Special Issue "Machine Learning in Fluid Dynamics: Theory and Applications"
Deadline for manuscript submissions: 15 June 2020.
Interests: fluid mechanics; complex systems; pattern formation; partial differential equations; non-Newtonian fluids; fluid–structure interaction; hydrodynamic stability; non-equilibrium thermodynamics; vortex induced oscillations; rheology; pathological flows; network analysis; philosophy of science; sustainability and science and creativity in mathematics and science
Special Issues and Collections in MDPI journals
Special Issue in Fluids: Recent Numerical Advances in Fluid Mechanics
Special Issue in Fluids: Recent Numerical Advances in Fluid Mechanics, Volume II
Nowadays, artificial intelligence plays a vital role in learning and extracting patterns from complex data. Despite their immense success in other disciplines, machine leraning tecniques are just beginning to be applied in the field of fluid dynamics. Such data analytics and statistical tools have been utilized, for example, for the physical model inference, subgrid scale closure modeling, model reduction, and fast emulators for data assimilation, paramater estimation, uncertainlty quantification, control and optimization. However, most of the approaches so far are black boxes and their generalizability, interpretibility, robustness and numerical analysis remain an open challange. Therefore, we invite you to submit your contribution in all aspects of data-driven/scientific/statistical learning to this special issue.
Topics in this call include, but are not limited to: new learning algorithms, parallel computing implementations, numerical analysis, parameterizations and turbulence modeling, reduced order modeling, intrusive and non-intrusive model development, near real time predictions, digital twins, and hybrid frameworks between physics-based and data-driven approaches as well as their implementations to the problems ariasing in canonical or realistic fluid dynamics applications.
Dr. Omer San
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 papers will be 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. Mathematics 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 1200 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.
- machine learning
- data mining
- big data analytics
- artificial intelligence
- data-driven modeling
- physics-based modelling
- hybrid analytics
- model order reduction
- data assimilation
- flow control and optimization
- turbulence modeling
- uncertainty quantification
- computational learning theory
- neural networks
- kernel methods
- sampling methods
- exploratory data analysis