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Title: Toward predictive and computationally affordable Lagrangian–Eulerian modeling of spray–wall interaction

Journal Article · · International Journal of Engine Research

The work presented in this article focuses on improving the understanding of spray–wall interaction phenomena and the predictivity of computational models for modern internal combustion engine–like conditions. Previous work from the authors highlighted some of the limitations of the currently available spray–wall interaction sub-models, especially those based on experimental observations carried out on single droplet impingement of non-hydrocarbon fluids. Previous experimental observations and direct numerical simulations provided unique qualitative and quantitative details that were leveraged to improve Lagrangian–Eulerian simulations of spray–wall interaction. In this work, Yarin and Weiss’ theory for droplet train impingements, as interpreted by Stanton and Rutland, was implemented in the CONVERGE software. A novel and mathematically rigorous calculation of the impingement frequency for Lagrangian parcels was proposed to replace the zero-droplet-spacing assumption present in the original model and improve the prediction of droplet splash. Preliminary testing and validation of the new formulation against experiments carried out in a constant volume vessel showed encouraging results. The feedback loop between experiments, Lagrangian–Eulerian simulations, and direct numerical simulations also motivated the investigation of the surface roughness model available in the Lagrangian–Eulerian framework. This part of the study pointed out the importance of correctly predicting the interaction between liquid and surrounding gas in the near-wall region. Overall, the results shown indicate that correctly capturing the pre-impingement physics and liquid–gas interaction, together with improving splash predictions, was key for improving the accuracy of Lagrangian–Eulerian computational fluid dynamics simulations of spray–wall impingement.

Sponsoring Organization:
USDOE
Grant/Contract Number:
NONE; EE0007292
OSTI ID:
1566210
Journal Information:
International Journal of Engine Research, Journal Name: International Journal of Engine Research Journal Issue: 2 Vol. 21; ISSN 1468-0874
Publisher:
SAGE PublicationsCopyright Statement
Country of Publication:
United Kingdom
Language:
English

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