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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Combined near- and far-field high-energy diffraction microscopy dataset for Ti-7Al tensile specimen elastically loaded in situ

High-energy diffraction microscopy (HEDM) constitutes a suite of combined X-ray characterization methods, which hold the unique advantage of illuminating the microstructure and micromechanical state of a material during concurrent in situ mechanical deformation. The data generated from HEDM experiments provides a heretofore unrealized opportunity to validate meso-scale modeling techniques, such as crystal plasticity finite element modeling (CPFEM), by explicitly testing the accuracy of these models at the length scales where the models predict their response. Combining HEDM methods with in situ loading under known and controlled boundary conditions represents a significant challenge, inspiring the recent development of a new high-precision rotation and axial motion system for simultaneously rotating and axially loading a sample. In this paper, we describe the initial HEDM dataset collected using this hardware on an alpha-titanium alloy (Ti-7Al) under in situ tensile deformation at the Advanced Photon Source, Argonne National Laboratory. We present both near-field HEDM data that maps out the grain morphology and intragranular crystallographic orientations and far-field HEDM data that provides the grain centroid, grain average crystallographic orientation, and grain average elastic strain tensor for each grain. Finally, we provide a finite element mesh that can be utilized to simulate deformation in the volume of this Ti-7Al specimen.

36 MATERIALS SCIENCE↗
DOE OSTI2020

RouteE: A Vehicle Energy Consumption Prediction Engine

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts. The pre-trained RouteE models are established using NREL’s Future Automotive Systems Technology Simulator paired with approximately 1 million miles of drive cycle data from the Transportation Secure Data Center, resulting in energy consumption behavior estimates over a representative sample of driving conditions for the United States. Validations have been performed using on-road fuel consumption data for conventional and electrified vehicle powertrains. Transferring the results of the on-road validation to a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology in a green-routing application would accurately select the route that consumes the least fuel 90% of the time. The novel machine learning techniques used in RouteE make it a flexible and robust tool for a variety of transportation applications.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

A non-fueled nuclear-heated rod for in-pile transient boiling studies

Separate-effects boiling experiments have recently been conducted in the Transient Reactor Test Facility at Idaho National Laboratory to investigate transient heating and irradiation effects on cladding-to-coolant heat transfer. Specifically, transient critical heat flux (CHF) remains an important area of research, and better understanding of this phenomenon has potential for improving predictive models related to operational and safety limits. Consequently, this knowledge is expected to improve efficiency of light-water reactor operations. A novel borated nuclear-heated rodlet (BNHR) was designed to enable observation of transient cladding-to-coolant heat transfer phenomena. The final BNHR design takes a surrogate approach, wherein nuclear heating is induced by 10 B(n, α) reactions rather than derived from fissions in a fueled specimen. The structure of the BNHR consists of a hollowed out borated (B nat ~ 2.05 wt %) stainless steel tube with an hourglass-shaped outer surface, capped at both ends with non-borated stainless steel. This geometry allows for inner-rodlet instrumentation and generation of the highest nuclear heating rates near the center of the rodlet to ensure onset of boiling near instrumentation for real-time observation. A novel approach to measuring the nuclear energy deposition rate in the BNHR separate and apart from the influence of the coolant, termed the n-a thermometer, is also detailed in this paper. This device has demonstrated excellent repeatability, and measurements indicate predictive modeling results for energy deposition in the BNHR rod agree within a 10% margin of the experiment measurements. In conclusion, these results give confidence that the BNHR design has successfully met experiment objectives.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Measurement of total and differential W + W - production cross sections in proton-proton collisions at √s=8 TeV with the ATLAS detector and limits on anomalous triple-gauge-boson couplings

The production of W boson pairs in proton-proton collisions at √s=8 TeV is studied using data corresponding to 20.3 fb -1 of integrated luminosity collected by the ATLAS detector during 2012 at the CERN Large Hadron Collider. The W bosons are reconstructed using their leptonic decays into electrons or muons and neutrinos. Events with reconstructed jets are not included in the candidate event sample. A total of 6636 WW candidate events are observed. Measurements are performed in fiducial regions closely approximating the detector acceptance. The integrated measurement is corrected for all acceptance effects and for the W branching fractions to leptons in order to obtain the total WW production cross section, which is found to be 71.1 ± 1.1(stat) -5.0+5.7(syst)±1.4(lumi) pb. This agrees with the next-to-next-to-leading-order Standard Model prediction of 63.2-1.4+1.6(scale)±1.2(PDF) pb. Fiducial differential cross sections are measured as a function of each of six kinematic variables. The distribution of the transverse momentum of the leading lepton is used to set limits on anomalous triple-gauge-boson couplings.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Systematic search for high-energy gamma-ray emission from bow shocks of runaway stars

Context. It has been suggested that the bow shocks of runaway stars are sources of high-energy gamma rays (E > 100 MeV). Theoretical models predicting high-energy gamma-ray emission from these sources were followed by the first detection of non-thermal radio emission from the bow shock of BD+43°3654 and non-thermal X-ray emission from the bow shock of AE Aurigae. Aims. We perform the first systematic search for MeV and GeV emission from 27 bow shocks of runaway stars using data collected by the Large Area Telescope (LAT) onboard the Fermi Gamma-ray Space Telescope (Fermi). Methods. We analysed 57 months of Fermi-LAT data at the positions of 27 bow shocks of runaway stars extracted from the Extensive stellar BOw Shock Survey catalogue (E-BOSS). A likelihood analysis was performed to search for gamma-ray emission that is not compatible with diffuse background or emission from neighbouring sources and that could be associated with the bow shocks. Results. None of the bow shock candidates is detected significantly in the Fermi-LAT energy range. We therefore present upper limits on the high-energy emission in the energy range from 100MeV to 300 GeV for 27 bow shocks of runaway stars in four energy bands. For the three cases where models of the high-energy emission are published we compare our upper limits to the modelled spectra. Our limits exclude the model predictions for ζ Ophiuchi by a factor ≈ 5.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Characterization of Extreme Hydroclimate Events in Earth System Models using ML/AI

Focal Area(s): (1) We put forward the concepts of data assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization and unsupervised learning applied to downscale information within Earth System Models (ESMs). (2) We discuss predictive modeling through the use of AI techniques and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI-driven model/component/parameterization selection) to improve the characterization of extreme hydroclimate events in ESMs. The AI-based models will run five-six order of magnitude times faster, yet will provide similar accuracy, allowing us to provide range bounds on uncertainty faster and thus enabling faster extreme event identification. (3) Further, we consider the insight gleaned from complex data (observed/simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI to improve the characterization of extreme hydroclimate events in ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Thermal, mechanical, and electrical properties of LSCo/mullite composite contact materials for solid oxide fuel cells

Lanthanum strontium cobaltite (LSCo) is considered as a good candidate cathode contact material for solid oxide fuel cells, due to high electrical conductivity. However, LSCo has a very large coefficient of thermal expansion (CTE) than the cells and metallic interconnects. As a result, poor mechanical stability is expected during thermal cycling. To minimize the CTE mismatch, we investigate a composite approach involving mixing LSCo with an inert material of low CTE, such as mullite at volume fractions from 0.1 to 0.4. Composite’s CTE shows a decreasing trend with increasing mullite volume fractions, and is consistent with model predictions. X-ray powder diffraction analysis of sintered LSCo/mullite composites exhibits no presence of other phases for samples aged for 500h at 800oC, indicating chemical compatibility. Electrical conductivity by a 4-pt method shows a decreasing trend with increasing mullite content. Contact strength of as-sintered and thermally cycled samples show that only the composite with 0.4 volume fraction has a measurable strength; the other composites have no strength. Overall, the composite approach is demonstrated in the LSCo/mullite system to lower the CTE and hence achieve thermal cycle stability. The addition of the inert phase to the LSCo matrix; however, also reduces the electrical conductivity.

Contact materials, LSCo, mullite, CTE, electrical ↗
DOE OSTI2016

Lidar-Enhanced Wind Turbine Control: Past, Present, and Future

The main challenges in harvesting energy from the wind arise from the unknown incoming turbulent wind field. Balancing the competing interests of reduction in structural loads and increasing energy production is the goal of a wind turbine controller to reduce the cost of producing wind energy. Conventional wind turbines use feedback methods to optimize these goals, reacting to wind disturbances after they have already impacted the wind turbine. Lidar sensors offer a means to provide additional inputs to a wind turbine controller, enabling new techniques to improve control methods, allowing a controller to actuate a wind turbine in anticipation of an incoming wind disturbance. This paper will look at the development of lidar-enhanced controls and how they have been used for various turbine load reductions with pitch actuation, as well as increased energy production with improved yaw control. Ongoing work will also be discussed to show that combining pitch and torque control using feedforward nonlinear model predictive control can lead to both reduced loads and increased energy production. Future work is also proposed on extending individual wind turbine controls to the wind plant level and determining how lidars can be used for control methods to further lower the cost of wind energy by minimizing wake impacts in a wind farm.

17 WIND ENERGY↗
DOE OSTI2017

The Use of Positrons to Survey Alteration Layers on Synthetic Nuclear Waste Glasses

In order to safeguard society and the environment, understanding radioactive waste glass alteration mechanisms in interactions with solutions and near-field materials, such as Fe, is essential to nuclear waste repository performance assessments. Alteration products are formed at the surface of glasses after reaction with solution. In this study, glass altered in the presence of Fe0 in aqueous solution formed two alteration layers: one embedded with Fe closer to the surface and one without Fe found deeper in the sample. Both layers were found to be thinner than the alteration layer found in glass altered in aqueous solution only. For the first time, Doppler Broadening Positron Annihilation Spectroscopy (DB-PAS) is used to non-destructively characterize the pore structures of glass altered in the presence of Fe0. Advantages and disadvantages of DB-PAS compared to other techniques used to analyze pore structures for altered glass samples are discussed. Ultimately, DB-PAS has shown to be an excellent choice for pore structure characterization for glasses with multiple alteration layers. Monte Carlo modeling predicted positron trajectories through the layers, and helped explain DB-PAS data, which showed that the deeper alteration layer without Fe had a similar composition and pore structure to layers on glass altered in water only.

Doppler Broadening Positron Annihilation Spectrosc↗
DOE OSTI2020

Monte Carlo simulations of Cu/Ni–Si–Mn co-precipitation in duplex stainless steels

First-Passage Kinetic Monte Carlo (FPKMC) simulations of species migration in duplex stainless steels were performed in order to establish relationships between alloy content, segregation behavior, and the formation of Ni-Si-Mn rich particles in cast duplex stainless steels during thermal aging. The Ni-Si-Mn-rich second phase forms after extended aging at reactor operating temperatures and degrades alloy properties. Simulations of Ni-Si-Mn cluster formation were validated through comparison with experimental results obtained through Atom Probe Tomography (APT) on similar alloy compositions, identifying several trends. First, Cu promotes the formation of Ni-Si-Mn clusters, but only when Ni or Mn prefer segregation to the surface of Cu particles; without the segregation of these species, the critical composition for the clusters to form was not achieved. Second, the width of precipitate-denuded zones near ?/d interfaces increases with decreasing Cu content. This finding was in strong agreement with APT results, further validating our model. Finally, our model predicts that Ni-Si-Mn cluster formation will be the most extensive when the Si:Mn ratio is approximately 1:1 and the least extensive when one of these key elements is less concentrated (Mn = 0.5 at.% or Si = 0.5 at.%). The implications of these results on how to improve alloy properties are discussed.

Cu co-precipitation, Atom probe tomography (APT), ↗
DOE OSTI2014

SU-E-J-156: Preclinical Inverstigation of Dynamic Tumor Tracking Using Vero SBRT Linear Accelerator: Motion Phantom Dosimetry Study

Purpose: Following the ‘end-to-end testing’ paradigm of Dynamic Target Tracking option in our Image-Guided dedicated SBRT VeroTM linac, we verify the capability of the system to deliver planned dose to moving targets in the heterogeneous thorax phantom (CIRSTM). The system includes gimbaled C-band linac head, robotic 6 degree of freedom couch and a tumor tracking method based on predictive modeling of target position using fluoroscopically tracked implanted markers and optically tracked infrared reflecting external markers. Methods: 4DCT scan of the motion phantom with the VisicoilTM implanted marker in the close vicinity of the target was acquired, the ‘exhale’=most prevalent phase was used for planning (iPlan by BrainLabTM). Typical 3D conformal SBRT treatment plans aimed to deliver 6-8Gy/fx to two types of targets: a)solid water-equivalent target 3cm in diameter; b)single VisicoilTM marker inserted within lung equivalent material. The planning GTV/CTV-to-PTV margins were 2mm, the block margins were 3 mm. The dose calculated by MonteCarlo algorithm with 1% variance using option Dose-to-water was compared to the ion chamber (CC01 by IBA Dosimetry) measurements in case (a) and GafchromicTM EBT3 film measurements in case (b). During delivery, the target 6 motion patterns available as a standard on CIRSTM motion phantom were investigated: in case (a), the target was moving along the designated sine or cosine4 3D trajectory; in case (b), the inserted marker was moving sinusoidally in 1D. Results: The ion chamber measurements have shown the agreement with the planned dose within 1% under all the studied motion conditions. The film measurements show 98.1% agreement with the planar calculated dose (gamma criteria: 3%/3mm). Conclusion: We successfully verified the capability of the SBRT VeroTM linac to perform real-time tumor tracking and accurate dose delivery to the target, based on predictive modeling of the correlation between implanted marker motion and external surrogate of breathing motion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Temporal dynamics of CO 2 and CH 4 loss potentials in response to rapid hydrological shifts in tidal freshwater wetland soils

Earth System Models predict climate extremes that will impact regional and global hydrology. Aquatic-terrestrial transition zones like wetlands are subjected to the immediate consequence of climate change with shifts in the magnitude and dynamics of hydrologic flow. Such fluctuating hydrology can alter the nature and rate of biogeochemical transformations and significantly impact the carbon balance of the ecosystem. We tested the impacts of fluctuating hydrology and, specifically, the role of antecedent moisture conditions in determining the dominant carbon loss mechanisms in soils sampled from a tidal freshwater wetland system in the lower Columbia River, WA, USA. Our objective was to understand shifts in biogeochemical processes in response to changing soil moisture, based on soil respiration and methane production rates, and to elucidate such responses based on the observed electron acceptor and metabolite profiles under laboratory conditions. Metabolomics and biogeochemical process rates provided evidence that soil redox was the principal factor driving metabolic function. Fluctuating redox conditions altered terminal electron acceptor and donor availability and recovery strengths of their concentrations in soil such that a disproportionate release of carbon dioxide stemmed from alternative anaerobic degradation processes like sulfate and iron reduction compared to carbon loss due to methano genesis. Our results show that extended and short-term saturation created conditions conducive to increasing metabolite availability for anaerobic decomposition processes, with a significant lag in methanogenesis. In contrast,extended drying caused a cellular-level stress response and rapid recycling of alternate electron acceptors.

anaerobic respiration, tidal wetlands, methane pro↗
DOE OSTI2021

Machine-learning based prediction of injection rate and solenoid voltage characteristics in GDI injectors

We report that current state-of-the-art gasoline direct-injection (GDI) engines use multiple injections as one of the key technologies to improve exhaust emissions and fuel efficiency. For this technology to be successful, secured adequate control of fuel quantity for each injection is mandatory. However, nonlinearity and variations in the injection quantity can deteriorate the accuracy of fuel control, especially with small fuel injections. Therefore, it is necessary to understand the complex injection behavior and to develop a predictive model to be utilized in the development process. This study presents a methodology for rate of injection (ROI) and solenoid voltage modeling using artificial neural networks (ANNs) constructed from a set of Zeuch-style hydraulic experimental measurements conducted over a wide range of conditions. A quantitative comparison between the ANN model and the experimental data shows that the model is capable of predicting not only general features of the ROI trend, but also transient and non-linear behaviors at particular conditions. In addition, the end of injection (EOI) could be detected precisely with a virtually generated solenoid voltage signal and the signal processing method, which applies to an actual engine control unit. A correlation between the detected EOI timings calculated from the modeled signal and the measurement results showed a high coefficient of determination.

42 ENGINEERING↗
DOE OSTI2014

New evidence for a substellar luminosity problem: Dynamical mass for the brown dwarf binary Gl 417BC

We present new evidence for a problem with cooling rates predicted by substellar evolutionary models that implies that model-derived masses in the literature for brown dwarfs and directly imaged planets may be too high. Based on our dynamical mass for Gl 417BC (L4.5+L6) and a gyrochronology system age from its young, solar-type host star, commonly used models predict luminosities 0.2-0.4 dex lower than we observe. This corroborates a similar luminosity-age discrepancy identified in our previous work on the L4+L4 binary HD 130948BC, which coincidentally has nearly identical component masses (≈50-55 M{sub Jup}) and age (≈800 Myr) as Gl 417BC. Such a luminosity offset would cause systematic errors of 15%-25% in model-derived masses at this age. After comparing different models, including cloudless models that should not be appropriate for mid-L dwarfs like Gl 417BC and HD 130948BC but actually match their luminosities better, we speculate the observed overluminosity could be caused by opacity holes (i.e., patchy clouds) in these objects. Moreover, from hybrid substellar evolutionary models that account for cloud disappearance, we infer the corresponding phase of overluminosity may extend from a few hundred million years up to a few gigayears and cause masses to be overestimated by up to 25%, even well after clouds disappear from view entirely. Thus, the range of ages and spectral types affected by this potential systematic shift in luminosity evolution would encompass most known directly imaged gas-giants and field brown dwarfs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Fast-ion transport in qmin>2, high- β steady-state scenarios on DIII-D

The results from experiments on DIII-D [J. L. Luxon, Fusion Sci. Technol. 48, 828 (2005)] aimed at developing high β steady-state operating scenarios with high-qminqmin confirm that fast-ion transport is a critical issue for advanced tokamak development using neutral beam injection current drive. In DIII-D, greater than 11 MW of neutral beam heating power is applied with the intent of maximizing β N and the noninductive current drive. However, in scenarios with q min >2 that target the typical range of q 95 = 5–7 used in next-step steady-state reactor models, Alfvén eigenmodes cause greater fast-ion transport than classical models predict. This enhanced transport reduces the absorbed neutral beam heating power and current drive and limits the achievable β N . Conversely similar plasmas except with q min just above 1 have approximately classical fast-ion transport. Experiments that take q min >3 plasmas to higher β P with q 95 = 11–12 for testing long pulse operation exhibit regimes of better than expected thermal confinement. Compared to the standard high-q min scenario, the high β P cases have shorter slowing-down time and lower ∇β fast , and this reduces the drive for Alfvénic modes, yielding nearly classical fast-ion transport, high values of normalized confinement, β N , and noninductive current fraction. These results suggest DIII-D might obtain better performance in lower-q 95 , high-q min plasmas using broader neutral beam heating profiles and increased direct electron heating power to lower the drive for Alfvén eigenmodes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Effects of slope steepness and cross-slope wind speed on fire spreading behavior for various vegetation

Wildland fire behavior is significantly influenced by environmental factors such as slope steepness, wind speed, and fuel type. Understanding these interactions is critical for improving predictive models and fire management. This study explores how slope steepness and cross-slope wind speed influence fire spread dynamics in various fuel bed types. Simulations are conducted using a physics-based wildland fire model, HIGRAD/FIRETEC, across six slope angles (0–50 %), four cross-slope wind speeds (4–10 m s –1 ), and three fuel bed types (grass, shrubland, and forest). Representative cases are additionally compared with FARSITE fireline evolution. Fire behavior is categorized into distinct propagation types based on spread characteristics and analyzed. The fire propagation angle, which indicates deviation from the wind direction, generally increases with steeper slopes and decreases with stronger cross-slope winds. Secondary upslope propagation is observed in shrubland under moderate slopes, while secondary downwind propagation occurs in all fuel beds at higher wind speeds. These findings highlight fire spread characteristics that differ from predictions by traditional models like Rothermel’s. By capturing complex propagation patterns and dynamics, this study demonstrates the value of a physics-based, atmosphere-fire coupled model for accurate wildland fire prediction. Incorporating secondary propagations and the influence of fuel bed complexities into predictive models can improve the accuracy of fire spread forecasts, enabling more effective fire management and risk mitigation efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Eight ultra-faint galaxy candidates discovered in year two of the dark energy survey

We report the discovery of eight new ultra-faint dwarf galaxy candidates in the second year of optical imaging data from the Dark Energy Survey (DES). Six of these candidates are detected at high confidence, while two lower-confidence candidates are identified in regions of non-uniform survey coverage. The new stellar systems are found by three independent automated search techniques and are identified as overdensities of stars, consistent with the isochrone and luminosity function of an old and metal-poor simple stellar population. The new systems are faint (M{sub V} > −4.7 mag) and span a range of physical sizes (17 pc < r{sub 1/2} < 181 pc) and heliocentric distances (25 kpc < D{sub ⊙} < 214 kpc). All of the new systems have central surface brightnesses consistent with known ultra-faint dwarf galaxies (μ ≳ 27.5 mag arcsec{sup −2}). Roughly half of the DES candidates are more distant, less luminous, and/or have lower surface brightnesses than previously known Milky Way satellite galaxies. Most of the candidates are found in the southern part of the DES footprint close to the Magellanic Clouds. We find that the DES data alone exclude (p < 10{sup −3}) a spatially isotropic distribution of Milky Way satellites and that the observed distribution can be well, though not uniquely, described by an association between several of the DES satellites and the Magellanic system. Our model predicts that the full sky may hold ∼100 ultra-faint galaxies with physical properties comparable to the DES satellites and that 20%–30% of these would be spatially associated with the Magellanic Clouds.

79 ASTRONOMY AND ASTROPHYSICS↗