Search NASA⌕ Search

SEARCH · Search NASA

Results for “Scattering problem”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Neutrino-Nucleus Scattering Cross Sections at Medium Energies

The weak interactions of neutrinos with other Standard Model particles are well described within the Standard Model of particle physics. However, modern accelerator-based neutrino experiments employ nuclei as targets, where neutrinos interact with bound nucleons, turning a seemingly simple electroweak process into a complex many-body problem in nuclear physics. At the time of writing this Encyclopedia of Particle Physics chapter, neutrino-nucleus interactions remain one of the leading sources of systematic uncertainty in accelerator-based neutrino oscillation measurements. This chapter provides a pedagogical overview of neutrino interactions with nuclei in the medium-energy regime, spanning a few hundred MeV to several GeV. It introduces the fundamental electroweak formalism, outlines the dominant interaction mechanisms - including quasielastic scattering, resonance production, and deep inelastic scattering - and discusses how nuclear effects such as Fermi motion, nucleon-nucleon correlations, meson-exchange currents, and final-state interactions modify observable cross sections. The chapter also presents a brief survey of the foundational and most widely used theoretical models for neutrino-nucleus cross sections, together with an overview of current and upcoming accelerator-based neutrino oscillation experiments that are shaping the field. Rather than targeting experts, this chapter serves as a primer for advanced undergraduates, graduate students, and early-career researchers entering the field. It provides a concise foundation for understanding neutrino-nucleus scattering, its relevance to oscillation experiments, and its broader connections to both particle and nuclear physics.

Pandey, Vishvas [Fermilab] (ORCID:0000000230827987↗
DOE OSTI2023

Resolution of a Few Problems in the Application of Quasilinear Theory to Calculating Diffusion Coefficients in Heliophysics

A theory of quasilinear diffusion for obliquely propagating electromagnetic waves was developed in the 1960's and applied in the 1970's to model scattering of relativistic electrons by a prescribed distribution of waves. In the latter work, a transformation of variables, from wavevector space to the temporal frequency and tangent of the wave normal angle, was used so that simple Gaussian functions of frequency and tangent of the wave normal angle could be multiplied together to define the distribution of wave power, although arbitrary distributions of power in these two variables is also permitted. Finally, in 2005, previous work was consolidated and has been widely used in heliophysics studies that require computation of quasilinear diffusion coefficients. Here it is shown that this transformation is inppropriate when the precise wave vector distribution is known. The correct transformation is derived and used to produce diffusion coefficients that can differ by orders of magnitude from those computed using the inappropriate transformation. The differences are largest when the distribution of wave power extends to wave normal angles near the resonance cone. When the ratio of the plasma frequency to the gyrofrequency is large, only low energies (keV) are affected, but as the ratio decreases higher energies (MeV) also show differences. It is also shown that the derivation from the 1960's uses a notation that results in the diffusion coefficients depending on the distribution of wave power with respect to the wave azimuthal angle whereas there should be no such dependence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Precision test of statistical dynamics with state-to-state ultracold chemistry

Chemical reactions represent a class of quantum problems that challenge both the current theoretical understanding and computational capabilities1. Reactions that occur at ultralow temperatures provide an ideal testing ground for quantum chemistry and scattering theories, because they can be experimentally studied with unprecedented control, yet display dynamics that are highly complex. Here we report the full product state distribution for the reaction 2KRb → K 2 + Rb 2 . Ultracold preparation of the reactants allows us complete control over their initial quantum degrees of freedom, whereas state-resolved, coincident detection of both products enables the probability of scattering into each of the 57 allowed rotational state-pairs to be measured. Our results show an overall agreement with a state-counting model based on statistical theory, but also reveal several deviating state-pairs. In particular, we observe a strong suppression of population in the state-pair closest to the exoergicity limit as a result of the long-range potential inhibiting the escape of products. Finally, the completeness of our measurements provides a benchmark for quantum dynamics calculations beyond the current state of the art.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Gaming the beamlines—employing reinforcement learning to maximize scientific outcomes at large-scale user facilities

Abstract Beamline experiments at central facilities are increasingly demanding of remote, high-throughput, and adaptive operation conditions. To accommodate such needs, new approaches must be developed that enable on-the-fly decision making for data intensive challenges. Reinforcement learning (RL) is a domain of AI that holds the potential to enable autonomous operations in a feedback loop between beamline experiments and trained agents. Here, we outline the advanced data acquisition and control software of the Bluesky suite, and demonstrate its functionality with a canonical RL problem: cartpole. We then extend these methods to efficient use of beamline resources by using RL to develop an optimal measurement strategy for samples with different scattering characteristics. The RL agents converge on the empirically optimal policy when under-constrained with time. When resource limited, the agents outperform a naive or sequential measurement strategy, often by a factor of 100%. We interface these methods directly with the data storage and provenance technologies at the National Synchrotron Light Source II, thus demonstrating the potential for RL to increase the scientific output of beamlines, and layout the framework for how to achieve this impact.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks

Physics-informed neural networks (PINNs) have shown to be effective tools for solving both forward and inverse problems of partial differential equations (PDEs). PINNs embed the PDEs into the loss of the neural network using automatic differentiation, and this PDE loss is evaluated at a set of scattered spatio-temporal points (called residual points). The location and distribution of these residual points are highly important to the performance of PINNs. However, in the existing studies on PINNs, only a few simple residual point sampling methods have mainly been used. Here, we present a comprehensive study of two categories of sampling for PINNs: non-adaptive uniform sampling and adaptive nonuniform sampling. We consider six uniform sampling methods, including (1) equispaced uniform grid, (2) uniformly random sampling, (3) Latin hypercube sampling, (4) Halton sequence, (5) Hammersley sequence, and (6) Sobol sequence. We also consider a resampling strategy for uniform sampling. To improve the sampling efficiency and the accuracy of PINNs, we propose two new residual-based adaptive sampling methods: residual-based adaptive distribution (RAD) and residual-based adaptive refinement with distribution (RAR-D), which dynamically improve the distribution of residual points based on the PDE residuals during training. Hence, we have considered a total of 10 different sampling methods, including six non-adaptive uniform sampling, uniform sampling with resampling, two proposed adaptive sampling, and an existing adaptive sampling. We extensively tested the performance of these sampling methods for four forward problems and two inverse problems in many setups. Our numerical results presented in this study are summarized from more than 6000 simulations of PINNs. Here, we show that the proposed adaptive sampling methods of RAD and RAR-D significantly improve the accuracy of PINNs with fewer residual points for both forward and inverse problems. Furthermore, the results obtained in this study can also be used as a practical guideline in choosing sampling methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Physics-informed neural networks for solving forward and inverse flow problems via the Boltzmann-BGK formulation

We report the Boltzmann equation with the Bhatnagar-Gross-Krook collision model (Boltzmann-BGK equation) has been employed to describe multiscale flows, i.e., from the hydrodynamic limit to free molecular flow. In this study we employ physics-informed neural networks (PINNs) to solve forward and inverse problems via the Boltzmann-BGK formulation (PINN-BGK), enabling PINNs to model flows in both the continuum and rarefied regimes. In particular, the PINN-BGK is composed of three sub-networks, i.e., the first for approximating the equilibrium distribution function, the second for approximating the non-equilibrium distribution function, and the third one for encoding the Boltzmann-BGK equation as well as the corresponding boundary/initial conditions. By minimizing the residuals of the governing equations and the mismatch between the predicted and provided boundary/initial conditions, we can approximate the Boltzmann-BGK equation for both continuous and rarefied flows. For forward problems, the PINN-BGK is utilized to solve various benchmark flows given boundary/initial conditions, e.g. Kovasznay flow, Taylor-Green flow, cavity flow, and micro Couette flow for Knudsen number up to 5. For inverse problems, we focus on rarefied flows in which accurate boundary conditions are difficult to obtain. We employ the PINN-BGK to infer the flow field in the entire computational domain given a limited number of interior scattered measurements on the velocity without using the (unknown) boundary conditions. Results for the two-dimensional micro Couette and micro cavity flows with Knudsen numbers ranging from 0.1 to 10 indicate that the PINN-BGK can infer the velocity field in the entire domain with good accuracy. Finally, we also present some results on using transfer learning to accelerate the training process. Specifically, we can obtain a three-fold speedup comparted to the standard training process (e.g., Adam plus L-BFG-B) for the two-dimensional flow problems considered in our work.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

In Situ Neutron Scattering Study of the Structure Dynamics of the Ru/Ca 2 N:e – Catalyst in Ammonia Synthesis

NH 3 synthesis is one of the most critical industrial processes. Compared to commercial iron catalysts, Ru catalysts show high intrinsic activity in this reaction but suffer from hydrogen poisoning. By loading Ru onto supports such as electrides and hydrides, the hydrogen poisoning problem can be significantly alleviated. However, relevant studies on the structural dynamics of the Ru/electride catalysts under reaction conditions are very scarce. Taking advantage of the high sensitivity to hydrogen species, it is possible to obtain insights into the structural changes during the reaction using in situ neutron techniques. In this study, we have investigated the structural evolution of the Ru/Ca 2 N:e – catalyst during the ammonia synthesis reaction by in situ neutron scattering (inelastic neutron scattering, INS) technique. In situ INS experiments suggest that Ca 2 N:e – is likely converted to the Ca 2 NH phase during the reaction. Unlike the previously known structure where H and N atoms are intermixed, the formed Ca 2 NH exhibits a segregated structure where the H and N atoms are located in different layers separated by the Ca layer. In conclusion, density functional theory calculations of the reaction energetics reveal that there are minor changes in the barriers and thermodynamics of the first N hydrogenation step between the two phases (Ca 2 NH phase with segregated H/N layers and intermixed Ca 2 NH phase), suggesting the impact of the phases on the reaction kinetics to be relatively minimal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Next-to-$\mathrm{MHV}$ Yang-Mills kinematic algebra

Kinematic numerators of Yang-Mills scattering amplitudes possess a rich Lie algebraic structure that suggest the existence of a hidden infinite-dimensional kinematic algebra. Explicitly realizing such a kinematic algebra is a longstanding open problem that only has had partial success for simple helicity sectors. In past work, we introduced a framework using tensor currents and fusion rules to generate BCJ numerators of a special subsector of NMHV amplitudes in Yang-Mills theory. Here we enlarge the scope and explicitly realize a kinematic algebra for all NMHV amplitudes. Master numerators are obtained directly from the algebraic rules and through commutators and kinematic Jacobi identities other numerators can be generated. Inspecting the output of the algebra, we conjecture a closed-form expression for the master BCJ numerator up to any multiplicity. We also introduce a new method, based on group algebra of the permutation group, to solve for the generalized gauge freedom of BCJ numerators. It uses the recently introduced binary BCJ relations to provide a complete set of NMHV kinematic numerators that consist of pure gauge.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

KAZR Hydrometeor and Insect Masks

The Ka-band ARM zenith pointing radar (aka, KAZR) is so sensitive that it detects cloud particles and individual insects. While detecting insects with Ka-band radar is beneficial and desirable to advance radar entomology, this sensitivity can be detrimental to radar meteorology because insects could be interpreted as clouds or precipitation. For example, misclassifying insects as clouds has been a problem for the ARM Active Remote Sensing of Clouds (ARSCL) Value Added Product since its inception (Clothiaux et al. 2000). Based on cloud particle and insect radar scattering properties, an algorithm was developed that identifies clouds, raindrops, ice particles, and insects in KAZR co- and cross-polarimeteric Doppler velocity spectra. The algorithm produces affirmative masks in the KAZR native time and height resolution indicating time-height locations of hydrometeors and insects. The hydrometeor mask contains binary information (e.g., yes/no hydrometeor presence), and the insect mask includes a proxy for insect activity that increases when more insects are detected in the Doppler velocity spectra. The algorithm was developed using KAZR medium sensitivity mode (MD) observations and was applied to two summer seasons of KAZR observations at the Southern Great Plains (SGP) Central Facility: May-October 2018 and 2019. In the future, this data set will be expanded to include other KAZR operating modes and observations from other ARM field sites. Details of the algorithm and data set can be found in: Williams, C.R., K.L. Johnson, S.E. Giangrande, J. C. Hardin, R. Oktem, and D. M. Romps, 2021: Identifying Insects, Clouds, and Precipitation using Vertically Pointing Polarimetric Radar Doppler Velocity Spectra. Atmospheric Measurement Techniques, submitted 6-Feb-2021. https://amt.copernicus.org/preprints/amt-2021-27/#discussion.For more information on the ARSCL VAP, see Clothiaux, E. E., T. P. Ackerman, G. G. Mace, K. P. Moran, R. T. Marchand, M. A. Miller, and B. E. Martner, 2000; J. Appl. Meteor., 39, 645-665.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Neutrino-Argon Cross Sections in MicroBooNE: Measurements Spanning Multiple Interaction Channels, Final States, and Neutrino Fluxes

Neutrinos are one of the most elusive particles in the Standard Model of particle physics due to their tiny interaction cross section, which makes them challenging to detect and study. There are three known flavors of neutrinos, and any given neutrino probabilistically oscillates between them as a function of the particle's energy and propagation distance. Experimental characterization of these oscillations elucidates fundamental properties of the neutrino and the Standard Model. Meeting the precision goals of ongoing and future oscillation measurements requires detailed modeling of the way neutrinos interact with nuclear matter. Precision modeling of these interactions is a challenging theoretical problem, rich with intricate physics effects to explore, and requires input from equally precise measurements of neutrino-nucleus interaction cross sections spanning a broad range of scattering channels. To fill this need, there is an ongoing multi-experiment effort to measure these cross sections across energies, interaction channels, and nuclear targets. This thesis describes three analyses reporting neutrino-argon cross section measurements with data from the MicroBooNE liquid argon time projection chamber detector. These span multiple interaction channels, final state topologies, and neutrino fluxes. The first analysis is a set of inclusive charged current muon neutrino cross section measurements for final states with and without protons, which provides a unique view of the hadronic final state produced in these interactions. Second is a set of cross section measurements for neutral current neutral pion production, which provides a vital dataset on this under-characterized channel. Third is significant progress on measuring neutrinos produced by kaons decaying at rest, which represents a unique opportunity to measure cross sections with a mono-energetic flux of neutrinos. These measurements are accompanied by a modeling study in the GiBUU theory framework, which probes the sensitivity of the muon neutrino and pion production measurements to the modeling of nucleon-nucleon final state interactions in neutrino-nucleus scattering.

Bogart, Benjamin [Michigan U.]↗
DOE OSTI2021

Neural-adjoint method for the inverse design of all-dielectric metasurfaces

All-dielectric metasurfaces exhibit exotic electromagnetic responses, similar to those obtained with metal-based metamaterials. Research in all-dielectric metasurfaces currently uses relatively simple unit-cell designs, but increased geometrical complexity may yield even greater scattering states. Although machine learning has recently been applied to the design of metasurfaces with impressive results, the much more challenging task of finding a geometry that yields a desired spectra remains largely unsolved. We propose and demonstrate a method capable of finding accurate solutions to ill-posed inverse problems, where the conditions of existence and uniqueness are violated. A specific example of finding the metasurface geometry which yields a radiant exitance matching the external quantum efficiency of gallium antimonide is demonstrated. We also show how the neural-adjoint method can intelligently grow the design search space to include designs that increasingly and accurately approximate the desired scattering response. The neural-adjoint method is not restricted to the case demonstrated and may be applied to plasmonics, photonic crystal, and other artificial electromagnetic materials.

42 ENGINEERING↗
DOE OSTI2026

Constrained variational optimization of counting-time allocation in sequential scattering measurements: Application to Bonse–Hart USANS

Sequential scattering measurements are often performed under a fixed experimental-time budget, even though the expected count rate varies strongly across the measured coordinate. When the dwell time at each measurement position can be controlled independently, this variation creates a general resource-allocation problem: how should the available time be distributed to minimize the uncertainty of the reconstructed profile? We formulate this problem as a constrained variational optimization for measurements governed by Poisson counting statistics. When each measurement is treated independently, minimizing the averaged squared relative uncertainty yields an inverse-square-root intensity allocation. The formulation is then generalized to include correlations between neighboring measurements and an instrumental resolution operator, leading to an allocation criterion that equalizes the marginal reduction in posterior uncertainty per unit measurement time. Bonse–Hart ultra-small-angle neutron scattering (USANS), in which reciprocal space is sampled sequentially through analyzer-angle stepping, provides an experimentally grounded application. Computational benchmarking shows that the optimized allocation outperforms uniform-time and constant-relative-error strategies, while application to an experimentally measured graphite USANS profile from the Spallation Neutron Source, using Poisson resampling under alternative schedules, demonstrates how counting time should be redistributed toward weak-intensity regions under an identical total duration. The resulting framework applies to sequential scattering and related scanning measurements whenever local dwell times are adjustable and directly determine the measurement uncertainties, and when the relevant correlation and instrumental-response models are available.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗
DOE OSTI2021

Late-time dark matter oscillations and the core-cusp problem

The core-cusp problem persists as an unresolved tension between the pre- dictions of ΛCDM cosmology and observations of dark matter (DM) profiles in dwarf spheroidal and other galaxies. We present a novel scenario for converting cusps into cores through reactivation of DM annihilation in galaxies at late times. This can happen in asymmetric DM models when there is a very small DM-number violating mass term that causes oscillations between DM and its antiparticle. Using analytic methods as well as gravitational N-body simulations, we show that this mechanism can robustly eliminate cusps from galactic DM profiles for light fermionic DM of mass $m_χ$ ~ (0.1 – 1) GeV and a lighter mediator into which the DM can annihilate. We identify regions of parameter space where annihilation of DM particles is more efficient than elastic scattering at reducing the inner density of the DM profile. Dark matter annihilation is therefore a qualitatively distinct alternative to the mechanism of elastic self-interacting dark matter for addressing the cusp-core problem.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Statistical modelling and Bayesian inversion for a Compton imaging system: application to radioactive source localization

Abstract This paper presents a statistical forward model for a Compton imaging system, called Compton imager. This system, under development at the University of Illinois Urbana Champaign, is a variant of Compton cameras with a single type of sensors which can simultaneously act as scatterers and absorbers. This imager is convenient for imaging situations requiring a wide field of view. The proposed statistical forward model is then used to solve the inverse problem of estimating the location and energy of point-like sources from observed data. This inverse problem is formulated and solved in a Bayesian framework by using a Metropolis within Gibbs algorithm for the estimation of the location, and an expectation-maximization algorithm for the estimation of the energy. This approach leads to more accurate estimation when compared with the deterministic standard back-projection approach, with the additional benefit of uncertainty quantification in the low photon imaging setting.

Tarpau, Cécilia (ORCID:0000000286539490)↗
DOE OSTI2026

A Brief Survey of Data Streaming Technologies

Streaming data is data that is emitted at variable volumes in a continuous, incremental manner with the goal of low-latency processing often at a different physical location. Network infrastructure is used to facilitate the connection between data sources and sinks, and must be robust to handle the requirements of the workflow. The U.S. Department of Energy Office of Science (DOE SC) a federal agency supporting fundamental scientific research for energy and the Nation’s largest supporter of basic research in the physical sciences. DOE SC has the responsibility for operating $\mathbf{1 0}$ National Laboratories, and 28 scientific user facilities supporting advanced supercomputers, particle accelerators, large x-ray light sources, neutron scattering sources, and other specialized facilities for nanoscience and genomics. This paper investigates the state of streaming data workfows, and details some of the approaches to this challenging problem.

Kissel, Ezra↗
DOE OSTI2022

Comparing machine learning and interpolation methods for loop-level calculations

The need to approximate functions is ubiquitous in science, either due to empirical constraints or high computational cost of accessing the function. In high-energy physics, the precise computation of the scattering cross-section of a process requires the evaluation of computationally intensive integrals. A wide variety of methods in machine learning have been used to tackle this problem, but often the motivation of using one method over another is lacking. Comparing these methods is typically highly dependent on the problem at hand, so we specify to the case where we can evaluate the function a large number of times, after which quick and accurate evaluation can take place. We consider four interpolation and three machine learning techniques and compare their performance on three toy functions, the four-point scalar Passarino-Veltman D_0 D 0 function, and the two-loop self-energy master integral M. We find that in low dimensions (d = 3), traditional interpolation techniques like the Radial Basis Function perform very well, but in higher dimensions (d=5, 6, 9) we find that multi-layer perceptrons (a.k.a neural networks) do not suffer as much from the curse of dimensionality and provide the fastest and most accurate predictions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Thermocouple Testing in Support of the AGR-5/6/7 Experiment

This report documents thermocouple testing performed in IRC Lab C-15 over a period of seven years. This testing supported selection and characterization of the thermocouple set used in the AGR-5/6/7 experiment. The following summary was taken directly from the report. Temperature measurement is a challenging aspect of very high temperature irradiation experiments because commonly used high-temperature commercial thermocouples such as platinum-rhodium (Types S, R, and B) and tungsten-rhenium (Type C), suffer dramatic drift because of neutron-induced transmutation. As a result, these types of thermocouples, which are used routinely for industrial temperature measurements outside of reactors, are used only in very special circumstances for reactor experiments. Conversely, because of their low neutron cross-sections, Type N thermocouples are affected to only a limited extent by neutron irradiation. However, the use of these nickel-based thermocouples is limited when the temperature exceeds 1050°C due to drift arising from minor alloying elements migrating from the thermocouple's metal sheath to the thermoelements. This change in the composition of the thermo-elements results in significant decalibration of the signal. The issues described above were recognized during the early planning stages of the final AGR experiment (designated AGR-5/6/7), and a thermocouple furnace testing program was performed over a seven-year period (2014-2019, 2021) to first select and then characterize the best thermocouple set for the high temperature regions of the AGR-5/6/7 irradiation experiment. The calculated temperature range of the AGR-5/6/7 experiment was 600–1500°C. For temperatures below 1000°C standard Type N thermocouples were deemed adequate. The furnace testing campaign identified two thermocouple types suitable for measuring temperatures above 1000°C, a Mo/Nb thermocouple developed at INL called HTIR-TC, and a Type N thermocouple developed by Cambridge University (called herein Cambridge Type N), which featured a custom high nickel alloy sheath. One of the original goals of the furnace testing program was to identify a thermocouple capable of low drift operation near the peak temperature expected in AGR-5/6/7, i.e., about 1400°C. The HTIR-TC design appeared promising in this regard, however a manufacturing difficulty proved to be a barrier and instead the furnace testing focused on drift performance at 1250°C. The manufacturing difficulty was that the Nb sheaths of the HTIR-TCs experienced extreme embrittlement when heat treated at 1600°C or greater. Heat treatment is needed to stabilize the emf output of this TC type, and the higher the heat treatment temperature the higher the peak temperature of stable operation. Because of the sheath embrittlement the heat treatment temperature had to be lowered to 1450°C resulting in a stable operating temperature of about 1250°C. One of the successes of the furnace testing program was identification of a shortcoming in the heat treatment procedure that had been traditionally used in the production of HTIR-TCs. The shortcoming was that the entire heated length of the HTIR-TC sensor was not being heat treated, but rather only the part of the sensor expected to experience temperatures above 1000°C. The problem manifested itself when the thermocouples were removed from the heat treat furnace and placed in another furnace with a different geometry, their indicated temperatures would be widely scattered, but mostly in the negative direction. The solution was to heat treat the entire heated length of the sensor. Since the deepest immersion depth in the AGR-5/6/7 experiment was about 40 inches, a heat treatment length of 48 inches was used. After this change was implemented, thermocouples which were moved into a new environment with a different temperature profile (i.e., a different furnace), produced accurate temperature measurements. Although assembly of the AGR-5/6/7 experiment was completed in September of 2017 (and irradiation begun in 2018), furnace testing of thermocouples continued in 2018 and 2019. The main purpose of this testing was to establish very long-term drift characteristics of the HTIR and Cambridge Type N thermocouples installed in the experiment. Representative thermocouples from the same lots as those installed in the AGR-5/6/7 experiment were used. Additionally, thermocouples of different designs, (particularly variations on the HTIR-TC design) were "piggy-backed" on this testing program to provide insights for instrumenting future very high temperature irradiation experiments. This two-year testing program demonstrated that HTIR-TCs and Cambridge Type N TCs could operate at 1250°C for up to 10,000 hrs (and in some cases longer) while experiencing negative drifts on the order of 2-4°C/1000 hrs. This performance was considered acceptable given the extreme operating environment the sensors faced.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

A Forward Analytic Model of Neutron Time-of-Flight Signals for Inferring Ion Temperatures from MagLIF Experiments

A forward analytic model is required to rapidly simulate the neutron time-of-flight (nToF) signals that result from magnetized liner inertial fusion (MagLIF) experiments at Sandia’s Z Pulsed Power Facility. Various experimental parameters, such as the burn-weighted fuel-ion temperature and liner areal density, determine the shape of the nToF signal and are important for characterizing any given MagLIF experiment. Extracting these parameters from measured nToF signals requires an appropriate analytic model that includes the primary deuterium-deuterium neutron peak, once-scattered neutrons in the beryllium liner of the MagLIF target, and direct beamline attenuation. Here, mathematical expressions for this model were derived from the general-geometry time- and energy-dependent neutron transport equation with anisotropic scattering. Assumptions consistent with the time-of-flight technique were used to simplify this linear Boltzmann transport equation into a more tractable form. Models of the uncollided and once-collided neutron scalar fluxes were developed for one of the five nToF detector locations at the Z-Machine. Numerical results from these models were produced for a representative MagLIF problem and found to be in good agreement with similar neutron transport simulations. Twenty experimental MagLIF data sets were analyzed using the forward models, which were determined to only be significantly sensitive to the ion temperature. The results of this work were also found to agree with values obtained separately using a zero scatter analytic model and a high-fidelity Monte Carlo simulation. Finally, inherent difficulties in this and similar techniques are identified, and a new approach forward is suggested.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗