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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Ground-state properties of light 4 n self-conjugate nuclei in ab initio no-core Monte Carlo shell model calculations with nonlocal N N interactions

We report J π = 0 + ground-state energies and point-proton radii of 4 He, 8 Be, 12 C, 16 O, and 20 Ne nuclei calculated by the ab initio no-core Monte Carlo shell model with the JISP16 and Daejeon16 nonlocal NN interactions. Ground-state energies are obtained in the basis spaces up to seven oscillator shells (N shell =7) with several oscillator energies (ℏω) around the optimal oscillator energy for the convergence of ground-state energies. These energy eigenvalues are extrapolated to obtain estimates of converged ground-state energies in each basis space using energy variances of computed energy eigenvalues. We further extrapolate these energy-variance-extrapolated energies obtained in the finite basis spaces to infinite basis-space results with an empirical exponential form. This form features a dependence on the basis-space size but is independent of the value of ℏω used for the harmonic-oscillator basis functions. Point-proton radii for these states of atomic nuclei are also calculated following techniques employed for the energies. From these results, it is found that the Daejeon16 NN interaction provides good agreement with experimental data up to approximately 16 O, while the JISP16 NN interaction provides good agreement with experimental data up to approximately 12 C. Beyond these nuclei, the interactions produce overbinding accompanied by radii that are too small. These findings suggest and encourage further revisions of nonlocal NN interactions towards the investigation of nuclear structure in heavier-mass regions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2000

SHDOM

SHDOM is a general purpose, publicly available, three-dimensional atmospheric radiative transfer model. SHDOM is an explicit method, which means it solves for the whole radiation field, as distinct from Monte Carlo methods which solve for particular radiative outputs. SHDOM is particularly well suited for remote sensing applications, where it can compute outgoing radiances at many angles from a cloud field at virtually no extra cost. SHDOM is not appropriate for calculating domain average quantities for which Monte Carlo methods excel. The I3RC intercomparison offers an opportunity to explore the pros and cons of SHDOM and Monte Carlo models on some real world inhomogeneous cloud fields. Specifically, we wish to determine the computer resources required to achieve a particular accuracy for a certain number of outputs using SHDOM and Monte Carlo models. This will help guide modelers on the appropriate choice of SHDOM or Monte Carlo for their applications. To emphasize the importance of this accuracy versus CPU time tradeoff, we are submitting two SHDOM entries (low and high resolution) in the I3RC.

Evans, K. Franklin↗
DOE OSTI2020

A Novel use of Direct Simulation Monte-Carlo to Model Dynamics of COVID-19 Pandemic Spread

In this report, we evaluate a novel method for modeling the spread of COVID-19 pandemic. In this new approach we leverage methods and algorithms developed for fully-kinetic plasma physics simulations using Particle-In-Cell (PIC) Direct Simulation Monte-Carlo (DSMC) models. This approach then leverages Sandia-unique simulation capabilities, and High-Performance Computer (HPC) resources and expertise in particle-particle interactions using stochastic processes. Our hypothesis is that this approach would provide a more efficient platform with assumptions based on physical data that would then enable the user to assess the impact of mitigation strategies and forecast different phases of infection. This work addresses key scientific questions related to the assumptions this new approach must make to model the interactions of people using algorithms typically used for modeling particle interactions in physics codes (kinetic plasma, gas dynamics). The model developed uses rational/physical inputs while also providing critical insight; the results could serve as inputs to, or alternatives for, existing models. The model work presented was developed over a four-week time frame, thus far showing promising results and many ways in which this model/approach could be improved. This work is aimed at providing a proof-of-concept for this new pandemic modeling approach, which could have an immediate impact on the COVID-19 pandemic modeling, while laying a basis to model future pandemic scenarios in a manner that is timely and efficient. Additionally, this new approach provides new visualization tools to help epidemiologists comprehend and articulate the spread of this and other pandemics as well as a more general tool to determine key parameters needed in order to better predict pandemic modeling in the future. In the report we describe our model for pandemic modeling, apply this model to COVID-19 data for New York City (NYC), assess model sensitivities to different inputs and parameters and , finally, propagate the model forward under different conditions to assess the effects of mitigation and associated timing. Finally, our approach will help understand the role of asymptomatic cases, and could be extended to elucidate the role of recovered individuals in the second round of the infection, which is currently being ignored.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1999

Monte Carlo mixture model of lifetime cancer incidence risk from radiation exposure on shuttle and international space station

Estimating uncertainty in lifetime cancer risk for human exposure to space radiation is a unique challenge. Conventional risk assessment with low-linear-energy-transfer (LET)-based risk from Japanese atomic bomb survivor studies may be inappropriate for relativistic protons and nuclei in space due to track structure effects. This paper develops a Monte Carlo mixture model (MCMM) for transferring additive, National Institutes of Health multiplicative, and multiplicative excess cancer incidence risks based on Japanese atomic bomb survivor data to determine excess incidence risk for various US astronaut exposure profiles. The MCMM serves as an anchor point for future risk projection methods involving biophysical models of DNA damage from space radiation. Lifetime incidence risks of radiation-induced cancer for the MCMM based on low-LET Japanese data for nonleukemia (all cancers except leukemia) were 2.77 (90% confidence limit, 0.75-11.34) for males exposed to 1 Sv at age 45 and 2.20 (90% confidence limit, 0.59-10.12) for males exposed at age 55. For females, mixture model risks for nonleukemia exposed separately to 1 Sv at ages of 45 and 55 were 2.98 (90% confidence limit, 0.90-11.70) and 2.44 (90% confidence limit, 0.70-10.30), respectively. Risks for high-LET 200 MeV protons (LET=0.45 keV/micrometer), 1 MeV alpha-particles (LET=100 keV/micrometer), and 600 MeV iron particles (LET=180 keV/micrometer) were scored on a per particle basis by determining the particle fluence required for an average of one particle per cell nucleus of area 100 micrometer(2). Lifetime risk per proton was 2.68x10(-2)% (90% confidence limit, 0.79x10(-3)%-0. 514x10(-2)%). For alpha-particles, lifetime risk was 14.2% (90% confidence limit, 2.5%-31.2%). Conversely, lifetime risk per iron particle was 23.7% (90% confidence limit, 4.5%-53.0%). Uncertainty in the DDREF for high-LET particles may be less than that for low-LET radiation because typically there is very little dose-rate dependence. Probability density functions for high-LET radiation quality and dose-rate may be preferable to conventional risk assessment approaches. Nuclear reactions and track structure effects in tissue may not be properly estimated by existing data using in vitro models for estimating RBEs. The method used here is being extended to estimate uncertainty in spacecraft shielding effectiveness in various space radiation environments.

NASA Center LaRC↗
NASA NTRS2003

Oversight and Development of a Community Monte Carlo Radiative Transfer Model

Under this grant we have developed a Monte Carlo radiative transfer code that will act as the nucleus for the 13RC Community Monte Carlo Model. All code is written in ANSI-compliant Fortran-95. Many modules define public type and procedures to manipulate them, but do not allow access to the type's internal components. This allows each module to do its own exhaustive error checking up-front, then proceed in a streamlined way. Many modules can read and write the state of their objects to persistent files. The code has been tested on a Macintosh running OS 10.2.4 and the Absoft Fortran compiler, and on Sun UltraSparcs running Solaris 5.8 and Forte V8 compilers. The code exposed bugs in the Intel Fortran Compiler (ifc) on the 13RC Linux host, and we are waiting for a resolution of these bugs before finished the port. the code base is under CVS versions control. The code base consists of the core code (nine modules providing the infrastructure), example integrators, and a suite of utilities and examples.

Source record↗
DOE OSTI2021

Particle-in-cell Monte Carlo-collision modeling of non-ideal effects in wave-heated dense microplasmas

A computational model for non-ideal plasma effects during the time evolution of a second-stage laser-heated discharge at high pressures is presented. The model extends a classical one-dimensional particle-in-cell Monte Carlo-collision (PIC-MCC) approach coupled with Maxwell's equations for the laser-heating process of a xenon plasma at 300 K temperature and 10–100 bar pressure. Plasma non-ideality resulting from Coulomb coupling at high plasma densities is manifested as a depression in the effective ionization potential of atoms and enhanced collision cross sections. These non-ideal effects are represented using the Ecker–Kröll model in the context of the PIC-MCC approach. We find that full ionization of the plasma is obtained on the picosecond timescale, starting from the skin layer and quickly expanding throughout the domain through an anomalous extension of the skin depth. More critically, we show that the inclusion of the non-ideal plasma effects results in more rapid ionization compared to an ideal plasma, especially at higher pressures. The ionization delay reduction is of the order of a fraction of a picosecond, corresponding to a 16% decrease at 100 bar. As the amplitude of the wave field is lowered, the ionization rate is lowered, making the plasma non-ideality effects more prominent.

Solmaz, Evrim (ORCID:0000000211830881)↗
DOE OSTI2020

Gamma Dose Measurements in ZPPR-15

Gamma doses were measured in the Zero Power Plutonium Reactor (ZPPR) to provide data for validation of calculations of gamma heating in important reactor components. Stainless steel-encapsulated LiF thermoluminescent dosimeters (TLDs) were irradiated in two configurations in ZPPR-15B and one configuration in ZPPR-15D to provide gamma heating data for the Integral Fast Reactor design in the mid-1980s. The ZPPR-15 experimental records were used to develop detailed as-built Monte Carlo models for the gamma dose measurements in ZPPR-15B and ZPPR-15D. These Monte Carlo models can be converted to deterministic models for calculations with deterministic codes. The reported uncertainty in the published gamma dose measurements is just the statistical uncertainty in the TLD readout. In addition to this statistical uncertainty in the TLD readout, several corrections and other factors contribute to the total uncertainty for the gamma dose measurements. The total uncertainty for the gamma dose measurements can be significantly larger than the published statistical uncertainty for the TLD readout. All known contributions to the total uncertainty were analyzed, and a total uncertainty was derived for the ZPPR-15 gamma dose measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantifying structural errors in cloud condensation nuclei activity from reduced representation of aerosol size distributions

Aerosol effects on clouds and radiation are the dominant contribution to uncertainty in radiative forcing relative to the pre-industrial atmosphere. While previous studies have assessed the impact of parametric uncertainty on modeled forcing, structural errors from the numerical representation of particle distributions have not been well quantified. Here we present a framework for quantifying error in aerosol size distributions and cloud condensation nuclei activity, which we apply to the widely used 4-mode version of the Modal Aerosol Module (MAM4). Box model predictions from the MAM4 are evaluated against the Particle Monte Carlo Model for Simulating Aerosol Interactions and Chemistry (PartMC-MOSAIC), a benchmark model that tracks the evolution of individual particles. We show that size distributions simulated by MAM4 diverge from those simulated by PartMC-MOSAIC after only a few hours of aging by condensation and coagulation in polluted conditions, which leads to large errors in modeled cloud condensation nuclei concentrations. We find that differences between MAM4 and PartMC-MOSAIC are largest under polluted conditions, where the size distribution evolves rapidly though aging by condensation of semi-volatile substances and coagulation among particles. These findings suggest that structural error in modeled aerosol properties contributes to the large inter-model variability in aerosol radiative forcing.

Fierce, Laura M.↗
DOE OSTI2026

Surrogate modeling of Monte Carlo radiation transport with convolutional neural networks for shielding optimization

Here, we present a machine learning (ML)-based surrogate model using convolutional neural networks (CNN) designed to emulate the attenuation of neutron fields as they pass through various shielding materials. This model can compute the outgoing neutron flux almost instantaneously and achieves reasonable accuracy compared to traditional Monte Carlo (MC)-based codes, which are computationally intensive. This emulator alleviates the complexity of neutron radiation transport through shielding materials by reducing the dimensionality and enables shielding optimization for a known radiation environment. This optimization process, which would have taken an unrealistic timeline due to several complex radiation transport simulations, can now be achieved in minutes, thus increasing computational capabilities in radiation shielding assessment. We demonstrate the applications of this emulator in computing effective dose rates and optimizing shielding solutions for a heavy-ion accelerator facility, such as the Facility for Rare Isotope Beams, where secondary neutrons produced via beam interactions dominate the radiation environment.

accelerator shielding↗
DOE OSTI2022

Methods for estimating X-ray machine output through measurement and simulation

We report ball grid arrays are increasingly being applied in the electronics industry and may require X-ray inspection to ensure the integrity and correct placement of solder pins. However, as the architecture of integrated circuits continues to narrow while simultaneously growing more complex, the risk of electronic failure due to radiation damage increases. While medical X-ray devices have been held to high standards and are repeatedly shown to be well characterized, devices used for electronic inspection are often lacking detailed characterization. This study presents unique methods to solve for important properties in X-ray inspection devices such as source to object distance and energy spectrum. This information can then be applied to Monte Carlo models to achieve better overall dose estimates to electronics, which will lead to superior manufactured products. Since X-ray devices can vary greatly in source characteristics, this work investigates spectral measurement and Monte Carlo representation of three X-ray devices. For a Philips SRO 33 100 medical diagnostic device, the spectral output followed expected trends given by the prediction software SpekCalc and Spektr. For the Dage XD7500NT, direct measurement showed a spectral artifact that through the use of Gafchromic films, was shown to be a contributing effect in the dose output. For the Rad Source RS1800, a high powered irradiation device, direct spectral measurement was not achieved. However, a Monte Carlo model using an assumed spectra was found to match ion chamber measurements to a high degree.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Selection of Sampling and Surrogate Modeling Methods for State-Point Evaluations of an AGN-201M Reactor

Nuclear reactor digital twins (DTs) have been proposed for use as a safeguards technology to efficiently monitor new and novel reactors as they come online. A safeguards DT needs to be capable of detecting misuse and diversion as they occur, requiring physics models to be accurate and efficient. Mathematical surrogate models are capable of achieving the necessary efficiency and can largely maintain the accuracy of higher-order models given a quality training sample. The Multiphysics Object-Oriented Simulation Environment (MOOSE) code framework is specifically equipped to generate training samples and create surrogate models using full-order reactor physics models. Utilizing an operational AGN-201M reactor’s specifications, two surrogate types were trained on samples of variable size, and using Cartesian products, Latin hypercube sampling, and quadrature sampling, each was compared and evaluated on accuracy when compared to a full-order Monte Carlo model. Both surrogate types were able to capture reactivity changes within 0.05 $ of the Monte Carlo model while reducing the computation costs by eight orders of magnitude.

MOOSE↗
DOE OSTI2025

Towards a new generation of solid total-energy detectors for neutron-capture time-of-flight experiments with intense neutron beams

Challenging neutron-capture cross-section measurements of small cross sections and samples with a very limited number of atoms require high-flux time-of-flight facilities. In turn, such facilities need innovative detection setups that are fast, have low sensitivity to neutrons, can quickly recover from the so-called γ-flash, and offer the highest possible detection sensitivity. In this paper, we present several steps towards such advanced systems. Specifically, we describe the performance of a high-sensitivity experimental setup at CERN n_TOF EAR2. It consists of nine sTED detector modules in a compact cylindrical configuration, two conventional used large-volume C 6 D 6 detectors, and one LaCl 3 (Ce) detector. The performance of these detection systems is compared using 93 Nb(n, γ) data. We also developed a detailed G EANT small4 Monte Carlo model of the experimental EAR2 setup, which allows for a better understanding of the detector features, including their efficiency determination. This Monte Carlo model has been used for further optimization, thus leading to a new conceptual design of a γ detector array, STAR, based on a deuterated-stilbene crystal array. Finally, the suitability of deuterated-stilbene crystals for the future STAR array is investigated experimentally utilizing a small stilbene-d12 prototype. The results suggest a similar or superior performance of STAR with respect to other setups based on liquid-scintillators, and allow for additional features such as neutron-gamma discrimination and a higher level of customization capability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2020

Algorithm Performance Dataset from NASA Open-Source Software

NASA Langley Research Center has recently developed and released the open-source software Multi Model Monte Carlo with Python (MXMCPy- LAR-19756-1) as a general capability for computing the statistics of outputs from an expensive, high-fidelity model by leveraging faster, low-fidelity models for speedup. Given a fixed computational budget and a collection of models with varying cost/accuracy, multi model Monte Carlo (MC) seeks a sample allocation strategy across the models that results in an estimator with optimal variance reduction. MXMCPy is a versatile tool that enables convenient access to many existing multi-model MC approaches (over a dozen algorithms available) within one modular and extensible package [1]. With MXMCPy, users can easily compare existing methods to determine the best choice for their particular problem,while developers have a basis for implementing and sharing new variance reduction approaches. However,there is currently very little understanding about which algorithm will perform best for a given problem (defined by the correlation between and relative cost of the available models) without a brute force search.

Geoffrey F Bomarito↗
NASA NTRS1990

The effect of catastrophic collisional fragmentation and diffuse medium accretion on a computational interstellar dust system

The effects of catastrophic collisional fragmentation and diffuse medium accretion on a the interstellar dust system are computed using a Monte Carlo computer model. The Monte Carlo code has as its basis an analytic solution of the bulk chemical evolution of a two-phase interstellar medium, described by Liffman and Clayton (1989). The model is subjected to numerous different interstellar processes as it transfers from one interstellar phase to another. Collisional fragmentation was found to be the dominant physical process that shapes the size spectrum of interstellar dust. It was found that, in the diffuse cloud phase, 90 percent of the refractory material is locked up in the dust grains, primarily due to accretion in the molecular medium. This result is consistent with the observed depletions of silicon. Depletions were found to be affected only slightly by diffuse cloud accretion.

Liffman, Kurt↗
NASA NTRS2022

Recommended Direct Simulation Monte Carlo Collision Model Parameters for Reacting Methane Flows

While hydrocarbon combustion and gas-surface interactions have been simulated for a variety of applications in continuum solvers, such processes have been rarely investigated in Direct Simulation Monte Carlo (DSMC). Thus Variable Hard/Soft Sphere (VHS/VSS)collision parameters are not available for most molecules of interest in the decomposition of methane, a significant pyrolysis gas product and potential atmospheric species for Titan re-entries. As these properties are essential for accurate modeling of gas transport and thermochemical effects, a method must be devised to compute them for use in DSMC. In this study, the methodology outlined in Stephani et al is utilized to compute the VHS/VSS parameters by fitting the Ω(1,1)and Ω(2,2) collision integrals [1]. These collision integrals are typically computed from intermolecular potentials and are used in CFD simulations to calculate transport properties such as viscosity, thermal conductivity, and diffusion. This approach ensures consistency between micro-scale collisions and macro-scale transport properties. To produce the necessary collision integrals needed for the fitting routine, we utilize the method described by Laricchiuta et al, where collision integrals are computed based on the constituent particles’ polarizability and effective electron number [2].Preliminary computations of pure-species Ω(1,1)and Ω(2,2)collision integrals produced from the coupled approach of Stephani et al and Laricchiuta et al for methane show good agreement with those computed via available ab-initio Potential Energy Surface Computations, as seen in Figure 1. Above 300K, no more than 12% deviation is observed between the two results over the temperature range of the fitted PES data [3].Current results of this study include full collision-specificVSS transport properties for a complex-species mixture involving major byproducts of pure methane decomposition. Targeted final results will include a comprehensive list of VSS parameters relevant toDSMC simulations of Titan atmospheric entry, based on the reduced kinetic model of Savajano et al [4].

M R Gosma↗
NASA NTRS1996

Early Energetic Particle Irradiation of the HED Parent Body Regolith

Previous studies have shown that many individual grains within the dark phase of the Kapoeta howardite were irradiated with energetic particles while residing on the surface of the early HED regolith. Particle tracks in these grains vary in density by more than an order of magnitude and undoubtedly were formed by energetic heavy (Fe) ions associated with early solar flares. Early Irradiation of HED Regolith: Concentrations of excess Ne alone are not sufficient to decide between competing galactic and solar irradiation models. However, from recent studies of depth samples of oriented lunar rocks, we have shown that the cosmogenic 21-Ne/22-Ne ratio produced in feldspar differs substantially between Galactic Cosmic Radiation (GCR) and solar protons, and that this difference is exactly that predicted from cross-section data. Using Ne literature data and new isotopic data we obtained on acid-etched, separated feldspar from both the light and dark phases of Kapoeta, we derive 21-Ne/22-Ne = 0.80 for the recent GCR irradiation and 21-Ne/22-Ne = 0.68 for the early regolith irradiation. This derived ratio indicates that the early Ne production in the regolith occurred by both galactic and solar protons. If we adopt a likely one-component regolith model in which all grains were exposed to galactic protons but individual grains had variable exposure to solar protons, we estimate that this early GCR irradiation lasted for about 3-6 m.y. More complex two-component regolith models involving separate solar and galactic irradiation would permit this GCR age to be longer. Higher-energy solar protons would permit the GCR to be longer. Higher-energy solar protons would permit the GCR age to be shorter. Further, cosmogenic 126(Xe) in Kapoeta dark is no more than a factor of about 2 higher than that observed in Kapoeta light. Because 126(Xe) can only be formed by galactic protons and not solar protons, these data support a short GCR irradiation for the HED regolith. This would also be the maximum time peRiod for the solar irradiation. Various asteroidal regolith models, based on Monte Carlo modeling of impact rates as a function of size and on irradiation features of meteorites, predict surface exposure times of about 0.1 to 10 m.y., and depend on such factors as gravity, rock mechanical properties, and micrometeoroid flux. Because the depth at which solar Fe tracks are produced (is much less than 1 micrometer) is much less than the depth at which Solar Cosmic Rays (SCR) Ne is produced (about 1 cm), for a reasonably well-stirred HED regolith the "surface exposure time" for SCR 21-Ne production should be significantly longer than that for solar tracks and some other surface irradiation features. Enhanced Solar Proton Irradiation: For bulk samples of Kapoeta dark feldspar and a one-component regolith model, the derived ratio of 21-Ne/22-Ne = 0.68 implies that the early production ratio of SCR 21-Ne to GCR 21-Ne was about 0.5-1.5. This ratio is independent of any assumptions about the fraction of dark grains that are irradiated or of the variability in the degree of solar irradiation among grains. The 21-Ne SCR/GCR ratio indirectly derived from bulk Kapoeta pyroxene is somewhat larger, as is the ratio derived for simple two-component regolith models. Individual feldspar grains that were extensively solar irradiated would require even larger 21-Ne SCR/GCR production ratios. In contrast, the theoretical SCR/GCR production ratio for lunar feldspar with 0 g/CM2 shield ing is is less than or equal to 2, and the lowest ratio observed in near-surface samples of lunar anorthosites is less than or equal to 1. Considering the greater solar distance of Vesta (compared to the Moon), the likelihood that SCR 21-Ne was acquired under some shielding where production rates are lower, and the likelihood that the exposure time to galactic protons exceeded the exposure time to solar protons because of their very different penetration depths, the 21-Ne SCR/GCR production ratio on the HED parent body was probably < 0.1. The relatively large difference between the derived 21-Ne SCR/GCR ratio in Kapoeta dark feldspar and the estimated production ratio strongly indicates that the early solar irradiation involved a flux -20-50x the recent solar flux. This enhanced proton flux was probably associated with an overall greater solar activity in the first approximately 10(exp 7) to 10(exp 8) years of solar history.

Bogard, D. D.↗
DOE OSTI2023

Evaluation of light collection from highly scattering media using wavelength-shifting fibers

Opaque scintillators are designed to have a short scattering length such that scintillation photons are probabilistically confined to a small region of space about their origin. The benefit of this feature is that information on the interaction event topology can be recorded with greater fidelity than in traditional highly transparent media with sensors at large distances from the light production region. Opaque scintillator detectors rely on wavelength-shifting fibers to extract the scintillation light; however, the efficiency of light collection has not yet been directly measured in experiment. We measured the efficiency of light collection as a function of the optical parameters of an opaque liquid and the distance from the origin of the light to the fiber. We use the experimental data to validate a Monte Carlo model of light transport and collection and discuss a simple diffusion model that reproduces the results of Monte Carlo simulation with high fidelity. Furthermore, this combination of validated models has the potential for use in predictions of performance in various designs of future opaque scintillator detectors such as LiquidO.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Diagnosing hot-spot symmetry in surrogate ignition experiments via secondary DT-neutron spectroscopy at the NIF

The directional energy spectrum of neutrons generated from the in-flight fusion reaction of 1-MeV tritons contains information about the hot-spot symmetry. The National Ignition Facility (NIF) fields Symmetry Capsule (Symcap) implosions, which have historically measured the symmetry of the radiation, drive by measuring the hot-spot shape via x-ray self-emission. Symcaps are used to tune the hot-spot symmetry for ignition experiments at the NIF. This work shows the relationship between directional secondary DT-n spectra and x-ray imaging data for a large database of Symcap implosions. A correlation is observed between the relative widths of the DT-n spectra measured with nTOFs and the shape measured with x-ray imaging. A Monte Carlo model, which computes the directional secondary DT-n spectrum, is used to interpret the results. A comparison of the x-ray and secondary DT-n data with the Monte Carlo model indicates that 56% of the variance between the two datasets is explained by a P2 asymmetry. More advanced simulations using HYDRA suggest that the unaccounted variance is due to P1 and P4 asymmetries present in the hot spot. The comparison of secondary DT-n data and x-ray imaging data to the modeling shows the DT-n data contain important information that supplements current P2 measurements and contain new information about the P1 asymmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗