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Title: Modeling Primary Atomization of Liquid Fuels using a Multiphase DNS/LES Approach

Abstract

As part of a Laboratory Directed Research and Development project, we are developing a modeling-and-simulation capability to study fuel direct injection in automotive engines. Predicting mixing and combustion at realistic conditions remains a challenging objective of energy science. And it is a research priority in Sandia’s mission-critical area of energy security, being also relevant to many flows in defense and climate. High-performance computing applied to this non-linear multi-scale problem is key to engine calculations with increased scientific reliability.

Authors:
 [1];  [1];  [1]
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1311528
Report Number(s):
SAND2016-7913R
646624
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
33 ADVANCED PROPULSION SYSTEMS; 97 MATHEMATICS AND COMPUTING

Citation Formats

Arienti, Marco, Oefelein, Joe, and Doisneau, Francois. Modeling Primary Atomization of Liquid Fuels using a Multiphase DNS/LES Approach. United States: N. p., 2016. Web. doi:10.2172/1311528.
Arienti, Marco, Oefelein, Joe, & Doisneau, Francois. Modeling Primary Atomization of Liquid Fuels using a Multiphase DNS/LES Approach. United States. doi:10.2172/1311528.
Arienti, Marco, Oefelein, Joe, and Doisneau, Francois. 2016. "Modeling Primary Atomization of Liquid Fuels using a Multiphase DNS/LES Approach". United States. doi:10.2172/1311528. https://www.osti.gov/servlets/purl/1311528.
@article{osti_1311528,
title = {Modeling Primary Atomization of Liquid Fuels using a Multiphase DNS/LES Approach},
author = {Arienti, Marco and Oefelein, Joe and Doisneau, Francois},
abstractNote = {As part of a Laboratory Directed Research and Development project, we are developing a modeling-and-simulation capability to study fuel direct injection in automotive engines. Predicting mixing and combustion at realistic conditions remains a challenging objective of energy science. And it is a research priority in Sandia’s mission-critical area of energy security, being also relevant to many flows in defense and climate. High-performance computing applied to this non-linear multi-scale problem is key to engine calculations with increased scientific reliability.},
doi = {10.2172/1311528},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2016,
month = 8
}

Technical Report:

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