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Enhancing the Predictive Capabilities for High P/T Fuel Sprays; Non-Ideal Thermodynamic Modelling Using PC-SAFT

Koukouvinis, F. ORCID: 0000-0002-3945-3707, Vidal-Roncero, A., Rodriguez, C. , Gavaises, M. ORCID: 0000-0003-0874-8534 & Pickett, L. (2020). Enhancing the Predictive Capabilities for High P/T Fuel Sprays; Non-Ideal Thermodynamic Modelling Using PC-SAFT. Ercoftac Series, 124,

Abstract

The present work aims to investigate the complex phenomena occurring during high-pressure/hightemperature fuel injection of the Engine Combustion Network (ECN) Spray-A case. While commonly in the literature transcritical mixing cases are approached using traditional cubic equation-of-state models, such models can prove insufficient in the accurate prediction of liquid density and speed of sound. The purpose of the present investigation is to employ a general tabulated approach which can be applied to any type of thermodynamic closure. At the same time, a more advanced model based on the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) is employed to create the thermodynamic table, as it is proven superior to the traditional cubic models, while also having the capacity of predicting Vapor-Liquid-Equilibrium. The model has been used for a combination of dodecane and nitrogen mixing, corresponding to the well known Spray-A conditions. Vapor penetration and mixing both in terms of temperature and mass fraction are found in agreement to experiments, within the experimental errors. Also, the thermodynamic states correspond well with the adiabatic isobaric-mixing curve, demonstrating the energyconservative nature of the approach.

Publication Type: Article
Subjects: Q Science > QC Physics
T Technology > TJ Mechanical engineering and machinery
Departments: School of Science & Technology > Engineering
SWORD Depositor:
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