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A Simulation of the Response of a Sounding Temperature Sensor Based on the Combination of a Genetic Algorithm and Computational Fluid Dynamics

Juanjuan Wang, Yajuan Jia*, Jiangping Nan

Xi’an Traffic Engineering Institute, Xi’an, 710300, China

* Corresponding Author: Yajuan Jia. Email: email

(This article belongs to the Special Issue: EFD and Heat Transfer II)

Fluid Dynamics & Materials Processing 2020, 16(6), 1161-1175. https://doi.org/10.32604/fdmp.2020.010328

Abstract

The present study aims at improving the accuracy of weather forecast by providing useful information on the behavior and response of a sounding temperature sensor. A hybrid approach relying on Computational Fluid Dynamics and a genetic algorithm (GA) is used to simulate the system represented by the bead thermistor and the surrounding air. In particular, the influence of different lead angles, sensor lead length, and lead number is considered. The results have shown that when the length of the lead wire of the bead thermistor is increased, the radiation temperature rise is reduced; when the number of lead wire is four and the angle between the lead wires is 180°, the solar radiation angle has a scarce influence on the radiation temperature rise of the sounding temperature sensor.

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APA Style
Wang, J., Jia, Y., Nan, J. (2020). A simulation of the response of a sounding temperature sensor based on the combination of a genetic algorithm and computational fluid dynamics. Fluid Dynamics & Materials Processing, 16(6), 1161-1175. https://doi.org/10.32604/fdmp.2020.010328
Vancouver Style
Wang J, Jia Y, Nan J. A simulation of the response of a sounding temperature sensor based on the combination of a genetic algorithm and computational fluid dynamics. Fluid Dyn Mater Proc. 2020;16(6):1161-1175 https://doi.org/10.32604/fdmp.2020.010328
IEEE Style
J. Wang, Y. Jia, and J. Nan, “A Simulation of the Response of a Sounding Temperature Sensor Based on the Combination of a Genetic Algorithm and Computational Fluid Dynamics,” Fluid Dyn. Mater. Proc., vol. 16, no. 6, pp. 1161-1175, 2020. https://doi.org/10.32604/fdmp.2020.010328



cc Copyright © 2020 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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