Accurate regression rate determination of hybrid rocket fuels using convolutional neural networks

Assenmacher, Oliver and Rüttgers, Alexander and Petrarolo, Anna (2022) Accurate regression rate determination of hybrid rocket fuels using convolutional neural networks. WAW Machine Learning, 2022-11-07 - 2022-11-09, Jena, Deutschland.

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Item URL in elib:

https://elib.dlr.de/191773/

Document Type:

Conference or Workshop Item (Poster)

Title:

Accurate regression rate determination of hybrid rocket fuels using convolutional neural networks

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Assenmacher, Oliver	UNSPECIFIED	https://orcid.org/0000-0003-4614-4715	UNSPECIFIED
Rüttgers, Alexander	UNSPECIFIED	https://orcid.org/0000-0001-6347-9272	UNSPECIFIED
Petrarolo, Anna	UNSPECIFIED	https://orcid.org/0000-0002-2291-2874	UNSPECIFIED

Date:

November 2022

Refereed publication:

Open Access:

Yes

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

Status:

Published

Keywords:

machine learning, hybrid rocket fuels, convolutional neural networks, data augmentation, high-performance computing, semantic segmentation

Event Title:

WAW Machine Learning

Event Location:

Jena, Deutschland

Event Type:

Workshop

Event Start Date:

7 November 2022

Event End Date:

9 November 2022

Organizer:

DLR Institut für Datenwissenschaften

HGF - Research field:

Aeronautics, Space and Transport

HGF - Program:

Space

HGF - Program Themes:

Space System Technology

DLR - Research area:

Raumfahrt

DLR - Program:

R SY - Space System Technology

DLR - Research theme (Project):

R - Tasks SISTEC

Location:

Köln-Porz

Institutes and Institutions:

Institute of Software Technology > High-Performance Computing
Institute of Space Propulsion > Spacecraft and Orbital Propulsion
Institute of Software Technology

Deposited By:

Assenmacher, Oliver

Deposited On:

21 Dec 2022 10:42

Last Modified:

24 Apr 2024 20:53

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