Steve R. Blattnig

Faster and more accurate transport procedures for HZETRN

The deterministic transport code HZETRN was developed for research scientists and design engineers studying the effects of space radiation on astronauts and instrumentation protected by various shielding materials and structures. In this work, several aspects of code verification are examined. First, a detailed derivation of the light particle (A= 4) numerical marching algorithms used in HZETRN is given. References are given for components of the derivation that already exist in the literature, and discussions are given for details that may have been absent in the past. The present paper provides a complete description of the numerical methods currently used in the code and is identified as a key component of the verification process. Next, a new numerical method for light particle transport is presented, and improvements to the heavy ion transport algorithm are discussed. A summary of round-off error is also given, and the impact of this error on previously predicted exposure quantities is shown. Finally, a coupled convergence study is conducted by refining the discretization parameters (step-size and energy grid-size). From this study, it is shown that past efforts in quantifying the numerical error in HZETRN were hindered by single precision calculations and computational resources. It is determined that almost all of the discretization error in HZETRN is caused by the use of discretization parameters that violate a numerical convergence criterion related to charged target fragments below 50AMeV. Total discretization errors are given for the old and new algorithms to 100g/cm^2 in aluminum and water, and the improved accuracy of the new numerical methods is demonstrated. Run time comparisons between the old and new algorithms are given for one, two, and three layer slabs of 100g/cm^2 of aluminum, polyethylene, and water. The new algorithms are found to be almost 100 times faster for solar particle event simulations and almost 10 times faster for galactic cosmic ray simulations.

GCR environmental models I: Sensitivity analysis for GCR environments

Accurate galactic cosmic ray (GCR) models are required to assess crew exposure during long-duration missions to the Moon or Mars. Many of these models have been developed and compared to available measurements, with uncertainty estimates usually stated to be less than 15%. However, when the models are evaluated over a common epoch and propagated through to effective dose, relative differences exceeding 50% are observed. This indicates that the metrics used to communicate GCR model uncertainty can be better tied to exposure quantities of interest for shielding applications. This is the first of three papers focused on addressing this need. In this work, the focus is on quantifying the extent to which each GCR ion and energy group, prior to entering any shielding material or body tissue, contributes to effective dose behind shielding. Results can be used to more accurately calibrate model-free parameters and provide a mechanism for refocusing validation efforts on measurements taken over important energy regions. Results can also be used as references to guide future nuclear cross-section measurements and radiobiology experiments. It is found that GCR with Z > 2 and boundary energies below 500 MeV/n induce less than 5% of the total effective dose behind shielding. This finding is important given that most of the GCR models are developed and validated against Advanced Composition Explorer/Cosmic Ray Isotope Spectrometer (ACE/CRIS) measurements taken below 500 MeV/n. It is therefore possible for two models to very accurately reproduce the ACE/CRIS data while inducing very different effective dose values behind shielding.

Galactic cosmic ray simulation at the NASA Space Radiation Laboratory

Most accelerator-based space radiation experiments have been performed with single ion beams at fixed energies. However, the space radiation environment consists of a wide variety of ion species with a continuous range of energies. Due to recent developments in beam switching technology implemented at the NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory (BNL), it is now possible to rapidly switch ion species and energies, allowing for the possibility to more realistically simulate the actual radiation environment found in space. The present paper discusses a variety of issues related to implementation of galactic cosmic ray (GCR) simulation at NSRL, especially for experiments in radiobiology. Advantages and disadvantages of different approaches to developing a GCR simulator are presented. In addition, issues common to both GCR simulation and single beam experiments are compared to issues unique to GCR simulation studies. A set of conclusions is presented as well as a discussion of the technical implementation of GCR simulation.

Variation in Lunar Neutron Dose Estimates

The radiation environment on the Moon includes albedo neutrons produced by primary particles interacting with the lunar surface. In this work, HZETRN2010 is used to calculate the albedo neutron contribution to effective dose as a function of shielding thickness for four different space radiation environments and to determine to what extent various factors affect such estimates. First, albedo neutron spectra computed with HZETRN2010 are compared to Monte Carlo results in various radiation environments. Next, the impact of lunar regolith composition on the albedo neutron spectrum is examined, and the variation on effective dose caused by neutron fluence-to-effective dose conversion coefficients is studied. A methodology for computing effective dose in detailed human phantoms using HZETRN2010 is also discussed and compared. Finally, the combined variation caused by environmental models, shielding materials, shielding thickness, regolith composition and conversion coefficients on the albedo neutron contribution to effective dose is determined. It is shown that a single percentage number for characterizing the albedo neutron contribution to effective dose can be misleading. In general, the albedo neutron contribution to effective dose is found to vary between 1–32%, with the environmental model, shielding material and shielding thickness being the driving factors that determine the exact contribution. It is also shown that polyethylene or other hydrogen-rich materials may be used to mitigate the albedo neutron exposure.

Towards a Credibility Assessment of Models and Simulations

*† ‡ § ** †† A scale is presented to evaluate the rigor of modeling and simulation (M&S) practices for the purpose of supporting a credibility assessment of the M&S results. The scale distinguishes required and achieved levels of rigor for a set of M&S elements that contribute to credibility including both technical and process measures. The work has its origins in an interest within NASA to include a “Credibility Assessment Scale” in development of a NASA standard for models and simulations.

GCR environmental models II: Uncertainty propagation methods for GCR environments

In order to assess the astronaut exposure received within vehicles or habitats, accurate models of the ambient galactic cosmic ray (GCR) environment are required. Many models have been developed and compared to measurements, with uncertainty estimates often stated to be within 15%. However, intercode comparisons can lead to differences in effective dose exceeding 50%. This is the second of three papers focused on resolving this discrepancy. The first paper showed that GCR heavy ions with boundary energies below 500 MeV/n induce less than 5% of the total effective dose behind shielding. Yet, due to limitations on available data, model development and validation are heavily influenced by comparisons to measurements taken below 500 MeV/n. In the current work, the focus is on developing an efficient method for propagating uncertainties in the ambient GCR environment to effective dose values behind shielding. A simple approach utilizing sensitivity results from the first paper is described and shown to be equivalent to a computationally expensive Monte Carlo uncertainty propagation. The simple approach allows a full uncertainty propagation to be performed once GCR uncertainty distributions are established. This rapid analysis capability may be integrated into broader probabilistic radiation shielding analysis and also allows error bars (representing boundary condition uncertainty) to be placed around point estimates of effective dose.

Reference field specification and preliminary beam selection strategy for accelerator-based GCR simulation

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 and possible biological considerations. 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, a preliminary approach for selecting beams at NSRL to simulate the designated reference field is presented. This approach is not a final design for the GCR simulator, but rather a single step within a broader design strategy. It is shown that the beam selection methodology is tied directly to the reference environment, allows facility constraints to be incorporated, and may be adjusted to account for additional constraints imposed by biological or animal care considerations. The major biology questions are not addressed herein but are discussed in a companion paper published in the present issue of this journal. Drawbacks of the proposed methodology are discussed and weighed against alternative simulation strategies.

Validation of nuclear models used in space radiation shielding applications

A program of verification and validation has been undertaken to assess the applicability of models to space radiation shielding applications and to track progress as these models are developed over time. In this work, simple validation metrics applicable to testing both model accuracy and consistency with experimental data are developed. The developed metrics treat experimental measurement uncertainty as an interval and are therefore applicable to cases in which epistemic uncertainty dominates the experimental data. To demonstrate the applicability of the metrics, nuclear physics models used by NASA for space radiation shielding applications are compared to an experimental database consisting of over 3600 experimental cross sections. A cumulative uncertainty metric is applied to the question of overall model accuracy, while a metric based on the median uncertainty is used to analyze the models from the perspective of model development by examining subsets of the model parameter space.

Optimal shielding thickness for galactic cosmic ray environments

Models have been extensively used in the past to evaluate and develop material optimization and shield design strategies for astronauts exposed to galactic cosmic rays (GCR) on long duration missions. A persistent conclusion from many of these studies was that passive shielding strategies are inefficient at reducing astronaut exposure levels and the mass required to significantly reduce the exposure is infeasible, given launch and associated cost constraints. An important assumption of this paradigm is that adding shielding mass does not substantially increase astronaut exposure levels. Recent studies with HZETRN have suggested, however, that dose equivalent values actually increase beyond ∼20g/cm2 of aluminum shielding, primarily as a result of neutron build-up in the shielding geometry. In this work, various Monte Carlo (MC) codes and 3DHZETRN are evaluated in slab geometry to verify the existence of a local minimum in the dose equivalent versus aluminum thickness curve near 20g/cm2. The same codes are also evaluated in polyethylene shielding, where no local minimum is observed, to provide a comparison between the two materials. Results are presented so that the physical interactions driving build-up in dose equivalent values can be easily observed and explained. Variation of transport model results for light ions (Z ≤ 2) and neutron-induced target fragments, which contribute significantly to dose equivalent for thick shielding, is also highlighted and indicates that significant uncertainties are still present in the models for some particles. The 3DHZETRN code is then further evaluated over a range of related slab geometries to draw closer connection to more realistic scenarios. Future work will examine these related geometries in more detail.

An Uncertainty Structure Matrix for Models and Simulations

Software that is used for aerospace flight control and to display information to pilots and crew is expected to be correct and credible at all times. This type of software is typically developed under strict management processes, which are intended to reduce defects in the software product. However, modeling and simulation (M&S) software may exhibit varying degrees of correctness and credibility, depending on a large and complex set of factors. These factors include its intended use, the known physics and numerical approximations within the M&S, and the referent data set against which the M&S correctness is compared. The correctness and credibility of an M&S effort is closely correlated to the uncertainty management (UM) practices that are applied to the M&S effort. This paper describes an uncertainty structure matrix for M&S, which provides a set of objective descriptions for the possible states of UM practices within a given M&S effort. The columns in the uncertainty structure matrix contain UM elements or practices that are common across most M&S efforts, and the rows describe the potential levels of achievement in each of the elements. A practitioner can quickly look at the matrix to determine where an M&S effort falls based on a common set of UM practices that are described in absolute terms that can be applied to virtually any M&S effort. The matrix can also be used to plan those steps and resources that would be needed to improve the UM practices for a given M&S effort.