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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Dependence of the impurity transport on the dominant turbulent regime in ELM-y H-mode discharges on the DIII-D tokamak

Laser blow-off injections of aluminum and tungsten have been performed on the DIII-D tokamak to investigate the variation of impurity transport in a set of dedicated ion and electron heating scans with a fixed value of the external torque. The particle transport is quantified via the Bayesian inference method, which, constrained by a combination of a charge exchange recombination spectroscopy, soft X-ray measurements, and VUV spectroscopy provides a detailed uncertainty quantification of transport coefficients. Contrasting discharge phases with a dominant electron and ion heating reveal 3-fold drop in the impurity confinement time and order of magnitude increase in midradius impurity diffusion, when additional electron heating is applied. Further, the calculated stationary aluminum density profiles reverse from peaked in electron heated to hollow in the ion heated case, following a similar trend as electron and carbon density. Comparable values of a core diffusion have been observed for W and Al ions, while differences in the propagation dynamics of these impurities are attributed to pedestal and edge transport. Modeling of the core transport with non-linear gyrokinetics code CGYRO, significantly underpredicts the magnitude of the variation in Al transport. Diffusion increases 3-times steeper with additional electron heat flux and 10-times lower diffusion is observed in ion heated case than predicted by the modeling. Here, the CGYRO model quantitatively matches the increase of the Al diffusion when approaching the linear threshold for the transition from the ion temperature gradient (ITG) to trapped electron mode (TEM).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Pan-tropical daily L-band microwave land surface emissivity retrieval from GNSS-R observations

The uncertainties in microwave land surface emissivity (MLSE) measurements have long limited the use of spaceborne microwave radiometer data. As an emerging observation method, Global Navigation Satellite System Reflectometry (GNSS-R) has demonstrated great potential in several land and ocean applications. In this study, a method for obtaining daily MLSE dataset in the pan-tropical region from Cyclone GNSS (CYGNSS) observations is presented and evaluated. The CYGNSS observations are first aggregated into the Equal-Area-Scalable-Earth (EASE) 2.0 36 km grid by a combined weight function of distance, time, and signal-to-noise ratio variance. Then, the method employs a pixel-by-pixel regression algorithm to conduct the daily MLSE retrieval using reference emissivity derived from the Soil Moisture Active Passive (SMAP) brightness temperature. The CYGNSS MLSE shows good agreement with SMAP MLSE, delivering an overall root-mean-square error (RMSE) of 0.022 and 0.017 for horizontal and vertical polarization, respectively, during the training set spanning the whole year of 2018. Furthermore, on the test set from January 2019 to May 2019, the RMSE values amounted to 0.030 and 0.023 for horizontal and vertical polarization, respectively. Temperature records from the International Soil Moisture Network are employed to calculate the emissivity and for in-situ validation, which yield an RMSE of 0.034 and 0.026 for the two polarizations, respectively. The proposed algorithm provides an encouraging approach to obtain accurate daily MLSE dataset for microwave remote sensing. Compared to the SMAP MLSE, the CYGNSS MLSE has a remarkable improvement of 86% in temporal resolution, greatly complementing the existing microwave emissivity datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hydrodynamic description of D meson production in high-energy heavy-ion collisions *

The large values and constituent-quark-number scaling of the elliptic flow of low-p T D mesons imply that charm quarks, initially produced through hard processes, might be partially thermalized through strong interactions with quark-gluon plasma (QGP) in high-energy heavy-ion collisions. To quantify the degree of thermalization of low-p T charm quarks, we compare the D 0 meson spectra and elliptic flow from a hydrodynamic model to experimental data as well as transport model simulations. We use an effective charm chemical potential at the freeze-out temperature to account for the initial charm quark production from hard processes and assume that they are thermalized in the local comoving frame of the medium before freeze-out. D 0 mesons are sampled statistically from the freeze-out hyper-surface of the expanding QGP as described by the event-by-event (3+1)D viscous hydrodynamic model CLVisc. Both the hydrodynamic and transport models can describe the elliptic flow of D 0 mesons at P T < 3 GeV/c as measured in Au+Au collisions at $sqrts_{NN} = 200$ GeV. Though the experimental data on spectra are consistent with the hydrodynamic result at small p T ~ 1 GeV/c, they deviate from the hydrodynamic model at high transverse momentum, GeV/c. The diffusion and parton energy loss mechanisms in the transport model can describe the measured spectra reasonably well within the theoretical uncertainty. Finally, our comparative study indicates that charm quarks only approach local thermal equilibrium at small p T , even though they acquire sizable elliptic flow comparable to light-quark hadrons at both small and intermediate p T .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Evaluation of silicon carbide as a divertor armor material in DIII-D H-mode discharges

Silicon carbide (SiC) represents a promising but largely untested plasma-facing material (PFM) for next-step fusion devices. In this work, an analytic mixed-material erosion model is developed by calculating the physical (via SDTrimSP) and chemical (via empirical scalings) sputtering yield from SiC, Si, and C. The Si content in the near-surface SiC layer is predicted to increase during D plasma bombardment due to more efficient physical and chemical sputtering of C relative to Si. Silicon erosion from SiC thereby occurs primarily from sputtering of the enriched Si layer, rather than directly from the SiC itself. SiC coatings on ATJ graphite, manufactured via chemical vapor deposition, were exposed to repeated H-mode plasma discharges in the DIII-D tokamak to test this model. The qualitative trends from analytic modeling are reproduced by the experimental measurements, obtained via spectroscopic inference using the S/XB method. Quantitatively the model slightly under-predicts measured erosion rates, which is attributed to uncertainties in the ion impact angle distribution, as well as the effect of edge-localized modes. After exposure, minimal changes to the macroscopic or microscopic surface morphology of the SiC coatings were observed. Compositional analysis reveals Si enrichment of about 10%, in line with expectations from the erosion model. Extrapolating to a DEMO-type device, an order-of-magnitude decrease in impurity sourcing, and up to a factor of 2 decrease in impurity radiation, is expected with SiC walls, relative to graphite, if low C plasma impurity content can be achieved. Furthermore, these favorable erosion properties motivate further investigations of SiC as a low-Z, non-metallic PFM.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Experimental observation and integrated modelling of proton-beryllium fusion in He and D plasmas at JET

Validated integrated modelling of JET ITER-like wall experiments in which fusion performance is driven by reactions between fast ions and intrinsically present metal wall impurities is presented. A steady-state L-mode plasma with dominant proton-beryllium fusion and neutron yields of up to ≈ 6·10 13 s -1 is developed in He and D, via radiofrequency heating of a H minority. The fusion drive is unambiguously confirmed by the neutral particle analyser, fast ion loss detector, and γ-ray diagnostics. Experiments are analysed via an integrated modelling framework, developed to model the two-stage proton beryllium-fusion chain and produce high-fidelity fusion product source terms. The modelling chain comprises TRANSP and JETTO for plasma core modelling, LOCUST for full orbit product tracking and collisional slowing-down, DRESS to resolve two- and three-body fusion kinematics, and MCNP for neutron transport calculations. Modelling shows that the primary 9 Be(p,n) 9 B reaction is the dominant neutron emitter at naturally present concentrations of beryllium in these experiments. The yield contribution of secondary reactions between fusion products and beryllium, 9 Be(d,n) 10 B and 9 Be(α,n) 12 C, is found to be negligible. The proton-deuteron knock-on effect in D plasmas is modelled, which is calculated to contribute ≈ 25% to the total neutron yield. For both He and D discharges the total computed neutron rates match fission chamber (FC) measurements within the combined experimental and computational uncertainty, with an average discrepancy of ≈ ± 20%. Realistic proton-beryllium neutron sources are propagated through JET’s MCNP neutron transport model which shows that 235 U FCs’ response is sensitive to p–Be source changes, with up to ≈ 10% variation compared to a D–D neutron source. We show that the high-energy tail of the fast proton minority can be studied with multi-foil neutron activation. The framework is also applied to the study of interactions between fast protons and boron impurities, of relevance to ITER. We calculate that in JET conditions a significant alpha source with DT-like energies could be generated through 11 B(p, α)2α fusion, and detected via γ-emission in secondary interactions between fast alphas and boron. The work represents an important step towards validating predictive integrated modelling capabilities for non-standard fusion reactions.

JET↗
DOE OSTI2023

Quantification of spatial and seasonal trends in the atmosphere and construction of statistical models for infrasonic propagation

SUMMARY Infrasonic waves are influenced by variations in the density, pressure and temperature as well as the ambient winds. Modelling infrasonic propagation can be challenging due to the dynamic nature of the atmosphere as well as the sparseness of measurements which result in variability and notable uncertainty. A framework is presented to quantify spatial and seasonal trends in atmospheric structure via analysis of the effective sound speed profile and identification of temporal trends in the middle atmospheric waveguide produced by the circumpolar vortex winds. Seasonal definitions identifying typical atmospheric structures during the summer, winter and spring/fall transition periods are identified using atmospheric data from 2010 through 2020. Seasonal trend analysis is conducted for a number of locations across the contiguous United States to quantify spatial variations in atmospheric structure that impact infrasonic propagation. For each season and location, empirical orthogonal function analysis is used to reduce the historical archive of atmospheric data into a smaller representative set that can be analysed using numerical tools more efficiently. Infrasonic ray tracing and finite-frequency modal propagation analyses are applied to construct propagation path geometry and transmission loss statistics which are useful in localization and yield estimation for infrasonic sources, respectively. An example application is detailed in which transmission loss statistics are combined with an explosive source model and noise statistics to quantify the capability of a network to detect nearby sources.

58 GEOSCIENCES↗
DOE OSTI2020

Optimizing LSST observing strategy for weak lensing systematics

ABSTRACT The Legacy Survey of Space and Time (LSST) survey will provide unprecedented statistical power for measurements of dark energy. Consequently, controlling systematic uncertainties is becoming more important than ever. The LSST observing strategy will affect the statistical uncertainty and systematics control for many science cases; here, we focus on weak lensing (WL) systematics. The fact that the LSST observing strategy involves hundreds of visits to the same sky area provides new opportunities for systematics mitigation. We explore these opportunities by testing how different dithering strategies (pointing offsets and rotational angle of the camera in different exposures) affect additive WL shear systematics on a baseline operational simulation, using the ρ-statistics formalism. Some dithering strategies improve systematics control at the end of the survey by a factor of up to ∼3–4 better than others. We find that a random translational dithering strategy, applied with random rotational dithering at every filter change, is the most effective of those strategies tested in this work at averaging down systematics. Adopting this dithering algorithm, we explore the effect of varying the area of the survey footprint, exposure time, number of exposures in a visit, and exposure to the Galactic plane. We find that any change that increases the average number of exposures (in filters relevant to WL) reduces the additive shear systematics. Some ways to achieve this increase may not be favorable for the WL statistical constraining power or for other probes, and we explore the relative trade-offs between these options given constraints on the overall survey parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Measurement of the B + /B 0 production ratio in e + e - collisions at the $\Upsilon$ (4S) resonance using B → J/Ψ($\ell\ell$)K decays at Belle

We measure the ratio of branching fractions for the $\Upsilon$ (4S) decays to B + B - and B 0 $\bar{B}$ 0 using B + → J/Ψ($\ell\ell$)K + and B 0 → J/Ψ($\ell\ell$)K 0 samples, where J/Ψ($\ell\ell$) stands for J/Ψ → $\ell$ + $\ell$ - ($\ell$ = e or μ), with 711 fb -1 of data collected at the $\Upsilon$ (4S) resonance with the Belle detector. We find the decay rate ratio of $\Upsilon$ (4S) → B + B - over $\Upsilon$ (4S) → B 0 $\bar{B}$ 0 to be 1.065 ± 0.012 ± 0.019 ± 0.047, which is the most precise measurement to date. The first and second uncertainties are statistical and systematic, respectively, and the third uncertainty is due to the assumption of isospin symmetry in B → J/Ψ($\ell\ell$) K.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Measurement of 𝐷-line energies in sodiumlike Ir

We report measurements of the 𝐷 1 and 𝐷 2 transition energies in Na-like Ir (Ir 66+ ). The 𝐷 1 3⁢𝑠−3⁢𝑝 1/2 transition energy, measured in the extreme ultraviolet (EUV) region at 169.977 ± 0.005 eV with a relative uncertainty of 29 ppm, represents one of the most precise 𝐷-line energy measurements to date for high atomic numbers 𝑍 ≥ 30. The 𝐷 2 3⁢𝑠−3⁢𝑝 3/2 transition energy, measured in the x-ray region, is 621.11 ± 0.06 eV. Therefore, there is a fine-structure separation of 451.13 ± 0.06 eV for the Na-like Ir 3⁢𝑝 levels. We present theoretical calculations of these energies using quantum electrodynamic-extended relativistic many-body perturbation theory and multiple-configuration Dirac-Hartree-Fock methods, and discuss the discrepancies between experimental and theoretical values. The prospect of determining the absolute nuclear charge radii of heavy elements, including rare isotopes, from these measurements is explored.

Atomic spectra↗
DOE OSTI2022

Evaluation of dynamic testing of full-scale wind turbine drivetrains with hardware-in-the-loop

Dynamometer testing of full-scale wind turbine drivetrains involves subjecting integrated components to extreme static loads, fatigue loads, or dynamic loads to replicate field conditions. This paper provides a detailed evaluation of the uncertainty and errors in applied loads and measured responses, and their magnitude relative to established repeatability bounds for a drivetrain subjected to static and dynamic loads on the 7.5 MW test bench at the Clemson University Wind Turbine Drivetrain Testing Facility. An ideal drivetrain simulation model is utilized to isolate the influence of load tracking errors on test article responses. It is shown that the test article response variations are mainly driven by run out and clearances inherent to the drivetrain. For the dynamic profiles, the load tracking errors are within acceptable limits. Furthermore, a frequency analysis is used to show that the test bench controller tracking performance is acceptable for profiles with frequency content up to 1.5 Hz.

17 WIND ENERGY↗
DOE OSTI2021

Revisiting spontaneous Raman scattering for direct oxygen atom quantification

In this paper, the counterintuitive and largely unknown Raman activity of oxygen atoms is evaluated for its capacity to determine absolute densities in gases with significant O-density. The study involves C O 2 microwave plasma to generate a self-calibrating mixture and establish accurate cross sections for the 3 P 2 ↔<!-- ↔ --> 3 P 1 and 3 P 2 ↔<!-- ↔ --> 3 P 0 transitions. The approach requires conservation of stoichiometry, confirmed within experimental uncertainty by a 1D fluid model. The measurements yield σ<!-- σ --> J = 2 →<!-- → --> 1 = 5.27 ±<!-- ± --> s y s : 0.53 r a n d : 0.17 ×<!-- × --> 10 -<!-- - --> 31 c m 2 / s r and σ<!-- σ --> J = 2 →<!-- → --> 0 = 2.11 ±<!-- ± --> s y s : 0.21 r a n d : 0.06 ×<!-- × --> 10 -<!-- - --> 31 c m 2 / s r , and the detection limit is estimated to be 1 ×<!-- × --> 10 15 c m -<!-- - --> 3 for systems without other scattering species.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Uncertainty Quantification in Scientific ML

The intricate interactions between data sampling, model selection and the inherent randomness in complex systems strongly emphasize the need for a rigorous characterization of ML algorithms. In conventional statistics, uncertainty quantification (UQ) provides this characterization by measuring how accurately a model reflects the physical reality and by studying the impact of different error sources on the prediction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

IER 557: Godiva Pulse Repeatability and Characterization (CED-3A Report)

Godiva IV is a fast burst critical assembly constructed of approximately 65 kg of highly enriched uranium (HEU) fuel alloyed with 1.5% molybdenum for strength. Godiva IV is proposed as the radiation source for IER 498: Design a Shielding Benchmark with a Metal Critical Source. IER 498 proposes a two-burst method to determine the performance of shielding samples, comparing the transmission of the source radiation to detectors with and without a shielding sample present. This eliminates the need for an absolute calibration and allows many uncertainties to cancel. However, the source term variability must be low compared to other sources of experimental uncertainty to ensure the overall uncertainty meets acceptable levels to provide useful measurements. The primary goal of this experiment is to quantify the source term variability, or reproducibility, of Godiva bursts, focusing on the 70 °C bursts planned for IER 498 measurements. Discussions during IER 498 noted that a number of bursts (on the order of six to ten) as identical as possible would be performed and that a 5-7% standard deviation in source intensity would be acceptable.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Posterior Regularized Bayesian Neural Network

Traditional NNs often lack the ability for uncertainty quantification. Bayesian NNs(BNNs) could help measure the confidence level by using distributions in NNs modeling. Besides, knowledge is commonly available and could improve the performance of BNNs if it can be properly incorporated. In this work, we propose a novel Posterior-Regularized BNN(PR-BNN) model by incorporating soft and hard constraints as a posterior regularization term. We also propose an augmented Lagrangian method and stochastic optimization algorithm for efficient updating via Monte Carlo sampling. The simulations and case studies for solar PV plants have shown the performance improvement of the proposed model over traditional BNNs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Application of NEAMS Multiphysics Framework for Species Tracking in Molten Salt Reactors

This report from Idaho National Laboratory (INL) summarizes the key modeling and simulation activities conducted under the Department of Energy (DOE) Molten Salt Reactor (MSR) Campaign during the Fiscal Year 2023 (FY23). The focus of the work was to leverage state-of-the-art modeling capabilities from the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) codes to enable novel multiphysics and multiscale modeling and simulation of MSRs. Through collaboration with NEAMS code developers, advanced multiphysics analysis capabilities for MSR systems were demonstrated by coupling depletion, thermal-hydraulics, and thermochemistry into an innovative framework for chemical species transport in MSRs. As a result, the framework can track nuclides throughout their lifetimes in the core, from production (depletion) to advection throughout the salt volume (thermal-hydraulics) and off-gassing or precipitation outside of the salt (thermochemistry). This work supports the near-term deployment of MSRs by integrating the synergistic efforts between the DOE’s MSR Campaign and NEAMS program. The resulting framework will help better connect system design modelers with experimentalists to better understand and predict complex physical behaviors in MSRs. Researchers and MSR developers alike can now leverage these new modeling and simulation capabilities to perform novel analyses with applications including: • MSR dynamics during normal operational transients and accident scenarios • Off-gas system design and performance for fuel cycle and depletion analysis • Corrosion and active chemistry control for reactor component health and lifetime determination • Source term, decay heat and activity determination in accident scenarios • Special nuclear material accountancy and chemical forensic analysis for safeguards • Digital twin development of experiments and experimental reactor demonstrations • Measurement requirements for instrumentation and control design • Uncertainty and sensitivity analysis of missing data to inform future experimental data collection.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Inferring Nuclear Hamiltonians from 3 rd -Generation Gravitational-Wave Detectors [Slides]

Neutrons stars are some of the densest objects in our universe. Thus, they provide us with a laboratory to study dense nuclear matter and its properties. The neutron star’s stability at such high densities, with an immense gravitational force, is due in large part to nuclear interactions. Specifically, nuclear 3-body forces provide significant repulsive contributions and at high densities. Current and future gravitational-wave detectors can help us to better understand these nuclear interactions. My project aims to predict the constraining power of the next generation of Gravitational Wave detectors: Cosmic Explorer. I have constructed a solver for the Tolman-Oppenheimer-Volkoff equations and studied equations of state with varying strengths of the 3-body forces. Using simulated data from Phillipe Landry at CITA, I can predict to which level of uncertainty Cosmic Explorer will enable us to measure nuclear 3-body force.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Efficient Signal Processing in BOTDA: Utilizing PCA and PCA-Based Neural Networks for Temperature Monitoring

This work presents a comparative analysis of the various signal processing techniques used in the Brillouin gain spectrum (BGS) peak estimation. Traditional fitting methods such as Lorentzian curve fitting (LCF) are slow and less effective in noisy data. PCA-based methods were tested on the experimental data: A Euclidian distance-based approach, and a probabilistic deep neural network (PDNN) based approach, both using 5 principal components to represent a single BGS. Both methods significantly reduce computational time with respect to LCF, whereas PDNN offers uncertainty insights along with the parameter value. Measuring a range of temperatures, analyzing accuracy, and speed, it can be concluded that PCA trained PDNN outperforms other methods, and appears to be helpful in scenario where large datasets are generated.

Brillouin optical time domain analysis↗