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

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At least 73 records · Page 4

Study of η(1405)/η(1475) in $J/\psi \to \gamma {K}_S^0{K}_S^0{\pi}^0$ decay

Using a sample of (10 . 09 ± 0 . 04) × 10 9 J/ψ decays collected with the BESIII detector, partial wave analyses of the decay $ J/\psi \to \gamma {K}_S^0{K}_S^0{\pi}^0$ are performed within the ${K}_S^0{K}_S^0{\pi}^0$ invariant mass region below 1.6 GeV/ c 2 . The covariant tensor amplitude method is used in both mass independent and mass dependent approaches. Both analysis approaches exhibit dominant pseudoscalar and axial vector components, and show good consistency for the other individual components. Furthermore, the mass dependent analysis reveals that the ${K}_S^0{K}_S^0{\pi}^0$ invariant mass spectrum for the pseudoscalar component can be well described with two isoscalar resonant states using relativistic Breit-Wigner model, i.e., the η (1405) with a mass of $1391.7\pm {0.7}_{-0.3}^{+11.3}$ MeV/ c 2 and a width of $60.8\pm {1.2}_{-12.0}^{+5.5}$ MeV, and the η (1475) with a mass of $1507.6\pm {1.6}_{-32.2}^{+15.5}$ MeV/ c 2 and a width of $115.8\pm {2.4}_{-10.9}^{+14.8}$ MeV. The first and second uncertainties are statistical and systematic, respectively. Alternate models for the pseudoscalar component are also tested, but the description of the ${K}_S^0{K}_S^0{\pi}^0$ invariant mass spectrum deteriorates significantly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A geospatial model for the analysis of time-dependent land subsidence induced by reservoir depletion

Land subsidence due to fluid depletion is an outcome of physical processes operating across a wide range of time and length scales. Although geomechanical models are crucial to simulate reservoir compaction and predict its long-term fate, their use across large regions often bears prohibitive computational costs. To overcome this obstacle, this paper proposes a simplified modelling framework consisting of (i) a near-field numerical solver simulating the coupling between fluid flow and rock deformation with reference to a simplified one-dimensional geometry and (ii) a far-field geospatial algorithm mapping ground settlements across a region through the superposition of poroelastic computations at multiple wells. The model computes the delay between depletion history and reservoir compaction in proximity of a producing well by assuming basal depletion of a fluid-saturated deformable disk, while the Geertsma solution of nucleus of strain is used to extrapolate the impact of such time-varying reservoir compaction around the well. This approach has been used to back-analyze the spatio-temporal progression of subsidence at the Groningen gas field. The results are compared against measurements collected over 50 year of production at 25 benchmark locations scattered over an area of 900 km 2 . It is shown that coupled simulations based on average values of rock compressibility and permeability lead to nonlinear trends of subsidence evolution in good agreement with field measurements, while uncoupled analyses overpredict settlements by more than 70%. Lastly, synthetic forecasts based on different rates of depletion were provided. The results suggest that slower depletion rates lead to lower subsidence at a given time, and that residual subsidence may continue to develop for several decades after interruption of production activities.

58 GEOSCIENCES↗

Analysis of scale-dependent kinetic and potential energy in sheared, stably stratified turbulence

Budgets of turbulent kinetic energy (TKE) and turbulent potential energy (TPE) at different scales $\ell$ in sheared, stably stratified turbulence are analysed using a filtering approach. Competing effects in the flow are considered, along with the physical mechanisms governing the energy fluxes between scales, and the budgets are used to analyse data from direct numerical simulation at buoyancy Reynolds number $Re_b=O(100)$ . The mean TKE exceeds the TPE by an order of magnitude at the large scales, with the difference reducing as $\ell$ is decreased. At larger scales, buoyancy is never observed to be positive, with buoyancy always converting TKE to TPE. As $\ell$ is decreased, the probability of locally convecting regions increases, though it remains small at scales down to the Ozmidov scale. The TKE and TPE fluxes between scales are both downscale on average, and their instantaneous values are correlated positively, but not strongly so, and this occurs due to the different physical mechanisms that govern these fluxes. Moreover, the contributions to these fluxes arising from the sub-grid fields are shown to be significant, in addition to the filtered scale contributions associated with the processes of strain self-amplification, vortex stretching and density gradient amplification. Probability density functions (PDFs) of the $Q,R$ invariants of the filtered velocity gradient are considered and show that as $\ell$ increases, the sheared-drop shape of the PDF becomes less pronounced and the PDF becomes more symmetric about $R=0$ .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Monte Carlo transport analysis to assess intensity dependent response of a carbon-doped GaN photoconductor

In this report evaluation of the photoresponse in wurtzite GaN photoconductive switches is presented based on kinetic Monte Carlo simulations. The focus is on electron transport physics and assessment of high frequency operation. The roles of GaN band structure, Pauli exclusion, and treatment of internal fields based on the fast multipole method are all comprehensively included. The implementation was validated through comparisons of velocity-field characteristics for GaN with computational results in the literature. Photocurrent widths of less than ~7 ps for the 1 μm device can be expected, which translates into a 100 GHz upper bound. Photocurrent pulse compression below the laser full width at half maxima at high applied fields are predicted based on the interplay of space-charge effects and the negative differential velocity characteristics of GaN.

36 MATERIALS SCIENCE↗

Analysis of scintillation light dependence on Liquid Argon purity in the ICARUS detector

Previous studies have investigated the correlation between impurities concentration in Liquid Argon (LAr) and the temporal evolution of either the slow scintillation decay time or the light yield.These impurities typically consist of various molecular species. Electronegative contaminants directly affect electron drift and photon production, while other molecules, such as nitrogen (N$_{2}$), can influence LAr scintillation properties without necessarily affecting electron lifetime.Many current and future neutrino and dark-matter experiments use LAr detectors. This study aims to evaluate the measured electron lifetime in relation to the timing characteristics of the scintillation light signal in the SBN ICARUS detector at Fermi National Accelerator Laboratory. The ICARUS detector consists of two cryostats that have shown different behaviors in the measured electron lifetime over the years. In particular, this study addresses the use of data collected under varying purity conditions in the two cryostats and presents the methodology used to extract scintillation timing characteristics and their correlation with LAr purity.

Saia, C. [Catania Astrophys. Observ.] (ORCID:00090↗

Covariate Dependent Sparse Functional Data Analysis

This study proposes a method to incorporate covariate information into sparse functional data analysis. The method aims at cases where each subject has a limited number of longitudinal measurements and is associated with static covariates. This research is motivated by several use cases in practice. One representative example is void swelling, a nuclear-specific material degradation mechanism. Void swelling is affected by many covariates, including alloy composition and irradiation type. How to accurately model the complicated joint effects of such covariates on the swelling process is the key to mitigating the effect of swelling and ensuring safe operation. Unlike most of the existing methods, the proposed method can handle high-dimensional covariates with the informative covariate identification procedure and sparse and irregularly spaced measurements, that is, does not require complete or dense observations. The main innovation of the proposed method is that we model the variation coming from covariates and the variation left conditioned on covariates, such that the functional principal component analysis and Gaussian process can be conducted in a unified manner. Further, we also propose a systematic approach to identify important covariates in the hypothesis testing context. The methodology is demonstrated on applications in nuclear engineering and healthcare and simulation studies.

42 ENGINEERING↗

Analysis of scintillation light dependence on liquid Argon purity

Previous studies have investigated the correlation between impurity concentrations in Liquid Argon (LAr) and the temporal evolution of either the slow scintillation decay time or the light yield. These impurities typically consist of various molecular species. Electronegative contaminants directly affect electron drift and photon production, while other molecules, such as nitrogen (N_2),can influence LAr scintillation properties without necessarily affecting electron lifetime. Many current and future neutrino and dark-matter experiments use LAr detectors. This study aims to evaluate the measured electron lifetimes in relation to the timing characteristics of the scintillation light signal in the SBN ICARUS detector at Fermi National Accelerator Laboratory. The ICARUS experiment consists of two cryostats that have shown some discrepancies in the measured electron lifetime over the years. In particular, this study addresses the use of data collected under varying purity conditions in the two cryostats.

Saia, Clara [Catania Astrophys. Observ.]↗

R-Value Measurements Performed on Uranium Targets Irradiated with Fission Spectrum Neutrons FY 2021 for F2019 Project

The separation and characterization of two irradiated uranium targets, a depleted uranium (DU) and a highly enriched uranium (HEU) target, was conducted in April of 2021. The two targets were assembled at Los Alamos National Laboratory (LANL) and irradiated using the critical assembly at the National Criticality Experiments Research Center (NCERC). Splits of the dissolved targets were received by Pacific Northwest National Laboratory (PNNL) after which the PNNL and LANL teams chemically separated the solutions using independent separation schemes and analyzed the separated fractions for short lived actinides and fission products. Chemical separations at PNNL were traced with stable or radioactive tracers to allow for the determination of chemical yields, analyzing using either inductively coupled plasma optical emission spectroscopy (ICP-OES), inductively coupled plasma mass spectrometry (ICP-MS) or gamma emission analysis (GEA) depending on the nature of the tracer. Several other analytical techniques were used by PNNL including kinetic phosphorescence analysis (KPA) and thermal ionization mass spectrometry (TIMS) depending on the analyte’s need. Comparisons were made between current and historical PNNL and LANL, as well as literature values. Overall, there was agreement between the two laboratories for the bulk of analytes, with some notable exceptions such as 111 Ag, and 141,143,144 Ce. Included in these comparisons were the short-lived actinides 237 U, 239 Np, the fission products 89 Sr, 91 Y, 95/97 Zr, 99 Mo, 111 Ag, 115/115 mCd, 136/137 Cs, 140 Ba, 141/143/144 Ce, 147 Nd, 153 Sm, 156 Eu, and 161 Tb, providing both total atoms as well as the R-values. The data presented in this report represents the sixth NCERC irradiation of HEU and DU (FY13, FY14, FY15, FY17, FY18, FY21), and their subsequent separation and analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Complementary workflows for identifying one-hop network behavior and multi-hop network dependencies

A network analysis tool evaluates network flow information in complementary workflows to identify one-hop behavior of network assets and also identify multi-hop dependencies between network assets. In one workflow (e.g., using association rule learning), the network analysis tool can identify significant one-hop communication patterns to and/or from network assets, taken individually. Based on the identified one-hop behavior, the network analysis tool can discover patterns of similar communication among different network assets, which can inform decisions about deploying patch sets, mitigating damage, configuring a system, or detecting anomalous behavior. In a different workflow (e.g., using deep learning or cross-correlation analysis), the network analysis tool can identify significant multi-hop communication patterns that involve network assets in combination. Based on the identified multi-hop dependencies, the network analysis tool can discover functional relationships between network assets, which can inform decisions about configuring a system, managing critical network assets, or protecting critical network assets.

97 MATHEMATICS AND COMPUTING↗

Yet Another Sunshine Mystery: Unexpected Asymmetry in GeV Emission from the Solar Disk

The Sun is one of the most luminous γ-ray sources in the sky and continues to challenge our understanding of its high-energy emission mechanisms. This study provides an in-depth investigation of the solar disk γ-ray emission, using data from the Fermi Large Area Telescope spanning 2008 August to 2022 January. We focus on γ-ray events with energies exceeding 5 GeV, originating from 0°5 angular aperture centered on the Sun, and implement stringent time cuts to minimize potential sample contaminants. We use a helioprojection method to resolve the γ-ray events relative to the solar rotation axes and combine statistical tests to investigate the distribution of events over the solar disk. We found that integrating observations over large time windows may overlook relevant asymmetrical features, which we reveal in this work through a refined time-dependent morphological analysis. We describe significant anisotropic trends and confirm compelling evidence of energy-dependent asymmetry in the solar disk γ-ray emission. Intriguingly, the asymmetric signature coincides with the Sun's polar field flip during the cycle 24 solar maximum, around 2014 June. Our findings suggest that the Sun's magnetic configuration plays a significant role in shaping the resulting γ-ray signature, highlighting a potential link between the observed anisotropies, solar cycle, and the solar magnetic fields. These insights pose substantial challenges to established emission models, prompting fresh perspectives on high-energy solar astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗

Machine Learning-Based Classification of Lignocellulosic Biomass from Pyrolysis-Molecular Beam Mass Spectrometry Data

High-throughput analysis of biomass is necessary to ensure consistent and uniform feedstocks for agricultural and bioenergy applications and is needed to inform genomics and systems biology models. Pyrolysis followed by mass spectrometry such as molecular beam mass spectrometry (py-MBMS) analyses are becoming increasingly popular for the rapid analysis of biomass cell wall composition and typically require the use of different data analysis tools depending on the need and application. Here, the authors report the py-MBMS analysis of several types of lignocellulosic biomass to gain an understanding of spectral patterns and variation with associated biomass composition and use machine learning approaches to classify, differentiate, and predict biomass types on the basis of py-MBMS spectra. Py-MBMS spectra were also corrected for instrumental variance using generalized linear modeling (GLM) based on the use of select ions relative abundances as spike-in controls. Machine learning classification algorithms e.g., random forest, k-nearest neighbor, decision tree, Gaussian Naïve Bayes, gradient boosting, and multilayer perceptron classifiers were used. The k-nearest neighbors (k-NN) classifier generally performed the best for classifications using raw spectral data, and the decision tree classifier performed the worst. After normalization of spectra to account for instrumental variance, all the classifiers had comparable and generally acceptable performance for predicting the biomass types, although the k-NN and decision tree classifiers were not as accurate for prediction of specific sample types. Gaussian Naïve Bayes (GNB) and extreme gradient boosting (XGB) classifiers performed better than the k-NN and the decision tree classifiers for the prediction of biomass mixtures. The data analysis workflow reported here could be applied and extended for comparison of biomass samples of varying types, species, phenotypes, and/or genotypes or subjected to different treatments, environments, etc. to further elucidate the sources of spectral variance, patterns, and to infer compositional information based on spectral analysis, particularly for analysis of data without a priori knowledge of the feedstock composition or identity.

59 BASIC BIOLOGICAL SCIENCES↗

Cholesterol-dependent enzyme activity of human TSPO1

The amino acid sequence of the tryptophan-rich sensory proteins (TSPO) is substantially conserved throughout all kingdoms of life. Human mitochondrial TSPO1 (HsTSPO1) binds to porphyrins and steroids, although its interactions with these molecules remains unknown.HsTSPO1 is associated with numerous physiological and pathological disorders, but the underlying molecular mechanisms are unknown. Here, we disclose the finding of human mitochondrial TSPO as a cholesterol-dependent protoporphyrin IX oxygenase. The results of our biochemical characterization are consistent with structural data and evolutionary analysis. The dependence ofHsTSPO1 activity on cholesterol may be the result of the coevolution of this membrane protein with the membrane system. Our study provides a molecular foundation for comprehending the various roles played by mitochondrial TSPO in normal physiological and pathological situations.

Science & Technology - Other Topics↗

R-Value Measurements Performed on Actinide Targets Irradiated using the GODIVA IV Critical Assembly in FY22

The separation and characterization of two irradiated uranium targets, a depleted uranium (DU) and a highly enriched uranium (HEU) target as well as a plutonium (Pu) target, was conducted in April of 2022. The three targets were assembled at Los Alamos National Laboratory (LANL) and irradiated using the GODIVA critical assembly at the National Criticality Experiments Research Center (NCERC). Splits of the dissolved targets were received by Pacific Northwest National Laboratory (PNNL) after which the PNNL and LANL teams chemically separated the solutions using independent separation schemes and analyzed the separated fractions for short lived actinides and fission products. Chemical separations were traced with stable or radioactive tracers to allow for the determination of chemical yields, analyzing using either inductively coupled plasma optical emission spectroscopy (ICP-OES), inductively coupled plasma mass spectrometry (ICP-MS) or gamma emission analysis (GEA) depending on the nature of the tracer. The Pu target solution was traced with stable elements at LANL to follow elemental fractionation during a Pu removal step. Many analytical techniques were used by PNNL including kinetic phosphorescence analysis (KPA), ICP-OES, ICP-MS, GEA, and thermal ionization mass spectrometry (TIMS) depending on the analyte’s need.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

BICEP/ Keck XVIII: Measurement of BICEP3 polarization angles and consequences for constraining cosmic birefringence and inflation

We use a custom-made calibrator to measure individual detectors’ polarization angles of BICEP3, a small aperture telescope observing the cosmic microwave background (CMB) at 95 GHz from the South Pole. We describe our calibration strategy and the statistical and systematic uncertainties associated with the measurement. We reach an unprecedented precision for such measurement on a CMB experiment, with a repeatability for each detector pair of 0.02°. Here, we show that the relative angles measured using this method are in excellent agreement with those extracted from CMB data. Because the absolute measurement is currently limited by a systematic uncertainty, we do not derive cosmic birefringence constraints from BICEP3 data in this work. Rather, we forecast the sensitivity of BICEP3 sky maps for such analysis. We investigate the relative contributions of instrument noise, lensing, and dust, as well as astrophysical and instrumental systematics. We also explore the constraining power of different angle estimators, depending on analysis choices. We establish that the BICEP3 2-year dataset (2017–2018) has an on-sky sensitivity to the cosmic birefringence angle of 𝜎 𝛼 = 0.07⁢8°, which could be improved to 𝜎 𝛼 = 0.05⁢5° by adding all of the existing BICEP3 data (through 2023). Furthermore, we emphasize the possibility of using the BICEP3 sky patch as a polarization calibration source for CMB experiments, which with the present data could reach a precision of 0.035°. Finally, in the context of inflation searches, we investigate the impact of detector-to-detector variations in polarization angles as they may bias the tensor-to-scalar ratio 𝑟. We show that while the effect is expected to remain subdominant to other sources of systematic uncertainty, it can be reliably calibrated using polarization angle measurements such as the ones we present in this paper.

Cosmic microwave background↗

Skeletal model reduction with forced optimally time dependent modes

Skeletal model reduction based on local sensitivity analysis of time dependent systems is presented in which sensitivities are modeled by forced optimally time dependent (f-OTD) modes. The f-OTD factorizes the sensitivity coefficient matrix into a compressed format as the product of two skinny matrices, i.e. f-OTD modes and f-OTD coefficients. The modes create a low-dimensional, time dependent, orthonormal basis which capture the directions of the phase space associated with most dominant sensitivities. These directions highlight the instantaneous active species, and reaction paths. Evolution equations for the f-OTD modes and coefficients are derived, and the implementation of f-OTD for skeletal reduction is described. For demonstration, skeletal reduction is conducted of the constant pressure ethylene-air burning in a zero-dimensional reactor, and new reduced models are generated. The laminar flame speed, the ignition delay, and the extinction curve as predicted by the models are compared against some existing skeletal models in literature for the same detailed model. Finally, the results demonstrate the capability of f-OTD to eliminate unimportant reactions and species in a systematic, efficient and accurate manner.

42 ENGINEERING↗

Oxidation Behavior of Irradiated and Unirradiated NBG-25 Graphite

This presentation discusses The xxidation behavior of irradiated and unirradiated NBG-25 Graphite results of thermogravimetric analysis of same-source specimens from the AGC-1 experiement. Minimal annealing effects, Substantial increase in OR with Irradiation using Conventional Rate Analysis, Apparent Dose Dependency, Examination of Onset (Alternate Analysis) Shows Competing Irradiation Effects, and Similar Test Matrix (without annealing) now under way with NBG-18 Graphite is reviewed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗