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Funded Projects / details

Cofinanciado por:

PTSpace 
ESA 

Project
TGF and High-energy astrophysics Observatory for gamma-Rays on board the Space Rider

Code 4000141332 THOR-SR Space Rider

Beneficiary Entity

LIP - Laboratório de Instrumentação e Física Experimental de Partículas


Project summary

THOR-SR is a high-energy astrophysics pathfinder mission whose scientific payload is based on CdTe and Si detectors to be launched on board the Space Rider. It will address gamma ray astrophysics, space weather and TGF monitoring, by performing spectroscopy, imaging, time variability and polarimetry. It is a large field of view instrument ( up to 2𝛑 sr) provided by a 4 layers CdTe stack detector, operating in the 0.1–10 MeV energy band.


Support under

Reforçar a investigação, o desenvolvimento tecnológico e a inovação

Region of Intervention

...

 

Funding

Total eligible cost

€ 489,408.00


EU financial support

€ 489.41


Funding LIP

€ 489,408.00


National public financial support

€ 0.00

 

Dates

Approval


Start

2023-01-01


End

2025-12-31



Publications


Evaluation of effective dose for gamma-rays of Terrestrial Gamma-ray Flashes in aviation: spectral- and atmosphere-effectsArticle in international journal (with direct contribution from team)published

Presentations


Development of a High-Energy Astrophysics Tracker for a Space Rider Orbital FlightOutreach seminar
Experiência GLOSS a bordo da International Space StationOutreach seminar
Large Field CdTe Monitor for Astrophysics and TGF Science on board the Space RiderPoster presentation in international conference
Observatório THOR a bordo do Space RiderOutreach seminar
TGF and High-energy astrophysics Observatory for gamma-Rays on board the Space Rider (THOR-SR)Presentation in national conference

Theses


Simulation, development and testing of CdTe based Instrument for THOR mission on board the Space Rider
Space Radiation in Low Earth Orbit and Space Weather on board the Space Rider
Space Rider maiden flight orbital particles identification using machine learning techniques
THOR Project Scientific Payload Environmental Tests Validation

Team


André Graça Neves
Carolina Isabel Oliveira Nunes de Gouveia
Cristiana Filipa Pereira Francisco
Filipa Alexandra Bessa de Almeida
Gabriel Falcão Paiva Fernandes
Joana da Orada Gonçalves
Jonathan Flunger
José Carlos Ferreira Sousa
Luís José Maia amoreira
Maria Inês Bento Neves
Mariana Sofia Rasteiro Letra
Mário Henrique Guerra Cainé
Miriam Abreu Neves
Pedro Fonseca da Cunha Roque Póvoa
Thomas Chappaz