Predictive Data-Driven Model Based on Generative Adversarial Network for Premixed Turbulence-Combustion Regimes
Author:
Affiliation:
1. Institute for Combustion Technology, Rwth Aachen University 52056 Aachen, Germany
2. Institute for Multiscale Thermofluids, School of Engineering, University of Edinburgh, Edinburgh, EH9 3FD, United Kingdom
Publisher
Informa UK Limited
Subject
General Physics and Astronomy,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry
Link
https://www.tandfonline.com/doi/pdf/10.1080/00102202.2022.2041624
Reference68 articles.
1. Turbulence–flame interactions in lean premixed hydrogen: transition to the distributed burning regime
2. Some Aspects of Scalar Dissipation
3. Vorticity transformation in high Karlovitz number premixed flames
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1. A generative adversarial network (GAN) approach to creating synthetic flame images from experimental data;Energy and AI;2023-07
2. Investigation of the generalization capability of a generative adversarial network for large eddy simulation of turbulent premixed reacting flows;Proceedings of the Combustion Institute;2022-09
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