Modeling and Optimization of Hydraulic and Thermal Performance of a Tesla Valve Using a Numerical Method and Artificial Neural Network

Kourosh Vaferi; Mohammad Vajdi; Amir Shadian; Hamed Ahadnejad; Farhad Sadegh Moghanlou; Hossein Nami; Haleh Jafarzadeh

doi:10.3390/e25070967

journal article Open Access Jun 22, 2023

Modeling and Optimization of Hydraulic and Thermal Performance of a Tesla Valve Using a Numerical Method and Artificial Neural Network

Kourosh Vaferi

Mohammad Vajdi

Amir Shadian Hamed Ahadnejad Farhad Sadegh Moghanlou Hossein Nami

Haleh Jafarzadeh

Entropy Vol. 25 No. 7 pp. 967 · MDPI AG

View at Publisher Save 10.3390/e25070967

Abstract

The Tesla valve is a non-moving check valve used in various industries to control fluid flow. It is a passive flow control device that does not require external power to operate. Due to its unique geometry, it causes more pressure drop in the reverse direction than in the forward direction. This device’s optimal performance in heat transfer applications has led to the use of Tesla valve designs in heat sinks and heat exchangers. This study investigated a Tesla valve with unconventional geometry through numerical analysis. Two geometrical parameters and inlet velocity were selected as input variables. Also, the pressure drop ratio (PDR) and temperature difference ratio (TDR) parameters were chosen as the investigated responses. By leveraging numerical data, artificial neural networks were trained to construct precise prediction models for responses. The optimal designs of the Tesla valve for different conditions were then reported using the genetic algorithm method and prediction models. The results indicated that the coefficient of determination for both prediction models was above 0.99, demonstrating high accuracy. The most optimal PDR value was 4.581, indicating that the pressure drop in the reverse flow direction is 358.1% higher than in the forward flow direction. The best TDR response value was found to be 1.862.

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Details

Published: Jun 22, 2023
Vol/Issue: 25(7)
Pages: 967
License: View

Authors

K

Kourosh Vaferi

Department of Mechanical Engineering, University of Mohaghegh Ardabili, Ardabil 5619913131, Iran

M

Mohammad Vajdi

Department of Mechanical Engineering, University of Mohaghegh Ardabili, Ardabil 5619913131, Iran

A

Amir Shadian

Department of Mechanical Engineering, University of Tabriz, Tabriz 5166616471, Iran

H

Hamed Ahadnejad

Department of Mechanical Engineering, University of Mohaghegh Ardabili, Ardabil 5619913131, Iran

F

Farhad Sadegh Moghanlou

Department of Mechanical Engineering, University of Mohaghegh Ardabili, Ardabil 5619913131, Iran

H

Hossein Nami

SDU Life Cycle Engineering, Department of Green Technology, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark

H

Haleh Jafarzadeh

Department of Civil Engineering, School of Science and Engineering, Khazar University, Baku 1096, Azerbaijan

Cite This Article

Kourosh Vaferi, Mohammad Vajdi, Amir Shadian, et al. (2023). Modeling and Optimization of Hydraulic and Thermal Performance of a Tesla Valve Using a Numerical Method and Artificial Neural Network. Entropy, 25(7), 967. https://doi.org/10.3390/e25070967

Modeling and Optimization of Hydraulic and Thermal Performance of a Tesla Valve Using a Numerical Method and Artificial Neural Network

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