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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Robust Estimation of Electron Density From Anatomic Magnetic Resonance Imaging of the Brain Using a Unifying Multi-Atlas Approach

Purpose: To develop a reliable method to estimate electron density based on anatomic magnetic resonance imaging (MRI) of the brain. Methods and Materials: We proposed a unifying multi-atlas approach for electron density estimation based on standard T1- and T2-weighted MRI. First, a composite atlas was constructed through a voxelwise matching process using multiple atlases, with the goal of mitigating effects of inherent anatomic variations between patients. Next we computed for each voxel 2 kinds of conditional probabilities: (1) electron density given its image intensity on T1- and T2-weighted MR images; and (2) electron density given its spatial location in a reference anatomy, obtained by deformable image registration. These were combined into a unifying posterior probability density function using the Bayesian formalism, which provided the optimal estimates for electron density. We evaluated the method on 10 patients using leave-one-patient-out cross-validation. Receiver operating characteristic analyses for detecting different tissue types were performed. Results: The proposed method significantly reduced the errors in electron density estimation, with a mean absolute Hounsfield unit error of 119, compared with 140 and 144 (P<.0001) using conventional T1-weighted intensity and geometry-based approaches, respectively. For detection of bony anatomy, the proposed method achieved an 89% area under the curve, 86% sensitivity, 88% specificity, and 90% accuracy, which improved upon intensity and geometry-based approaches (area under the curve: 79% and 80%, respectively). Conclusion: The proposed multi-atlas approach provides robust electron density estimation and bone detection based on anatomic MRI. If validated on a larger population, our work could enable the use of MRI as a primary modality for radiation treatment planning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

SPRUCE Root Production Assessed with Manual Minirhizotrons Resolved to Plant Functional Type, 2015-2021

This dataset contains raw root length and diameter for individual roots and estimated root population production measurements from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. Measurements started at the beginning of whole ecosystem warming manipulations in 2015 through 2021 (2015-05-26 to 2021-09-01). Root morphology and estimated production were quantified throughout the peat profile with manual minirhizotrons deployed within SPRUCE plots. Images were processed using commercial software to quantify the length and diameter of individual roots. Roots were visually assigned to a plant functional type (PFT) of either (ericaceous) shrub, herb (sedges and Maianthemum trifolium), or tree (Larix laricina, Picea mariana) based on expert opinion. The biomass of individual roots was estimated using PFT-specific allometric equations (Iversen et al., 2018). Production per day was estimated as the length of new roots produced between imaging sessions, divided by the number of days between imaging sessions. These values were placed on a m2 aboveground area basis and scaled to a standard depth of 1m (roots are not evenly distributed with depth, do not interpret value as being on a m3 basis). Maximum and average (weighted by production length) depth of each PFT were also estimated within each minirhizotron tube. Annual production was interpolated as the average of four methods to scale these data (see Weber et al, 2026). Standing crop of roots was estimated for each tube as the maximum visible amount (both length and mass) of roots of that PFT for that year. These data expand the ability of researchers to accurately estimate the belowground dynamics of peatland vegetation, as well as the role that fine roots may play in impacting the fluxes of carbon within peatlands. This dataset contains three data files in comma-separate values (*.csv) format. This dataset contains one data file in comma-separate values (.csv) format. Additional metadata are provided: three data dictionaries and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Short-depth circuits for efficient expectation-value estimation

The evaluation of expectation values Tr[$\rho \mathcal{O}$] for some pure state $\rho$ and Hermitian operator $\mathcal{O}$ is of central importance in a variety of quantum algorithms. Near-optimal techniques have been developed in the past and require a number of measurements N approaching the Heisenberg limit N = O(1/ ε) as a function of target accuracy ε. The use of quantum phase estimation (QPE) requires, however, long circuit depths C = O(1/ ε) making its implementation difficult on near-term noisy devices. The more direct strategy of operator averaging is usually preferred as it can be performed using N = O(1/ε 2 ) measurements and no additional gates aside from those needed for the state preparation. In this work we use a simple but realistic model to describe the bound state of a neutron and a proton (the deuteron) to show that the latter strategy can require an overly large number of measurements in order to achieve a prefixed relative target accuracy ε r . Further, we propose to overcome this problem using a single step of QPE and classical postprocessing. This approach leads to a circuit depth C = O (ε μ ) (with μ ≥ 0) and to a number of measurements N = O (1/ε 2 + ν ) for 0 < ν ≤ 1 and a much smaller prefactor. We provide detailed descriptions of two implementations of our strategy for ν = 1 and ν ≈ 0.5 and derive appropriate conditions that a particular problem instance has to satisfy in order for our method to provide an advantage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Visualization of Current and Mapping of Elements in Quantum Dot Solar Cells

The delicate influence of properties such as high surface state density and organic-inorganic boundaries on the individual quantum dot electronic structure complicates pursuits toward forming quantitative models of quantum dot thin films ab initio. Our report describes the application of electron beam-induced current (EBIC) microscopy to depleted-heterojunction colloidal quantum dot photovoltaics (DH-CQD PVs), a technique which affords one a map of current production within the active layer of a PV device. The effects of QD sample size polydispersity as well as layer thickness in CQD active layers as they pertain to current production within these PVs are imaged and explained. The results from these experiments compare well with previous estimations, and confirm the ability of EBIC to function as a valuable empirical tool for the design and betterment of DH-CQD PVs. Lastly, extensive and unexpected PbS QD penetration into the mesoporous TiO 2 layer is observed through imaging of device cross sections by energy-dispersive X-ray spectroscopy combined with scanning transmission electron microscopy. Finally, the effects of this finding are discussed and corroborated with the EBIC studies on similar devices.

14 SOLAR ENERGY↗
DOE OSTI2020

The Lorentzian inversion formula and the spectrum of the 3d O(2) CFT

We study the spectrum and OPE coefficients of the three-dimensional critical O(2) model, using four-point functions of the leading scalars with charges 0, 1, and 2 ( s , $\phi$, and t ). We obtain numerical predictions for low-twist OPE data in several charge sectors using the extremal functional method. We compare the results to analytical estimates using the Lorentzian inversion formula and a small amount of numerical input. We find agreement between the analytic and numerical predictions. We also give evidence that certain scalar operators lie on double-twist Regge trajectories and obtain estimates for the leading Regge intercepts of the O(2) model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Search for resonances in events with photon and jet final states in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A search for resonances in events with the γ+jet final state has been performed using proton-proton collision data collected at $\sqrt s$ = 13 TeV by the CMS experiment at the LHC. The total data analyzed correspond to an integrated luminosity of 138 fb –1 . Models of excited quarks and quantum black holes are considered. Using a wide-jet reconstruction for the candidate jet, the γ+jet invariant mass spectrum measured in data is examined for the presence of resonances over the standard model continuum background. The background is estimated by fitting this mass distribution with a functional form. The data exhibit no statistically significant deviations from the expected standard model background. Exclusion limits at 95% confidence level on the resonance mass and other parameters are set. Excited light-flavor quarks (excited bottom quarks) are excluded up to a mass of 6.0 (3.8) TeV. Quantum black hole production is excluded for masses up to 7.5 (5.2) TeV in the Arkani-Hamed-Dimopoulos-Dvali (Randall-Sundrum) model. These lower mass bounds are the most stringent to date among those obtained in the γ+jet final state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

The Momentum Distribution of Liquid ⁴He

We report a high-resolution neutron Compton scattering study of liquid ⁴He under milli-Kelvin temperature control. To interpret the scattering data, we performed Quantum Monte Carlo calculations of the atomic momentum distribution and final state effects for the conditions of temperature and density considered in the experiment. There is excellent agreement between the observed scattering and ab initio calculations of its lineshape at all temperatures. We also used model fit functions to obtain from the scattering data empirical estimates of the average atomic kinetic energy and Bose condensate fraction. These quantities are also in excellent agreement with ab initio calculations. We conclude that contemporary Quantum Monte Carlo methods can furnish accurate predictions for the properties of Bose liquids, including the condensate fraction, close to the superfluid transition temperature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

The value of soil respiration measurements for interpreting and modeling terrestrial carbon cycling

A recent acceleration of model-data synthesis activities has leveraged many terrestrial carbon (C) datasets, but utilization of soil respiration (RS) data has not kept pace with other types such as eddy covariance (EC) fluxes and soil C stocks. Here we argue that RS data, including non-continuous measurements from survey sampling campaigns, have unrealized value and should be utilized more extensively and creatively in data synthesis and modeling activities. We identify three major challenges in interpreting RS data, and discuss opportunities to address them. The first challenge is that when RS is compared to ecosystem respiration (RECO) measured from EC towers, it is not uncommon to find substantial mismatch, indicating one or both flux methodologies are unreliable. We argue the most likely cause of mismatch is unreliable EC data, and there is an unrecognized opportunity to utilize RS for EC quality control. The second challenge is that RS integrates belowground heterotrophic (RH) and autotrophic (RA) activity, whereas modelers generally prefer partitioned fluxes, and few models include an explicit RS output. Opportunities exist to use the total RS flux for data assimilation and model benchmarking methods rather than less-certain partitioned fluxes. Pushing for more experiments that not only partition RS but also monitor the age of RA and RH, as well as for the development of belowground RA components in models, would allow for more direct comparison between measured and modeled values. The third challenge is that soil respiration is generally measured at a very different resolution than that needed for comparison to EC or ecosystem- to global-scale models. Measuring soil fluxes with finer spatial resolution and more extensive coverage, and downscaling EC fluxes to match the scale of RS, will improve chamber and tower comparisons. Opportunities also exist to estimate RH at regional scales by implementing decomposition functional types, akin to plant functional types. We conclude by discussing the benefits that wide use of RS data will bring to model development, and database developments that will make RS data more robust, useful, and broadly available to the research community.

carbon cycle↗
DOE OSTI2023

Adaptive sampling quasi-Newton methods for zeroth-order stochastic optimization

Here, we consider unconstrained stochastic optimization problems with no available gradient information. Such problems arise in settings from derivative-free simulation optimization to reinforcement learning. We propose an adaptive sampling quasi-Newton method where we estimate the gradients using finite differences of stochastic function evaluations within a common random number framework. We develop modified versions of a norm test and an inner product quasi-Newton test to control the sample sizes used in the stochastic approximations and provide global convergence results to the neighborhood of a locally optimal solution. We present numerical experiments on simulation optimization problems to illustrate the performance of the proposed algorithm. When compared with classical zeroth-order stochastic gradient methods, we observe that our strategies of adapting the sample sizes significantly improve performance in terms of the number of stochastic function evaluations required.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Sample-based synthesis of two-scale structures with anisotropy

A vast majority of natural or synthetic materials are characterized by their anisotropic properties, such as stiffness. Such anisotropy is effected by the spatial distribution of the fine-scale structure and/or anisotropy of the constituent phases at a finer scale. In design, proper control of the anisotropy may greatly enhance the efficiency and performance of synthesized structures. In this paper, we propose a sample-based two-scale structure synthesis approach that explicitly controls anisotropic effective material properties of the structure on the coarse scale by orienting sampled material neighborhoods at the fine scale. We first characterize the non-uniform orientations distribution of the sample structure by showing that the principal axes of an orthotropic material may be determined by the eigenvalue decomposition of its effective stiffness tensor. Such effective stiffness tensors can be efficiently estimated based on the two-point correlation functions of the fine-scale structures. Then we synthesize the two-scale structure by rotating fine-scale structures from the sample to follow a given target orientation field. Finally, the effectiveness of the proposed approach is demonstrated through examples in both 2D and 3D.

42 ENGINEERING↗
DOE OSTI2015

An improved thermodynamic model for the complexation of trivalent actinides and lanthanide with oxalic acid valid to high ionic strength.

The dissociation constants of oxalic acid (Ox), and the stability constants of Am 3+ , Cm 3+ and Eu 3+ with Ox 2– have been determined at 25 °C, over a range of concentration varying from 0.1 to 6.60 m NaClO4 using potentiometric titration and extraction techniques, respectively. The experimental data support the formation of complexes, M(Ox) n 3 – 2n , where (M = Am 3+ , Cm 3+ and Eu 3+ and n = 1 and 2). The dissociation constant and the stability constant values measured as a function of NaClO 4 concentration were used to estimate the Pitzer parameters for the respective interactions of Am 3+ , Cm 3+ and Eu 3+ with Ox. Furthermore, the stability constants data of Am 3+ –Ox measured in NaClO 4 and in NaCl solutions from the literature were simultaneously fitted in order to refine the existing actinide–oxalate complexation model that can be used universally in the safety assessment of radioactive waste disposal. The thermodynamic stability constant: log β 0 101 = 6.30 ± 0.06 and log β 0 102 = 10.84 ± 0.06 for Am 3+ was obtained by simultaneously fitting data in NaCl and NaClO 4 media. Additionally, log β 0 101 = 6.72 ± 0.08 and log β 0 102 = 11.05 ± 0.09 for the Cm 3+ and log β 0 101 = 6.67 ± 0.08 and log β 0 102 = 11.15 ± 0.09 for the Eu 3+ were calculated by extrapolation of data to zero ionic strength in NaClO 4 medium only. For all stability constants, the Pitzer model gives an excellent representation of the data using interaction parameters β (0) , β (1) , and CΦ determined in this work. The thermodynamic model developed in this work will be useful in accurately modeling the potential solubility of trivalent actinides and early lanthanides to ionic strength of 6.60 m in low temperature environments in the presence of Ox. Furthermore, the work is also applicable to the accurate modeling transport of rare earth elements in various environments under the surface conditions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Latent map Gaussian processes for mixed variable metamodeling

Gaussian processes (GPs) are ubiquitously used in sciences and engineering as metamodels. Standard GPs, however, can only handle numerical or quantitative variables. Here we introduce latent map Gaussian processes (LMGPs) that inherit the attractive properties of GPs and are also applicable to mixed data which have both quantitative and qualitative inputs. The core idea behind LMGPs is to learn a continuous, low-dimensional latent space or manifold which encodes all qualitative inputs. To learn this manifold, we first assign a unique prior vector representation to each combination of qualitative inputs. We then use a low-rank linear map to project these priors on a manifold that characterizes the posterior representations. As the posteriors are quantitative, they can be directly used in any standard correlation function such as the Gaussian or Matern. Hence, the optimal map and the corresponding manifold, along with other hyperparameters of the correlation function, can be systematically learned via maximum likelihood estimation. Through a wide range of analytic and real-world examples, we demonstrate the advantages of LMGPs over state-of-the-art methods in terms of accuracy and versatility. In particular, we show that LMGPs can handle variable-length inputs, have an explainable neural network interpretation, and provide insights into how qualitative inputs affect the response or interact with each other. We also employ LMGPs in Bayesian optimization and illustrate that they can discover optimal compound compositions more efficiently than conventional methods that convert compositions to qualitative variables via manual featurization.

42 ENGINEERING↗
DOE OSTI2022

Predictive process mapping for laser powder bed fusion: A review of existing analytical solutions

One of the main challenges in the laser powder bed fusion (LPBF) process is making dense and defect-free components. These porosity defects are dependent upon the melt pool geometry and the processing conditions. Power-velocity (PV) processing maps can aid in visualizing the effects of LPBF processing variables and mapping different defect regimes such as lack-of-fusion, under-melting, balling, and keyholing. This work presents an assessment of existing analytical equations and models that provide an estimate of the melt pool geometry as a function of material properties. The melt pool equations are then combined with defect criteria to provide a quick approximation of the PV processing maps for a variety of materials. Finally, the predictions of these processing maps are compared with experimental data from the literature. Here, the predictive processing maps can be computed quickly and can be coupled with dimensionless numbers and high-throughput (HT) experiments for validation. The present work provides a boundary framework for designing the optimal processing parameters for new metals and alloys based on existing analytical solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Hydrodynamic and magnetohydrodynamic simulations of wire turbulence

In this paper, we report on simulations of laboratory experiments in which magnetized supersonic flows are driven through a wire mesh. The goal of the study was to investigate the ability of such a configuration to generate supersonic, MHD turbulence. We first report on the morphological structures that develop in both magnetized and non-magnetized cases. We then analyze the flow using a variety of statistical measures, including power spectra and probability distribution functions of the density. Using these results we estimate the sonic mach number in the flows downstream of the wire mesh. Finally, we find the initially hypersonic (M s = 20) planar shock through the wire mesh does lead to downstream turbulent conditions. However, in both magnetized and non-magnetized cases, the resultant turbulence was marginally supersonic to transonic (M s ~1), and highly anisotropic in structure.

(Magnetohydrodynamics) MHD↗
DOE OSTI2017

Error correction in multi-fidelity molecular dynamics simulations using functional uncertainty quantification

We use functional, Fréchet, derivatives to quantify how thermodynamic outputs of a molecular dynamics (MD) simulation depend on the potential used to compute atomic interactions. Our approach quantifies the sensitivity of the quantities of interest with respect to the input functions as opposed to its parameters as is done in typical uncertainty quantification methods. We show that the functional sensitivity of the average potential energy and pressure in isothermal, isochoric MD simulations using Lennard–Jones two-body interactions can be used to accurately predict those properties for other interatomic potentials (with different functional forms) without re-running the simulations. This is demonstrated under three different thermodynamic conditions, namely a crystal at room temperature, a liquid at ambient pressure, and a high pressure liquid. The method provides accurate predictions as long as the change in potential can be reasonably described to first order and does not significantly affect the region in phase space explored by the simulation. The functional uncertainty quantification approach can be used to estimate the uncertainties associated with constitutive models used in the simulation and to correct predictions if a more accurate representation becomes available.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Laser Doppler vibrometry for piezoelectric coefficient ($d_{33}$) measurements in irradiated aluminum nitride

Sensors used for experiments in advanced reactors must survive in harsh environments. Few material systems can be used to construct sensors viable for extreme conditions. Aluminum nitride (AlN) is one such material because it has high thermal stability and radiation resistance and sustains good piezoelectric and dielectric properties at high temperatures. In this work, the piezoelectric coefficient $d_{33}$ of the AlN single-crystal with thermal and irradiation damage was investigated using an indirect method with a laser Doppler vibrometer (LDV). Surface electrodes were deposited on the AlN samples, and the vibration response of the samples to an applied voltage was monitored using the LDV as a function of the excitation frequency. The $d_{33}$ estimation was based on the excitation voltage and the thickness-mode displacement extracted from the LDV measurements. Further, six AlN substrates were irradiated with 8 MeV Al 2+ at three fluences (10 15 , 10 16 , and 10 17 ions/cm 2 ) and two temperatures (300 °C and 500 °C). The $d_{33}$ for the six irradiated samples and one pristine sample were measured, and the measurement uncertainty was estimated based on five repeated tests. All samples were also measured by a commercial piezometer for comparison. The experimental results demonstrate that the piezoelectric coefficients obtained by LDV were about 0.8–1.16 pm/V lower than those obtained by the piezometer. With the compensation of the clamping effect, the corrected LDV values are similar to the piezometer results. Both show similar trends in all samples, which validates the feasibility of the proposed method for $d_{33}$ measurement. Based on the LDV results, the irradiated samples show a 12%–22% decrease in $d_{33}$ compared with the pristine samples. The samples irradiated under the same fluence at a higher temperature (500 °C) demonstrated a lower $d_{33}$ than those at 300 °C. The effect of the retro-reflective tape, sample temperature, and sample size on the $d_{33}$ measurement were also studied.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Thermal conductivity of self-ion irradiated nanocrystalline zirconium thin films

Thermomechanical stability and high thermal conductivity are important for nuclear cladding material performance and reliability, which degrade over time under irradiation. The literature suggests nanocrystalline materials as radiation tolerant, but little or no evidence is present from thermal transport perspective. In this study, we irradiated 10 nm grain size zirconium thin films with 800 keV Zr + beam from a 6 MV HVE Tandem accelerator to achieve various doses of 3 × 10 10 to 3.26 × 10 14 ions/cm 2 , corresponding to displacement per atom (dpa) of 2.1 × 10 –4 to 2.28. Transmission electron microscopy showed significant grain growth, texture evolution and oxidation in addition to the creation of displacement defects due to the irradiation. The specimens were co-fabricated with micro-heaters to establish thermal gradients that were mapped using infrared thermometry. An energy balance approach was used to estimate the thermal conductivity of the specimens, as function of irradiation dosage. As a result, up to 32% reduction of thermal conductivity was measured for the sample exposed to a dose of 2.1 dpa (3 × 10 14 ions/cm 2 ).

36 MATERIALS SCIENCE↗