Study of multi-component spray and combustion and their optimization with machine learning in internal combustion engines

Gao, Suya

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University of Illinois at Urbana-Champaign

Study of multi-component spray and combustion and their optimization with machine learning in internal combustion engines

dc:creator Gao, Suya

thesis:degree_name Ph.D.

dc:date2022

Abstract

dc:description

Made available in DSpace on 2022-04-29T21:45:51Z (GMT). No. of bitstreams: 2 GAO-DISSERTATION-2021.pdf: 31346492 bytes, checksum: 9483598b32d12c09866ab8281c1dffac (MD5) LICENSE.txt: 4208 bytes, checksum: 2db90b9fb61dec52ea8217f767b9aac8 (MD5) Previous issue date: 2021-11-12

Degree

thesis:*

Name thesis:degree_name: Ph.D.
Level thesis:degree_level: Dissertation
Discipline thesis:degree_discipline: Mechanical Engineering
Grantor: University of Illinois at Urbana-Champaign
Year dc:date: 2022

Author and committee

dc:creator, dc:contributor.*

Author dc:creator: Gao, Suya
Contributors dc:contributor: Lee, Chia-Fon F
Stephani, Kelly
Wang, Xinlei
West, Matthew

Subjects

dc:subject × 1

Mechanical science

Rights

dc:rights

Language dc:language: en, eng

Identifiers

dc:identifier.*

Handle dc:identifier: http://hdl.handle.net/2142/113960
OAI identifier oai:identifier: oai:www.ideals.illinois.edu:2142/113960

Study of multi-component spray and combustion and their optimization with machine learning in internal combustion engines

Abstract

Degree

Author and committee

Subjects

Rights

Identifiers

Chain of custody

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