SOURCE-LINKED INTELLIGENCE
Development of a Novel Machine Learning-based model for Multiphase flows
Development of a Novel Machine Learning-based model for Multiphase flows Multiphase flow (MF) is the simultaneous flow of materials with two or more thermodynamic phases. MF occurs in numerous settings: bioengineering, conventional and nuclear power plants, oil and gas production and transport, pharmaceutical industry, combustion engines, chemical industry, flows inside the human body, biological industry, and process technology, to name a few. Researchers use experimental and theoretical techniques to study MF. Experimental techniques are usually restricted to smaller domains or laboratory scales due to very high costs; in addition, experiments in realistic conditions are very difficult to manage. On the other hand, theory usually requires numerical computation, which is very time-consuming for realistic MF problems. The objective of this study is to develop a novel machine learning (ML)-based hidden fluid dy
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 215534.4
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T02:21:08.944Z. This is not the publication date.