Issue |
E3S Web Conf.
Volume 321, 2021
XIII International Conference on Computational Heat, Mass and Momentum Transfer (ICCHMT 2021)
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|
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Article Number | 03001 | |
Number of page(s) | 7 | |
Section | Modeling and Simulation | |
DOI | https://doi.org/10.1051/e3sconf/202132103001 | |
Published online | 11 November 2021 |
Sensitivity analysis of heat transfers in an asymmetrically heated turbulent channel flow
Laboratoire PROMES-CNRS (UPR 8521), Université de Perpignan via Domitia, Technosud-Rambla de la thermodynamique,, 66100 Perpignan – France
* Corresponding author: martin.david@promes.cnrs.fr
A sensitivity analysis of heat transfers in an asymmetrically heated turbulent channel flow is performed using a dedicated heat transfer correlation. The investigated correlation is developed to study the heat transfers between the fluid and the wall in gas-pressurized solar receivers of concentrated solar power tower. The working conditions correspond to high-temperature levels and high heat fluxes. The correlation of the Nusselt number depends on five parameters: the Reynolds number, the Prandtl number, the fluid temperature, the hot and cold wall temperatures. We investigate the sensitivity of the heat flux to the wall and fluid temperatures. The results obtained with the global uncertainty management are compared to direct computations of the errors of measurement. In the global uncertainty management, the heat flux sensitivity is studied with the Taylor expansion of the function. This method assumes the quasilinearity and the quasi-normality of the function; therefore, only small variations of parameters are computed. The study points out the importance of the temperature measurement accuracy for the heat flux evaluation in asymmetrically heated turbulent channel flow. In particular, the results show that the cold wall heat flux is very sensitive to the variations of the cold wall temperature and the bulk temperature of the fluid. The hot wall is less influenced by the temperature variations than the cold wall. The global uncertainty management produces satisfying results on the prediction of the error linked to the uncertainties on bulk temperature. Nevertheless, the hot and cold wall temperature uncertainty propagation are poorly estimated by the method.
© 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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