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Modeling and optimization method of an indirectly irradiated solar receiver
This work presents the modeling and optimization of an indirectly irradiated solar receiver. A numerical model of the cavity-absorber block is put forward with the coupling of the net-radiation method using infinitesimal areas and a CFD code. An iterative method with a relaxation factor made it poss...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308248/ https://www.ncbi.nlm.nih.gov/pubmed/30596028 http://dx.doi.org/10.1016/j.mex.2018.12.006 |
Sumario: | This work presents the modeling and optimization of an indirectly irradiated solar receiver. A numerical model of the cavity-absorber block is put forward with the coupling of the net-radiation method using infinitesimal areas and a CFD code. An iterative method with a relaxation factor made it possible to obtain the temperature distribution and the developed code was implemented in the form of UDF and used as boundary conditions in the CFD model of the absorber to simulate the flow of air and heat transfer. The good ability of the receiver to transfer heat to the fluid is proved with a 92% thermal efficiency obtained. Then the combination of the Kriging surface response method and the MOGA allowed the mathematical optimization of the receiver. The multi-objective optimization made it possible to obtain 3 candidates giving the best combinations of design parameters from the fixed objectives. Three bullet points, highlighting the customization of the procedure. • A practical analysis using the net-radiation method using infinitesimal areas is applied for cavity radiative exchange model. • The code developed for the cavity is implemented in the boundary conditions at the level of the ANSYS Fluent CFD model allowing the simulation of the conjugated transfers within the absorber. • The optimization method proposed is the combination of the Kriging surface response method for quantitative and qualitative analysis of the design parameters and MOGA to obtain different combinations seeking to maximize or to minimize the chosen parameters. |
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