Emerging Techniques and Their Application in Turbomachinery
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Turbomachinery".
Deadline for manuscript submissions: closed (30 July 2022) | Viewed by 13248
Special Issue Editors
Interests: connected and automated vehicles; V2X; industrial IoT; digital twins; big data; intelligent machines; cooperative connected technologies
Special Issues, Collections and Topics in MDPI journals
Interests: computing in mathematics; natural science; engineering and medicine; aerospace engineering; fluid dynamics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Turbomachinery plays a significant role in the economy, especially in large-scale industrial systems. Turbomachinery also represents high-emission equipment in the energy field, including thermal power plants, gas turbine power plants, hydropower stations, and nuclear power stations. With the in-depth integration of a new generation of information technology, academia and industry have carried out significant research and development in emerging technology fields, such as Industry 4.0, big data, the Internet of Things (IoT), cloud computing, artificial intelligence, and blockchain. These emerging technologies create both opportunities and challenges to turbomachinery development.
This Special Issue invites high-quality research papers covering a wide range of topics related to new emerging techniques and their turbomachinery applications. The papers are expected to provide contributions, data, and ideas for improving the new emerging approach currently used in turbomachinery design and analysis.
In this Special Issue, original research articles and reviews are welcome. Research areas may include, but are not limited to, the following new emerging techniques: artificial intelligence, machine learning, big data, and digital twins, and their application in the following fields:
- Turbomachinery aerodynamic design and analysis;
- Turbomachinery aerodynamic optimization;
- Turbomachinery structural optimization;
- Turbomachinery operation and maintenance.
We look forward to receiving your contributions.
Dr. Yanjun Shi
Dr. Matthias Meinke
Prof. Dr. Juan Du
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. Machines 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
- compressors
- turbines
- CFD
- artificial intelligence
- machine learning
- big data
- digital twins
- intelligent operation
- aerodynamic/structural design optimization
- blade design
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