GFM
Multiphase Fluids
Date of inception 16 September 2009
Leader: Sergio Chiva Vicent
Departament: Dep. d'Enginyeria Mecànica i Construcció
Website: https://www.uji.es/serveis/ocit/base/grupsinvestigacio/detall?codi=166
The Multiphase Fluids Group (GFM) was created in 2006, and belonging to the Department of Mechanical Engineering and Construction of the Higher School of Technology and Experimental Sciences (ESTCE), it develops several lines of research related to the behavior of fluids, focusing on those in which more than one phase coexists. It is currently made up of two professors and three university professors, a laboratory technician, as well as pre- and postdoctoral researchers, with an average of 15 members in recent years. In recent years, the group has developed extensive activity dedicated to the creation of measurement equipment dedicated to the characterization of the gas phase in multiphase fluids, especially focused on miniaturized capacitive and resistive sensors. It has also developed a wire-mesh system capable of measuring at different points at the same time. In addition, great activity has been developed in the use of images as part of the measurement system. The use of CFD techniques has been a constant in recent years, with important developments in codes such as OpenFoam or ANSYS.
Researchers
Classifications
- ODS: Industry, innovation and infrastructure, Affordable and clean energy, Sustainable cities and communities, Clean water and sanitation
- AREA: Energy, Environment, Industrial production, Mathematics and data analysis, Materials and nanotechnology
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Prevailing specialties (top 10)
Obtained from publications help
Obtained from publications
The displayed thematic specialties have been obtained through the application of artificial intelligence models, derived as a result of the Hercules Project from those publications with an abstract, provided that the record does not come from commercial databases, which impose restrictions on data usage.
The displayed thematic specialties have been obtained through the application of artificial intelligence models, derived as a result of the Hercules Project from those publications with an abstract, provided that the record does not come from commercial databases, which impose restrictions on data usage.
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