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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Environmental Characterization Scans Using Sodium-Iodide Gamma Spectroscopy to Determine Ra-226 Concentration in Surface Soil - 16326

The recent natural gas drilling boom has brought heightened attention to the issue of TENORM waste management. Radioactive residues from the extraction, treatment, and purification of materials containing uranium and thorium, or their progeny, pose a public health hazard primarily in the form of ground water contamination. Hydraulic fracturing can liberate formation waters from shale; the high salinity of which can cause radium to move with the water to the surface. The disposal and handling of this water has been a subject of public controversy. For soil remediation projects, radium-226 is generally one of the radionuclides of concern due to its alpha emissions. However performing a survey scan for Ra-226 is difficult because its photon emissions are low energy and have minimal probability of emission per decay (186.2 keV, 3.3% abundance). Additionally resolving its emission from U-235 (185.7 keV, 57% abundance) with field instrumentation is not feasible. Therefore detection of Ra-226 relies on the presence and photon emissions of its progeny. This paper outlines methodology for calculating the minimum detectable concentration of Ra-226 in characterization scans using a sodium-iodide detector array coupled with a multi-channel analyzer. Using progeny ingrowth as a detection proxy requires knowing decay time in order to determine progeny emission rates. Knowledge of site history, process, and prior survey results can be key in determining an accurate decay time. However in the absence of such information in-situ measurements can be used to estimate decay time by comparing observed progeny emission ratios against established values. These values are determined using Oak Ridge National Laboratory's ORIGEN-ARP program to generate photon energy spectra for Ra-226 and its progeny at specified time intervals. Once decay time is established, the detector's minimum detectable concentration can be calculated by synthesizing the expected emission spectra and Los Alamos National Laboratory's Monte Carlo N-Particle transport code to simulate detector response. Traditionally, one of the steps in calculating a system's minimum detectable concentration is to place an appropriate button source under the detector, record the response, and then move the source by a specified increment. This process is repeated until the detector's spatial efficiency has been mapped. Due to the impracticality of performing this with Ra-226 button sources of varying decay times, Monte Carlo N-Particle transport code was utilized to determine the detector's spatial efficiency. A dime sized source with the established emission spectra was placed into the center of a rectangle of soil. This rectangle, including the source, was used as a lattice element to fill the region of space below the detector. The simulation was designed to track the energy distribution of pulses created in the sodium iodide crystal using the F8 tally, and was setup to isolate each source; thereby correlating detector response to source position. The simulation output required post-processing to determine conversion factors from counts per second to disintegrations per second. Post-processing accounted for subtraction of the Compton continuum, and average the data over the scanning pattern to obtain the expected spatial sensitivity during a characterization study. This was performed for the following photo-peaks: 609 keV (Bi-214), and 1764 keV (Bi-214). For calculation of the scan minimum detectable concentration, the surveyor efficiency coefficient from NUREG 1507 was supplanted in favor of a scan speed deviation factor. This was used because the detector utilizes computerized data collection (spatial and spectral). This report finds that, for two shielded 10.16 cm x 10.16 cm x 40.64 cm sodium-iodide crystals with integrated multi-channel analyzers, the minimum detectable concentration in surface soils is less than 1 pCi per gram Ra-226 for a 1 second survey measurement. These results assume a volumetric source with a maximum depth of 15.24 cm and a minimum decay time of 21 days. Verification of the system's capabilities was performed by sending soil samples from scanned areas, and locations where in-situ measurements were performed, to an independent laboratory for analysis. The laboratory results demonstrated that scanned area was principally comprised of soil containing less than 1 pCi per gram Ra-226. This borders the system MDC and it underestimated the concentration of radium in the soil. The probable causes of this is escape of radon gas from the surface soil. Radon is the daughter of radium, and has a high mobility in soil. If the gas escapes, then the progeny used as the detection proxy will be present in lower than expected concentrations. Radionuclide identification using high volume sodium-iodide crystals in low level characterization scans is demonstrated to be possible. Further system refinement will focus on developing a methodology to estimate a radon escape factor for site specific use. Accounting for radon escape in the top 15.24 cm of soil will allow the system to better estimate Ra-226 concentrations in soil. This is a significant advancement over the gross counting statistics used in most studies to satisfy MARSSIM survey requirements, because it will increase stakeholder confidence. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatiotemporally continuous SW–PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multisource data from complementary satellites/sensors is challenging because of co-registration, intercalibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage and characterize the diurnal cycles of SW–PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW–PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1°×0.1°), and they include estimates of the direct and diffuse components of SW–PAR. We used independently widely distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy's Atmospheric System Research (ASR) program to evaluate the performance of our products, and we further analyzed and compared the spatiotemporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of -3.96 and -0.71 W m -2 and root-mean-square errors (RMSEs) of 103.50 and 35.40 W m -2 , respectively). The developed products capture the complex spatiotemporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations in SW–PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Discrete Regularization for Calibration of Geologic Facies Against Dynamic Flow Data

Abstract Subsurface flow model calibration involves many more unknowns than measurements, leading to ill‐posed problems with nonunique solutions. To alleviate nonuniqueness, the problem is regularized by constraining the solution space using prior knowledge. In certain sedimentary environments, such as fluvial systems, the contrast in hydraulic properties of different facies types tends to dominate the flow and transport behavior, making the effect of within facies heterogeneity less significant. Hence, flow model calibration in those formations reduces to delineating the spatial structure and connectivity of different lithofacies types and their boundaries. A major difficulty in calibrating such models is honoring the discrete, or piecewise constant, nature of facies distribution. The problem becomes more challenging when complex spatial connectivity patterns with higher‐order statistics are involved. This paper introduces a novel formulation for calibration of complex geologic facies by imposing appropriate constraints to recover plausible solutions that honor the spatial connectivity and discreteness of facies models. To incorporate prior connectivity patterns, plausible geologic features are learned from available training models. This is achieved by learning spatial patterns from training data, e.g., ‐SVD sparse learning or the traditional Principal Component Analysis. Discrete regularization is introduced as a penalty functions to impose solution discreteness while minimizing the mismatch between observed and predicted data. An efficient gradient‐based alternating directions algorithm is combined with variable splitting to minimize the resulting regularized nonlinear least squares objective function. Numerical results show that imposing learned facies connectivity and discreteness as regularization functions leads to geologically consistent solutions that improve facies calibration quality.

Khaninezhad, Mohammad‐Reza↗
DOE OSTI2019

An adjoint method for neoclassical stellarator optimization

Stellarators remain an enticing route to steady-state fusion power. However, to achieve the required confinement, the magnetic geometry must be highly optimized. This optimization requires navigating high-dimensional spaces, often necessitating the use of gradient-based methods. The gradient of the neoclassical fluxes is expensive to compute with classical methods, requiring $O(N)$ flux computations, where $N$ is the number of parameters. To reduce the cost of the gradient computation, we present an adjoint method for computing the derivatives of moments of the neoclassical distribution function for stellarator optimization. The linear adjoint method allows derivatives of quantities which depend on solutions of a linear system, such as moments of the distribution function, to be computed with respect to many parameters from the solution of only two linear systems. This reduces the cost of computing the gradient to the point that the finite-collisionality neoclassical fluxes can be used within an optimization loop. With the neoclassical adjoint method, we compute solutions of the drift kinetic equation and an adjoint drift kinetic equation to obtain derivatives of neoclassical quantities with respect to geometric parameters. When the number of parameters in the derivative is large ( $O(10^{2})$ ), this adjoint method provides up to a factor of 200 reduction in cost. We demonstrate adjoint-based optimization of the field strength to obtain minimal bootstrap current on a surface. With adjoint-based derivatives, we also compute the local sensitivity to magnetic perturbations on a flux surface and identify regions where tight tolerances on error fields are required for control of the bootstrap current or radial transport. Moreover, the solve for the ambipolar electric field is accelerated using a Newton method with derivatives obtained from the adjoint method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Predicting strength distributions of MEMS structures using flaw size and spatial density

The populations of flaws in individual layers of microelectromechanical systems (MEMS) structures are determined and verified using a combination of specialized specimen geometry, recent probabilistic analysis, and topographic mapping. Strength distributions of notched and tensile bar specimens are analyzed assuming a single flaw population set by fabrication and common to both specimen geometries. Both the average spatial density of flaws and the flaw size distribution are determined and used to generate quantitative visualizations of specimens. Scanning probe-based topographic measurements are used to verify the flaw spacings determined from strength tests and support the idea that grain boundary grooves on sidewalls control MEMS failure. The findings here suggest that strength controlling features in MEMS devices increase in separation, i.e., become less spatially dense, and decrease in size, i.e., become less potent flaws, as processing proceeds up through the layer stack. The method demonstrated for flaw population determination is directly applicable to strength prediction for MEMS reliability and design.

Instruments & Instrumentation↗
DOE OSTI2015

Thermodynamic perturbation theory for associating fluids confined in a one-dimensional pore

In this paper, a new theory is developed for the self-assembly of associating molecules confined to a single spatial dimension, but allowed to explore all orientation angles. The interplay of the anisotropy of the pair potential and the low dimensional space results in orientationally ordered associated clusters. This local order enhances association due to a decrease in orientational entropy. Unlike bulk 3D fluids which are orientationally homogeneous, association in 1D necessitates the self-consistent calculation of the orientational distribution function. To test the new theory, Monte Carlo simulations are performed and the theory is found to be accurate. It is also shown that the traditional treatment in first order perturbation theory fails to accurately describe this system. The theory developed in this paper may be used as a tool to study hydrogen bonding of molecules in 1D zeolites as well as the hydrogen bonding of molecules in carbon nanotubes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Dislocation structures, interfacing, and magnetism in the L1 0 - MnGa on η ⊥ - Mn 3 N 2 bilayer

Ferromagnetic L1 0 -MnGa was grown by molecular beam epitaxy under ultrahigh vacuum conditions to a 73 ± 5 nm thickness atop of 50 ± 5 nm thick molecular beam epitaxy grown antiferromagnetic η ⊥ -Mn 3 N 2 on a MgO(001) substrate. The MnGa grew along the c-axis with an out-of-plane spacing of c = 3.71 ± 0.01 Å and a relaxed in-plane spacing of a = 4.00 ± 0.05 °A measured with X-ray diffraction and reflection high-energy electron diffraction respectively. Williamson-Hall analysis revealed 67 ± 17 nm tall columnar grains with a residual stress of 2.40 ± 0.26 (×10 -3 ). A radial distribution plot of screw dislocations observed in scanning tunneling microscopy images found an in-plane coherence length of 15 ± 5 nm. Reflection high-energy electron diffraction analysis of the in-plane lattice spacing during growth reveals a critical thickness of 1.05 ± 0.65 nm for the MnGa, by which the MnGa film relaxes by incorporating dislocations of both edge and screw type. Vibrating sample magnetometry was employed to obtain the magnetic properties of the bilayer system. It is found that the dislocation density plays a significant role in understanding the measured moment per unit cell, where a large dislocation density lowers the moment per unit cell significantly due to chemical layering disorder. Finally, this finding is important for materials development of large saturation magnetization.

36 MATERIALS SCIENCE↗
DOE OSTI2017

New mechanism of semiconductor polarization at the interface with an organic insulator

A semiconductor—organic-insulator system with spatially distributed charge is created with a uniquely low density of fast surface states (N{sub ss}) at the interface. A system with N{sub ss} ≈ 5 × 10{sup 10} cm{sup –2} is obtained for the example of n-Ge and the physical characteristics of the interface are measured for this system with liquid and metal field electrodes. For a system with an organic insulator, the range of variation of the surface potential from enrichment of the space-charge region of the semiconductor to the inversion state is first obtained without changing the mechanism of interaction between the adsorbed layer and the semiconductor surface. The effect of enhanced polarization of the space-charge region of the semiconductor occurs due to a change in the spatial structure of mobile charge in the organic dielectric layer. The system developed in the study opens up technological opportunities for the formation of a new generation of electronic devices based on organic film structures and for experimental modeling of the electronic properties of biological membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

hkl-projects/ioc-hkl

HKL-IOC is an open source EPICS IOC that performs real‑time crystallographic HKL calculations for diffractometers and scattering instruments. It integrates the Python hkl library with EPICS through PyDevice, exposing HKL calculations and diffractometer geometry transformations as standard EPICS process variables. This allows beamline and laboratory control systems to convert between motor positions and reciprocal‑space coordinates, configure diffractometer geometries, and drive scans directly in HKL space. The software is written in Python and designed to run alongside existing EPICS deployments without requiring changes to core EPICS components. It is intended for use at synchrotron and neutron scattering facilities, as well as laboratory X‑ray diffractometers, where reliable and reproducible HKL calculations are needed for experiment control, data collection, and automation. HKL-IOC is distributed under the GNU General Public License v3.0 (GPL‑3.0) and contributions and extensions for additional geometries and beamlines are welcomed.

Baekey, Alex↗
DOE OSTI2017

ATDM LANL FleCSI: Topology and Execution Framework

FleCSI is a compile-time configurable C++ framework designed to support multi-physics application development. As such, FleCSI attempts to provide a very general set of infrastructure design patterns that can be specialized and extended to suit the needs of a broad variety of solver and data requirements. This means that FleCSI is potentially useful to many different ECP projects. Current support includes multidimensional mesh topology, mesh geometry, and mesh adjacency information, n-dimensional hashed-tree data structures, graph partitioning interfaces, and dependency closures (to identify data dependencies between distributed-memory address spaces). FleCSI introduces a functional programming model with control, execution, and data abstractions that are consistent with state-of-the-art task-based runtimes such as Legion and Charm++. The model also provides support for fine-grained, data-parallel execution with backend support for runtimes such as OpenMP and C++17. The FleCSI abstraction layer provides the developer with insulation from the underlying runtimes, while allowing support for multiple runtime systems, including conventional models like asynchronous MPI. The intent is to give developers a concrete set of user-friendly programming tools that can be used now, while allowing flexibility in choosing runtime implementations and optimizations that can be applied to architectures and runtimes that arise in the future. This project is essential to the ECP Ristra Next-Generation Code project, part of ASC ATDM, because it provides a hierarchically parallel programming model that is consistent with the design of modern system architectures, but which allows for the straightforward expression of algorithmic parallelism in a portably performant manner.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

E-Invariant Quantized Motion of Valence Quarks

In sub-proton space wave processes are impossible. The analog of the Klein–Gordon equation in sub-proton space is elliptical and describes a stationary system with a constant number of particles. For dynamical processes, separation of variables is used and in each quantum of motion of the quark two states are distinguished: a localization state and a translation state with infinite velocity. Alternation of these states describes the motion of a quark. The mathematical expectations of the lifetimes of the localization states and the spatial extents of the translation states for a free quark and for a quark in a centrally symmetric potential are found. The action after one quantum of motion is equal to the Planck constant. The one-sided Laplace transform is used to determine the Green’s function. Use of path integrals shows that the quantized trajectory of a quark is a broken line enveloping the classical trajectory of oscillation of the quark. Comparison of the calculated electric charge distribution in a proton with its experimental value gives satisfactory results. A hypothesis is formulated, according to which the three Grand Geometries of space correspond to the three main interactions of elementary particles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Situational awareness-enhancing community-level load mapping with opportunistic machine learning

Motivated by present and forthcoming challenges in the adoption and integration of distributed renewable energy, we develop a machine learning (ML) approach that builds short-fuse mappings connecting the occasionally-unobservable true load in one target community with information-rich signals collected from relatively more instrumented reference communities. Our setting is inspired by and tailored to target communities with significant unobservable behind-the-meter solar generation, where true load (a relatively well-behaved quantity of interest to grid operators) is hard to discern during daytime due to insufficient instrumentation and/or privacy reasons, but that can be related to reference communities with low unobservable distributed variable generation or with sufficient instrumentation. The developed mapping, herein realized with Support Vector Machine regression, is built using nighttime data from all communities, when their distributed generation is low or zero. Our ML algorithm opportunistically learns to correlate signals of interest and then is operationally used the next day to shed light into target community load evolution. The mapping is subsequently rebuilt, rolling its short-fuse scope perpetually forward in time. Here, we demonstrate the efficacy of our approach on nine synthetically generated topologies and associated timeseries stemming from real-world data, on which we observe cumulative error performance that yields lower than 10% and 15% daily-averaged mean absolute percentage errors in target community load estimation on more than about 75% and 90% of days, respectively, in multiple yearly evaluations that shed light on long-term performance also under seasonal and one-off effects. The proposed ML-powered methodology can offer grid operators much-improved visibility into a previously obscure space and can also serve as an additional source of information in broader, multi-modal solar disaggregation solutions.

14 SOLAR ENERGY↗
DOE OSTI2025

Numerically exact configuration interaction at quadrillion-determinant scale

The combinatorial growth of configuration interaction (CI) has long limited this formally exact quantum chemistry method to only the smallest molecules. Here, we report a numerically exact CI calculation exceeding one quadrillion (10 15 ) determinants, made possible by a lossless categorical compression strategy within the small-tensor-product distributed active space (STP-DAS) framework. This approach overcomes the traditional memory bottlenecks of CI by a numerically exact compression of the wavefunction representation and reformulating the most computationally demanding matrix–vector operations. Using this method, we performed a fully relativistic CI calculation of the ground state of HBrTe with over 10 15 complex-valued determinants in just 34.5 h on 1000 computing nodes—the largest CI calculation ever reported. We further achieved fast computation for systems with hundreds of billions of determinants on only a few compute nodes. Extensive benchmarks confirm that the method retains full numerical exactness while cutting memory and computational cost by orders of magnitude. Compared to previous state-of-the-art CI calculations, this work achieves a 1000 times increase in CI space, a 10 6 -fold increase in floating-point operations performed, and a 10 6 -fold improvement in computational speed.

Computational chemistry↗
DOE OSTI2020

Effects of lithium intercalation in twisted bilayer graphene

In this work, we investigate the effects of lithium intercalation in twisted bilayers of graphene, using first-principles electronic structure calculations. To model this system we employ commensurate supercells that correspond to twist angles of 7.34° and 2.45°. From the energetics of lithium absorption we demonstrate that for low Li concentration the intercalants cluster in the AA regions with double the density of a uniform distribution. The charge donated by the Li atoms to the graphene layers results in modifications to the band structure that can be qualitatively captured using a continuum model with modified interlayer couplings in a region of parameter space that has yet to be explored either experimentally or theoretically. Thus, the combination of intercalation and twisted layers simultaneously provides the means for spatial control over material properties and an additional knob with which to tune moiré physics in twisted bilayers of graphene, with potential applications ranging from energy storage and conversion to quantum information.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Denoising of polychromatic CT images based on their own noise properties

Purpose: Because of high diagnostic accuracy and fast scan time, computed tomography (CT) has been widely used in various clinical applications. Since the CT scan introduces radiation exposure to patients, however, dose reduction has recently been recognized as an important issue in CT imaging. However, low-dose CT causes an increase of noise in the image and thereby deteriorates the accuracy of diagnosis. In this paper, the authors develop an efficient denoising algorithm for low-dose CT images obtained using a polychromatic x-ray source. The algorithm is based on two steps: (i) estimation of space variant noise statistics, which are uniquely determined according to the system geometry and scanned object, and (ii) subsequent novel conversion of the estimated noise to Gaussian noise so that an existing high performance Gaussian noise filtering algorithm can be directly applied to CT images with non-Gaussian noise. Methods: For efficient polychromatic CT image denoising, the authors first reconstruct an image with the iterative maximum-likelihood polychromatic algorithm for CT to alleviate the beam-hardening problem. We then estimate the space-variant noise variance distribution on the image domain. Since there are many high performance denoising algorithms available for the Gaussian noise, image denoising can become much more efficient if they can be used. Hence, the authors propose a novel conversion scheme to transform the estimated space-variant noise to near Gaussian noise. In the suggested scheme, the authors first convert the image so that its mean and variance can have a linear relationship, and then produce a Gaussian image via variance stabilizing transform. The authors then apply a block matching 4D algorithm that is optimized for noise reduction of the Gaussian image, and reconvert the result to obtain a final denoised image. To examine the performance of the proposed method, an XCAT phantom simulation and a physical phantom experiment were conducted. Results: Both simulation and experimental results show that, unlike the existing denoising algorithms, the proposed algorithm can effectively reduce the noise over the whole region of CT images while preventing degradation of image resolution. Conclusions: To effectively denoise polychromatic low-dose CT images, a novel denoising algorithm is proposed. Because this algorithm is based on the noise statistics of a reconstructed polychromatic CT image, the spatially varying noise on the image is effectively reduced so that the denoised image will have homogeneous quality over the image domain. Through a simulation and a real experiment, it is verified that the proposed algorithm can deliver considerably better performance compared to the existing denoising algorithms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI1991

Nuclear Safety [Vol. 32, No. 4, October-December 1991]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 477 Report on the International Symposium on the Use of Probabilistic Safety Assessment for Operational Safety—PSA '91, S. Chakraborty and M. Khatib-Rahbar; 488 Good Relationships Are Pivotal in Nuclear Data Bases, A. S. Heger and B. V. Koen; 494 Technical Note: The Interagency Nuclear Safety Review Panel's Evaluation of the Ulysses Space Mission, J. A. Sholtis, Jr., D. A. Huff, L. B. Gray, N. P. Klug, and R. O. Winchester; ACCIDENT ANALYSIS: 502 The Severe Accident Analysis Program for the Savannah River Nuclear Production Reactors, M. L. Hyder; CONTROL AND INSTRUMENTATION: 511 A Framework for Selecting Suitable Control Technologies for Nuclear Power Plant Systems, R. A. Kisner; DESIGN FEATURES: 521 Containments for Gas-Cooled Power Reactors History and Status, P.W. Williams; ENVIRONMENTAL EFFECTS: 537 Indoor Radon: A Natural Risk, N. H. Harley and J.H. Harley; On the Importance of the Atmospheric Parameters in the Fission Products Distribution of a Severe Reactor Accident, M. C. Barla and A. R. Bayulken; Book Review: Health Effects of Exposure to Low Levels of Ionizing Radiation BEIR V, C. R. Richmond; WASTE AND SPENT FUEL MANAGEMENT: 555 Activities Related to Waste and Spent Fuel Management, M. D. Muhlheim and E. G. Silver OPERATING EXPERIENCES: 567 Effects of Component Aging on the Westhinghouse Control Rod Drive System, K. Sullivan and W. Gunther; 577 Reactor Shutdown Experience, Compiled by J. W. Cletcher, 580 Selected Safety-Related Events, Compiled by G. A. Murphy; 582 Operating U 8 Power Reactors, Compiled by M. D. Muhlheim and E. G. Silver, RECENT DEVELOPMENTS: 596 General Administrative Activities, Compiled by M. D. Muhlheim and E. G. Silver; 610 Reports, Standards, and Safety Guides, D. S. Queener; 614 Proposed Rule Changes as of June 30, 1991; ANNOUNCEMENTS: 520 Workshop on PC PRAISE: A Probabilistic Fracture Mechanics Personal Computer Code for Nuclear Power Plant Piping Reliability Assessment; 536 Fifth Workshop on Nuclear Power Plant Containment Integrity; 624 New OECD "International Information System on Occupational Exposure (ISOE)"; 625 Harvard School of Public Health Announces Short Courses; 625 Eighth Power Plant Dynamics, Control and Testing Symposium; 626 Second Training Course on Off-Site Emergency Planning and Response for Nuclear Accidents; 618 The Authors; 622 Reviewers of Nuclear Safety, Vol 32.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Spin relaxation rate for heavy quarks in weakly coupled QCD plasma

We compute the relaxation rate of the spin density of heavy quarks in a perturbative QCD plasma to leading-log order in the coupling constant g. The spin relaxation rate Γ s in spin hydrodynamics is shown to be Γ s ~ g 4 log(1/g)T(T/M) 2 in the heavy-quark limit T/M $\ll$ 1, which is smaller than the relaxation rate of other non- hydrodynamic modes by additional powers of T/M. We demonstrate three different methods to evaluate the spin relaxation rate: 1) the Green-Kubo formula in the spin hydrodynamic regime, 2) the spin density correlation function in the strict hydrodynamic limit, and 3) quantum kinetic theory of the spin distribution function in momentum space. We highlight the interesting differences between these methods, while they are ultimately connected to each other by the underlying Ward-Takahashi identity for the non-conserved spin density.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗