Estimation of equivalence ratio distribution in diesel spray using a computational fluid dynamics

Yasumasa Suzuki, Taku Tsujimura, Jin Kusaka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

It is important to understand the mechanism of mixing and atomization of the diesel spray. In addition, the computational prediction of mixing behavior and internal structure of a diesel spray is expected to promote the further understanding about a diesel spray and development of the diesel engine including devices for fuel injection. In this study, we predicted the formation of diesel fuel spray with 3D-CFD code and validated the application by comparing experimental results of the fuel spray behavior and the equivalence ratio visualized by Layleigh-scatter imaging under some ambient, injection and fuel conditions. Using the applicable constants of KH-RT model, we can predict the liquid length spray on a quantitative level. under various fuel injection, ambient and fuel conditions. On the other hand, the change of the vapor penetration and the fuel mass fraction and equivalence ratio distribution with change of fuel injection and ambient conditions quantitatively. The 3D-CFD code used in this study predicts the spray cone angle and entrainment of ambient gas are predicted excessively, therefore there is the possibility of the improvement in the prediction accuracy by the refinement of fuel droplets breakup and evaporation model and the quantitative prediction of spray cone angle.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSPIE
Volume9232
ISBN (Print)9781628412864
DOIs
Publication statusPublished - 2014
EventInternational Conference on Optical Particle Characterization, OPC 2014 - Tokyo
Duration: 2014 Mar 102014 Mar 14

Other

OtherInternational Conference on Optical Particle Characterization, OPC 2014
CityTokyo
Period14/3/1014/3/14

Fingerprint

Spray
computational fluid dynamics
Computational Fluid Dynamics
sprayers
equivalence
Computational fluid dynamics
Equivalence
Fuel injection
fuel injection
fuel sprays
Injection
Cones
charge flow devices
cones
predictions
Air entrainment
diesel fuels
Atomization
Diesel fuels
diesel engines

Keywords

  • 3D-CFD
  • Diesel spray
  • Laser diagnosis
  • Rayleigh scattering

ASJC Scopus subject areas

  • Applied Mathematics
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

Cite this

Suzuki, Y., Tsujimura, T., & Kusaka, J. (2014). Estimation of equivalence ratio distribution in diesel spray using a computational fluid dynamics. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 9232). [923205] SPIE. https://doi.org/10.1117/12.2063644

Estimation of equivalence ratio distribution in diesel spray using a computational fluid dynamics. / Suzuki, Yasumasa; Tsujimura, Taku; Kusaka, Jin.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 9232 SPIE, 2014. 923205.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Suzuki, Y, Tsujimura, T & Kusaka, J 2014, Estimation of equivalence ratio distribution in diesel spray using a computational fluid dynamics. in Proceedings of SPIE - The International Society for Optical Engineering. vol. 9232, 923205, SPIE, International Conference on Optical Particle Characterization, OPC 2014, Tokyo, 14/3/10. https://doi.org/10.1117/12.2063644
Suzuki Y, Tsujimura T, Kusaka J. Estimation of equivalence ratio distribution in diesel spray using a computational fluid dynamics. In Proceedings of SPIE - The International Society for Optical Engineering. Vol. 9232. SPIE. 2014. 923205 https://doi.org/10.1117/12.2063644
Suzuki, Yasumasa ; Tsujimura, Taku ; Kusaka, Jin. / Estimation of equivalence ratio distribution in diesel spray using a computational fluid dynamics. Proceedings of SPIE - The International Society for Optical Engineering. Vol. 9232 SPIE, 2014.
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