ALBERT

Description: The deterministic radiation transport code HZETRN (High charge (Z) and Energy TRaNsport) was developed by NASA to study the effects of cosmic radiation on astronauts and instrumentation shielded by various materials. This work presents an analysis of computed differential flux from HZETRN compared with measurement data from three balloon-based experiments over a range of atmospheric depths, particle types, and energies. Model uncertainties were quantified using an interval-based validation metric that takes into account measurement uncertainty both in the flux and the energy at which it was measured. Average uncertainty metrics were computed for the entire dataset as well as subsets of the measurements (by experiment, particle type, energy, etc.) to reveal any specific trends of systematic over- or under-prediction by HZETRN. The distribution of individual model uncertainties was also investigated to study the range and dispersion of errors beyond just single scalar and interval metrics. The differential fluxes from HZETRN were generally well-correlated with balloon-based measurements; the median relative model difference across the entire dataset was determined to be 30%. The distribution of model uncertainties, however, revealed that the range of errors was relatively broad, with approximately 30% of the uncertainties exceeding 40%. The distribution also indicated that HZETRN systematically under-predicts the measurement dataset as a whole, with approximately 80% of the relative uncertainties having negative values. Instances of systematic bias for subsets of the data were also observed, including a significant underestimation of alpha particles and protons for energies below 2.5 GeV/u. Muons were found to be systematically over-predicted at atmospheric depths deeper than 50 g/cm(sup 2) but under-predicted for shallower depths. Furthermore, a systematic under-prediction of alpha particles and protons was observed below the geomagnetic cutoff, suggesting that improvements to the light ion production cross sections in HZETRN should be investigated.

Description: Exposure to galactic cosmic rays (GCR) on long duration deep space missions presents a serious health risk to astronauts, with large uncertainties connected to the biological response. In order to reduce the uncertainties and gain understanding about the basic mechanisms through which space radiation initiates cancer and other endpoints, radiobiology experiments are performed. Some of the accelerator facilities supporting such experiments have matured to a point where simulating the broad range of particles and energies characteristic of the GCR environment in a single experiment is feasible from a technology, usage, and cost perspective. In this work, several aspects of simulating the GCR environment in the laboratory are discussed. First, comparisons are made between direct simulation of the external, free space GCR field and simulation of the induced tissue field behind shielding. It is found that upper energy constraints at the NASA Space Radiation Laboratory (NSRL) limit the ability to simulate the external, free space field directly (i.e. shielding placed in the beam line in front of a biological target and exposed to a free space spectrum). Second, variation in the induced tissue field associated with shielding configuration and solar activity is addressed. It is found that the observed variation is within physical uncertainties, allowing a single reference field for deep space missions to be defined. Third, an approach for simulating the reference field at NSRL is presented. The approach allows for the linear energy transfer (LET) spectrum of the reference field to be approximately represented with discrete ion and energy beams and implicitly maintains a reasonably accurate charge spectrum (or, average quality factor). Drawbacks of the proposed methodology are discussed and weighed against alternative simulation strategies. The neutron component and track structure characteristics of the proposed strategy are discussed in this context.

Description: The code RITRACKS (Relativistic Ion Tracks) was developed to simulate detailed stochastic radiation track structures of ions of different types and energies. Many new capabilities were added to the code during the recent years. Several options were added to specify the times at which the tracks appear in the irradiated volume, allowing the simulation of dose-rate effects. The code has been used to simulate energy deposition in several targets: spherical, ellipsoidal and cylindrical. More recently, density changes as well as a spherical shell were implemented for spherical targets, in order to simulate energy deposition in walled tissue equivalent proportional counters. RITRACKS is used as a part of the new program BDSTracks (Biological Damage by Stochastic Tracks) to simulate several types of chromosome aberrations in various irradiation conditions. The simulation of damage to various DNA structures (linear and chromatin fiber) by direct and indirect effects has been improved and is ongoing. Many improvements were also made to the graphic user interface (GUI), including the addition of several labels allowing changes of units. A new GUI has been added to display the electron ejection vectors. The parallel calculation capabilities, notably the pre- and post-simulation processing on Windows and Linux machines have been reviewed to make them more portable between different systems. The calculation part is currently maintained in an Atlassian Stash repository for code tracking and possibly future collaboration.

Description: The NASA Space Radiation Risk project is responsible for integrating new experimental and computational results into models to predict risk of cancer and acute radiation syndrome (ARS) for use in mission planning and systems design, as well as current space operations. The project has several parallel efforts focused on proving NASA's radiation risk projection capability in both the near and long term. This presentation will give an overview, with select results from these efforts including the following topics: verification, validation, and streamlining the transition of models to use in decision making; relative biological effectiveness and dose rate effect estimation using a combination of stochastic track structure simulations, DNA damage model calculations and experimental data; ARS model improvements; pathway analysis from gene expression data sets; solar particle event probabilistic exposure calculation including correlated uncertainties for use in design optimization.

Description: The high relative biological effectiveness (RBE) of high charged and energy (HZE) particles for cell death, DNA mutations and cancer remain based on experimental data. In this work, we propose that the existence of DNA repair domains is sufficient to predict both cell death and mutation frequencies for any LET by only taking into account experimental data from low-LET, offering one mechanism for RBE across LET. We hypothesize that whenever multiple DNA double-strand breaks (DSBs) are generated within the same DNA repair domain, DSBs are actively regrouped for more efficient repair [1]. This hypothesis has been supported by the low-LET sublinear dose response observed at doses greater than ~1Gy for 53BP1 radiation-induced foci (RIF) reflecting increasing DSB/RIF with dose [2]. Previously, we modeled radiation-induced cell death of human breast cells by first inferring the size of these domains from the dose dependence of low-LET RIF, and by associating a lethality factor to the number of pairs of DSBs in each RIF [1]. In this work, we first integrate the new NASA computer models RITCARD (Relativistic Ion Tracks, Chromosome Aberrations, Repair, and Damage) [3] and BDSTracks (Biological Damage by Stochastic Tracks) for a more accurate microdosimetry and a better model of the nuclear organization to predict the location of DSBs. A large array of particles and energy are simulated, covering more than three orders of magnitude for LET (~1-1000 keV/m). Next, we extend our previous model to predict mutation frequencies by assuming that clustered DSBs increase mutation probability, which is formalized by the mutation frequency being linearly dependent on both the number of DSBs and the number of pairs of DSBs inside individual RIF. Linear coefficients are estimated so that simulations predict accurately mutation frequencies observed in Chinese hamster cells exposed to low-LET. Keeping these coefficients unchanged, we then predict mutation frequencies induced by HZE by simulating DSBs and obtain RBEs for mutations and cell death following the expected experimental bell shape for LET dependence. We also observe an orientation effect that needs to be confirmed, showing different RBE depending on the angle of the HZE beam hitting the main axis of the cell.

Description: This paper develops techniques for predicting the uncertainty range of an output variable given input-output data. These models are called Interval Predictor Models (IPM) because they yield an interval valued function of the input. This paper develops IPMs having a radial basis structure. This structure enables the formal description of (i) the uncertainty in the models parameters, (ii) the predicted output interval, and (iii) the probability that a future observation would fall in such an interval. In contrast to other metamodeling techniques, this probabilistic certi cate of correctness does not require making any assumptions on the structure of the mechanism from which data are drawn. Optimization-based strategies for calculating IPMs having minimal spread while containing all the data are developed. Constraints for bounding the minimum interval spread over the continuum of inputs, regulating the IPMs variation/oscillation, and centering its spread about a target point, are used to prevent data over tting. Furthermore, we develop an approach for using expert opinion during extrapolation. This metamodeling technique is illustrated using a radiation shielding application for space exploration. In this application, we use IPMs to describe the error incurred in predicting the ux of particles resulting from the interaction between a high-energy incident beam and a target.

Description: The galactic cosmic ray (GCR) simulator at the NASA Space Radiation Laboratory (NSRL) is intended to deliver the broad spectrum of particles and energies encountered in deep space to biological targets in a controlled laboratory setting. In this work, certain aspects of simulating the GCR environment in the laboratory are discussed. Reference field specification and beam selection strategies at NSRL are the main focus, but the analysis presented herein may be modified for other facilities. First, comparisons are made between direct simulation of the external, free space GCR field and simulation of the induced tissue field behind shielding. It is found that upper energy constraints at NSRL limit the ability to simulate the external, free space field directly (i.e. shielding placed in the beam line in front of a biological target and exposed to a free space spectrum). Second, variation in the induced tissue field associated with shielding configuration and solar activity is addressed. It is found that the observed variation is likely within the uncertainty associated with representing any GCR reference field with discrete ion beams in the laboratory, given current facility constraints. A single reference field for deep space missions is subsequently identified. Third, an approach for selecting beams at NSRL to simulate the designated reference field is presented. Drawbacks of the proposed methodology are discussed and weighed against alternative simulation strategies. The neutron component and track structure characteristics of the simulated field are discussed in this context.

Description: Exploration missions to Mars and other destinations raise many questions about the health of astronauts. The continuous exposure of astronauts to galactic cosmic rays is one of the main concerns for long-term missions. Cosmic ionizing radiations are composed of different ions of various charges and energies notably, highly charged energy (HZE) particles. The HZE particles have been shown to be more carcinogenic than low-LET radiation, suggesting the severity of chromosomal aberrations induced by HZE particles is one possible explanation. However, most mathematical models predicting cell death and mutation frequency are based on directly fitting various HZE dose response and are in essence empirical approaches. In this work, we assume a simple biological mechanism to model DNA repair and use it to simultaneously explain the low- and high-LET response using the exact same fitting parameters. Our work shows that the geometrical position of DNA repair along tracks of heavy ions are sufficient to explain why high-LET particles can induce more death and mutations. Our model is based on assuming DNA double strand breaks (DSBs) are repaired within repair domain, and that any DSBs located within the same repair domain cluster into one repair unit, facilitating chromosomal rearrangements and increasing the probability of cell death. We introduced this model in 2014 using simplified microdosimetry profiles to predict cell death. In this work, we collaborated with NASA Johnson Space Center to generate more accurate microdosimetry profiles derived by Monte Carlo techniques, taking into account track structure of HZE particles and simulating DSBs in realistic cell geometry. We simulated 224 data points (D, A, Z, E) with the BDSTRACKS model, leading to a large coverage of LET from ~10 to 2,400 keV/m. This model was used to generate theoretical RBE for various particles and energies for both cell death and mutation frequencies. The RBE LET dependence is in agreement with experimental data known in human and murine cells. It suggests that cell shape and its orientation with respect to the HZE particle beam can modify the biological response to radiation. Such discovery will be tested experimentally and, if proven accurate, will be another strong supporting evidence for DNA repair domains and their critical role in interpreting cosmic radiation sensitivity.

Description: 3DHZETRN-v2 includes a detailed three dimensional (3D) treatment of neutron/light-ion transport based on a quasi-elastic/multiple-production assumption allowing improved agreement of the neutron/light-ion fluence compared with results of three Monte Carlo (MC) codes in the sense that the variance with respect to the individual MC results is less than the variance among the MC code results. The current numerical methods are no longer the main limitation to HZETRN code development and further changes in the nuclear model are required. In a prior study, an improved quasi-elastic spectrum based on a solution of the transport approximation to nuclear media effects showed promise, but the remaining multiple-production spectrum was based on a database derived from the Ranft model that used Bertini multiplicities. In the present paper, we will implement a more complete Serber first step into the 3DHZETRN-v2 code, but we retain the Bertini-Ranft branching ratios and evaporation multiplicities. It is shown that the new Serber model in the 3HZETRN-v2 code reduces the variance with individual MC codes, which are largely due to nuclear cross section model differences.