Proton Radiation Belt Anisotropy as Seen by ICARE-NG Head-A

Self Cite

CNES and ONERA have developed a radiation monitor ICARE-NG (Influence sur les Composants Avancés des Radiations de l'Espace-Nouvelle Génération) to measure protons and electrons in radiation belts. This instrument is able to measure a wide range of energy for protons and electrons, but no measurements of few MeV protons are performed. The objective of this study is to extend capabilities of this radiation monitor by adding a low-energy proton sensor. In this article the design of a sensor for low-energy protons compatible with the ICARE-NG instrument is presented. Response functions for protons and electrons of the low-energy proton sensor are calculated using Monte-Carlo simulations. The calculation of predicted count rates of particles are performed. The manufacturing of the instrument as well as tests are discussed.

Section: The Instrument's Geometrymentioning

confidence: 99%

“…To take into account the response functions of the sensor and particle distributions, expected count rates for each channel are computed. The expression of count rates for a given deposited energy channel is provided in (2) and extracted from [20].…”

Section: ) the Modeling Of Calculated Counts Of Particlesmentioning

confidence: 99%

A Proton Sensor for Energies From 2 to 20 MeV

Ruffenach

Bourdarie

Mekki

et al. 2020

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“…Over the last two decades, several efforts have been done towards creating standardized modular radiation monitors that can be easily adapted to many different satellites. Many of these monitors are based on sophisticated radiation monitors that can detect different kinds of particles and resolve their energy [1,2]. Others are based on low-cost detectors, e.g., static random access memories (SRAMs) that can characterize the radiation environment by measuring single-event upsets (SEU) or single-event latchups (SEL) [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17].…”

mentioning

confidence: 99%

The CELESTA CubeSat In-Flight Radiation Measurements and Their Comparison With Ground Facilities Predictions

Coronetti,

Zimmaro,

García Alía

et al. 2024

The CELESTA CubeSat has employed radiation monitors developed by the Conseil Europeeene pour la Recherche Nucleaire (CERN), used for measuring the radiation environment at accelerators, to measure the space radiation field in a medium-Earth orbit (MEO). The technology is based on three static random access memories (SRAMs) that are sensitive to singleevent upsets (SEUs) and single-event latchups (SELs). The measurements were performed for the duration of 2 months. A statistically significant amount of SEUs and SELs were collected. No solar proton event effects were observed in the data during this period. The in-flight rates were compared with respect to estimations coming from the environmental space fluxes available in the Outil de Modelisation de l'Environmment Radiative Externe (OMERE) tool suite and ground facility measurements done with ions and protons. The analysis emphasizes the importance of employing more sophisticated satellite shielding models for the calculation of the fluxes reaching the detectors as well as the need to know accurately the proton energy threshold of the SEU cross section Weibull response of the devices. Both observations mainly arise from the peculiar spectral distribution of protons in this MEO peaking at 10-20 MeV, which differs from those of a low-Earth orbit environment.

A New Technique Based on Convolutional Neural Networks to Measure the Energy of Protons and Electrons With a Single Timepix Detector

Ruffenach

Bourdarie

Bergmann

et al. 2021

The Timepix chip has been exposed to the outer space for the first time with the SATRAM (Space Application of Timepix-based Radiation Monitor) instrument on Proba-V (Project for On-Board Autonomy Vegetation), a European Space Agency's (ESA) satellite. This study's objective is to develop a new technique to improve the separation of protons and electrons, which are detected by the single layer Timepix detector in SATRAM. The current identification method, proposed by S. Gohl et al. [1], is based on pattern recognition and stopping power measurements. In this article, the limitations of this method are discussed. A new method based on neural network trained with Geant4 data is proposed. Its validation with SATRAM data is presented. Similarly, a neural network trained with Geant4 data is introduced. Its purpose is to deduce the particles' incident energy using the energy deposited in the Timepix.