Simultaneous soot parameters fields predictions accuracy improvements in laminar sooting flames from soot radiation measurements — a multi-task learning approach-Reference-Cited by-同舟云学术

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Simultaneous soot parameters fields predictions accuracy improvements in laminar sooting flames from soot radiation measurements — a multi-task learning approach

Published:2024-10 Issue: Volume:238 Page:115390
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Wang Qianlong^ORCID,Li Ting,Gong Mingxue,Kashif Muhammad^ORCID,Yin Xingzhi,Wu Yi^ORCID

Publisher

Elsevier BV

Reference18 articles.

1. Probing soot formation , chemical and physical evolution , and oxidation : A review of in situ diagnostic techniques and needs;Michelsen;Proc. Combust. Inst.,2017

2. Transfer-learning-based multi-wavelength laser sensor for high fidelity and real-time monitoring of ambient temperature and humidity;Ma;Appl. Opt.,2023

3. Retrieving soot volume fraction fields for laminar axisymmetric diffusion flames using convolutional neural networks;Rodríguez;Fuel,2021

4. Reconstructing temperature fields from OH distribution and soot volume fraction in turbulent flames using an artificial neural network;Nie;Combust. Flame,2024

5. Machine learning-assisted soot temperature and volume fraction fields predictions in the ethylene laminar diffusion flames;Tao;Opt. Express,2021

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