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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The GREEN ‘omics of Nutrient Feedbacks to Soil Warming

The GREEN ‘omics of Nutrient Feedbacks in Soil project advanced the DOE Biological and Environmental Research (BER) mission by developing and applying isotope-enabled ’omics tools to understand how soil microbes regulate carbon and nutrient cycling. Guided by the Growth Rate, growth Efficiency, and stoichiometry of Essential Nutrients (GREEN ’omics) framework, the project aimed to build a predictive, systems-level understanding of microbial traits that control ecosystem biogeochemistry. In a collaboration among Northern Arizona University (lead), West Virginia University, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory, we combined quantitative stable isotope probing (qSIP), Chip-SIP, NanoSIMS, and genome-resolved metagenomics across long-term experiments in Arctic, boreal, temperate, and tropical ecosystems. The project produced three key outcomes: 1) We showed that community-weighted temperature sensitivities of bacterial growth (Q10) can predict ecosystem-scale soil respiration responses across diverse soils. 2) We provided the first in situ evidence for density-dependent population dynamics in soil bacteria and demonstrated that nutrient additions intensify competition, concentrating carbon use into fewer taxa. 3) We improved and extended isotope-enabled ’omics methods by quantifying qSIP measurement error to guide experimental design and coupling SIP with genome-resolved metagenomics to reveal cross-kingdom interactions among bacteria, fungi, and viruses. Together, these results show that a small number of microbial traits and taxa exert disproportionate control over soil carbon and nutrient cycling, providing critical data and methods to improve representation of microbial processes in Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Fermilab PIP-II Master Oscillator and Precision Reference Line Design and Construction

The phase averaging reference line system pro- vides the RF phase reference, LO and clock sig- nals to the LLRF and other accelerator sub- systems. The PIP-II linac has RF systems at three frequencies – 162.5 MHz, 325 MHz and 650 MHz. A temperature-stabilized, low-phase- noise oscillator is used as the master oscil- lator. Phase reference signals at 162.5 MHz, 325 MHz, and 650 MHz, along with LO signals at 182.5 MHz, 345 MHz, 670 MHz and LLRF clocks at 1320 MHz and 1300 MHz, are generated in temperature-controlled RF modules at each fre- quency section. A phase reference from each module travels to the next section, where it is doubled to produce required frequencies. The reference also travels alongside the accelerating cavities in the tunnel, allowing cavity probe and reference cables to temperature track and reduce measurement errors from temperature changes or phase drift.

Syed, Ahmed [Fermilab]↗
DOE OSTI2026

Two-Way Coupled CFD/DEM Simulation of Electromagnetic Heating in a Fluidized Bed Reactor

A set of tools has been developed to couple a multiphase reacting computational fluid dynamics solver (MFIX) with two computational electromagnetic solvers (COMSOL and Elmer). In contrast to several recent investigations, which calculate a single static EM field prior to the CFD calculation, in the present work the electromagnetic field is periodically updated during the simulation. This enables the EM field and associated EM heating predictions to reflect the effects of evolving material properties (temperature, composition, size etc.) and the evolving distribution of material in the system. The present work uses effective medium theory (EMT) for the electromagnetic field calculations since the goal is to apply the tool for industrial scale reacting systems. Predictions using MFIX/COMSOL and MFIX/Elmer are compared to in bed thermocouple measurements from a fluidized bed experiment and recent simulation predictions and recent experiments performed at NETL. The NETL experiments also include packed bed operating conditions. Coupled MFIX/COMSOL simulations at these conditions are compared with similar simulations using only COMSOL to measure errors due to the solver coupling approach.

CFD↗
DOE OSTI2022

Scalable deep learning for watershed model calibration

Watershed models such as the Soil and Water Assessment Tool (SWAT) consist of high-dimensional physical and empirical parameters. These parameters often need to be estimated/calibrated through inverse modeling to produce reliable predictions on hydrological fluxes and states. Existing parameter estimation methods can be time consuming, inefficient, and computationally expensive for high-dimensional problems. In this paper, we present an accurate and robust method to calibrate the SWAT model (i.e., 20 parameters) using scalable deep learning (DL). We developed inverse models based on convolutional neural networks (CNN) to assimilate observed streamflow data and estimate the SWAT model parameters. Scalable hyperparameter tuning is performed using high-performance computing resources to identify the top 50 optimal neural network architectures. We used ensemble SWAT simulations to train, validate, and test the CNN models. We estimated the parameters of the SWAT model using observed streamflow data and assessed the impact of measurement errors on SWAT model calibration. We tested and validated the proposed scalable DL methodology on the American River Watershed, located in the Pacific Northwest-based Yakima River basin. Our results show that the CNN-based calibration is better than two popular parameter estimation methods (i.e., the generalized likelihood uncertainty estimation [GLUE] and the dynamically dimensioned search [DDS], which is a global optimization algorithm). For the set of parameters that are sensitive to the observations, our proposed method yields narrower ranges than the GLUE method but broader ranges than values produced using the DDS method within the sampling range even under high relative observational errors. The SWAT model calibration performance using the CNNs, GLUE, and DDS methods are compared using R 2 and a set of efficiency metrics, including Nash-Sutcliffe, logarithmic Nash-Sutcliffe, Kling-Gupta, modified Kling-Gupta, and non-parametric Kling-Gupta scores, computed on the observed and simulated watershed responses. The best CNN-based calibrated set has scores of 0.71, 0.75, 0.85, 0.85, 0.86, and 0.91. The best DDS-based calibrated set has scores of 0.62, 0.69, 0.8, 0.77, 0.79, and 0.82. The best GLUE-based calibrated set has scores of 0.56, 0.58, 0.71, 0.7, 0.71, and 0.8. The scores above show that the CNN-based calibration leads to more accurate low and high streamflow predictions than the GLUE and DDS sets. Our research demonstrates that the proposed method has high potential to improve our current practice in calibrating large-scale integrated hydrologic models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

An Extreme-precision Radial-velocity Pipeline: First Radial Velocities from EXPRES

The EXtreme-PREcision Spectrograph (EXPRES) is an environmentally stabilized, fiber-fed, R = 137,500, optical spectrograph. It was recently commissioned at the 4.3 m Lowell Discovery Telescope near Flagstaff, Arizona. The spectrograph was designed with a target radial-velocity (RV) precision of 30 cm s{sup −1}. In addition to instrumental innovations, the EXPRES pipeline, presented here, is the first on-sky, optical, fiber-fed spectrograph to employ many novel techniques—including an “extended flat” fiber used for wavelength-dependent quantum efficiency characterization of the CCD, a flat-relative optimal extraction algorithm, chromatic barycentric corrections, chromatic calibration offsets, and an ultra-precise laser frequency comb for wavelength calibration. We describe the reduction, calibration, and RV analysis pipeline used for EXPRES and present an example of our current sub-meter-per-second RV measurement precision, which reaches a formal, single-measurement error of 0.3 m s{sup −1} for an observation with a per-pixel signal-to-noise ratio of 250. These velocities yield an orbital solution on the known exoplanet host 51 Peg that matches literature values with a residual rms of 0.895 m s{sup −1}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Modeling Stochastic Variability in Multiband Time-series Data

In preparation for the era of time-domain astronomy with upcoming large-scale surveys, we propose a state-space representation of a multivariate damped random walk process as a tool to analyze irregularly-spaced multifilter light curves with heteroscedastic measurement errors. We adopt a computationally efficient and scalable Kalman filtering approach to evaluate the likelihood function, leading to maximum O(k 3 n) complexity, where k is the number of available bands and n is the number of unique observation times across the k bands. This is a significant computational advantage over a commonly used univariate Gaussian process that can stack up all multiband light curves in one vector with maximum O(k 3 n 3 ) complexity. Using such efficient likelihood computation, we provide both maximum likelihood estimates and Bayesian posterior samples of the model parameters. Three numerical illustrations are presented: (i) analyzing simulated five-band light curves for a comparison with independent single-band fits; (ii) analyzing five-band light curves of a quasar obtained from the Sloan Digital Sky Survey Stripe 82 to estimate short-term variability and timescale; (iii) analyzing gravitationally lensed g- and r-band light curves of Q0957+561 to infer the time delay. Two R packages, Rdrw and timedelay, are publicly available to fit the proposed models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Chemical Cartography with APOGEE: Mapping Disk Populations with a 2-process Model and Residual Abundances

We apply a novel statistical analysis to measurements of 16 elemental abundances in 34,410 Milky Way disk stars from the final data release (DR17) of APOGEE-2. Building on recent work, we fit median abundance ratio trends [X/Mg] versus [Mg/H] with a 2-process model, which decomposes abundance patterns into a "prompt" component tracing core-collapse supernovae and a "delayed" component tracing Type Ia supernovae. For each sample star, we fit the amplitudes of these two components, then compute the residuals Δ[X/H] from this two-parameter fit. The rms residuals range from ~0.01–0.03 dex for the most precisely measured APOGEE abundances to ~0.1 dex for Na, V, and Ce. The correlations of residuals reveal a complex underlying structure, including a correlated element group comprised of Ca, Na, Al, K, Cr, and Ce and a separate group comprised of Ni, V, Mn, and Co. Selecting stars poorly fit by the 2-process model reveals a rich variety of physical outliers and sometimes subtle measurement errors. Residual abundances allow for the comparison of populations controlled for differences in metallicity and [α/Fe]. Relative to the main disk (R = 3–13 kpc), we find nearly identical abundance patterns in the outer disk (R = 15–17 kpc), 0.05–0.2 dex depressions of multiple elements in LMC and Gaia Sausage/Enceladus stars, and wild deviations (0.4–1 dex) of multiple elements in ω Cen. The residual abundance analysis opens new opportunities for discovering chemically distinctive stars and stellar populations, for empirically constraining nucleosynthetic yields, and for testing chemical evolution models that include stochasticity in the production and redistribution of elements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.

The remoteness and extreme conditions of the Arctic make it a very difficult environment to investigate. In these polar regions covered by sea ice, the wind is relatively strong due to the absence of obstructions and redistributes a large part of the deposited snow mass, which complicates estimates for precipitation hardly distinguishable from blowing or drifting snow. Moreover, the snow mass balance in the sea ice system is still poorly understood, notably due to the complex structure of its surface. Quantitatively assessing the snow distribution on sea ice and its connection to the sea ice surface features is an important step to remove the snow mass balance uncertainties (i.e., snow transport contribution) in the Arctic environment. In this work we introduce snowBedFoam 1.0., a physics-based snow transport model implemented in the open-source fluid dynamics software OpenFOAM. We combine the numerical simulations with terrestrial laser scan observations of surface dynamics to simulate snow deposition in a MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate) sea ice domain with a complicated structure typical for pressure ridges. The results demonstrate that a large fraction of snow accumulates in their vicinity, which compares favorably against scanner measurements. However, the approximations imposed by the numerical framework, together with potential measurement errors (precipitation), give rise to quantitative inaccuracies, which should be addressed in future work. The modeling of snow distribution on sea ice should help to better constrain precipitation estimates and more generally assess and predict snow and ice dynamics in the Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Quantifying experimental edge plasma evolution via multidimensional adaptive Gaussian process regression

The edge density and temperature of tokamak plasmas are strongly correlated with energy and particle confinement and their quantification is fundamental to understanding edge dynamics. These quantities exhibit behaviours ranging from sharp plasma gradients and fast transient phenomena (e.g. transitions between low and high confinement regimes) to nominal stationary phases. Analysis of experimental edge measurements therefore require robust fitting techniques to capture potentially stiff spatiotemporal evolution. Additionally, fusion plasma diagnostics inevitably involve measurement errors and data analysis requires a statistical framework to accurately quantify uncertainties. This paper outlines a generalized multidimensional adaptive Gaussian process routine capable of automatically handling noisy data and spatiotemporal correlations. We focus on the edge-pedestal region in order to underline advancements in quantifying time-dependent plasma profiles including transport barrier formation on the Alcator C-Mod tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1967

Metal flame spray coating protects electrical cables in extreme environment

Metal flame spray coating prevents EMF measurement error in sheathed instrumentation cables which are externally attached to cylinders which were cooled on the inside, but exposed to gamma radiation on the outside. The coating provides a thermoconductive path for radiation induced high temperatures within the cables.

Brady, R. D.↗
NASA NTRS1968

Mm-wave power meter mount

E-band thermistor mount and a technique for adjusting a temperature compensating thermistor to provide an electrically balanced bridge are used for measuring RF power in the mm-wavelength. The mount is relatively insensitive to temperature effects that cause measurement errors in single ended circuits.

Mullen, D. L.↗
NASA NTRS1968

Computer graphics data conditioning

Graphics data conditioning program expedites engineering analysis of flight data and ensures timely correction of measurement errors. By adding interactive computer graphic displays to existing data conditioning programs, computational results are immediately visible, enabling on-line intervention and control of computer processing.

Hagenau, K. H.↗
NASA NTRS1955

Transonic Free-Flight Investigation of the Longitudinal Aerodynamic Characteristics of a 1/10-Scale Steel-Wing Model of the Northrop MX-775A Missile with Leading-Edge Extensions, Inboard Trailing-Edge Flaps, and a Speed Brake on the Vertical Tail

Results are presented of a free-flight investigation between Mach numbers of 0.7 to 1.3 and Reynolds numbers of 3.1 x 10(exp 6) to 7.0 x 10(exp 6) to determine the longitudinal aerodynamic characteristics of the Northrop MX-775A missile. This missile has a weng, body, and vertical tail, but has no horizontal tail. The basic wing plan form has an aspect ratio of 5.5, 45 deg of sweepback of the 0.406 streamwise chord line, and a taper ratio of 0.4. A 1/10-scale steel-wing model of the missile was flown with modifications to the basic wing plan form consisting of leading-edge chord-extensions deflected 7 deg downward together with the forward 15 percent of the wing chord, and inboard trailing-edge flaps deflected 5 deg downward. In addition, the model had a static-pressure tube mounted at the tip of the vertical tail for position-error measurements and had a speed brake also mounted on the vertical tail to trim the model to positive lift coefficients and to permit determination of the trim and drag effectiveness of the brake. The data are uncorrected for the effects of wing elasticity, but experimental wing influence coefficients are presented.

Arbic, R. G.↗
NASA NTRS1971

Instrument accurately measures stress loads in threaded bolts

Interferometric instrument response is linearly related to axial tensile stresses, and, under idealized conditions, measurement errors are within approximately plus or minus 1 percent. Ultimate accuracy of instrument depends on a number of variables, such as bolt material, dimensions, and geometry and uniformity of stresses and temperature.

Rollins, F. R., Jr.↗