Issue |
E3S Web Conf.
Volume 321, 2021
XIII International Conference on Computational Heat, Mass and Momentum Transfer (ICCHMT 2021)
|
|
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Article Number | 02020 | |
Number of page(s) | 6 | |
Section | Energy | |
DOI | https://doi.org/10.1051/e3sconf/202132102020 | |
Published online | 02 December 2021 |
Characterisation of optical properties of solar nanofluids by an inverse problem based on a numerical model
1
Department of Mechanical Engineering and Construction, Universitat Jaume I, Av. de Vicent Sos Baynat, s/n 12071 Castelló de la Plana, Spain
2
Department of Structural Mechanics and Hydraulic Engineering, University of Granada, Campus Universitario Fuentenueva, Edf. Politécnico, 18071 Granada, Spain
* Corresponding author: mondragn@uji.es
Some nanoparticles (NPs) possess an outstanding photothermal conversion under optical illumination. For this reason, these NPs are under research in a wide variety of light-induced heating applications such as solar nanofluids, which could be used for direct light absorption in solar collectors. Experimental characterisation of solar nanofluids for their application to light-to-heat conversion processes requires a considerable amount of resources to determine the properties of this mixture, at the nanoscale level. On this ground, an inverse problem based on a high-frequency and light-to-heat finite element model is proposed in the present work to numerically predict the optical properties of these nanofluids. In particular, a cost function based on a L2 norm is formulated to compare experimental measurements and numerical predictions. Then, this function is minimised by means of heuristic techniques –specifically, genetic algorithms- and the desired properties can be determined. In conclusion, the current work presents a numerical tool that could help in the characterisation of properties of solar nanofluids and contribute to reduce the number of experiments to be conducted for this purpose.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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