Opendata, web and dolomites

ADMITTED SIGNED

Advanced Data Methods for Improved Tiltrotor Test and Design

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

Project "ADMITTED" data sheet

The following table provides information about the project.

Coordinator
TXT E-SOLUTIONS SPA 

Organization address
address: Via Frigia 27
city: MILANO
postcode: 20126
website: www.txt.it

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 Italy [IT]
 Total cost 1˙718˙330 €
 EC max contribution 1˙718˙330 € (100%)
 Programme 1. H2020-EU.3.4.5.3. (IADP Fast Rotorcraft)
 Code Call H2020-CS2-CFP08-2018-01
 Funding Scheme CS2-RIA
 Starting year 2019
 Duration (year-month-day) from 2019-02-01   to  2023-11-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    TXT E-SOLUTIONS SPA IT (MILANO) coordinator 790˙000.00
2    SCUOLA UNIVERSITARIA PROFESSIONALE DELLA SVIZZERA ITALIANA CH (MANNO) participant 482˙500.00
3    STICHTING NATIONAAL LUCHT- EN RUIMTEVAARTLABORATORIUM NL (AMSTERDAM) participant 445˙830.00

Map

 Project objective

Flight testing is an important phase during the development of an aircraft to validate the design. During flight, data is gathered and design problems are identified and solved. The collected data are fundamental for the analysis and Aircraft are properly instrumented to generate large amounts of information. Such huge amount of data needs to be properly evaluated and traditional methods and platforms are no more effective. Flight testing is a significant cost contributor to the aircraft production life cycle and is still extensively deployed. Flight test programmes take several years and more prototypes are built to reduce lead times. Strong adherence to rigour safety and certification requirements and generally unchanged circular advisories inhibit the potential improvement of flight test designs. Innovative algorithms and statistical estimation are not achieving its full potential in the industrialized flight testing environment. The methods in this proposal increase the quality and productivity of an experiment, leading to a required test point reduction or increased predictive capabilities. The purpose of this project is to define and implement a state-of-the-art platform able to support data analysis. This is achieved by adopting a complex hardware architecture to support big data analysis and implementing specific algorithms to support data correlation, time series management and statistical analysis. Furthermore, to support flight test engineers, novel approaches based on machine learning are provided to support the technicians in detecting specific flight conditions. The same platform is also adapted to support the development of the Next Generation Civil Tilt Rotor Technology Demonstrator.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "ADMITTED" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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

More projects from the same programme (H2020-EU.3.4.5.3.)

RoCS (2019)

Rotorcraft Certification by Simulation

Read More  

TRINIDAT (2019)

Tilt Rotor INlet Innovative Design And Testing

Read More  

STEADIEST (2019)

Design, development and flight qualification of a supercritical composite shaft drive line for tiltrotor main drive system

Read More