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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Predicting the formation of fractionally doped perovskite oxides by a function-confined machine learning method

Abstract Fractionally doped perovskites oxides (FDPOs) have demonstrated ubiquitous applications such as energy conversion, storage and harvesting, catalysis, sensor, superconductor, ferroelectric, piezoelectric, magnetic, and luminescence. Hence, an accurate, cost-effective, and easy-to-use methodology to discover new compositions is much needed. Here, we developed a function-confined machine learning methodology to discover new FDPOs with high prediction accuracy from limited experimental data. By focusing on a specific application, namely solar thermochemical hydrogen production, we collected 632 training data and defined 21 desirable features. Our gradient boosting classifier model achieved a high prediction accuracy of 95.4% and a high F1 score of 0.921. Furthermore, when verified on additional 36 experimental data from existing literature, the model showed a prediction accuracy of 94.4%. With the help of this machine learning approach, we identified and synthesized 11 new FDPO compositions, 7 of which are relevant for solar thermochemical hydrogen production. We believe this confined machine learning methodology can be used to discover, from limited data, FDPOs with other specific application purposes.

08 HYDROGEN↗
DOE OSTI2014

Heating and current drive requirements towards steady state operation in ITER

Steady state scenarios envisaged for ITER aim at optimizing the bootstrap current, while maintaining sufficient confinement and stability to provide the necessary fusion yield. Non-inductive scenarios will need to operate with Internal Transport Barriers (ITBs) in order to reach adequate fusion gain at typical currents of 9 MA. However, the large pressure gradients associated with ITBs in regions of weak or negative magnetic shear can be conducive to ideal MHD instabilities, reducing the no-wall limit. The E × B flow shear from toroidal plasma rotation is expected to be low in ITER, with a major role in the ITB dynamics being played by magnetic geometry. Combinations of H/CD sources that maintain weakly reversed magnetic shear profiles throughout the discharge are the focus of this work. Time-dependent transport simulations indicate that, with a trade-off of the EC equatorial and upper launcher, the formation and sustainment of quasi-steady state ITBs could be demonstrated in ITER with the baseline heating configuration. However, with proper constraints from peeling-ballooning theory on the pedestal width and height, the fusion gain and the maximum non-inductive current are below the ITER target. Upgrades of the heating and current drive system in ITER, like the use of Lower Hybrid current drive, could overcome these limitations, sustaining higher non-inductive current and confinement, more expanded ITBs which are ideal MHD stable.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1954

Preliminary Altitude Operational Characteristics of a J57-P1 Turbojet Engine

The operational characteristics of a J57-P1 turbojet engine have been investigated at altitudes between 15,000 and 66,000 feet in the Lewis altitude wind tunnel. Included in this study is a discussion of fuel nozzle coking, the altitude operating limits with and without the standard engine control, the compressor surge characteristics, and the engine starting and windmilling characteristics. Severe circumferential turbine outlet temperature gradients which occurred at high altitude as a result of fuel nozzle coking were alleviated by the manufacturer's change in the fuel flow divider schedule and in a nozzle gasket material. Compressor air bleed is required to prevent surge of the outboard compressor in the low engine speed region. The maximum altitude at which the engine was operated without the control was about 66,000 feet at 0.8 flight Mach number and at a reduced engine speed to avoid compressor surge; with the engine control in operation, the altitude operating limit is reduced to approximately 59,000 feet. The maximum altitude at which the engine was started was about 40,000 feet.

Wallner, Lewis E.↗
DOE OSTI2022

Unraveling the effects of management and climate on carbon fluxes of U.S. croplands using the USDA Long-Term Agroecosystem (LTAR) network

Understanding the carbon fluxes and dynamics from a broad range of agricultural systems has the potential to improve our ability to increase carbon sequestration while maintaining crop yields. Short-term, single-location studies have limited applicability, but long-term data from a network of many locations can provide a broader understanding across gradients of climate and management choices. Here we examine eddy covariance measured carbon dioxide (CO 2 ) fluxes from cropland sites across the United States Department of Agriculture's Long-Term Agroecosystem Research (LTAR) network. The dataset was collected between 2001 and 2020, spanning 13 sites for a total of 182 site-years. Average seasonal patterns of net ecosystem CO 2 exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (R eco ) were determined, and subsequent regression analysis on these “flux climatologies” was used to identify relationships to mean annual temperature (MAT), mean annual precipitation (MAP), cropping systems, and management practices. At rainfed sites, carbon fluxes were better correlated with MAP (r2 ≤ 0.5) than MAT (r2 ≤ 0.22). Net carbon balance was different among cropping systems (p < 0.001), with the greatest net carbon uptake occurring in sugarcane (Saccharum spp. hybrids) and the least in soybean (Glycine max) fields. Crop type had a greater effect on carbon balance than irrigation management at a Nebraska site. Across cropping systems, grain crops often had higher GPP and were more likely to have net uptake when compared to legume crops. This multi-site analysis highlights the potential of the LTAR network to further carbon flux research using eddy covariance measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Prospects and challenges for fungal metatranscriptomes of complex communities

We report that the ability to extract and purify messenger RNA directly from plants, decomposing organic matter and soil, followed by high-throughput sequencing of the pool of expressed genes, has spawned the emerging research area of metatranscriptomics. Each metatranscriptome provides a snapshot of the composition and relative abundance of actively transcribed genes, and thus provides an assessment of the interactions between soil microorganisms and plants, and collective microbial metabolic processes in many environments. We highlight current approaches for analysis of fungal transcriptome and metatranscriptome datasets across a gradient of community complexity, and note benefits and pitfalls associated with those approaches. Finally, we discuss knowledge gaps that limit our current ability to interpret metatranscriptome datasets and suggest future research directions that will require concerted efforts within the scientific community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Enhanced Boundary Layer Height Detection Using Ceilometer, Surface Meteorology, and Radiation Products With a Random Forest Ensemble Method

This study develops and evaluates a Random Forest (RF) model for estimating planetary boundary layer height (PBLH) using 9 years of data from the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) user facility, with potential application in the NOAA Surface Radiation (SURFRAD) Network. The model integrates ceilometer, surface meteorology, and radiation measurements, and is trained using thermodynamic PBLH estimates derived from radiosondes. This approach aims to bridge gaps between aerosol-based and thermodynamic-based PBLH estimates. The RF model outperformed traditional methods during daytime and better captured transition periods, demonstrating improved accuracy and robustness. At ARM SGP, it showed a substantial reduction in both bias and RMSE, with a bias near zero (−4.9 m) compared with traditional Haar Wavelet (HW) (70.9 m) and Vaisala BL-View software (124.1 m), and an RMSE of 303.2 m, lower than both BL-View (566.9 m) and HW (404.6 m). During daytime hours, RF consistently outperformed both alternatives, maintaining lower bias and RMSE across all periods. At a second evaluation site, RF achieved the lowest overall RMSE (323.7 m), similar to HW (326.4 m) and significantly better than BL-View (738.3 m). However, all models showed reduced accuracy under stable nighttime conditions, limiting the reliability of PBLH estimates. Key predictors for the model included the lifting condensation level height (LCLH), aerosol gradients, and month for seasonal variability. The study underscores the potential of integrating machine learning with multiple data sets such as surface energy and thermodynamic data to advance PBLH estimation.

boundary layer height↗
DOE OSTI2021

Noise-induced barren plateaus in variational quantum algorithms

Abstract Variational Quantum Algorithms (VQAs) may be a path to quantum advantage on Noisy Intermediate-Scale Quantum (NISQ) computers. A natural question is whether noise on NISQ devices places fundamental limitations on VQA performance. We rigorously prove a serious limitation for noisy VQAs, in that the noise causes the training landscape to have a barren plateau (i.e., vanishing gradient). Specifically, for the local Pauli noise considered, we prove that the gradient vanishes exponentially in the number of qubits n if the depth of the ansatz grows linearly with n . These noise-induced barren plateaus (NIBPs) are conceptually different from noise-free barren plateaus, which are linked to random parameter initialization. Our result is formulated for a generic ansatz that includes as special cases the Quantum Alternating Operator Ansatz and the Unitary Coupled Cluster Ansatz, among others. For the former, our numerical heuristics demonstrate the NIBP phenomenon for a realistic hardware noise model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Proof-of-principle demonstration of Nb{sub 3}Sn superconducting radiofrequency cavities for high Q{sub 0} applications

Many future particle accelerators require hundreds of superconducting radiofrequency (SRF) cavities operating with high duty factor. The large dynamic heat load of the cavities causes the cryogenic plant to make up a significant part of the overall cost of the facility. This contribution can be reduced by replacing standard niobium cavities with ones coated with a low-dissipation superconductor such as Nb{sub 3}Sn. In this paper, we present results for single cell cavities coated with Nb{sub 3}Sn at Cornell. Five coatings were carried out, showing that at 4.2 K, high Q{sub 0} out to medium fields was reproducible, resulting in an average quench field of 14 MV/m and an average 4.2 K Q{sub 0} at quench of 8 × 10{sup 9}. In each case, the peak surface magnetic field at quench was well above H{sub c1}, showing that it is not a limiting field in these cavities. The coating with the best performance had a quench field of 17 MV/m, exceeding gradient requirements for state-of-the-art high duty factor SRF accelerators. It is also shown that—taking into account the thermodynamic efficiency of the cryogenic plant—the 4.2 K Q{sub 0} values obtained meet the AC power consumption requirements of state-of-the-art high duty factor accelerators, making this a proof-of-principle demonstration for Nb{sub 3}Sn cavities in future applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Predicting nonresonant pressure-driven MHD modes in equilibria with low magnetic shear

Nonresonant internal modes can be difficult to anticipate as there is no resonant surface in the plasma. However, equilibria that are unstable to multiple nonresonant magnetohydrodynamic (MHD) modes may be more prone to global loss of confinement since these instabilities generate spatially extended linear displacements, potentially enhancing magnetic field line chaos via nonlinear interactions. Here, we successfully predict the unstable nonresonant pressure-driven modes for equilibria with zero shear in the plasma core, irrational q on axis, and a central pressure gradient, which is consistent with pre-crash profiles in sawtoothing tokamak plasmas in the large-aspect-ratio limit. A criterion for identifying nonresonant modes most likely to be unstable is developed from the convergents of the continued fraction representation of q 0 . A higher-order analysis of the standard Energy Principle reveals the conditions under which these modes are expected to dominate. Linear growth rate spectra, as a function of toroidal mode number (up to n = 30), calculated using the initial-value extended-MHD code, M3D-C1, recover the characteristic dependence observed for ideal infernal modes. Nonresonant modes have also been invoked in some ideal sawtooth crash models. Finally, this work provides a mechanism to predict the mode numbers of infernal modes and, potentially, the width of some post-sawtooth-crash profiles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Sensor Reduction for Diversion Detection in a Realistic Heat Pipe Microreactor Using Supervised Machine Learning

Microreactors are designed as a smaller, cheaper, and safer alternative to traditional nuclear power plants. Their non-traditional characteristics and prospect of mass production and deployment will likely require new approaches to nuclear safeguards. The primary proliferation concern with microreactors is the diversion of fuel material. Such diversion may produce measurable defects in key physical attributes like neutron flux, which may in turn be detectable using machine learning models. Preliminary work has demonstrated this ability for modeled nominal and diversion scenarios using large quantities of energy integrated neutron flux data. In practice, the number of available sensors for such measurements will be limited and energy integrated flux information will not be available. This work explores the ability of tree-based gradient boosted ensemble models to classify a given microreactor core is nominal or diversion, and determine the number of fuel pins diverted in the case of diversion with reduced numbers of sensors and more realistic detector responses. Classification accuracy of greater than 98% and regression errors as low as 5% of the total number of fuel pins were achieved with as few as 15 sensors, compared to 99% and 4.1% with a maximum of 240 sensors.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

SU-F-J-29: Dosimetric Effect of Image Registration ROI Size and Focus in Automated CBCT Registration for Spine SBRT

Purpose: Spinal stereotactic body radiotherapy (SBRT) involves highly conformal dose distributions and steep dose gradients due to the proximity of the spinal cord to the treatment volume. To achieve the planning goals while limiting the spinal cord dose, patients are setup using kV cone-beam CT (kV-CBCT) with 6 degree corrections. The kV-CBCT registration with the reference CT is dependent on a user selected region of interest (ROI). The objective of this work is to determine the dosimetric impact of ROI selection. Methods: Twenty patients were selected for this study. For each patient, the kV-CBCT was registered to the reference CT using three ROIs including: 1) the external body, 2) a large anatomic region, and 3) a small region focused in the target volume. Following each registration, the aligned CBCTs and contours were input to the treatment planning system for dose evaluation. The minimum dose, dose to 99% and 90% of the tumor volume (D99%, D90%), dose to 0.03cc and the dose to 10% of the spinal cord subvolume (V10Gy) were compared to the planned values. Results: The average deviations in the tumor minimum dose were 2.68%±1.7%, 4.6%±4.0%, 14.82%±9.9% for small, large and the external ROIs, respectively. The average deviations in tumor D99% were 1.15%±0.7%, 3.18%±1.7%, 10.0%±6.6%, respectively. The average deviations in tumor D90% were 1.00%±0.96%, 1.14%±1.05%, 3.19%±4.77% respectively. The average deviations in the maximum dose to the spinal cord were 2.80%±2.56%, 7.58%±8.28%, 13.35%±13.14%, respectively. The average deviation in V10Gy to the spinal cord were 1.69%±0.88%, 1.98%±2.79%, 2.71%±5.63%. Conclusion: When using automated registration algorithms for CBCT-Reference alignment, a small target-focused ROI results in the least dosimetric deviation from the plan. It is recommended to focus narrowly on the target volume to keep the spinal cord dose below tolerance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Enrichment of Root Endophytic Bacteria from Populus deltoides and Single-Cell-Genomics Analysis

ABSTRACT Bacterial endophytes that colonize Populus trees contribute to nutrient acquisition, prime immunity responses, and directly or indirectly increase both above- and below-ground biomasses. Endophytes are embedded within plant material, so physical separation and isolation are difficult tasks. Application of culture-independent methods, such as metagenome or bacterial transcriptome sequencing, has been limited due to the predominance of DNA from the plant biomass. Here, we describe a modified differential and density gradient centrifugation-based protocol for the separation of endophytic bacteria from Populus roots. This protocol achieved substantial reduction in contaminating plant DNA, allowed enrichment of endophytic bacteria away from the plant material, and enabled single-cell genomics analysis. Four single-cell genomes were selected for whole-genome amplification based on their rarity in the microbiome (potentially uncultured taxa) as well as their inferred abilities to form associations with plants. Bioinformatics analyses, including assembly, contamination removal, and completeness estimation, were performed to obtain single-amplified genomes (SAGs) of organisms from the phyla Armatimonadetes , Verrucomicrobia , and Planctomycetes , which were unrepresented in our previous cultivation efforts. Comparative genomic analysis revealed unique characteristics of each SAG that could facilitate future cultivation efforts for these bacteria. IMPORTANCE Plant roots harbor a diverse collection of microbes that live within host tissues. To gain a comprehensive understanding of microbial adaptations to this endophytic lifestyle from strains that cannot be cultivated, it is necessary to separate bacterial cells from the predominance of plant tissue. This study provides a valuable approach for the separation and isolation of endophytic bacteria from plant root tissue. Isolated live bacteria provide material for microbiome sequencing, single-cell genomics, and analyses of genomes of uncultured bacteria to provide genomics information that will facilitate future cultivation attempts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Ion Transport in Concentrated Crosslinked Solid Polymer Electrolytes

Crosslinking polymers is a common approach to create mechanically stable solid materials such as polymer electrolytes for lithium batteries. In conventional liquid electrolytes, the solvent molecules move freely to accommodate the field-induced motion of ions. However, in crosslinked polymer electrolytes, the rearrangement of polymer segments is constrained by the deformation limits of the network. Herein, we develop a new transport model that accounts for both the formation of concentration gradients and the elasticity of the electrolyte. The elasticity is incorporated by adding an additional term related to the entropy of crosslinked strands to the electrochemical potential of the salt. The resulting Crosslink Model contains two adjustable parameters: $\mathcal{N}$, the average number of monomers in a strand, and λ crit , the maximum strain the network can sustain. These solid-like constraints produce singularities in the governing transport equations, fundamentally altering the concentration profiles. Plateaus in salt concentrations emerge near the electrodes, and network elasticity introduces a strain overpotential. When compared to a Baseline Model ($\mathcal{N}$ → ∞, equivalent to concentrated solution theory), which predicts steepest gradients near the electrodes, both models yield similar current–voltage relationships. Model predictions are compared to electrochemical data for a poly(ethylene oxide)-based crosslinked polymer electrolyte.

Patel, Vivaan [University of California, Berkeley,↗
DOE OSTI2017

Stan : A Probabilistic Programming Language

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectation propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can also be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

2020 State of the Science Report, Chapter 7: Changes in Oceanographic Systems Associated with Marine Renewable Energy Devices

Oceanographic processes define the marine environment: the flow of water determines the concentrations of dissolved gases and nutrients, transports sediments, and maintains the habitats and water quality that support marine organisms and healthy ecosystems. Important physical processes in the ocean include, but are not limited to, tidal circulation and basin flushing, wave action, local and basin-scale ocean currents, temperature and salinity gradients, sediment transport forming and shaping coastlines, and the exchange of heat and dissolved gases at the air-water interface. Harnessing energy with marine renewable energy (MRE) devices has the potential to affect these processes in both the nearfield (within a few device lengths) and the farfield (farther from the device, from the scale of multiple devices to the scale of an enclosed basin) by removing energy from the system, changing natural flow patterns around devices, and/or decreasing wave heights. https://tethys.pnnl.gov/publications/state-of-the-science-2020-chapter-7-oceanographic-systems

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Gradient Flow Renormalization of Quasi-Parton Distributions

Gradient flow, is a method that allows us to construct lattice quasi PDFs that are finite in the continuum limit. In the small flow time limit, the moments of the smeared quasi PDFs are proportional to those of the light-front PDFs. These proportionality coefficient obey a renormalization group equation that allows us to derive renormalization scale evolution equations for the matching kernel that relates the smeared quasi PDF and the renormalized light-front PDFs. Based on these results we propose a new methodology for obtaining light-front PDFs from lattice QCD.

Orginos, K.↗
NASA NTRS1978

Turbulent convection within rapidly rotating superadiabatic fluids with horizontal temperature gradients

A model is developed for small scale thermally driven turbulent convection in rapidly rotating systems. The Boussinesq equations of adiabatic and inviscid flow are perturbed about a basic state which is superadiabatic and which contains a horizontal temperature gradient balanced by a geostrophic wind. The growth rates and length scales of the most unstable modes are determined. It is found that these modes are either zonally or latitudinally symmetric, depending on the latitude and the horizontal temperature gradient. The transports of heat and momentum by the modes are computed. The linear amplitudes are assumed to be limited by shear instability. The model predicts a latitude dependent eddy diffusivity. The applicability of the model to astrophysical and planetary bodies is briefly discussed.

Flasar, F. M.↗
NASA NTRS1980

Baffle aperture design study of hollow cathode equipped ion thrusters

A simple theoretical model which can be used as an aid in the design of the baffle aperture region of a hollow cathode equipped ion thruster was developed. An analysis of the ion and electron currents in both the main and cathode discharge chambers is presented. From this analysis a model of current flow through the aperture, which is required as an input to the design model, was developed. This model was verified experimentally. The dominant force driving electrons through the aperture was the force due to the electrical potential gradient. The diffusion process was modeled according to the Bolm diffusion theory. A number of simplifications were made to limit the amount of detailed plasma information required as input to the model to facilitate the use of the model in thruster design. This simplified model gave remarkably consistant results with experimental results obtained with a given thruster geometry over substantial changes in operating conditions. The model was uncertain to about a factor of two for different thruster cathode region geometries. The design usefulness was limited by this factor of two uncertainty and by the accuracy to which the plasma parameters required as inputs to the model were specified.

Brophy, J. R., Jr.↗