Modeling and Optimization of Hydrodynamic and Aerodynamic Flow Processes
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control, Modeling and Optimization".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 364
Special Issue Editors
Interests: fluid–solid–acoustic coupling prediction technology; ship structural safety
Interests: green ships; energy-saving equipment
Special Issue Information
Dear Colleagues,
The modeling and optimization of hydrodynamic and aerodynamic flow processes are key issues in fluid dynamics research and are widely applied across many fields, including process equipment, aerospace, marine vessels, energy and power engineering, and environmental engineering. At present, with the rapid development of computer technology and numerical algorithms, traditional modeling methods based on simplified assumptions are gradually being replaced by high-precision, multi-scale numerical simulation techniques. For example, turbulence simulation technology, which has been rapidly advancing, enables precise capture of the evolution of flow fields. Emerging technologies such as fluid structure coupling modeling and multiphase flow modeling have gradually become research hotspots. The flow control and optimization methods based on artificial intelligence and machine learning have emerged as a novel approach, with stronger capabilities in mechanism discovery, becoming more efficient and intelligent means of evaluation and optimization design.
This Special Issue on “Modeling and Optimization of Hydrodynamic and Aerodynamic Flow Processes” seeks high-quality papers that focus on the development and application of modeling and optimization methods for flow processes. Topics include, but are not limited to, methods and applications in the following areas:
- High fidelity modeling methods and applications for hydrodynamic and aerodynamic flow processes;
- Refined experimental measurement techniques for flow processes;
- High-fidelity digital twin technologies for flow processes;
- Modeling methods for multiphase flows and flow interface evolution;
- Artificial intelligence-based modeling and prediction methods for flow processes;
- Data-driven approaches for flow feature extraction;
- Adjoint theory-based optimization methods for flow processes;
- Multi-field coupling modeling and optimization methods in flow processes;
- Application of flow process modeling and optimization methods in sustainable development;
- Innovations in aerodynamics/hydrodynamics for low-carbon aviation, green ships, and energy-saving equipment.
Dr. Weipeng Zhang
Dr. Pei Xu
Dr. Hang Guo
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 250 words) can be sent to the Editorial Office for assessment.
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. Processes is an international peer-reviewed open access semimonthly 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
- modeling method
- optimization methods
- high fidelity
- refined measurement
- digital twin
- multiphase flows
- artificial intelligence
- flow feature extraction
- adjoint theory
- multi-field coupling
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