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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluation of Nominal Energy Storage at Existing Hydropower Reservoirs in the US

Long-term planning and operation of hydropower reservoirs require an understanding of both water and energy storage. As energy storage needs of the evolving grid increase, we must account for the water and energy storage potential of these reservoirs. Given the limitations of current data on existing hydropower, we compile statistics related to storage volume and hydraulic head from publicly available data sets and examine differences in descriptions of US hydropower storage. Assembled characteristics are used to calculate nominal energy storage capacity, a simple measure of potential to generate power from a given volume of water, not factoring in detailed constraints. Inventory-based estimates of energy storage are calculated at 2,075 dams, which helps put the potential for US hydropower to support energy storage in context with similar evaluations in other regions and with other energy storage technologies. The national energy storage capacity ranges between 34.5 and 45.1 TWh depending on the information used, with 52% of energy storage located at the 10 largest reservoirs in the US. Energy storage capacities are also calculated at 236 dams with historical volume and elevation data. Finally, reservoir inflows provide context for the storage volumes and sensitivities to hydrologic variability. Larger reservoirs with greater storage volume to inflow ratios are concentrated in the Western US, but the majority of hydropower reservoirs store less than the annual inflow. We address several infrastructure and water resource informatics challenges and highlight remaining issues, including representing seasonal or shorter variability in water volumes and representing connected hydropower facilities.

13 HYDRO ENERGY↗
DOE OSTI2022

Dynamic signal recovery in distribution grids using compressive lossy measurements

Distribution system state estimation requires reliable aggregation of the measured data. However, the large volume of the measured data imposes a significant stress on the underlying communication infrastructure. With the challenges associated with measurement availability, current distribution systems are typically unobservable. To cope with the unobservability issue, compressive sensing theory allows us to recover system state information from a small number of measurements provided the states of the distribution system exhibit sparsity. In this paper, we evaluate the robustness of an updated Kalman filtered modified compressive sensing (KF-ModCS) technique that dynamically estimates the grid states using a small fraction of measured data. In practice, measurements used for sparsity based state estimation may also be intermittent due to communication network induced losses. Further, to understand the effect of packet losses on KF-ModCS, we provide an upper bound for the expected variances of the state estimation error for a given rate of information loss. This upper bound is further improved if the support set of the sparse signal that characterizes the state dynamics does not change over time and/or the reduced model is observable. Simulations based on two practical data sets collected from actual customers in a distribution grid validate the theoretical results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Number of holes contained within the Fermi surface volume in underdoped high-temperature superconductors

Here, we provide a potential solution to the longstanding problem relating Fermi surface reconstruction to the number of holes contained within the Fermi surface volume in underdoped high T c superconductors. On considering uniaxial and biaxial charge-density wave order, we show that there exists a relationship between the ordering wave vector, the hole doping, and the cross-sectional area of the reconstructed Fermi surface whose precise form depends on the volume of the starting Fermi surface. We consider a “large” starting Fermi surface comprising 1+p hole carriers, as predicted by band structure calculations, and a “small” starting Fermi surface comprising p hole carriers, as proposed in models in which the Coulomb repulsion remains the dominant energy. Using the reconstructed Fermi surface cross-sectional area obtained in quantum oscillation experiments in YBa 2 Cu 3 O 6+x and HgBa 2 CuO 4+x and the established methods for estimating the chemical hole doping, we find the ordering vectors obtained from x-ray scattering measurements to show a close correspondence with those expected for the small starting Fermi surface. We therefore show the quantum oscillation frequency and charge-density wave vectors provide accurate estimates for the number of holes contributing to the Fermi surface volume in the pseudogap regime.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Predicting Biological Cleanliness: An Empirical Bayes Approach for Spacecraft Bioburden Accounting

To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Bayesian Framework for Bioburden Density Estimation in Planetary Protection

To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SU-F-R-44: Modeling Lung SBRT Tumor Response Using Bayesian Network Averaging

Purpose: The prediction of tumor control after a patient receives lung SBRT (stereotactic body radiation therapy) has proven to be challenging, due to the complex interactions between an individual’s biology and dose-volume metrics. Many of these variables have predictive power when combined, a feature that we exploit using a graph modeling approach based on Bayesian networks. This provides a probabilistic framework that allows for accurate and visually intuitive predictive modeling. The aim of this study is to uncover possible interactions between an individual patient’s characteristics and generate a robust model capable of predicting said patient’s treatment outcome. Methods: We investigated a cohort of 32 prospective patients from multiple institutions whom had received curative SBRT to the lung. The number of patients exhibiting tumor failure was observed to be 7 (event rate of 22%). The serum concentration of 5 biomarkers previously associated with NSCLC (non-small cell lung cancer) was measured pre-treatment. A total of 21 variables were analyzed including: dose-volume metrics with BED (biologically effective dose) correction and clinical variables. A Markov Chain Monte Carlo technique estimated the posterior probability distribution of the potential graphical structures. The probability of tumor failure was then estimated by averaging the top 100 graphs and applying Baye’s rule. Results: The optimal Bayesian model generated throughout this study incorporated the PTV volume, the serum concentration of the biomarker EGFR (epidermal growth factor receptor) and prescription BED. This predictive model recorded an area under the receiver operating characteristic curve of 0.94(1), providing better performance compared to competing methods in other literature. Conclusion: The use of biomarkers in conjunction with dose-volume metrics allows for the generation of a robust predictive model. The preliminary results of this report demonstrate that it is possible to accurately model the prognosis of an individual lung SBRT patient’s treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-65: Motion Difference Between the Pancreas and Nearby Veins for Pancreas Motion Monitoring Using Ultrasound During Radiation Therapy

Purpose: As it is generally difficult to outline the pancreas on an ultrasound b-mode image, visualized structures such as the portal or the splenic veins are assumed to have the same motion as the pancreas. These structures can be used as a surrogate for monitoring pancreas motion during radiation therapy (RT) delivery using ultrasound. To verify this assumption, we studied the motion difference between the head of the pancreas, the portal vein, the tail of the pancreas, and splenic vein. Methods: 4DCT data acquired during RT simulation were analyzed for a total of 5 randomly selected patients with pancreatic cancer. The data was sorted into 10 respiratory phases from 0% to 90% (0%: end of the inspiration, 50%: end of expiration) . The head of the pancreas (HP), tail of the pancreas (TP), portal vein (PV), and splenic vein (SV) were contoured on all 10 phases. The volume change and motion were measured in the left-right (LR), anterior-superior (AP), and superior-inferior (SI) directions. Results: The volume change for all patients/phases were: 1.2 ± 3% for HP, 0.78 ± 1.6% for PV, 2.5 ± 2.9% for TP, and 0.53 ± 2.1% for SV. Motion for each structure was estimated from the centroid displacements due to the uniformity of the structures and the small volume change. The measured motion between HP and PV was: LR: 0.1 ± 0.17 mm, AP: 0.04 ± 0.1 mm, SI: 0.17 ± 0.16 mm and between TP and the PV was: LR: 0.05 ± 0.3 mm, AP: 0.1 ± 0.4 mm, SI: 0.01 ± 0.022 mm. Conclusion: There are small motion differences between the portal vein and the head of the pancreas, and the splenic vein and the tail of the pancreas. This suggests the feasibility of utilizing these features for monitoring the pancreas motion during radiation therapy.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2007

Coupled Groups of g-Modes in a Sun with Mixed Core

Groups of linear g-modes can sum to create long-lived nonlinear oscillations in small "hot volumes" very deep in the Sun that help drive the modes. In these volumes (dimensions -10 Mm), the time average rate of He-3 burning doubles as temperature fluctuations exceed 10% and rises by an order of magnitude for fluctuations of 25%. To be consistent with locally large motions, we impose a mixed shell on an otherwise standard solar model before computing g-mode solutions. Mixing in the assumed shell r = (0.10+/-0.03) R(sub sun) is rapid (<<10(exp 6) yr) with slower mixing somewhat beyond. If l is the principal spherical harmonic index, a set of g-modes for any single l less than or equal to 15 with five consecutive radial harmonics can be excited with nearly linear thermal amplitudes, A(sub T) less than or equal to 0.053, throughout the star and a fractional temperature fluctuation in its hot volume of (Delta)T/T less than or equal to 0.18. These thresholds for excitation will become smaller when sets for several values of l are computed simultaneously. There is some evidence for the rotation of g-mode sets in the long solar activity record and g-mode upward wave flux has been suggested to explain the 1.3 yr reversing flows tentatively detected below the Sun's convective envelope (CE). The large local amplitudes needed for excitation implies that g-modes may transport a non-negligible fraction of the solar luminosity, yet their near linear amplitudes outside the hot volume suggests amplitudes over most of the solar surface that would be barely detectable for l > 3. A formalism is presented for summing the g-modes and estimating growth rates under the approximation that modes are strictly linear except in a hot volume which holds only a few percent of mode kinetic energy. Finally over the range 2 less than or equal to l less than or equal to 30, we summed all zonal harmonics, m, for a given l and computed the relative angular orientations that would release the most nuclear energy. This should be close to the physically preferred angular state of such a family and a few examples were displayed.

Wolff, Charles L.↗
DOE OSTI2016

Quantifying the Effect of Lidar Turbulence Error on Wind Power Prediction

Currently, cup anemometers on meteorological towers are used to measure wind speeds and turbulence intensity to make decisions about wind turbine class and site suitability; however, as modern turbine hub heights increase and wind energy expands to complex and remote sites, it becomes more difficult and costly to install meteorological towers at potential sites. As a result, remote-sensing devices (e.g., lidars) are now commonly used by wind farm managers and researchers to estimate the flow field at heights spanned by a turbine. Although lidars can accurately estimate mean wind speeds and wind directions, there is still a large amount of uncertainty surrounding the measurement of turbulence using these devices. Errors in lidar turbulence estimates are caused by a variety of factors, including instrument noise, volume averaging, and variance contamination, in which the magnitude of these factors is highly dependent on measurement height and atmospheric stability. As turbulence has a large impact on wind power production, errors in turbulence measurements will translate into errors in wind power prediction. The impact of using lidars rather than cup anemometers for wind power prediction must be understood if lidars are to be considered a viable alternative to cup anemometers.In this poster, the sensitivity of power prediction error to typical lidar turbulence measurement errors is assessed. Turbulence estimates from a vertically profiling WINDCUBE v2 lidar are compared to high-resolution sonic anemometer measurements at field sites in Oklahoma and Colorado to determine the degree of lidar turbulence error that can be expected under different atmospheric conditions. These errors are then incorporated into a power prediction model to estimate the sensitivity of power prediction error to turbulence measurement error. Power prediction models, including the standard binning method and a random forest method, were developed using data from the aeroelastic simulator FAST for a 1.5 MW turbine. The impact of lidar turbulence error on the predicted power from these different models is examined to determine the degree of turbulence measurement accuracy needed for accurate power prediction.

17 WIND ENERGY↗
NASA NTRS2000

Attenuation of Weather Radar Signals Due to Wetting of the Radome by Rainwater or Incomplete Filling of the Beam Volume

A search of scientific literature, both printed and electronic, was undertaken to provide quantitative estimates of attenuation effects of rainfall on weather radar radomes. The emphasis was on C-band (5 cm) and S-Band (10 cm) wavelengths. An empirical model was developed to estimate two-way wet radome losses as a function of frequency and rainfall rate for both standard and hydrophobic radomes. The model fits most of the published data within +/- 1 dB at both target wavelengths for rain rates from less than ten to more than 200 mm/hr. Rainfall attenuation effects remain under 1 dB at both frequencies regardless of radome type for rainfall rates up to 10 mm/hr. S-Band losses with a hydrophobic radome such as that on the WSR-88D remain under 1 dB up to 100 mm/hr. C-Band losses on standard radomes such as that on the Patrick AFB (Air Force Base) WSR-74C can reach as much as 5 dB at 50 mm/hr. In addition, calculations were performed to determine the reduction in effective reflectivity, Z, when a radar target is smaller than the sampling volume of the radar. Results are presented for both the Patrick Air Force Base WSR-74C and the WSR-88D as a function of target size and range.

Merceret, Francis J.↗
DOE OSTI2024

Cost and Performance Estimates for State-of-the-Art and Advanced 1×1 H-Class Natural Gas-Fired Power Plants

As an extension of NETL's Fossil Energy Baseline for Electricity Generating Units Volume 1: Coal and Natural Gas to Electricity (FEB Rev 4a, this study develops cost and performance estimates for analogous NGCC cases using a state-of-the-art 2023 vintage H-Class CT in a 1×1 configuration, where a single combustion turbine and heat recovery steam generator are coupled to a single steam turbine on a common shaft. These 1×1 H-Class cases are used to develop cost and performance estimates of X-Class 1×1 NGCC cases with advanced performance characteristics, analogous to NETL’s cost and performance projections report.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1972

Analysis of space tug operating techniques (study 2.4). Volume 1: Executive summary

The costs of tug refurbishment were studied, using existing cost estimating relationships, to establish the cost of maintaining the reusable third stage of the space transportation system. Refurbishment operations sheets which describe the actual tasks that are necessary to keep the equipment functioning properly were used along with refurbishment operations sheets which contain all of the pertinent descriptive information for each of the major vehicle areas. Tug refurbishment costs per mission are tabulated.

Source record↗
NASA NTRS1972

GEODYN programmers guide, volume 2, part 1

A guide to the GEODYN Program is presented. The program estimates orbit and geodetic parameters. It possesses the capability to estimate that set of orbital elements, station positions, measurement biases, and a set of force model parameters such that the orbital tracking data from multiple arcs of multiple satellites best fit the entire set of estimated parameters. GEODYN consists of 113 different program segments, including the main program, subroutines, functions, and block data routines. All are in G or H level FORTRAN and are currently operational on GSFC's IBM 360/95 and IBM 360/91.

Mullins, N. E.↗
NASA NTRS1993

An alternative model for estimating liquid diffusion coefficients requiring no viscosity data

An equation, based on the free volume of a liquid solvent, was derived via dimensional analysis, to predict binary diffusion coefficients. The equation assumed that interaction between the solute and liquid solvent molecules followed a Lennard-Jones potential. The equation was compared to other diffusivity equations and was found to give good results over the temperature range examined.

Morales, Wilfredo↗
DOE OSTI2014

Hunting the most distant stars in the Milky Way: methods and initial results

We present a new catalog of 404 M giant candidates found in the UKIRT Infrared Deep Sky Survey (UKIDSS). The 2400 deg{sup 2} available in the UKIDSS Large Area Survey Data Release 8 resolve M giants through a volume four times larger than that of the entire Two Micron All Sky Survey. Combining near-infrared photometry with optical photometry and proper motions from the Sloan Digital Sky Survey yields an M giant candidate catalog with less M dwarf and quasar contamination than previous searches for similarly distant M giants. Extensive follow-up spectroscopy of this sample will yield the first map of our Galaxy's outermost reaches over a large area of sky. Our initial spectroscopic follow-up of ∼30 bright candidates yielded the positive identification of five M giants at distances ∼20-90 kpc. Each of these confirmed M giants have positions and velocities consistent with the Sagittarius stream. The fainter M giant candidates in our sample have estimated photometric distances ∼200 kpc (assuming [Fe/H] = 0.0), but require further spectroscopic verification. The photometric distance estimates extend beyond the Milky Way's virial radius, and increase by ∼50% for each 0.5 dex decrease in assumed [Fe/H]. Given the number of M giant candidates, initial selection efficiency, and volume surveyed, we loosely estimate that at least one additional Sagittarius-like accretion event could have contributed to the hierarchical build-up of the Milky Way's outer halo.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1984

Thunderstorm cloud height-rainfall rate relations for use with satellite rainfall estimation techniques

Observational studies of thunderstorm cloud height-rainfall rate and cloud height-volume rainfall rate relations are reviewed with significant variations being noted among climatological regimes. Analysis of the Florida (summer) and Oklahoma (spring) relations are made using a one-dimensional cloud model to ascertain the important factors in determining the individual cloud-rain relations and the differences between the two regimes. In general, the observed relations are well simulated by the model-based calculations. The generally lower predicted rain rates in Oklahoma (as compared to Florida) result from lower precipitation efficiencies which are due to a combination of larger entrainment (related to larger vertical wind shear) and drier environment. The generally steeper slope of the Oklahoma rain rate height curves is shown to be due to a stronger variation in maximum vertical velocity with cloud top height, which, in turn, is related to the greater static stability in the range of cloud tops. The impact of the regime-to-regime variations on empirical rain estimation schemes based on satellite-observed cloud height or cloud temperature information is discussed and a rain estimation approach based on model-generated cloud-rain relations is outlined.

Adler, R. F.↗