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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Analytic Modeling of a Deep Shielding Problem

Previous generations of scientists would make tremendous efforts to simplify non-tractable problems and generate simpler models that preserved the fundamental physics. This process involved applying assumptions and simplifications to reduce the complexity of the problem until it reached a solvable form. Each assumption and simplification was chosen and applied with the intent to preserve the essential physics of the problem, since, if the core physics of the problem were eliminated, the simplified model served no purpose. Moreover, if done correctly, solutions to the reduced model would serve as useful approximations to the original problem. In a sense, solving the simple models laid the ground-work for and provided insight into the more complex problem. Today, however, the affordability of high performance computing has essentially replaced the process for analyzing complex problems. Rather than "building up" a problem by understanding smaller, simpler models, a user generally relies on powerful computational tools to directly arrive at solutions to complex problems. As computational resources grow, users continue trying to simulate new, more complex, or more detailed problems, resulting in continual stress on both the code and computational resources. When these resources are limited, the user will have to make concessions by simplifying the problem while trying to preserve important details. In the context of MCNP, simplifications typically come as reductions in geometry, or by using variance reduction techniques. Both approaches can influence the physics of the problem, leading to potentially inaccurate or non-physical results. Errors can also be introduced as a result of faulty input into a computational tool: something as simple as transposing numbers in a tally input can result in incorrect answers. In this paradigm, reduced complexity computational and analytical models still have an important purpose. The explicit form of an analytic solution is arguably the best way to understand the qualitative properties of simple models. In contrast to "building up" a complex problem through understanding simpler problems, results from detailed computational scenarios can be better explained by "building down" the complex model through simple models rooted in the fundamental or essential phenomenology. Simplified analytic and computational models can be used to 1) increase a user's confidence in the computational solution of a complex model, 2) confirm there are no user input errors, and 3) ensure essential assumptions of the simulation tool are preserved. This process of using analytic models to develop a more valuable analysis of simulation results is named the results analysis methodology. The utility of the results assessment methodology and a complimentary sensitivity analysis is exemplified through the analysis of the neutron flux in a dry used fuel storage cask. This application was chosen due to current scientific interest in used nuclear fuel storage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Analytic Modeling of a Deep Shielding Problem

Previous generations of scientists would make tremendous efforts to simplify non-tractable problems and generate simpler models that preserved the fundamental physics. This process involved applying assumptions and simplifications to reduce the complexity of the problem until it reached a solvable form. Each assumption and simplification was chosen and applied with the intent to preserve the essential physics of the problem, since, if the core physics of the problem were eliminated, the simplified model served no purpose. Moreover, if done correctly, solutions to the reduced model would serve as useful approximations to the original problem. In a sense, solving the simple models laid the ground-work for and provided insight into the more complex problem. Today, however, the affordability of high performance computing has essentially replaced the process for analyzing complex problems. Rather than "building up" a problem by understanding smaller, simpler models, a user generally relies on powerful computational tools to directly arrive at solutions to complex problems. As computational resources grow, users continue trying to simulate new, more complex, or more detailed problems, resulting in continual stress on both the code and computational resources. When these resources are limited, the user will have to make concessions by simplifying the problem while trying to preserve important details. In the context of the Monte Carlo N-Particle radiation transport simulation tool, simplifications typically come as reductions in geometry, or by using variance reduction techniques. Both approaches can influence the physics of the problem, leading to potentially inaccurate or non-physical results. Errors can also be introduced as a result of faulty input into a computational tool: something as simple as transposing numbers in a tally input can result in incorrect answers. In this paradigm, reduced complexity computational and analytical models still have an important purpose. The explicit form of an analytic solution is arguably the best way to understand the qualitative properties of simple models. In contrast to "building up" a complex problem through understanding simpler problems, results from detailed computational scenarios can be better explained by "building down" the complex model through simple models rooted in the fundamental or essential phenomenology. Simplified analytic and computational models can be used to 1) increase a user's confidence in the computational solution of a complex model, 2) confirm there are no user input errors, and 3) ensure essential assumptions of the simulation tool are preserved. This process of using analytic models to develop a more valuable analysis of simulation results is named the results assessment methodology. The utility of the results assessment methodology and a complimentary sensitivity analysis is exemplified through the analysis of the neutron flux in a dry used fuel storage cask. This application was chosen due to current scientific interest in used nuclear fuel storage.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Analytic Modeling of a Deep Shielding Problem

Previous generations of scientists would make tremendous efforts to simplify non-tractable problems and generate simpler models that preserved the fundamental physics. This process involved applying assumptions and simplifications to reduce the complexity of the problem until it reached a solvable form. Each assumption and simplification was chosen and applied with the intent to preserve the essential physics of the problem, since, if the core physics of the problem were eliminated, the simplified model served no purpose. Moreover, if done correctly, solutions to the reduced model would serve as useful approximations to the original problem. In a sense, solving the simple models laid the ground-work for and provided insight into the more complex problem. Today, however, the affordability of high performance computing has essentially replaced the process for analyzing complex problems. Rather than "building up" a problem by understanding smaller, simpler models, a user generally relies on powerful computational tools to directly arrive at solutions to complex problems. As computational resources grow, users continue trying to simulate new, more complex, or more detailed problems, resulting in continual stress on both the code and computational resources. When these resources are limited, the user will have to make concessions by simplifying the problem while trying to preserve important details. In the context of the Monte Carlo N-Particle radiation transport simulation tool, simplifications typically come as reductions in geometry, or by using variance reduction techniques. Both approaches can influence the physics of the problem, leading to potentially inaccurate or non-physical results. Errors can also be introduced as a result of faulty input into a computational tool: something as simple as transposing numbers in a tally input can result in incorrect answers. In this paradigm, reduced complexity computational and analytical models still have an important purpose. The explicit form of an analytic solution is arguably the best way to understand the qualitative properties of simple models. In contrast to "building up" a complex problem through understanding simpler problems, results from detailed computational scenarios can be better explained by "building down" the complex model through simple models rooted in the fundamental or essential phenomenology. Simplified analytic and computational models can be used to 1) increase a user's confidence in the computational solution of a complex model, 2) con firm there are no user input errors, and 3) ensure essential assumptions of the simulation tool are preserved. This process of using analytic models to develop a more valuable analysis of simulation results is named the results assessment methodology. The utility of the results assessment methodology and a complimentary sensitivity analysis is exempli fied through the analysis of the neutron flux in a dry used fuel storage cask. This application was chosen due to current scientific interest in used nuclear fuel storage.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Shorter function summaries for finite state machine-based high consequence systems using logic synthesis and tautologies (Final Report LDRD 24-1302)

Computer programs are often viewed as collections of functions – each function has parameters (inputs) and computes a return value, and each has potential side effects that modify program state (outputs). In this research, a Sandia symbolic execution tool designed to support “human-in-the-loop” analysis was modified to automatically create “function summaries,” and a new tool, “diaboolical,” was created to support enhancing readability of the summary using a novel approach to bit-vector simplification that leverages logic synthesis and tautologies. For this effort, students at Auburn University created several finite state machines (FSMs) to serve as exemplars for high-consequence systems. Function summaries for each of the machines were obtained, and then portions of the summaries were simplified using both diaboolical and the simplification procedure of a popular SMT solver. A comparison of the results shows that diaboolical can often produce smaller function summaries, with expression length improvements over the unsimplified function summaries ranging from 0% to 90% for diaboolical and 0% to 65% for the SMT solver, though diaboolical had a significantly greater cost in time. Diaboolical was evaluated against a collection of “arbitrary” C-code as well as FSM exemplars, and for both datasets it achieved an approximately 10% improvement in expression length compared to simplifications that could be obtained using existing techniques. Function summaries can assist assurance efforts that evaluate existing systems and their executable code. A smaller function summary is likely easier for humans to understand and could thus increase the ability and efficacy of assurance practices centered around the analysis of executable artifacts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Holographic entropy relations repackaged

We explore the structure of holographic entropy relations (associated with ‘information quantities’ given by a linear combination of entanglement entropies of spatial sub-partitions of a CFT state with geometric bulk dual). Such entropy relations can be recast in multiple ways, some of which have significant advantages. Motivated by the already-noted simplification of entropy relations when recast in terms of multipartite information, we explore additional simplifications when recast in a new basis, which we dub the K-basis, constructed from perfect tensor structures. For the fundamental information quantities such a recasting is surprisingly compact, in part due to the interesting fact that entropy vectors associated to perfect tensors are in fact extreme rays in the holographic entropy cone (as well as the full quantum entropy cone). More importantly, we prove that all holographic entropy inequalities have positive coefficients when expressed in the K-basis, underlying the key advantage over the entropy basis or the multipartite information basis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Elements of complexity in subsurface modeling, exemplified with three case studies

There are complexity elements to consider when applying subsurface flow and transport models to support environmental analyses. Modelers balance the benefits and costs of modeling along the spectrum of complexity, taking into account the attributes of more simple models (e.g., lower cost, faster execution, easier to explain, less mechanistic) and the attributes of more complex models (higher cost, slower execution, harder to explain, more mechanistic and technically defensible). In this paper, modeling complexity is examined with respect to considering this balance. The discussion of modeling complexity is organized into three primary elements: 1) modeling approach, 2) description of process, and 3) description of heterogeneity. Three examples are used to examine these complexity elements. Two of the examples use simulations generated from a complex model to develop simpler models for efficient use in model applications. The first example is designed to support performance evaluation of soil vapor extraction remediation in terms of groundwater protection. The second example investigates the importance of simulating different categories of geochemical reactions for carbon sequestration and selecting appropriate simplifications for use in evaluating sequestration scenarios. In the third example, the modeling history for a uranium-contaminated site demonstrates that conservative parameter estimates were inadequate surrogates for complex, critical processes and there is discussion on the selection of more appropriate model complexity for this application. All three examples highlight how complexity considerations are essential to create scientifically defensible models that achieve a balance between model simplification and complexity.

conceptual models↗
DOE OSTI2023

Reproducible benchmark for the SNAP 8 experimental reactor at dry conditions

Here, this work provides fully reproducible benchmark models of the Systems for Nuclear Auxiliary Power (SNAP) 8 Experimental Reactor. Validation benchmarks of the criticality configuration experiments under dry conditions with no coolant are presented. In addition, relevant reactivity worth experiments, and measurement of power distributions are validated and presented here. Discrepancies between modeled and experimental results are at most 110 pcm for fuel and poison worths, and critical configurations that do not manipulate control elements are within 50 pcm. Larger discrepancies found in reflector element worth experiments are due to experimental methodology which was noted as being simplified due to limited calculational capabilities at the time, while discrepancy in the control element manipulated critical configuration is due the absence of structural components for modeling simplification. Power distributions closely follow what was observed in experiment with expected peaking in reflecting elements. All models are well documented with cited references describing and justifying assumptions, simplifications, and adjustments to reproduce the models with any nuclear safety codes; model inputs and outputs are stored in the snapReactors GitHub repository.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Hyperoxia-mediated transcriptional activation of cytochrome P4501A1 (CYP1A1) and decreased susceptibility to oxygen-mediated lung injury in newborn mice

Highlights: • Hyperoxia causes enhanced transcriptional activation of human CYP1A1-Luciferase expression in newborn mice in vivo. • Transgenic mice carrying the human CYP1A1-luc promoter are less susceptible to hyperoxic lung in injury and in vivo. • CYP1A1-Luc mice display increased levels of endogenous hepatic and pulmonary CYP1A as well as NADP(H) quinone oxidoreductase (NQO1) expression after hyperoxia exposure, compared to wild type mice. • The increased endogenous expression of CYP1A1 and NQO1 contributes to the beneficial effects seens in CYP1A1-Luc mice. Hyperoxia contributes to the development of bronchopulmonary dysplasia (BPD) in premature infants. In this study, we tested the hypothesis that newborn transgenic mice carrying the human CYP1A1-Luc promoter will display transcriptional activation of the human CYP1A1 promoter in vivo upon exposure to hyperoxia, and that these mice will be less susceptible to hyperoxic lung injury and alveolar simplification than similarly exposed wild type (WT) mice. Newborn WT (CD-1) or transgenic mice carrying a 13.2 kb human CYP1A1 promoter and the luciferase (Luc) reporter gene (CYP1A1-luc) were maintained in room air or exposed to hyperoxia (85% O{sub 2}) for 7–14 days. Hyperoxia exposure of CYP1A1-Luc mice for 7 and 14 days resulted in 4- and 30-fold increases, respectively, in hepatic Luc (CYP1A1) expression, compared to room air controls. In lung, hyperoxia caused a 2-fold induction of reporter Luc at 7 days, but the induction declined after 14 days. The newborn CYP1A1-Luc mice were less susceptible to lung injury and alveolar simplification than similarly exposed wild type (WT) CD-1 mice. Also, the CYP1A1-Luc mice showed increased levels of hepatic and pulmonary CYP1A1 expression and hepatic CYP1A2 activity after hyperoxia exposure. Hyperoxia also increased NADP(H) quinone reductase (NQO1) pulmonary gene expression in both CD-1 and CYP1A1-Luc mice at both time points, but this was more pronounced in the latter at 14 days. Our results support the hypothesis that hyperoxia activates the human CYP1A1 promoter in newborn mice, and that increased endogenous expression of CYP1A1 and NADP(H) quinone reductase (NQO1) contributes to the decreased susceptibilities to hyperoxic lung injury in the transgenic animals. This is the first report providing evidence of hyperoxia-mediated transcriptional activation of the human CYP1A1 promoter in newborn mice, and this in conjunction with decreased lung injury, suggests that these phenomena have important implications for BPD.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Directional finite difference method for directly solving 3D gyrokinetic field equations with enhanced accuracy

The gyrokinetic (GK) field equation is a three-dimensional (3D) elliptic equation, but it is often simplified to a set of two-dimensional (2D) equations by assuming that the field does not vary along a specific direction. However, this simplification can introduce inevitable 0th-order numerical errors, as nonlinear mode coupling in toroidal geometry can produce undesirable harmonic modes that violate the assumption. In this work, we propose a novel directional finite difference method (FDM) with a local coordinate transformation to better resolve the target field of interest. The directional FDM can accurately solve 3D GK field equations without simplifications, which can overcome the limitations of conventional methods. The accuracy and efficiency of different FDMs are analyzed in great detail for a variety of geometries, from simple 2D Cartesian coordinates to realistic 3D curvilinear coordinates. The 0th-order numerical errors of simplified 2D GK equations were found to be more problematic for low-harmonic modes and low aspect ratio geometries such as spherical tokamaks. On the other hand, the directional 3D FDM can accurately resolve a much wider range of harmonic modes aligned to the direction of interest, including the low-harmonic modes. In conclusion, we demonstrate that the directional 3D FDM is a highly effective algorithm for solving the 3D GK field equations, achieving accuracy improvements of 10 to 100 times or more, particularly for low-harmonic modes in spherical tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Influence of alloy solidification path on melt pool behavior in additive manufacturing

Numerical models used to study transport phenomena in laser-powder bed fusion processes often rely on assumptions and simplifications to reduce their computational expense. One common simplification is in the description of latent heat evolution during the solid-liquid phase change (i.e., the solidification pathway), justified by the fact that the mushy zone thickness is similar to the numerical grid spacing used for continuum transport models. The lack of resolution of transport phenomena in the mushy zone motivates the use of computationally convenient solidification paths such as linear or sigmoidal relationships over pathways derived from fundamental solidification theory such as equilibrium or Scheil models. In the present work, an uncertainty quantification (UQ) framework is used to analyze the influence of solidification pathway selection on the solidification dynamics and melt pool geometries in laser based additive manufacturing (AM) of IN625. Results show the solidification pathway has a quantifiable influence on the cooling rate at the liquidus isotherm, mushy zone thickness, and solidification time. Due to similarities in the latent heat evolution at the beginning of solidification, the equilibrium and Scheil models predict similar cooling rates near the liquidus isotherm, however the wider freezing range of Scheil leads to a wider mushy zone compared to equilibrium. The non-physical latent heat release profiles of sigmoidal and linear paths lead to significant overpredictions of cooling rates at the liquidus isotherm compared to equilibrium and Scheil. Finally, these results indicate that careful consideration should be given to the choice of solidification pathway to ensure reliable model predictions.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Higher-order time integration of Coulomb collisions in a plasma using Langevin equations

The extension of Langevin-equation Monte-Carlo algorithms for Coulomb collisions from the conventional Euler–Maruyama time integration to the next higher order of accuracy, the Milstein scheme, has been developed, implemented, and tested. This extension proceeds via a formulation of the angular scattering directly as stochastic differential equations in the fixed-frame spherical-coordinate velocity variables. Results from the numerical implementation show the expected improvement [O(Δt) vs. O(Δt{sup 1/2})] in the strong convergence rate both for the speed |v| and angular components of the scattering. An important result is that this improved convergence is achieved for the angular component of the scattering if and only if the “area-integral” terms in the Milstein scheme are included. The resulting Milstein scheme is of value as a step towards algorithms with both improved accuracy and efficiency. These include both algorithms with improved convergence in the averages (weak convergence) and multi-time-level schemes. The latter have been shown to give a greatly reduced cost for a given overall error level when compared with conventional Monte-Carlo schemes, and their performance is improved considerably when the Milstein algorithm is used for the underlying time advance versus the Euler–Maruyama algorithm. A new method for sampling the area integrals is given which is a simplification of an earlier direct method and which retains high accuracy. This method, while being useful in its own right because of its relative simplicity, is also expected to considerably reduce the computational requirements for the direct conditional sampling of the area integrals that is needed for adaptive strong integration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Interface- and discontinuity-aware numerical schemes for plasma 3-T radiation diffusion in two and three dimensions

A set of numerical schemes is developed for two- and three-dimensional time-dependent 3-T radiation diffusion equations in systems involving multi-materials. To resolve sub-cell structure, interface reconstruction is implemented within any cell that has more than one material. Therefore, the system of 3-T radiation diffusion equations is solved on two- and three-dimensional polyhedral meshes. The focus of the development is on the fully coupling between radiation and material, the treatment of nonlinearity in the equations, i.e., in the diffusion terms and source terms, treatment of the discontinuity across cell interfaces in material properties, the formulations for both transient and steady states, the property for large time steps, and second order accuracy in both space and time. The discontinuity of material properties between different materials is correctly treated based on the governing physics principle for general polyhedral meshes and full nonlinearity. The treatment is exact for arbitrarily strong discontinuity. The scheme is fully nonlinear for the full nonlinearity in the 3-T diffusion equations. Three temperatures are fully coupled and are updated simultaneously. The scheme is general in two and three dimensions on general polyhedral meshes. The features of the scheme are demonstrated through numerical examples for transient problems and steady states. The effects of some simplifications of numerical schemes are also shown through numerical examples, such as linearization, simple average of diffusion coefficient, and approximate treatment for the coupling between radiation and material.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Mass transfer effects in a gasification riser

In the development of multiphase reacting computational fluid dynamics (CFD) codes, a number of simplifications were incorporated into the codes and models. One of these simplifications was the use of a simplistic mass transfer correlation for the faster reactions and omission of mass transfer effects completely on the moderate speed and slow speed reactions such as those in a fluidized bed gasifier. Another problem that has propagated is that the mass transfer correlation used in the codes is not universal and is being used far from its developed bubbling fluidized bed regime when applied to circulating fluidized bed (CFB) riser reactors. These problems are true for the major CFD codes. To alleviate this problem, a mechanistic based mass transfer coefficient algorithm has been developed based upon an earlier work by Breault et al. This fundamental approach uses the local hydrodynamics to predict a local, time varying mass transfer coefficient. The predicted mass transfer coefficients and the corresponding Sherwood numbers agree well with literature data and are typically about an order of magnitude lower than the correlation noted above. The incorporation of the new mass transfer model gives the expected behavior for all the gasification reactions evaluated in the paper. At the expected and typical design values for the solid flow rate in a CFB riser gasifier an ANOVA analysis has shown the predictions from the new code to be significantly different from the original code predictions. The new algorithm should be used such that the conversions are not over predicted. Additionally, its behaviors with changes in solid flow rate are consistent with the changes in the hydrodynamics.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

A streamline coordinate analysis of a turbulent boundary layer subject to pressure gradients and curvature on the windward side of a bump

Direct numerical simulation (DNS) of a turbulent boundary layer over the Gaussian (Boeing) bump is performed. This boundary layer exhibits a series of adverse and favourable pressure gradients and convex and concave curvature effects before separating. These effects on turbulent boundary layers are characterised and compared with a lower-Reynolds-number flow over the same geometry. The momentum budgets are analysed in the streamline-aligned coordinate system upstream of the separation region. These momentum budgets allow the simplification of equations to facilitate an integral analysis. Integral-analysis-based approximations for Reynolds stresses in the inner and outer regions of the boundary layer are also formulated. The shear and wall-normal Reynolds stress profiles normalised by these approximations exhibit a better collapse compared with friction velocity and Zagarola–Smits normalisations in the strong favourable pressure gradient region and in the mild adverse pressure region that precedes it in this flow. Simplification of these Reynolds stress approximations along with results from the DNS are used to obtain semi-empirical approximations that are able to provide stress closure in terms of wall solution fields for the turbulent boundary layer under consideration.

42 ENGINEERING↗
DOE OSTI2014

Bayesian data fusion for spatial prediction of categorical variables in environmental sciences

First developed to predict continuous variables, Bayesian Maximum Entropy (BME) has become a complete framework in the context of space-time prediction since it has been extended to predict categorical variables and mixed random fields. This method proposes solutions to combine several sources of data whatever the nature of the information. However, the various attempts that were made for adapting the BME methodology to categorical variables and mixed random fields faced some limitations, as a high computational burden. The main objective of this paper is to overcome this limitation by generalizing the Bayesian Data Fusion (BDF) theoretical framework to categorical variables, which is somehow a simplification of the BME method through the convenient conditional independence hypothesis. The BDF methodology for categorical variables is first described and then applied to a practical case study: the estimation of soil drainage classes using a soil map and point observations in the sandy area of Flanders around the city of Mechelen (Belgium). The BDF approach is compared to BME along with more classical approaches, as Indicator CoKringing (ICK) and logistic regression. Estimators are compared using various indicators, namely the Percentage of Correctly Classified locations (PCC) and the Average Highest Probability (AHP). Although BDF methodology for categorical variables is somehow a simplification of BME approach, both methods lead to similar results and have strong advantages compared to ICK and logistic regression.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Computationally efficient dielectric calculations of molecular crystals

The microscopic dielectric response is a key quantity for electronic materials such as organic semiconductors. Calculations of this response for molecular crystals are currently either expensive or rely on extreme simplifications such as multipole expansions which lack microscopic detail. We present an alternate approach using a microscopic analogue of the Clausius-Mossotti equation, which constructs the dielectric response of a crystal from an eigenvalue decomposition of the dielectric response of individual molecules. This method can potentially be used to examine the effects of defects, disorder, and surfaces on the dielectric properties of molecular solids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Systematic problems with using dark matter simulations to model stellar halos

The limits of available computing power have forced models for the structure of stellar halos to adopt one or both of the following simplifying assumptions: (1) stellar mass can be 'painted' onto dark matter (DM) particles in progenitor satellites; (2) pure DM simulations that do not form a luminous galaxy can be used. We estimate the magnitude of the systematic errors introduced by these assumptions using a controlled set of stellar halo models where we independently vary whether we look at star particles or painted DM particles, and whether we use a simulation in which a baryonic disk galaxy forms or a matching pure DM simulation that does not form a baryonic disk. We find that the 'painting' simplification reduces the halo concentration and internal structure, predominantly because painted DM particles have different kinematics from star particles even when both are buried deep in the potential well of the satellite. The simplification of using pure DM simulations reduces the concentration further, but increases the internal structure, and results in a more prolate stellar halo. These differences can be a factor of 1.5-7 in concentration (as measured by the half-mass radius) and 2-7 in internal density structure. Given this level of systematic uncertainty, one should be wary of overinterpreting differences between observations and the current generation of stellar halo models based on DM-only simulations when such differences are less than an order of magnitude.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Latitudinal and energy dependence of energetic neutral atom spectral indices measured by the Interstellar Boundary Explorer

We investigate the latitudinal and energy dependence of the globally distributed 0.5–6 keV energetic neutral atom (ENA) spectra measured by the Interstellar Boundary Explorer (IBEX) during the first 3 yrs of the mission. Our results are: (1) the ENA spectral indices at the two lowest energies (0.89 and 1.47 keV) exhibit no clear trend with ecliptic latitude θ, while those at ∼2.29 and ∼3.41 keV exhibit a clear latitudinal pattern; flatter spectra occur above 60° latitude and steeper spectra occur ±30° of the equator. (2) The latitudinal dependence of the spectral indices at different energies can be represented by the cosine function γ=a{sub 0}+a{sub 1}cos(a{sub 2}θ) with unique offsets, amplitudes, and phase angles; the higher energy ENA indices transition to successively larger amplitudes within ±45° of the equator. Our results confirm the previously reported latitudinal organization of the ENA spectra and their remarkable similarity to that of the solar wind (SW) speed observed by Ulysses in the inner heliosphere. While earlier studies showed that the ∼0.5–6 keV globally distributed ENA spectral indices could be represented as single power laws over much of the sky, our new results indicate that this is an over-simplification because the spectral indices have an energy and latitude dependence. This dependence is an important factor that must be taken into consideration by models and simulations that seek to map the IBEX ENA observations back to the latitudinal profile of the SW speed structure observed in the inner heliosphere.

79 ASTRONOMY AND ASTROPHYSICS↗