Open Access

ARTICLE

Influence of the Channel Design on the Heat Exchange Characteristics of Pulsating Flows in the Supply System of an Engine

Leonid Plotnikov^*, Danil Davydov, Dmitry Krasilnikov, Vladislav Shurupov

Turbines and Engines Department, Ural Federal University named after the first President of Russia B. N. Yeltsin, Yekaterinburg, 620062, Russia

* Corresponding Author: Leonid Plotnikov. Email:

(This article belongs to the Special Issue: Heat and Mass Transfer in Energy Equipment)

Frontiers in Heat and Mass Transfer 2024, 22(5), 1309-1322. https://doi.org/10.32604/fhmt.2024.056680

Received 28 July 2024; Accepted 23 September 2024; Issue published 30 October 2024

Abstract

Heat engines based on reciprocating machines remain in demand as energy converters in a variety of industries around the world. The aim of the study was to evaluate the gas-dynamic, consumable and heat exchange characteristics of non-stationary air flows in a supply system with transverse profiling of valve channels based on experimental studies. Valve channels with cross sections in the form of a circle, square and triangle were used to control the consumable and heat exchange characteristics of the flows in the supply system of the reciprocating-engine model. The article presents data on changes in local velocity, volumetric airflow and instantaneous heat transfer coefficient of non-stationary airflow in supply systems with different valve channel designs. A spectral analysis of the pulsations of the local heat transfer coefficient was also performed. The Nusselt number was calculated for the studied supply systems. The figured valve channels lead to an increase in the volumetric airflow through the supply system up to 32% compared with the basic configuration. The use of a square valve channel leads to suppression of heat transfer (drop is about 15 %) compared to the basic supply system, and the use of a triangular valve channel causes an intensification of heat transfer (growth is about 17.5%). The obtained data can be useful for refining mathematical models, adjusting machine learning algorithms, and improving design methods for supply systems of reciprocating machines to improve their technical, economic, and environmental characteristics.

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