Heat Transfer Features of Pulsating Turbulent Flow in a Pipe: Experimental Optimization

DOI

10.2991/978-94-6463-136-4_27How to use a DOI?

Keywords

Pulsating Frequency; Nusselt Number; Particle Swirm Optimization; heat transfer Coefficient

Abstract

The heat transmission improvement methods are widely utilized to raise the level of performance of the latent heat storage systems, the heat pipe is a broadly used technique utilized to improve the transmission of heat enhancement technique. Current paper comprises use of the heat pipe to vary the heat input, pulsating frequency, and flow velocity. The Heat input is varied in 0, 25, 50, 75 and 100 watts; pulsating frequency in upstream and downstream with frequency changed from 0 to 3.33 Hz; Flow velocity varied and calculated from Reynolds number which varies from 6000 to 13000. The experimental results were carried out using the design of experiments with output parameters as coefficient of heat transfer along with Nusselt number. The behavior of coefficient of heat transfer with respect to input parameters is discussed. The Analysis of variance is accustomed to check the reliability of the outcomes. The optimized input response selected using Particle swirm optimization shows Pulsating frequency of 3.33 Hz, Heat input of 100 W and Reynolds number of 13443 giving optimum heat transfer coefficient.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Siddhanath V. Nishandar
AU  - Ashok T. Pise
AU  - Digvijay A. Mhamane
PY  - 2023
DA  - 2023/05/01
TI  - Heat Transfer Features of Pulsating Turbulent Flow in a Pipe: Experimental Optimization
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 306
EP  - 319
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_27
DO  - 10.2991/978-94-6463-136-4_27
ID  - Nishandar2023
ER  -