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MAGISTER SIGNED

Machine learning for Advanced Gas turbine Injection SysTems to Enhance combustoR performance.

Total Cost €

0

EC-Contrib. €

0

Partnership

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 MAGISTER project word cloud

Explore the words cloud of the MAGISTER project. It provides you a very rough idea of what is the project "MAGISTER" about.

lean    royce    physical    lifetime    pressure    usa    fourth    learning    engineering    germany    enabler    combustors    goals    mixed    ge    grow    rolls    barely    introduces    meet    innovation    aviation    shape    last    scientists    monitor    decades    air    cyber    stringent    council    relevance    decisions    safran    shaped    clean    itn    health    regulations    network    automated    engine    machine    predictability    industrial    thermoacoustics    revolutionary    sensitivity    premixed    internet    pollutant    shows    area    engines    utilize    severe    emissions    persistently    revolution    2050    predict    full    surface    reduce    world    advisory    understand    outreach    vision    encounters    input    phenomenon    ensures    aircraft    operated    reliability    risk    flight    spirit    humans    fall    participation    combustor    transportation    talents    respect    oems    combustion    manufacturers    analyze    ecosystems    magister    tested    industry    oscillations    career   

Project "MAGISTER" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITEIT TWENTE 

Organization address
address: DRIENERLOLAAN 5
city: ENSCHEDE
postcode: 7522 NB
website: www.utwente.nl

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Netherlands [NL]
 Total cost 3˙873˙159 €
 EC max contribution 3˙873˙159 € (100%)
 Programme 1. H2020-EU.1.3.1. (Fostering new skills by means of excellent initial training of researchers)
 Code Call H2020-MSCA-ITN-2017
 Funding Scheme MSCA-ITN-ETN
 Starting year 2017
 Duration (year-month-day) from 2017-09-01   to  2021-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITEIT TWENTE NL (ENSCHEDE) coordinator 766˙122.00
2    THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE UK (CAMBRIDGE) participant 546˙575.00
3    GENERAL ELECTRIC DEUTSCHLAND HOLDING GMBH DE (FRANKFURT AM MAIN) participant 498˙432.00
4    TECHNISCHE UNIVERSITAET MUENCHEN DE (MUENCHEN) participant 498˙432.00
5    ANSYS FRANCE SAS FR (MONTIGNY LE BRETONNEUX) participant 262˙875.00
6    ASSOCIATION POUR LA RECHERCHE ET LE DEVELOPPEMENT DES METHODES ET PROCESSUS INDUSTRIELS FR (PARIS) participant 262˙875.00
7    CENTRE EUROPEEN DE RECHERCHE ET DE FORMATION AVANCEE EN CALCUL SCIENTIFIQUE FR (TOULOUSE) participant 262˙875.00
8    SAFRAN HELICOPTER ENGINES FR (BORDES) participant 262˙875.00
9    SAFRAN SA FR (PARIS 15) participant 262˙875.00
10    KARLSRUHER INSTITUT FUER TECHNOLOGIE DE (KARLSRUHE) participant 249˙216.00
11    BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY US (STANFORD) partner 0.00
12    FDX Fluid Dynamix GmbH DE (Berlin) partner 0.00
13    GENERAL ELECTRIC (SWITZERLAND) GMBH CH (BADEN) partner 0.00
14    GEORGIA INSTITUTE OF TECHNOLOGY US (ATLANTA) partner 0.00
15    KONINKLIJKE LUCHTVAART MAATSCHAPPIJNV NL (AMSTELVEEN) partner 0.00
16    ROLLS-ROYCE POWER ENGINEERING PLC UK (DERBY) partner 0.00
17    SHELL RESEARCH LIMITED UK (LONDON) partner 0.00

Map

 Project objective

Air transportation is expected to grow persistently over the next decades. Clean combustion technology for aircraft engines is a key enabler to reduce the impact of this growth on ecosystems and humans’ health. The vision for European aviation is shaped by the Advisory Council for Aviation Research and Innovation in Europe in the Flight Path 2050 goals, which define stringent regulations on pollutant emissions. To meet these goals, the major engine manufacturers develop lean premixed combustors operated at very high pressure. This development introduces a large risk for reduced reliability and lifetime of engines: pressure oscillations in the combustor called thermoacoustics. Much research has been dedicated to study this phenomenon over the last decades with mixed success. Industrial experience shows that the pressure oscillations often surface as late as the full engine has been built and tested. Traditional engineering methods fall short of predictability during the design of the engines due to a high sensitivity of thermoacoustics with respect to barely known input parameters. Aviation industry encounters currently the fourth industrial revolution: cyber-physical systems analyze and monitor technical systems and take automated decisions. This industrial revolution is known as “Industry 4.0” in Germany and “Industrial Internet” in the USA. An essential enabler of the fourth industrial revolution is Machine Learning. The ITN MAGISTER will utilize Machine Learning to predict and understand thermoacoustics in aircraft engine combustors, and lead combustion research a revolutionary new approach in this area. The participation of the major aircraft engine OEMs GE, Rolls Royce, Safran ensures industrial relevance and outreach of the results. The project will shape early career talents in a network of world leading scientists and industrial partners to work on one of the most severe design issues in aviation technology in the spirit of the fourth industrial revolution.

 Deliverables

List of deliverables.
Comparison of different machine learning algorithms. Documents, reports 2020-02-17 16:47:38
Workshop C Other 2020-02-17 16:47:35
Data Management Plan (DMP) Open Research Data Pilot 2020-02-17 16:47:43
Application of machine learning in CFD. Documents, reports 2020-02-17 16:47:58
Workshop B Other 2020-02-17 16:47:35
Modelling of acoustically absorbing liners. Documents, reports 2020-02-17 16:48:10
MAGISTER web site operational Websites, patent fillings, videos etc. 2020-01-28 16:25:38
Summer school: Thermo-acoustics and combustion dynamics in aero gas turbine engines Other 2020-01-28 16:25:38
Workshop A Other 2020-01-28 16:25:38

Take a look to the deliverables list in detail:  detailed list of MAGISTER deliverables.

 Publications

year authors and title journal last update
List of publications.
2019 Sara Navarro Arredondo, Jim Kok
A model to study spontaneous oscillations in a lean premixed combustor using non-linear analysis
published pages: , ISSN: , DOI:
Proceedings of the 26th International Congress on Sound and Vibration 2020-01-28
2019 McCartney M., Haeringer M., Polifke W.,
Comparison of Machine Learning Algorithms in the Interpolation and Extrapolation of Flame Describing Functions.
published pages: , ISSN: , DOI:
Proceedings of the ASME Turbo Expo 2019 2020-01-28
2019 Alireza Ghasemi, J.B.W. Kok
Numerical Study Of A Swirl Atomized Spray Response To Acoustic Perturbations.
published pages: , ISSN: , DOI:
Proceedings of the 26th International Congress on Sound and Vibration 2020-01-28

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The information about "MAGISTER" are provided by the European Opendata Portal: CORDIS opendata.

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