Data-driven propagation prediction of subsonic and supersonic turbulent jets by combining self-similarity analysis model and artificial neural network

Data-driven propagation prediction of subsonic and supersonic turbulent jets by combining self-similarity analysis model and artificial neural network

Previous self-similarity analysis models for turbulent jet flames (TJF) have inherent limitations in the flame tip location and velocity prediction based on experimental data. A novel model (BP-TJF) to predict the propagation process of subsonic and supersonic TJF is proposed by combining developed...

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Bibliographic Details
Main Authors: Gang Li, Rui Yang, Haisheng Zhen, Hu Wang, Haifeng Liu, Qinglong Tang, Mingfa Yao
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Applications in Energy and Combustion Science
Subjects:
Turbulent jet flame
Self-similarity model
Flame propagation prediction
Artificial neural network
Online Access:http://www.sciencedirect.com/science/article/pii/S2666352X23001255

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http://www.sciencedirect.com/science/article/pii/S2666352X23001255

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