About the Journal

The Journal of Artificial Intelligence in Fluid Dynamics JAIFD is an online, open access (free submission, free publication, and free access) peer-reviewed journal for the publication of research and developments in the field of artificial intelligence applications in Fluid dynamics. JAIFD seeks to provide the forum for the exchange and dissemination of knowledge on all issues relevant to emerging topics and on-going researchers in Fluid dynamics with Artificial Intelligence.

Fluid Dynamics research have been progressing during the past few years, driven by the incorporation of massive amounts of data, either in textual or graphical form, generated from multi-scale simulations, laboratory experiments, and real data from the field. Artificial Intelligence (AI) and its adjacent field, Machine Learning (ML), are about to reach standardization in most fields of computational science and engineering, as they provide multiple ways for extracting information from data that turn into knowledge, with the aid of portable software implementations that are easy to adopt. There is emphasis on original research and application papers on current developments and advances in both theory and practice. The journal provides a forum for researchers to share, contribute and promote various forms of manuscripts such as original research, reviews, mini reviews, rapid communication, perspectives, opinions, letters, and other short articles.

JAIFD is an international peer reviewed journal that publishes theoretical, computational, and experimental research related to:

Artificial Intelligence and Machine Learning approaches (AI and ML) applied to Aeromechanics,

Hydrodynamics,

Plasma Dynamics,

Underground Hydrodynamics,

Biomechanics Of Continuous Media

Computational Fluid Dynamics

Big Data related to Fluid Dynamics

Special attention is given to new trends developing at the leading edge of science, such as theory and application of AI and ML applications in Multi-Phase Flows, Chemically Reactive Flows, Liquid and Gas Flows In Electromagnetic Fields, new hydrodynamical methods of increasing oil output, new approaches to the description of turbulent flows, etc. All the published content are made available to the readers to access and use limitlessly when cited under the terms of Creative Commons Attribution License.  

 

Current Issue

Vol. 1 No. 1 (2022): Volume 1 Issue 1
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