4.7 Article

Design optimization with computational fluid dynamic analysis of β-type Stirling engine

Journal

APPLIED THERMAL ENGINEERING
Volume 113, Issue -, Pages 87-102

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.applthermaleng.2016.10.063

Keywords

Stirling engine; Thermodynamic analysis; Multi-objective optimization; CFD analysis

Funding

  1. National Natural Science Foundation of China [51476140]
  2. Program of Introducing Talents of Discipline to University [B08026]

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The real performance of Stirling engine always deviates from prescribed theoretical potential. This is mainly because of complex interaction of different engine parameters, heat transfer process of oscillating flows and fluid dynamics. In order to develop an effective methodology to optimize geometric design of Stirling engines a beta-type rhombic drive Stirling engine was investigated whose initial experimental efficiency and output power was relatively low. This paper presents a sensitivity analysis of p-type Stirling model and proposed a combined method to carry out multi-objective optimization of a Stirling engine using detailed information of pressure and volume provided by CFD analysis. The geometric parameters of heat exchangers including heater and cooler tubes diameter with length, regenerator length, matrix mesh and wire diameter were considered for maximizing thermal efficiency, output power and minimizing flow resistance power loss in Stirling engine. CFD analysis covers a detailed study of real and optimized model with best experimental agreement. The CFD results include the detailed description of Stirling cycle With temperature contour, velocity vectors and pressure-volume variation in compression and expansion spaces. The proposed modification results an increase of 2 percentage points in thermal efficiency and more than 80 W in power output when the dead volume of heater, cooler and regenerator is reduced up to 54%, 42% and 24% respectively. The additional dead volume leads to a phase shift of the pressure which is also the main reason of lowering output results. (C) 2016 Elsevier Ltd. All rights reserved.

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