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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Estimating the Efficiency of Phosphopeptide Identification by Tandem Mass Spectrometry

Mass spectrometry has played a significant role in the identification of unknown phosphoproteins and sites of phosphorylation in biological samples. Analyses of protein phosphorylation, particularly large scale phosphoproteomic experiments, have recently been enhanced by efficient enrichment, fast and accurate instrumentation, and better software, but challenges remain because of the low stoichiometry of phosphorylation and poor phosphopeptide ionization efficiency and fragmentation due to neutral loss. Phosphoproteomics has become an important dimension in systems biology studies, and it is essential to have efficient analytical tools to cover a broad range of signaling events. To evaluate current mass spectrometric performance, we present here a novel method to estimate the efficiency of phosphopeptide identification by tandem mass spectrometry. Phosphopeptides were directly isolated from whole plant cell extracts, dephosphorylated, and then incubated with one of three purified kinases—casein kinase II, mitogen-activated protein kinase 6, and SNF-related protein kinase 2.6—along with {sup 16}O{sub 4}- and {sup 18}O{sub 4}-ATP separately for in vitro kinase reactions. Phosphopeptides were enriched and analyzed by LC-MS. The phosphopeptide identification rate was estimated by comparing phosphopeptides identified by tandem mass spectrometry with phosphopeptide pairs generated by stable isotope labeled kinase reactions. Overall, we found that current high speed and high accuracy mass spectrometers can only identify 20%–40% of total phosphopeptides primarily due to relatively poor fragmentation, additional modifications, and low abundance, highlighting the urgent need for continuous efforts to improve phosphopeptide identification efficiency. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Estimating soybean yields from high-temporal-resolution multi-source data using deep learning

Accurate and timely crop yield prediction is crucial for ensuring food security and maintaining stable agricultural markets. In recent years, there has been a surge in interest in leveraging high-temporal-resolution, multi-source data for effective crop growth monitoring and yield estimation. A notable challenge arises from the difficulty in capturing the intricate interactions between variables across different time steps within these high-temporal-resolution time series datasets. This complexity hinders the reliable extraction of yield information from voluminous and often noisy datasets, especially during periods of extreme weather events. Here, in this study, we propose an Attention and Graph Isomorphism Network-enhanced Bi-directional Long Short-Term Memory network (AGB-LSTM) for estimating county-level soybean yield in the United States. This model integrates a diverse set of remote sensing data, including Near-Infrared Reflectance of Vegetation (NIRv), Sun-Induced chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP), along with environmental covariates. The AGB-LSTM effectively leverages information related to crop yield from high-temporal-resolution time series data (5-days), achieving an accuracy of R²= 0.67 and rRMSE = 14.46%. This approach significantly outperforms traditional machine learning methods such as Random Forest (RF) (R²= 0.52, rRMSE = 17.36%) and Bi-LSTM (R²= 0.58, rRMSE = 16.17%). Sensitivity experiments with different time steps and ranges demonstrated that our model could accurately and stably predict yields 1 to 2 months before harvest. Moreover, data with a finer temporal resolution consistently improved prediction performance, resulting in an approximately 20% increase in and an approximately 20% decrease in rRMSE compared to using monthly composites. We also evaluated the robustness of the model under extreme climate events and observed strong performance (R²= 0.50, rRMSE = 21.32%). Finally, yield mapping for major soybean-producing regions in North America in 2023 revealed spatial patterns that closely matched USDA yield reports. Our findings suggest that the AGB-LSTM model is a promising and effective method for estimating yield and has notable potential for global crop yield forecasting.

Deep learning↗
DOE OSTI2021

Multiscale Data-Driven Seismic Full-Waveform Inversion With Field Data Study

Seismic full-waveform inversion (FWI), which uses iterative methods to estimate high-resolution subsurface models from seismograms, is a powerful imaging technique in exploration geophysics. In recent years, the computational cost of FWI has grown exponentially due to the increasing size and resolution of seismic data. Moreover, it is a nonconvex problem and can encounter local minima due to the limited accuracy of the initial velocity models or the absence of low frequencies in the measurements. To overcome these computational issues, we develop a multiscale data-driven FWI method based on fully convolutional networks (FCNs). In preparing the training data, we first develop a real-time style transform method to create a large set of synthetic subsurface velocity models from natural images. We then develop two convolutional neural networks with encoder-decoder structures to reconstruct the low- and high-frequency components of the subsurface velocity models, separately. To validate the performance of our data-driven inversion method and the effectiveness of the synthesized training set, we compare it with conventional physics-based waveform inversion approaches using both synthetic and field data. Finally, these numerical results demonstrate that, once our model is fully trained, it can significantly reduce the computation time and yield more accurate subsurface velocity models in comparison with conventional FWI.

58 GEOSCIENCES↗
NASA NTRS2019

New Estimates of Ice and Oxygen Fluxes Across the Entire Lid of Lake Vostok From Observations of Englacial Radio Wave Attenuation

Over deep Antarctic subglacial lakes, spatially varying ice thickness and the pressure‐dependent melting point of ice result in distinct areas of melting and freeze‐on at the ice‐water interface, that is, at the lake lid. These ice mass fluxes drive lake circulation and, because basal Antarctic ice contains air clathrate, affect the input of oxygen to the lake, with implications for subglacial life. Inferences of rates of melting and freeze‐on, that is, accretion rates, from radar layer tracking and geodesy are limited in spatial coverage and resolution. Here we develop a new method to estimate accretion rate, and the resulting oxygen input at a lake lid, using airborne radar data over Lake Vostok together with ice‐temperature and chemistry data from the Vostok ice core. Because the lake lid is a coherent reflector of known reflectivity (at our radar frequency), we can infer depth‐averaged radio wave attenuation in the ice, with a spatial resolution of ~1 km along flight lines. Spatial variation in attenuation depends mostly on variation in ice temperature near the lid, which in turn varies strongly with ice mass flux at the lid. We model ice temperature versus depth with ice mass flux as a parameter, thus linking that flux to observed depth‐averaged attenuation. The resulting map of melt and accretion rates independently reproduces features known from earlier studies but now covers the entire lid. We find that freeze‐on is dominant when integrated over the lid, with an ice imbalance of 0.05 to 0.07 cu.km/year, which is robust against uncertainties.

Dale P. Winebrenner↗
NASA NTRS2009

Variability of Marine Aerosol Fine-Mode Fraction and Estimates of Anthropogenic Aerosol Component Over Cloud-Free Oceans from the Moderate Resolution Imaging Spectroradiometer (MODIS)

In this study, we examine seasonal and geographical variability of marine aerosol fine-mode fraction (f(sub m)) and its impacts on deriving the anthropogenic component of aerosol optical depth (tau(sub a)) and direct radiative forcing from multispectral satellite measurements. A proxy of f(sub m), empirically derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 data, shows large seasonal and geographical variations that are consistent with the Goddard Chemistry Aerosol Radiation Transport (GOCART) and Global Modeling Initiative (GMI) model simulations. The so-derived seasonally and spatially varying f(sub m) is then implemented into a method of estimating tau(sub a) and direct radiative forcing from the MODIS measurements. It is found that the use of a constant value for fm as in previous studies would have overestimated Ta by about 20% over global ocean, with the overestimation up to 45% in some regions and seasons. The 7-year (2001-2007) global ocean average tau(sub a) is 0.035, with yearly average ranging from 0.031 to 0.039. Future improvement in measurements is needed to better separate anthropogenic aerosol from natural ones and to narrow down the wide range of aerosol direct radiative forcing.

Yu, Hongbin↗
DOE OSTI2018

Inert and Adsorptive Tracer Tests for Field Measurement of Flow-Wetted Surface Area

Field tests in a discrete rock fracture validated a combined inert/adsorbing tracer test method to estimate the contact area between fluids circulating through a fracture and the bulk rock matrix (i.e., flow-wetted surface area, A). Tracer tests and heat injections occurred at a mesoscale well field in Altona, NY. A subhorizontal bedding plane fracture ~7.6 m below ground surface connects two wells separated by 14.1 m. Recovery of the adsorbing tracer cesium was roughly 72% less than the inert tracer iodide. Using an advection-dispersion-reaction model in one-dimension, the adsorbing/inert tracer method identified substantial flow channelization. These results are consistent with Ground Penetrating Radar (GPR) and thermal sensors. All characterization methods suggest circulating fluids were concentrated in a narrow, 1–2 m wide channel directly connecting the injection and production well. The inert/adsorbing tracer method identified two flow channels with areas of 28 and 80 m 2 . A one-dimensional heat transport model predicted production well temperature rises 20.5°C in 6 days, whereas measured temperature rise was 17.6°C. For comparison, two-dimensional heat transport through a fracture of uniform aperture (i.e., homogeneous permeability) predicted roughly 670 days until production well temperature would rise 17.6°C. This suggests that the use of a fracture of uniform aperture to predict heat transport may drastically overpredict the thermal performance of a geothermal system. In the context of commercial geothermal reservoirs, the results of this study suggest that combined inert/adsorbing tracer tests could predict production well thermal draw-down, leading to improved reservoir monitoring and management.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

The effect of subpixel clouds on remote sensing

A method for estimating the cloud effect on remote sensing is described, and it is applied to cloudiness in several climatological conditions. The algorithm is based on the Haurwitz (1948) measurements of the cloud layer transmission of solar radiation for an overcast sky and on an empirical interpolation of data for broken cloudiness by Pochop et al. (1968). Radiances for a sunny area observed directly from space and through a cloud, and for a shady area observed from space and through a cloud are computed. Methods for detecting the cloud effect from satellite images are discussed. The relation between cloud reflectance and cloud size is studied. It is observed that the subpixel clouds affect the detected radiance and vegetation index, and the effect depends on the cloud types and the dependence of the cloud transmissivity on cloud fraction. Procedures for decreasing or eliminating cloud effect are examined.

Kaufman, Yoram J.↗
DOE OSTI2019

A Versatile and Accurate Method for Halo Mass Determination from Phase-space Distribution of Satellite Galaxies

We propose a versatile and accurate method to estimate the halo mass and concentration from the kinematics of satellite galaxies. We construct the 6D phase-space distribution function of satellites from a cosmological simulation based on the similarity of internal dynamics for different halos. Within the Bayesian statistical framework, not only can we efficiently infer the halo mass and concentration, we can also treat various observational effects, including the selection function, incomplete data, and measurement errors, in a rigorous and straightforward manner. Through tests with mock samples, we show that our method is valid and accurate, as well as more precise than pure steady-state methods. It can constrain the halo mass to within ~20% using only 20 tracers and has a small intrinsic uncertainty of ~10%. In addition to the clear application to the Milky Way and similar galaxies, our method can be extended to galaxy groups or clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2003

Density Estimation with Mercer Kernels

We present a new method for density estimation based on Mercer kernels. The density estimate can be understood as the density induced on a data manifold by a mixture of Gaussians fit in a feature space. As is usual, the feature space and data manifold are defined with any suitable positive-definite kernel function. We modify the standard EM algorithm for mixtures of Gaussians to infer the parameters of the density. One benefit of the approach is it's conceptual simplicity, and uniform applicability over many different types of data. Preliminary results are presented for a number of simple problems.

Macready, William G.↗
NASA NTRS1993

A study of the threshold method utilizing raingage data

The threshold method for estimation of area-average rain rate relies on determination of the fractional area where rain rate exceeds a preset level of intensity. Previous studies have shown that the optimal threshold level depends on the climatological rain-rate distribution (RRD). It has also been noted, however, that the climatological RRD may be composed of an aggregate of distributions, one for each of several distinctly different synoptic conditions, each having its own optimal threshold. In this study, the impact of RRD variations on the threshold method is shown in an analysis of 1-min rainrate data from a network of tipping-bucket gauges in Darwin, Australia. Data are analyzed for two distinct regimes: the premonsoon environment, having isolated intense thunderstorms, and the active monsoon rains, having organized convective cell clusters that generate large areas of stratiform rain. It is found that a threshold of 10 mm/h results in the same threshold coefficient for both regimes, suggesting an alternative definition of optimal threshold as that which is least sensitive to distribution variations. The observed behavior of the threshold coefficient is well simulated by assumption of lognormal distributions with different scale parameters and same shape parameters.

Short, David A.↗
NASA NTRS1993

Biophysical characterization and surface radiation balance

The Kursk 1991 Experiment (KUREX-91) was conducted as one of a suite of international studies to develop capabilities to monitor global change. The studies were designed specifically to understand the earth's land-surface vegetation and atmospheric boundary layer interaction. An intensive field campaign was conducted at a site near Kursk, Russia during the month of July in 1991 by a team of international scientists to aid in the understanding of land-surface-atmosphere interactions in an agricultural/grassland setting. We were one of several teams of scientists participating at KUREX-91 at the Streletskaya Steppe Researve near Kursk, Russia. The main goals of our research were to: (1) characterize biophysical properties of the prairie vegetation; and (2) to characterize radiation regime through measurements and from estimates derived from canopy bidirectional reflectance data. Four objectives were defined to achieve these goals: (1) determine dependence of leaf optical properties on leaf water potential of some dominant species in discrete wavebands in the visible, near-infrared, and mid-infrared (spanning 0.4-2.3 microns range); (2) characterize the effective leaf area index (LAI) and leaf angle distribution of prairie vegetation; (3) characterize the radiation regime of the prairie vegetation through measures of the radiation balance components; and (4) examine, develop, and test methods for estimating albedo, APAR, and LAI from canopy bidirectional reflectance data. Papers which were the result of the research efforts are included.

Walter-Shea, Elizabeth A.↗
NASA NTRS2003

Moessbauer Spectroscopy of Mineral Separates from SNC Meteorites

Numerous workers have recently focused attention on the issue of the oxygen fugacity (f(sub O2)) of martian samples. Estimates of fO2 based on Fe-Ti oxides and D(sub Eu)/D(sub Gd) and D(sub Eu)/D(sub Sm) ratios suggest a range of fO2 values for SNC meteorites from IW+2.5 - IW+3.5 for Shergotty to IW- 2.0 - IW+0.2 for QUE94201. Fe(3+)/Fe(2+) is also a function of f(sub O2), and synchrotron micro-XANES values for olivine, pyroxene, and feldspar Fe(3+) have been reported. However, the relationship between the reported Fe(3+) values and the other methods for estimating f(sub O2) is not clear, and further measurements of Fe(3+)/Fe(2+) by a more conventional technique have been needed. Accordingly, in this project, new Mossbauer spectroscopy data on mineral separates handpicked from 10 SNC meteorites are reported.

Dyar, M. D.↗
NASA NTRS2023

Optimal Estimation Inversion of Ionospheric Electron Density from GNSS-POD Limb Measurements: Part I-Algorithm and Morphology

GNSS-LEO radio links from Precise Orbital Determination (POD) and Radio Occultation (RO) antennas have been used increasingly in characterizing the global 3D distribution and variability of ionospheric electron density (N e ). In this study, we developed an optimal estimation (OE) method to retrieve N e profiles from the slant total electron content (hTEC) measurements acquired by the GNSS-POD links at negative elevation angles (ε < 0°). Although both OE and onion-peeling (OP) methods use the Abel weighting function in the N e inversion, they are significantly different in terms of performance in the lower ionosphere. The new OE results can overcome the large N e oscillations, sometimes negative values, seen in the OP retrievals in the E-region ionosphere. In the companion paper in this Special Issue, the HmF2 and NmF2 from the OE retrieval are validated against ground-based ionosondes and radar observations, showing generally good agreements in NmF2 from all sites. Nighttime hmF2 measurements tend to agree better than the daytime when the ionosonde heights tend to be slightly lower. The OE algorithm has been applied to all GNSS-POD data acquired from the COSMIC-1 (2006–2019), COSMIC-2 (2019–present), and Spire (2019–present) constellations, showing a consistent ionospheric N e morphology. The unprecedented spatiotemporal sampling of the ionosphere from these constellations now allows a detailed analysis of the frequency–wavenumber spectra for the N e variability at different heights. In the lower ionosphere (~150 km), we found significant spectral power in DE1, DW6, DW4, SW5, and SE4 wave components, in addition to well-known DW1, SW2, and DE3 waves. In the upper ionosphere (~450 km), additional wave components are still present, including DE4, DW4, DW6, SE4, and SW4. The co-existence of eastward- and westward-propagating wave4 components implies the presence of a stationary wave4 (SPW4), as suggested by other earlier studies. Further improvements to the OE method are proposed, including a tomographic inversion technique that leverages the asymmetric sampling about the tangent point associated with GNSS-LEO links.

GNSS constellation↗
NASA NTRS2018

Estimating CO2 Emissions Using Real and Simulated Total Column Observations

Total column measurements of CO2 (XCO2) have been proposed as a possible way to estimate emissions from large urban regions. Using calculations from the Weather Research and Forecasting (WRF) model with a 1km emissions field, we investigate the viability of both real and proposed observing systems consisting of surface and/or column measurements for constraining emission sources of various types and sizes in the San Francisco Bay Area. We find that column observations are best suited for assessing enhancements downwind of very large emissions sources. For smaller sources (such as highways), in situ surface monitors are required to provide sufficient sensitivity. We explore methods for estimating emissions from the real and simulated observations.

Raheja, Garima↗
DOE OSTI2024

Sampling Size Optimization for Bioburden Density Estimation in Planetary Protection

Planetary protection (PP) is a discipline that focuses on minimizing the biological contamination of spacecraft to ensure compliance with international policy. Precise estimation of bioburden - the total number of microbes in or on spacecraft hardware – and the bioburden density are of utmost importance for PP. Such estimation is the way concordance with requirements is demonstrated, and it is critical for quantifying the potential risk of inadvertently contaminating other planetary bodies. Although a suite of molecular techniques have been used to thoroughly characterize and profile the microbiome of various cleanroom environments and spacecraft, the gold standard remains the physical enumeration of microbes via culturing of samples directly taken from spacecraft and associated surfaces. However, due to technical, budgetary, and programmatic constraints, only a manageable portion (around 10%) of the entire spacecraft surface is directly sampled with cotton swabs or wipes. To generate the bioburden current best estimate (CBE) for components not directly verifiable, the accepted approach is to apply a NASA-defined bioburden estimate based on the components’ manufacturing or assembly environment. This approach utilizes a prespecified bioburden density estimation that applies a maximum value across the total surface area of the specified component. For hardware components that underwent similar assembly processes, an implied bioburden is adopted for all components, based on a direct verification of a representative component within the same lot. Once all components have a CBE, the bioburden estimates are generated. In previous publication [ 1], we have shown that statistical risks quantifying the accuracy of the estimates for sampled, prespecified, and implied components can be derived and ranked. For mean squared error (MSE) function, the risks are available analytically and hence a cost function can be obtained to optimize the risks with respect to the sampling area and sampling cost. Since the sampling area and sampling cost are two complimentary variables, their sum will have a well-defined minimum. This paper presents the multivariate optimization of the integrated risk of an empirical Bayes estimator to determine the optimal sampling schedule for a given number of components. It is assumed that given a number of components, N, the bioburden density for each component can either be sampled, implied, or prespecified. The multivariate optimization searches through different options to sample, imply or prespecify the bioburden density for a component, and account for the component’s surface area and cost of sampling. The idea of the optimization is based on the observation that the statistical risk of using an estimator is a monotonically decreasing function of the sampled area. The larger the sampled area, the lower the risk of using the estimator as the estimator becomes more and more accurate as the sampling area increases. On the other hand, the cost of sampling is monotonically increasing as the sampled surface grows. This makes the risk and total cost of sampling complimentary variables which can be counterbalanced to achieve an optimal overall value with respect to the sampled surface. In this paper, the integrated risk has been used to quantify the accuracy of the estimator. This risk has been selected because it depends on neither the true value of the parameter nor on the collected data. The cost of each sample was also available to obtain the total cost of sampling of N components. The paper will present the results based on computer-simulated data as well as the data collected during the InSight mission. The computer-simulated data have N components with randomly generated total areas and each component assigned to one of the three categories according to the method of estimating of bioburden density: sampled, implied, or prespecified. The cost of sampling is also available. The cost of sampling is estimated based on a cost model provided by the planetary protection group at JPL. For this paper, the overall cost was assumed to be a linear function of exposure. The optimization process finds the allocation of the components to the three categories that minimizes the tradeoff between integrated risk and total cost. For the InSight data, a set of components is selected representing all three categories, and optimization is performed to determine if the performed allocation was optimal or if a better allocation could have been obtained. To the best of our knowledge, this work is the first attempt not only perform an accurate estimation of bioburden density but also do it in an optimal way.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Comparison of Statistical Estimation Techniques for Mars Entry, Descent, and Landing Reconstruction from MEDLI-like Data Sources

Flight data from an entry, descent, and landing (EDL) sequence can be used to reconstruct the vehicle's trajectory, aerodynamic coefficients and the atmospheric profile experienced by the vehicle. Past Mars missions have contained instruments that do not provide direct measurement of the freestream atmospheric conditions. Thus, the uncertainties in the atmospheric reconstruction and the aerodynamic database knowledge could not be separated. The upcoming Mars Science Laboratory (MSL) will take measurements of the pressure distribution on the aeroshell forebody during entry and will allow freestream atmospheric conditions to be partially observable. This data provides a mean to separate atmospheric and aerodynamic uncertainties and is part of the MSL EDL Instrumentation (MEDLI) project. Methods to estimate the flight performance statistically using on-board measurements are demonstrated here through the use of simulated Mars data. Different statistical estimators are used to demonstrate which estimator best quantifies the uncertainties in the flight parameters. The techniques demonstrated herein are planned for application to the MSL flight dataset after the spacecraft lands on Mars in August 2012.

Dutta, Soumyo↗
NASA NTRS1993

Microphysical properties of the November 26 cirrus cloud retrieved by Doppler radar/IR radiometer technique

Gaining information about cirrus cloud microphysics requires development of remote sensing techniques. In an earlier paper. Matrosov et al. (1992) proposed a method to estimate ice water path (IWP) (i.e., vertically integrated ice mass content IMC) and characteristic particle size averaged through the cloud from combined groundbased measurements of radar reflectivities and IR brightness temperatures of the downwelling thermal radiation in the transparency region of 10-12 mu m. For some applications, the vertically averaged characteristic particle sizes and IWP could be the appropriate information to use. However, vertical profiles of cloud microphysical parameters can provide a better understanding of cloud structure and development. Here we describe a further development of the previous method by Matrosov et al. (1992) for retrieving vertical profiles of cirrus particle sizes and IMC rather than their vertically averaged values. In addition to measurements of radar reflectivities, the measurements of Doppler velocities are used in the new method. This provides us with two vertical profiles of measurements to infer two vertical profiles of unknowns, i.e., particle characteristic sizes and IMC. Simultaneous measurements of the IR brightness temperatures are still needed to resolve an ambiguity in particle size-fall velocity relationships.

Matrosov, Sergey Y.↗
NASA NTRS2004

Verification of an Analytical Method for Measuring Crystal Nucleation Rates in Glasses from DTA Data

A recently proposed analytical (DTA) method for estimating the nucleation rates in glasses has been evaluated by comparing experimental data with numerically computed nucleation rates for a model lithium disilicate glass. The time and temperature dependent nucleation rates were predicted using the model and compared with those values from an analysis of numerically calculated DTA curves. The validity of the numerical approach was demonstrated earlier by a comparison with experimental data. The excellent agreement between the nucleation rates from the model calculations and fiom the computer generated DTA data demonstrates the validity of the proposed analytical DTA method.

Ranasinghe, K. S.↗