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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The Need for a New LLNL Pulsed Sphere Neutron Leakage Spectra Series

Here, it is shown that spectra measured as part of the Lawrence Livermore National Laboratory Pulsed Sphere (LPS) program offer decisive information to locate formatting or physics issues in nuclear data of key interest for fusion reactor simulations. However, experiments from this measurement series are not benchmarks. For instance, their uncertainties are incomplete. There are also many open questions—e.g., on the setup, the detector response, and whether LPS are accurately modeled—that cannot be answered anymore given the limited documentation and that many of the experimenters are no longer actively working. This limited knowledge has implications when one tries to adjust nuclear data to LPS spectra. Usually, one adjusts to benchmarks representing an application with the hope to get more precise nuclear data for the application of interest where differential data might be scarce and/or to reduce nuclear data uncertainties in the application simulations. However, it is demonstrated that adjustment with LPS spectra without accounting for missing uncertainties and modeling potential biases in the experimental data leads to adjusted data that are highly unphysical. That means adjusted data differ significantly from evaluated data based on information from differential experiments; also, application quantities predicted with the adjusted data deviate distinctly from experimental ones. While we can approximate our limited knowledge on these experiments with Gaussian processes in the adjustment process, this modeling of bias is arbitrary rather than based on a physics explanation, calling into doubt the validity of resulting adjusted data. Thus, we discuss here the need for a new measurement series, learning from the strengths and weaknesses of the LPS program, to yield decisive and well-benchmarked integral experiments to support fusion reactor research.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Leaf water potential measurements using the pressure chamber: Synthetic testing of assumptions towards best practices for precision and accuracy

Leaf water potential (ψ leaf ), typically measured using the pressure chamber, is the most important metric of plant water status, providing high theoretical value and information content for multiple applications in quantifying critical physiological processes including drought responses. Pressure chamber measurements of ψ leaf (ψ leafPC ) are most typical, yet, the practical complexity of the technique and of the underlying theory has led to ambiguous understanding of the conditions to optimize measurements. Consequently, specific techniques and precautions diversified across the global research community, raising questions of reliability and repeatability. Here, we surveyed specific methods of ψ leafPC from multiple laboratories, and synthesized experiments testing common assumptions and practices in ψ leafPC for diverse species: (i) the need for equilibration of previously transpiring leaves; (ii) leaf storage before measurement; (iii) the equilibration of ψ leaf for leaves on bagged branches of a range of dehydration; (iv) the equilibration of ψ leaf across the lamina for bagged leaves, and the accuracy of measuring leaves with artificially ‘elongated petioles’; (v) the need in ψ leaf measurements for bagging leaves and high humidity within the chamber; (vi) the need to avoid liquid water on leaf surfaces; (vii) the use of ‘pulse’ pressurization versus gradual pressurization; and (viii) variation among experimenters in ψ leafPC determination. Based on our findings we provide a best practice protocol to maximise accuracy, and provide recommendations for ongoing species-specific tests of important assumptions in future studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Dark energy survey year 1 results: Constraining baryonic physics in the Universe

ABSTRACT Measurements of large-scale structure are interpreted using theoretical predictions for the matter distribution, including potential impacts of baryonic physics. We constrain the feedback strength of baryons jointly with cosmology using weak lensing and galaxy clustering observables (3 × 2pt) of Dark Energy Survey (DES) Year 1 data in combination with external information from baryon acoustic oscillations (BAO) and Planck cosmic microwave background polarization. Our baryon modelling is informed by a set of hydrodynamical simulations that span a variety of baryon scenarios; we span this space via a Principal Component (PC) analysis of the summary statistics extracted from these simulations. We show that at the level of DES Y1 constraining power, one PC is sufficient to describe the variation of baryonic effects in the observables, and the first PC amplitude (Q1) generally reflects the strength of baryon feedback. With the upper limit of Q1 prior being bound by the Illustris feedback scenarios, we reach $\sim 20{{\ \rm per\ cent}}$ improvement in the constraint of $S_8=\sigma _8(\Omega _{\rm m}/0.3)^{0.5}=0.788^{+0.018}_{-0.021}$ compared to the original DES 3 × 2pt analysis. This gain is driven by the inclusion of small-scale cosmic shear information down to 2.5 arcmin, which was excluded in previous DES analyses that did not model baryonic physics. We obtain $S_8=0.781^{+0.014}_{-0.015}$ for the combined DES Y1+Planck EE+BAO analysis with a non-informative Q1 prior. In terms of the baryon constraints, we measure $Q_1=1.14^{+2.20}_{-2.80}$ for DES Y1 only and $Q_1=1.42^{+1.63}_{-1.48}$ for DESY1+Planck EE+BAO, allowing us to exclude one of the most extreme AGN feedback hydrodynamical scenario at more than 2σ.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Micro‐ and Nanoscale Heterogeneities in Zeolite Beta as Measured by Atom Probe Tomography and Confocal Fluorescence Microscopy

Micro- and nanoscale information on the activating and deactivating coking behaviour of zeolite catalyst materials increases our current understanding of many industrially applied processes, such as the methanol-to-hydrocarbon (MTH) reaction. Atom probe tomography (APT) was used to reveal the link between framework and coke elemental distributions in 3D with sub-nanometre resolution. APT revealed 10–20 nanometre-sized Al-rich regions and short-range ordering (within nanometres) between Al atoms. With confocal fluorescence microscopy, it was found that the morphology of the zeolite crystal as well as the secondary mesoporous structures have a great effect on the microscale coke distribution throughout individual zeolite crystals over time. Additionally, a nanoscale heterogeneous distribution of carbon as residue from the MTH reaction was determined with carbon-rich areas of tens of nanometres within the zeolite crystals. Finally, a short length-scale affinity between C and Al atoms, as revealed by APT, indicates the formation of carbon-containing molecules next to the acidic sites in the zeolite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Siting bioenergy facilities in the United States: Measuring participation in decisions and distribution of effects

Scientists and stakeholders can inform the process of siting renewable energy facilities in ways that do not perpetuate socioeconomic disparities associated with fossil fuel industries or create new ones. Procedural justice indicators and distributional justice indicators that incorporate environmental, social, and economic objectives can be used to site energy facilities in ways that increase benefits and reduce negative impacts to disadvantaged and underserved populations. A generic list of potential energy justice indicators for siting bioenergy facilities was developed collaboratively between U.S. bioenergy researchers and diverse agriculture, energy, and energy and environmental justice stakeholders and experts. From this list smaller numbers of indicators can be selected or modified with communities for local siting of bioenergy facilities. Groups of indicators can be used to guide biorefinery or biopower siting and permitting decisions, e.g., to compare siting options, to draw early attention to key problems, or to track progress toward justice-related targets.

09 BIOMASS FUELS↗
DOE OSTI2022

An Alternative Timing and Synchronization Approach for Situational Awareness and Predictive Analytics

Accurate and synchronized timing information is required by power system operators for controlling the grid infrastructure (relays, Phasor Measurement Units (PMUs), etc.) and determining asset positions. Satellite-based global positioning system (GPS) is the primary source of timing information. However, GPS disruptions today (both intentional and unintentional) can significantly compromise the reliability and security of our electric grids. A robust alternate source for accurate timing is critical to serve both as a deterrent against malicious attacks and as a redundant system in enhancing the resilience against extreme events that could disrupt the GPS network. To achieve this, we rely on the highly accurate, terrestrial atomic clock-based network for alternative timing and synchronization. In this paper, we discuss an experimental setup for an alternative timing approach. The data obtained from this experimental setup is continuously monitored and analyzed using various time deviation metrics. We also use these metrics to compute deviations of our clock with respect to the National Institute of Standards and Technologys (NIST) GPS data. The results obtained from these metric computations are elaborately discussed. Finally, we discuss the integration of the procedures involved, like real-time data ingestion, metric computation, and result visualization, in a novel microservices-based architecture for situational awareness.

Chinthavali, Supriya↗
DOE OSTI2020

Non-visual analysis of miniaturized melt wire arrays for in-pile measurement of peak irradiation temperature

As a part of the in-pile instrumentation program, the Idaho National Laboratory (INL) has established in-house capabilities to fabricate and test new advanced manufactured printed sensors for measurement of peak temperature inside the harsh environment of a nuclear test reactor. Although nuclear test reactors may use standard methods that can provide real-time temperature information, such as thermocouples, the need for feedthroughs for real-time measurements greatly increases the cost of the experiment. Some experiments also present the problem of limited space available for instrumentation. To address this need, INL is working to improve temperature detection options for such applications. The lab is developing advanced manufactured melt wire arrays to determine peak temperatures in experiments with limited space. Furthermore, capabilities to print multiple melt wires with different melting properties on a single miniaturized unit is being established. Recent results and knowledge from this ongoing work have made it possible to develop unique temperature sensors that can accomplish user specific temperature ranges inside the harsh environments experienced during radiation testing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Flow friction in a wide rectangular duct with a beveled inlet: Informal Notes of Fundamental Fluid Physics Studies

Fundamental streamwise pressure distributions were measured at Idaho State University to address a primary objective of obtaining insight into the apparent evolution of air flow regimes at moderate Reynolds numbers in thin, wide rectangular ducts with converging inlets. Ducts of 3.030 and 4.077 mm spacings s (called three and four mm), having non-dimensional lengths of (L/s) ≈ 500.8 and 372.2 and widths (W/s) ≈ 114.6 and 83.2, respectively, were compared. Flow rates ranged from Reynolds numbers based on hydraulic diameter (Re Dh ) of about 980 to 10,000 and corresponding non-dimensional downstream pressure gradient parameters (-K p ) covered the range 0.038 to 0.0061, respectively.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems

The high complexity and multiscale nature of many engineered systems—such as those in nuclear power plants—make representing and forecasting their dynamic behavior challenging. Physics-based models can be overly complex and computationally intractable, whereas machine learning (ML) tools are often data-hungry and prone to unphysical solutions. This study proposes a knowledge-informed ML-aided hybrid residual modeling approach that offers accurate and efficient time series forecasting for the operation of dynamical engineered systems. Hybrid residual modeling entails a baseline solution from domain knowledge and known physics expressions about the system dynamics integrated with an ML model to capture undiscovered information from the mismatch (i.e., residuals) between true states from measurements and baseline-predicted outputs. This study further quantifies the ML model uncertainty to provide trustworthy solutions. Real-time operational data from thermal-hydraulic flow loops of the cryogenic moderator system in Oak Ridge National Laboratory’s Spallation Neutron Source facility were used to demonstrate the potential of knowledge-informed uncertainty-aware ML in real-world applications. The state variables of the cryogenic helium loop were modeled with (1) first principles–based system identification (sysID), (2) long short-term memory (LSTM) neural network, and (3) hybrid sysID (baseline) + LSTM (residual). The superior predictive capability of the sysID+LSTM model versus stand-alone sysID and LSTM is confirmed by average performance metrics and individual data points across different prediction horizons. By creating a robust representation of the underlying physical system, the widely applicable hybrid residual modeling approach will enable the future development of digital twins for performance prediction, prognostics, and operation control.

Zhao, Xingang↗
DOE OSTI2022

Physics‐Informed Machine Learning Method for Large‐Scale Data Assimilation Problems

Abstract We develop a physics‐informed machine learning approach for large‐scale data assimilation and parameter estimation and apply it for estimating transmissivity and hydraulic head in the two‐dimensional steady‐state subsurface flow model of the Hanford Site given synthetic measurements of said variables. In our approach, we extend the physics‐informed conditional Karhunen‐Loéve expansion (PICKLE) method to modeling subsurface flow with unknown flux (Neumann) and varying head (time‐dependent Dirichlet) boundary conditions. We demonstrate that the PICKLE method is comparable in accuracy with the standard maximum a posteriori (MAP) method, but is significantly faster than MAP for large‐scale problems. Both methods use a mesh to discretize the computational domain. In MAP, the parameters and states are discretized on the mesh; therefore, the size of the MAP parameter estimation problem directly depends on the mesh size. In PICKLE, the mesh is used to evaluate the residuals of the governing equation, while the parameters and states are approximated by the truncated conditional Karhunen‐Loéve expansions with the number of parameters controlled by the smoothness of the parameter and state fields, and not by the mesh size. For a considered example, we demonstrate that the computational cost of PICKLE increases near linearly (as N 1.15 ) with the number of grid nodes N , while that of MAP increases much faster (as N 3.28 ). We also show that once trained for one set of Dirichlet boundary conditions (i.e., one river stage), the PICKLE method provides accurate estimates of the hydraulic head for any value of the Dirichlet boundary conditions (i.e., for any river stage).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

High throughput, spatially resolved thermal properties measurement using attachable and reusable 3ω sensors

The 3ω method is a well-established thermal technique used to measure the thermal conductivity of materials and the thermal resistance of interfaces. It has significant advantages over other steady state and transient thermal techniques in its ability to provide spatially resolved thermal property measurements over a wide range of thermal conductivity. Despite its advantages, it has been restricted to lab-scale use because of the difficulty involved in sample preparation and sensor fabrication and is limited to non-metallic substrates. High-throughput 3ω measurements with reusable sensors have not been realized yet. In this work, we demonstrate a method of applying reusable 3ω sensors fabricated on flexible polyimide films to measure bulk and spatially resolved thermal properties. Here, we establish the limits of thermal conductivity measurement with the method to be 1 to 200 W/mK, and within the measurement limit, we verify the method by comparing the measured thermal conductivities of standard samples with established values. From the 3ω measurements, we also determine the thermal resistance of an interlayer of thermal grease as a function of pressure and compare it against the resistance calculated from direct thickness measurements to demonstrate the ability of this method to provide spatially resolved subsurface information. The technique presented is general and applicable to both metallic and non-metallic substrates, providing a method for high-throughput 3ω measurements with reusable sensors and without considerable sample preparation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Entangled spin-polarized excitons from singlet fission in a rigid dimer

Abstract Singlet fission, a process that splits a singlet exciton into a biexciton, has promise in quantum information. We report time-resolved electron paramagnetic resonance measurements on a conformationally well-defined acene dimer molecule, TIPS-BP1', designed to exhibit strongly state-selective relaxation to specific magnetic spin sublevels. The resulting optically pumped spin polarization is a nearly pure initial state from the ensemble. The long-lived spin coherences modulate the signal intrinsically, allowing a measurement scheme that substantially removes noise and uncertainty in the magnetic resonance spectra. A nonadiabatic transition theory with a minimal number of spectroscopic parameters allows the quantitative assignment and interpretation of the spectra. In this work, we show that the rigid dimer TIPS-BP1' supports persistent spin coherences at temperatures far higher than those used in conventional superconducting quantum hardware.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Statistical Complexity of Quantum Learning

Abstract Learning problems involve settings in which an algorithm has to make decisions based on data, and possibly side information such as expert knowledge. This study has two main goals. First, it reviews and generalizes different results on the data and model complexity of quantum learning, where the data and/or the algorithm can be quantum, focusing on information‐theoretic techniques. Second, it introduces the notion of copy complexity, which quantifies the number of copies of a quantum state required to achieve a target accuracy level. Copy complexity arises from the destructive nature of quantum measurements, which irreversibly alter the state to be processed, limiting the information that can be extracted about quantum data. As a result, empirical risk minimization is generally inapplicable. The paper presents novel results on the copy complexity for both training and testing. To make the paper self‐contained and approachable by different research communities, an extensive background material is provided on classical results from statistical learning theory, as well as on the distinguishability of quantum states. Throughout, the differences between quantum and classical learning are highlighted by addressing both supervised and unsupervised learning, and extensive pointers are provided to the literature.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Gamma-ray measurements for inertial confinement fusion applications

High-energy γ rays generated from inertial confinement fusion (ICF) experiments have become an important signature for studying the dynamics of implosion processes. Due to their high-energy and penetrating nature, γ rays are the most unperturbed fusion products, which can preserve the original birth information of the fusion process. Fusion γ rays provide a direct measure of nuclear reaction rates (unlike x rays) without being compromised by Doppler spreading (unlike neutrons). However, unambiguous γ-ray measurements for ICF study further required a decade-long period of technological development, which included a deepening understanding of fusion γ-ray characteristics and innovations in instrument performance. This review article introduces the production mechanism of the prompt and secondary γ rays and various ICF performance parameters (e.g., bang time and burn width), which can be derived from γ-ray measurement. A technical overview will be followed by summarizing γ-ray detectors fielded or proposed, especially for high-yield ICF experiments at the Omega Laser Facility and National Ignition Facility. Over the past few years, γ-ray diagnostic technologies have been extended beyond ICF research. A few examples of non-ICF applications of γ-ray detectors are introduced at the end of this article.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Statistical analysis of magnetic divertor configuration influence on H-mode transitions

DIII-D plasmas are compared for two upper divertor configurations: with the outer strike point on the small angle slot (SAS) divertor target and with the outer strike point on the horizontal divertor target (HT). Scanning the vertical distance between the magnetic null point and the divertor target over a range 0.10–0.16 m is shown to increase the threshold power, $P_\mathrm{th}$, and edge plasma power, $P_\mathrm{Loss},$ for the low-to-high confinement (L–H) and H–L transitions respectively, by up to a factor of 1.4. The X-point height scans were performed at three L-mode core plasma line average electron densities, $\bar{n}_\mathrm{e} = $ 1.2, 2.2 and 3.6 $\times 10^{19}\,\mathrm{m}^{-3}$, to investigate the density dependence of divertor magnetic configuration influence on $P_\mathrm{th}$. The X-point height, $Z_\textrm{x-pt}$, was further extended across the range 0.16–0.22 m with the more open HT divertor configuration, for which a clear decrease in $P_\mathrm{th}$ with increasing $Z_\textrm{x-pt}$ is observed. The dependence of $P_\textrm{th}$ on divertor magnetic geometry is further investigated using a time-dependent probability density function (PDF) model and information geometry to elucidate the roles played by pedestal plasma turbulence and perpendicular velocity flows. The degree of stochasticity of the plasma turbulence is observed to be sensitive to the plasma heating rate. The calculated square of the information rate shows changes in the relative density fluctuations and perpendicular velocity PDFs begin 2–5 ms prior to the L–H transition for three plasmas; providing a crucial measurement of the dynamic timescale of external transport barrier formation. Additionally, both information length and rate provide potential predictors of the L–H transition for these plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Effect of Sample Thickness on the Tensile Strength of Small Graphite Discs

This report formally documents the completion of the Advanced Reactor Technologies (ART) Level 3 Milestone (M3TG-24OR0501054), “Continue activities related to Split Disc-DIC - complete analysis of effect of sample thickness on one fine grain graphite,” due May 31, 2024. Details within this report outline the status of activities aimed at elucidating the effect of sample thickness on the tensile strength measurement using the small-disc, split-disc testing standard in support of the US Department of Energy’s ART Graphite R&D Program. The ASTM D8289, Standard Test Method for Tensile Strength Estimate by Disc Compression of Manufactured Graphite, was developed to provide an alternative means for testing tensile strength on smaller specimens, which are compatible with available irradiation capsule volumes, and other compatibility measurements. ASTM D8289 specifies that acceptable specimen diameter can range from 6 to 12.7 mm and that the maximum allowed sample thickness should be half of the diameter. However, information is limited with respect to the effect of thickness on the measured splitting tensile strength. This report documents efforts to understand the effect of sample thickness on splitting tensile strength. The work involved testing Ø12.7 mm samples of fine-grain graphites 2114 and IG-110 of different thicknesses (6.35, 5, 4, and 3 mm). The digital image correlation (DIC) method was applied to the samples, along with the ASTM D8289 Standard, to help interpret the measured results.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Trajectory Shaper: A Solution for Disrupted Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) can effectively reduce energy consumption, alleviate traffic congestion, and enhance safety. However, communication-related constraints and uncooperative vehicle users can disrupt CACC during real-world operations, significantly undermining the putative benefits of CACC. To alleviate the negative impacts of disrupted CACC, this study develops the trajectory shaper (TS) methods as backup solutions for two scenarios: (i) communication between vehicles is infeasible, and vehicles execute adaptive cruise control (ACC) using local sensor measurements; (ii) follower vehicles reject forming a cooperative platoon and execute their local distributed controllers using the information attained via communication. When communication is infeasible, a distributed TS is devised on each vehicle to modify the sensor measurements, enabling safe and efficient ACC operations. When communication is available but uncooperative agents are involved, the lead vehicle of the platoon executes a centralized TS to modify the information shared with uncooperative agents, achieving optimal platoon-level performance. The centralized and distributed TSs are implemented based on the model predictive control algorithms to yield optimal modifications on input information. Robustness is also factored to tackle model uncertainties during TS operations to ensure safety and efficiency. Numerical experiments validate the control performance of the proposed TSs.

Zhou, Anye [ORNL] (ORCID:0000000301455579)↗
DOE OSTI2021

Measured and satellite-derived albedo data for estimating bifacial photovoltaic system performance

The albedo of the ground surface is an important factor in the cost-effectiveness of a bifacial photovoltaic (PV) system. To improve the availability of reliable albedo data, datasets of ground albedo and associated meteorological data were developed by using existing measurement network data and data measured by the PV industry. The measured datasets include time-series data as well as summary information of tabular monthly and yearly data and plots of monthly and hourly albedo values. Satellite-derived values of albedo are available from the National Solar Radiation Data Base (NSRDB). The NSRDB albedos were compared to the measured albedos for Surface Radiation budget (SURFRAD) network locations for the period 2001–2017, and the mean bias difference results were from -0.044 to +0.056. Overall, these differences are greater than the albedo measurement uncertainty of ±0.02; consequently, the NSRDB albedos should be used with caution for estimating the performance of bifacial PV systems. Differences between SURFRAD and NSRDB albedos are attributed to the NSRDB method for determining albedo and to the ground surfaces within the NSRDB 4 km spatial resolution pixel consisting of a mixture of surface types rather than just the single surface types viewed by the albedometers at the SURFRAD stations.

14 SOLAR ENERGY↗