LAPSE:2023.23975v1
Published Article
LAPSE:2023.23975v1
Laminar Burning Velocity Model Based on Deep Neural Network for Hydrogen and Propane with Air
March 27, 2023
The aim of the study was to develop deep neural network models for laminar burning velocity (LBV) calculations. The present study resulted in models for hydrogen−air and propane−air mixtures. An original data-preparation/data-generation algorithm was also developed in order to obtain the datasets sufficient in quality and quantity for models training. The discussion about the current analytical models highlighted issues with both experimental data and methodology of creating those analytical models. It was concluded that there is a need for models that can capture data from multiple experimental techniques with ease and automate the model design and training process. We presented a full machine learning based approach that fulfills these requirements. Not only model development, but also data preparation was described in detail as it is crucial in obtaining good results. Resulting models calculations were compared with popular analytical models and experimental data gathered from literature. The calculations comparison showed that the models developed were characterized by the smallest error with regards to the experiments and behaved equally well for variable pressure, temperature, and equivalence ratio. The source code of ready-to-use models has been provided and can be easily integrated in, for example, CFD software.
Keywords
artificial neural network, Computational Fluid Dynamics, laminar flame speed, Machine Learning
Suggested Citation
Malik K, Żbikowski M, Teodorczyk A. Laminar Burning Velocity Model Based on Deep Neural Network for Hydrogen and Propane with Air. (2023). LAPSE:2023.23975v1
Author Affiliations
Malik K: Institute of Heat Engineering, Faculty of Power and Aeronautical Engineering, Warsaw University of Technology, Nowowiejska 21/25, 00-665 Warsaw, Poland [ORCID]
Żbikowski M: Institute of Heat Engineering, Faculty of Power and Aeronautical Engineering, Warsaw University of Technology, Nowowiejska 21/25, 00-665 Warsaw, Poland [ORCID]
Teodorczyk A: Institute of Heat Engineering, Faculty of Power and Aeronautical Engineering, Warsaw University of Technology, Nowowiejska 21/25, 00-665 Warsaw, Poland [ORCID]
Journal Name
Energies
Volume
13
Issue
13
Article Number
E3381
Year
2020
Publication Date
2020-07-01
Published Version
ISSN
1996-1073
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Original Submission
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PII: en13133381, Publication Type: Journal Article
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LAPSE:2023.23975v1
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doi:10.3390/en13133381
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Mar 27, 2023
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