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Document type:
Zeitschriftenaufsatz 
Author(s):
Ma, Hao; Zhang, Botao; Zhang, Chi; Haidn, Oskar J. 
Title:
Generative adversarial networks with physical evaluators for spray simulation of pintle injector 
Abstract:
Due to the adjustable geometry, pintle injectors are especially suitable for liquid rocket engines, which require a widely throttleable range. However, applying the conventional computational fluid dynamics approaches to simulate the complex spray phenomenon in the whole range still remains a great challenge. In this paper, a novel deep learning approach used to simulate instantaneous spray fields under continuous operating conditions is explored. Based on one specific type of neural network and...    »
 
Dewey Decimal Classification:
620 Ingenieurwissenschaften 
Journal title:
AIP Advances 
Year:
2021 
Journal volume:
11 
Journal issue:
Pages contribution:
075007 
Language:
en 
Fulltext / DOI:
Publisher:
AIP Publishing 
E-ISSN:
2158-3226 
Accepted:
01.06.2021 
Date of publication:
02.07.2021 
TUM Institution:
Lehrstuhl für Aerodynamik und Strömungsmechanik