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Transient nozzle flow simulations of gasoline direct fuel injectors

Authors :
Kazuhiro Uehara
Raul Payri
Navid Shahangian
Leila Sharifian
Yasushi Noguchi
Pedro Martí-Aldaraví
M. J. Martínez
Source :
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia, instname
Publication Year :
2020
Publisher :
Elsevier, 2020.

Abstract

[EN] In the field of Internal Combustion Engines (ICE) the usage of Gasoline Direct fuel injectors (GDi) with gasoline, iso-octane, ethanol (or other alternative fuels) has gained relevance in the past years with the goal of reducing fuel consumption and thus emissions. In this type of direct injections, the injector plays a major role in defining the air-fuel mixture quality. Nevertheless, the study of the phenomena inside the nozzle becomes a challenge due to its reduced size, high flow velocities and multiphase flow nature. Computational Fluid Dynamics (CFD) tools allow gaining valuable insight and understanding into such complex flow physics. Therefore, the objective of this work is the development of a predictive methodology for simulating two GDi nozzles. Unsteady Reynolds-Averaged Navier Stokes (URANS) is chosen for modeling the turbulence. The Homogeneous Relaxation Model (HRM) is used to investigate the possible phase change of the fuel through cavitation or flash boiling. Different injection conditions are simulated and results are compared against experimental data of mass flow and momentum rate for validation. CFD is able to accurately predict steady state values, but transients are very dependent on the initial and boundary conditions imposed on the model. A methodology for their definition is proposed and tested, and with it the accuracy in the prediction of the opening transient is improved.<br />Authors would like to acknowledge Toyota Motor Corporation (TMC) for providing the funds for this project. Authors would like to thank the "Fundacion del Centro de Supercomputacion de Castilla y Leon" (FCSCL) and "ACT now HPC Cloud Cluster" for allowing the use of their clusters to perform part of the simulations carried out in this work. Additionally, the Ph.D. student Maria Martinez has been funded by a grant from the Government of Generalitat Valenciana with reference ACIF/2018/118.

Details

Language :
English
Database :
OpenAIRE
Journal :
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia, instname
Accession number :
edsair.doi.dedup.....84b8ff4eb14195616950030e6c4f8d3b