Developments of Modelling, Diagnostics, and AI-Aided Techniques in Combustion and Fire Science
A special issue of Fire (ISSN 2571-6255).
Deadline for manuscript submissions: 31 October 2025 | Viewed by 88
Special Issue Editors
Interests: fire dynamics; combustion modeling; multiphase flows; machine learning
Interests: fluid dynamics; turbulent combustion
Interests: fire dynamics; jet fire; wildfire
Special Issues, Collections and Topics in MDPI journals
Interests: numerical simulation; hydrogen combustion
Special Issue Information
Dear Colleagues,
Fire is an unexpected and uncontrolled combustion process, and due to its wide-scale variations and the involvement of various combustible materials, it is unique in many aspects. For example, in the realm of fire modelling, the simplicity, efficiency and easy implementation of the models gain more attention, so most fire models incorporate many empirical parameters. In contrast, the fundamental combustion science that primarily focuses on the engine or furnace applications with relatively limited-scale variations places a high requirement on the high-fidelity and accuracy of modelling, with the intention to better inspect and optimize the thermal efficiency and pollution emissions of combustors. This difference is also seen in the area of optical diagnostics, where the photography commonly used for fire positioning is in contrast to the modern laser technology that requires more sophisticated instruments, providing detailed measurements of burning structures in combustion science. More examples could be found in the recent developments of Al-aided techniques.
This Special Issue thus focuses on the differences and connections between fundamental combustion and fire science, aiming to provide new perspectives on modeling, diagnostics and data-driven techniques, which is expected to better promote the development of robust research methods for fire science. We cordially invite the researchers and experts in the fields, including, but not limited to, wildfire, leakage fire and hydrogen combustion, to contribute to this Special Issue, which will provide an excellent platform to exchange invaluable insights and gain extended knowledge on fire dynamics and its connections to fundamental combustion.
Dr. Yong Hu
Dr. Masaya Muto
Dr. Kuibin Zhou
Dr. Reo Kai
Dr. Kin Pang Cheong
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fire is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- wildfire
- jet fire
- hydrogen combustion
- explosion
- modeling
- fluid dynamics
- diagnostics
- turbulent flow
- radiation
- machine learning
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