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Experimental analysis of the velocity field and surface temperature distribution during flow boiling in microchannels through IR thermography and machine learning tools

Grant number: 20/10867-5
Support Opportunities:Scholarships in Brazil - Post-Doctoral
Effective date (Start): May 01, 2021
Effective date (End): April 30, 2022
Field of knowledge:Engineering - Mechanical Engineering - Transport Phenomena
Principal Investigator:Gherhardt Ribatski
Grantee:Douglas Martins Rocha
Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Associated research grant:16/09509-1 - Phase change heat transfer processes of high performance applied to solar energy recovery, AP.TEM


The development of high efficient compact heat exchangers is crucial to enable the use of solar power concentration to increase the power generation capacity and efficiency of solar energy systems. The phase-change process in microchannels can be a promising approach for solar energy systems cooling since it enables high heat transfer rates, which minimizes the need for space, and reduces the costs of material and working fluid. However, the thermo-hydraulic behavior of flow boiling in microchannels is not completely understood because of the aspects associated with boiling under confined conditions, which implies fluid maldistribution, thermal instabilities, and premature surface dryout. In this context, the combination of infrared thermography and optical velocimetry techniques for the flow and heat transfer characterization is a promising approach. Thus, this Post-PhD proposal aims to obtain the velocity field and the temperature distribution during convective boiling inside microchannels. The velocity profile will be obtained through the Spatial Filter Velocimetry (SFV) technique and the temperature distribution through IR thermography. Hence, a quasi-real-time calibration method for the IR thermometry will be developed based on a neural network algorithm for flow boiling experiments. A Research Internship Abroad (BEPE) at the Department of Nuclear Science & Engineering (NSE) of Massachusetts Institute of Technology (MIT) supervised by Prof. Matteo Bucci is scheduled in this proposal aiming to develop the calibration method for the IR thermometry. Further, aiming to increase the spatial resolution of the velocity fields, the parameters of the SFV technique will be optimized using machine learning (ML) tools. Such optimization will be carried out under the supervision of Prof. Agma Juci Machado Traina from the Institute of Mathematics and Computer Science (ICMC) of the University of São Paulo (USP), who has a great experience in image analysis based ML tools. The experiments and the analysis of the obtained results will be carried out under the supervision of Prof. Gherhardt Ribatski from the Department of Mechanical Engineering of São Carlos School of Engineering (EESC-USP), who is the head of the Heat Transfer Research Group's lab (HTRG). The HTRG possesses a unique laboratory infrastructure in Brazil composed of modern high-speed video and IR cameras, such equipment essential for this proposal. Based on the experimental results, mechanistic models will be developed to provide reliable tools for the design of high-efficient compact heat sinks. It must be mentioned that the candidate is familiarized with the subject of this proposal since his doctorate was focused on the measurement of the velocity field through SFV during single and two-phase flows, which provided him advanced skills on photonics, image analysis, and programming. (AU)

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