Assessment of galactic cosmic ray models

Abstract

[1] Among several factors involved in the development of a manned space mission concept, the astronauts' health is a major concern that needs to be considered carefully. Galactic cosmic rays (GCRs), which mainly consist of high-energetic nuclei ranging from hydrogen to iron and beyond, pose a major radiation health risk in long-term space missions. It is therefore required to assess the radiation exposure of astronauts in order to estimate their radiation risks. This can be done either by performing direct measurements or by making computer based simulations from which the dose can be derived. A necessary prerequisite for an accurate estimation of the exposure using simulations is a reliable description of the GCR spectra. The aim of this work is to compare GCR models and to test their applicability for the exposure assessment of astronauts. To achieve this, commonly used models capable of describing both light and heavy GCR particle spectra were evaluated by investigating the model spectra for various particles over several decades. The updated Badhwar-O'Neill model published in the year 2010, CREME2009 which uses the International Standard model for GCR, CREME96 and the Burger-Usoskin model were examined. Hydrogen, helium, oxygen and iron nuclei spectra calculated by the different models are compared with measurements from various high-altitude balloon and space-borne experiments. During certain epochs in the last decade, there are large discrepancies between the GCR energy spectra described by the models and the measurements. All the models exhibit weaknesses in describing the increased GCR flux that was observed in

Exploiting different active silicon detectors in the International Space Station: ALTEA and DOSTEL galactic cosmic radiation (GCR) measurements

“…This model choice is strongly motivated by the wide availability of the model itself and supported by the good agreement found between the re-normalized ALTEA data and the DOSTEL data. Weaknesses of the CREME96 model have been nevertheless pointed out in recent works (see, e.g., Mrigakshi et al 2012). Further work is in progress to test the sensitivity of this re-normalization on the chosen model, by using more performing tools such as Badhwar/O'Neill (O'Neill et al 2015) or DLR (Matthiä et al 2013) models.…”

Neutron background environment measured by the Mars Science Laboratory's Dynamic Albedo of Neutrons instrument during the first 100 sols

“…A review paper on these commonly used GCR models has recently been published by Mrigakshi , et al . []. As noted, selecting a GCR model appropriate for the epoch when the measurements are made is a key for the accurate estimate of GCR‐induced neutron environment.…”

“…A comparison of different GCR models is described in Usoskin et al [2005], where a way was suggested to relate one model to another. A review paper on these commonly used GCR models has recently been published by Mrigakshi, et al [2012]. As noted, selecting a GCR model appropriate for the epoch when the measurements are made is a key for the accurate estimate of GCR-induced neutron environment.…”

Analysis of the Forbush Decreases and Ground‐Level Enhancement on September 2017 Using Neutron Spectrometers Operated in Antarctic and Midlatitude Stations

“…The solar modulation potential is a modeling parameter which is based on ground measurements and depends on the choice of the local interstellar spectrum (LIS) model. In the past LIS spectra have been established in many ways (Burger et al, ; Mrigakshi et al, ) and the Burger‐Usoskin LIS spectrum was considered in this work (Usoskin et al, ). However, the physical interpretation of the modulation potential is not straightforward during periods of active Sun (Usoskin et al, ) and requires more refined physical analyses.…”

“…The standard methods to determine ϕ(t) are based on NMs, whose advantages are the existence of an worldwide network, the efficient integration time (typically t int > 1 min) and the high coverage of the geomagnetic latitudes using one of the several yield functions calculated in the literature (Clem & Dorman, ; Flückiger et al, ; Mangeard et al, ; Mishev et al, ; Nagashima, ). As previously described, ϕ(t) depend on models for the Berger‐Usoskin LIS spectrum (Mrigakshi, ). Monthly averaged modulation parameters from 1951 are available (Herbst et al, ; Usoskin et al, ; Usoskin et al, ), using several LISs and several NMs.…”