2025
DOI：https://doi.org/10.69997/sct.101931
