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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Pulse-timing study of Vela X-1 based on Hakucho and Tenma data - 1980-1984

The extensive observations of Vela X-1 acquired from 1980 to 1984 with the Hakucho and Tenma satellites, using a pulse-filtering technique that provides a significant improvement in pulse-timing precision, are reexamined. The details of the preparation of this data base, including the determination of updated orbital parameters based on these and previously published observations covering a 10-yr interval, are reported. Preparatory to estimation of angular-acceleration flux-correlation pairs, substantially improved estimates of the power density of fluctuations in the derivative of the pulse frequency on analysis periods between 0.5 and 80 days are presented. These results support the phenomenological hypothesis that unresolved fluctuations in the angular acceleration of the neutron star, describable as random noise, are responsible for the entire history of the observed variation in pulse frequency of Vela X-1 on all time scales longer than a few days.

Deeter, J. E.↗
NASA NTRS2014

Solar Dynamics Observatory and Hinode Observations of a Blowout Jet in a Coronal Hole

A blowout jet occurred within the south coronal hole on 9 February 2011 at 09:00 UT and was observed by the Atmospheric Imaging Assembly (AIA) and Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory, and by the EUV Imaging Spectrometer (EIS) and X-Ray Telescope (XRT) onboard the Hinode spacecraft during coronal-hole monitoring performed as part of Hinode Operations Program No. 177. Images from AIA show expanding hot and cold loops from a small bright point with plasma ejected in a curtain up to 30 Mm wide. The initial intensity front of the jet had a projected velocity of 200 km/s, and the line-of-sight (LOS) velocities measured by EIS are between 100 and 250 km/s. The LOS velocities increased along the jet, implying that an acceleration mechanism operates within the body of the jet. The jet plasma had a density of 2.7×10(exp 8) /cu.cm and a temperature of 1.4 MK. During the event a number of bright kernels were seen at the base of the bright point. The kernels have sizes of ≈ 1000 km, are variable in brightness, and have lifetimes of 1 - 15 minutes. An XRT filter ratio yields temperatures of 1.5 - 3.0 MK for the kernels. The bright point existed for at least ten hours, but disappeared within two hours after the jet, which lasted for 30 minutes. HMI data reveal converging photospheric flows at the location of the bright point, and the mixed-polarity magnetic flux canceled over a period of four hours on either side of the jet.

Spectral line↗
DOE OSTI2021

High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data

Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, a Kalman filter-based method was developed to estimate the spatio-temporal dynamics of daytime average net ecosystem exchange (NEEday) at 0.5-m resolution over a 550 m by 700 m study site. We integrated multi-scale, multi-type datasets, including normalized difference vegetation indices (NDVIs) obtained from a novel automated mobile sensor system (or tram system) and a greenness index map obtained from airborne imagery. We took advantage of the significant correlations between NDVI and NEEday identified based on flux chamber measurements. The weighted average of the estimated NEEday within the flux-tower footprint agreed with the flux tower data in term of its seasonal dynamics. We then evaluated the spatial variability of the growing season average NEEday, as a function of polygon geomorphic classes; i.e., the combination of polygon types—which are known to present different degradation stages associated with permafrost thaw—and microtopographic features (i.e., troughs, centers and rims). Our study suggests the importance of considering microtopographic features and their spatial coverage in computing spatially aggregated carbon exchange.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Observations of compact sources in galaxy clusters using MUSTANG2

Compact sources can cause scatter in the scaling relationships between the amplitude of the thermal Sunyaev–Zel’dovich Effect (tSZE) in galaxy clusters and cluster mass. Estimates of the importance of this scatter vary – largely due to limited data on sources in clusters at the frequencies at which tSZE cluster surveys operate. In this paper, we present 90 GHz compact source measurements from a sample of 30 clusters observed using the MUSTANG2 instrument on the Green Bank Telescope. We present simulations of how a source’s flux density, spectral index, and angular separation from the cluster’s centre affect the measured tSZE in clusters detected by the Atacama Cosmology Telescope (ACT). By comparing the MUSTANG2 measurements with these simulations we calibrate an empirical relationship between 1.4 GHz flux densities from radio surveys and source contamination in ACT tSZE measurements. We find 3 per cent of the ACT clusters have more than a 20 per cent decrease in Compton-y but another 3 per cent have a 10 per cent increase in the Compton-y due to the matched filters used to find clusters. As sources affect the measured tSZE signal and hence the likelihood that a cluster will be detected, testing the level of source contamination in the tSZE signal using a tSZE-selected catalogue is inherently biased. We confirm this by comparing the ACT tSZE catalogue with optically and X-ray-selected cluster catalogues. Furthermore, there is a strong case for a large, high-resolution survey of clusters to better characterize their source population.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

Estimating Evapotranspiration with Land Data Assimilation Systems

Advancements in both land surface models (LSM) and land surface data assimilation, especially over the last decade, have substantially advanced the ability of land data assimilation systems (LDAS) to estimate evapotranspiration (ET). This article provides a historical perspective on international LSM intercomparison efforts and the development of LDAS systems, both of which have improved LSM ET skill. In addition, an assessment of ET estimates for current LDAS systems is provided along with current research that demonstrates improvement in LSM ET estimates due to assimilating satellite-based soil moisture products. Using the Ensemble Kalman Filter in the Land Information System, we assimilate both NASA and Land Parameter Retrieval Model (LPRM) soil moisture products into the Noah LSM Version 3.2 with the North American LDAS phase 2 (NLDAS-2) forcing to mimic the NLDAS-2 configuration. Through comparisons with two global reference ET products, one based on interpolated flux tower data and one from a new satellite ET algorithm, over the NLDAS2 domain, we demonstrate improvement in ET estimates only when assimilating the LPRM soil moisture product.

Peters-Lidard, C. D.↗
NASA NTRS2012

The Impact of AMSR-E Soil Moisture Assimilation on Evapotranspiration Estimation

An assessment ofETestimates for current LDAS systems is provided along with current research that demonstrates improvement in LSM ET estimates due to assimilating satellite-based soil moisture products. Using the Ensemble Kalman Filter in the Land Information System, we assimilate both NASA and Land Parameter Retrieval Model (LPRM) soil moisture products into the Noah LSM Version 3.2 with the North American LDAS phase 2 CNLDAS-2) forcing to mimic the NLDAS-2 configuration. Through comparisons with two global reference ET products, one based on interpolated flux tower data and one from a new satellite ET algorithm, over the NLDAS2 domain, we demonstrate improvement in ET estimates only when assimilating the LPRM soil moisture product.

Peters-Lidard, Christa D.↗
NASA NTRS2019

Application of Synoptic Magnetograms for Prediction of Solar Activity Using Ensemble Kalman Filter

Solar activity predictions using the data assimilation approach have demonstrated great potential to build reliable long-term forecasts of solar activity. In particular, it has been shown that the Ensemble Kalman Filter (EnKF) method applied to a non-linear dynamo model is capable of predicting solar activity up to one sunspot cycle ahead in time, as well as estimating the properties of the next cycle a few years before it begins. These developments assume an empirical relationship between the mean toroidal magnetic field flux and the sunspot number. Estimated from the sunspot number series, variations of the toroidal field have been used to assimilate the data into the Parker-Kleeorin-Ruzmakin (PKR) dynamo model by applying the EnKF method. The dynamo model describes the evolution of the toroidal and poloidal components of the magnetic field and the magnetic helicity. Full-disk magnetograms provide more accurate and complete input data by constraining both the toroidal and poloidal global field components, but these data are available only for the last four solar cycles. In this presentation, using the available magnetogram data, we discuss development of the methodology and forecast quality criteria (including forecast uncertainties and sources of errors). We demonstrate the influence of limited time series observations on the accuracy of solar activity predictions. We present EnKF predictions of the upcoming Solar Cycle 25 based on both the sunspot number series and observed magnetic fields and discuss the uncertainties and potential of the data assimilation approach.

Kitiashvili, Irina N.↗
NASA NTRS1982

A system for measuring methane fluxes from inland and coastal wetland environments

A CH4 measuring system with a sensitivity of 0.01 ppmv and a response time of 1 sec is described. Pulses are separable from moving and stationary readings, the device floats, and air velocity in the chamber can be controlled in the range 0-4.4 m/sec. The system is set on the water so that controlled speed air from beneath can enter an inner chamber and be pumped through a gas filter correlation system (GFC) before being returned to the chamber. The GFC mechanism yields an absorption signal in the form of a dc voltage, which a processor orders printed on a strip chart as a function of time. Detection of the CH4 amounts is through IR absorption, and the sensitivity of the instrument has been measured at .002-.051 g/sq m per day with air flows in the range 0.90-4.40 m/sec. The unit can be modified to detect CO and CO2, and further applications for low plant canopies and land surfaces are indicated.

Sebacher, D. I.↗
DOE OSTI2023

A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)

Tropical forest dynamics play a crucial role in the global carbon, water, and energy cycles. However, realistically simulating the dynamics of competition and coexistence between different plant functional types (PFTs) in tropical forests remains a significant challenge. This study aims to improve the modeling of PFT coexistence in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a vegetation demography model implemented in the Energy Exascale Earth System Model (E3SM) land model (ELM), ELM-FATES. Specifically, we explore (1) whether plant trait relationships established from field measurements can constrain ELM-FATES simulations and (2) whether machine learning (ML)-based surrogate models can emulate the complex ELM-FATES model and optimize parameter selections to improve PFT coexistence modeling. We conducted three ensembles of ELM-FATES experiments at a tropical forest site near Manaus, Brazil. By comparing the ensemble experiments without (Exp-CTR) and with (Exp-OBS) consideration of observed trait relationships, we found that accounting for these relationships slightly improves the simulations of water, energy, and carbon variables when compared to observations but degrades the simulation of PFT coexistence. Using ML-based surrogate models trained on Exp-CTR, we optimized the trait parameters in ELM-FATES and conducted another ensemble of experiments (Exp-ML) with these optimized parameters. The proportion of PFT coexistence experiments significantly increased from 21 % in Exp-CTR to 73 % in Exp-ML. After filtering the experiments that allow for PFT coexistence to agree with observations (within 15 % tolerance), 33 % of the Exp-ML experiments were retained, which is a significant improvement compared to the 1.4 % in Exp-CTR. Exp-ML also accurately reproduces the annual means and seasonal variations in water, energy, and carbon fluxes and the field inventory of aboveground biomass. This study represents a reproducible method that utilizes machine learning to identify parameter values that improve model fidelity against observations and PFT coexistence in vegetation demography models for diverse ecosystems. Our study also suggests the need for new mechanisms to enhance the robust simulation of coexisting plants in ELM-FATES and has significant implications for modeling the response and feedbacks of ecosystem dynamics to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

QSO photometric redshifts using machine learning and neural networks

ABSTRACT The scientific value of the next generation of large continuum surveys would be greatly increased if the redshifts of the newly detected sources could be rapidly and reliably estimated. Given the observational expense of obtaining spectroscopic redshifts for the large number of new detections expected, there has been substantial recent work on using machine learning techniques to obtain photometric redshifts. Here, we compare the accuracy of the predicted photometric redshifts obtained from deep learning (DL) with the k-nearest neighbour (kNN) and the decision tree regression (DTR) algorithms. We find using a combination of near-infrared, visible, and ultraviolet magnitudes, trained upon a sample of Sloan Digital Sky Survey quasi-stellar objects, that the kNN and DL algorithms produce the best self-validation result with a standard deviation of σΔz = 0.24 (σΔz(norm) = 0.11). Testing on various subsamples, we find that the DL algorithm generally has lower values of σΔz, in addition to exhibiting a better performance in other measures. Our DL method, which uses an easy to implement off-the-shelf algorithm with neither filtering nor removal of outliers, performs similarly to other, more complex, algorithms, resulting in an accuracy of Δz < 0.1 up to z ∼ 2.5. Applying the DL algorithm trained on our 70 000 strong sample to other independent (radio-selected) data sets, we find σΔz ≤ 0.36 (σΔz(norm) ≤ 0.17) over a wide range of radio flux densities. This indicates much potential in using this method to determine photometric redshifts of quasars detected with the Square Kilometre Array.

Curran, S. J.↗
NASA NTRS2001

Asteroid Size-Frequency Distribution

A total of six deep exposures (using AOT CAM01 with a 6 inch PFOV) through the ISOCAM LW10 filter (IRAS Band 1, i.e. 12 micron) were obtained on an approximately 15 arcminute square field centered on the ecliptic plane. Point sources were extracted using the technique described. Two known asteroids appear in these frames and 20 sources moving with velocities appropriate for main belt asteroids are present. Most of the asteroids detected have flux densities less than 1 mJy, i,e., between 150 and 350 times fainter than any of the asteroids observed by IRAS. These data provide the first direct measurement of the 12 pm sky-plane density for asteroids on the ecliptic equator. The median zodiacal foreground, as measured by ISOCAM during this survey, is found to be 22.1 +/- 1.5 mJy per pixel, i.e., 26.2 +/- 1.7 MJy/sr. The results presented here imply that the actual number of kilometer-sized asteroids is significantly greater than previously believed and in reasonable agreement with the Statistical Asteroid Model.

Tedesco, Edward F.↗
NASA NTRS2003

A new dynamical atmospheric ionizing radiation (AIR) model for epidemiological studies

A new Atmospheric Ionizing Radiation (AIR) model is currently being developed for use in radiation dose evaluation in epidemiological studies targeted to atmospheric flight personnel such as civilian airlines crewmembers. The model will allow computing values for biologically relevant parameters, e.g. dose equivalent and effective dose, for individual flights from 1945. Each flight is described by its actual three dimensional flight profile, i.e. geographic coordinates and altitudes varying with time. Solar modulated primary particles are filtered with a new analytical fully angular dependent geomagnetic cut off rigidity model, as a function of latitude, longitude, arrival direction, altitude and time. The particle transport results have been obtained with a technique based on the three-dimensional Monte Carlo transport code FLUKA, with a special procedure to deal with HZE particles. Particle fluxes are transformed into dose-related quantities and then integrated all along the flight path to obtain the overall flight dose. Preliminary validations of the particle transport technique using data from the AIR Project ER-2 flight campaign of measurements are encouraging. Future efforts will deal with modeling of the effects of the aircraft structure as well as inclusion of solar particle events. Published by Elsevier Ltd on behalf of COSPAR.

Aviation↗
DOE OSTI2021

DART-PFLOTRAN: An ensemble-based data assimilation system for estimating subsurface flow and transport model parameters

Ensemble-based Data Assimilation (EDA), based on the Monte Carlo approach, has been effectively applied to estimate model parameters through inverse modeling in subsurface flow and transport problems. However, implementation of EDA approach involves a complicated workflow that include setting up and executing ensemble forward model simulations, processing observations and model simulation results for parameter updates, and repeat for sequential or iterative EDA. To facilitate the management of such workflow and lower the barriers for adopting EDA-based parameter estimation in subsurface science, we develop a generic software frame-work linking the Data Assimilation Research Testbed (DART) with a massively parallel subsurface FLOw and TRANsport code PFLOTRAN. The new DART-PFLOTRAN leverages both the core data assimilation engines in DART and the computational power afforded by PFLOTRAN. In addition to the standard smoother and filtering options, DART-PFLOTRAN enables an iterative EDA workflow based on the Ensemble Smoother for Multiple Data Assimilation method (ES-MDA) to improve estimation accuracy for nonlinear forward problems. Here, we verify the implementation of ES-MDA in DART-PFLOTRAN using two synthetic cases designed to estimate static permeability and dynamic exchange fluxes across the riverbed, respectively, from continuous temperature measurements made across a depth profile. One-dimensional hydro-thermal simulations are performed in both cases to relate temperature responses with the parameters of interest. In the case of estimating dynamic parameters, we demonstrate the flexibility of DART-PFLOTRAN in automating sequential ES-MDA workflow, which will significantly reduce the time researchers spend on managing complex workflows in similar applications. Both studies yield accurate estimations of the parameters compared to their synthetic truth, while ES-MDA leads to more accurate estimation when a high level of nonlinearity exist between observed responses and unknown parameters. With a code base in Python and Fortran, DART-PFLOTRAN paves the way for applications in large-scale subsurface inverse modeling by automating the complex workflow of sequential ES-MDA that can be executed on various computing platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Flux and estimated spectra from a low-intensity laser-driven X-ray source

Laser-driven X-rays as probes for high-energy-density physics spans an extremely large parameter space with laser intensities varying by 8 orders of magnitude. We have built and characterized a soft X-ray source driven by a modest intensity laser of 4 × 10 13 W/cm 2 . Emitted X-rays were measured by diamond radiation detectors and a filtered soft X-ray camera. A material-dependence study on Al, Ti, stainless steel alloy 304, Fe, Cu and Sn targets indicated 5-μm-thick Cu foils produced the highest X-ray yield. X-ray emission in the laser direction and emission in the reverse direction depend strongly on the foil material and the thickness due to the opacity and hydrodynamic disassembly time. The time-varying X-ray signals are used to measure the material thinning rate and is found to be ~1.5 μm/ns for the materials tested implying thermal temperature around 0.6 eV. The X-ray spectra from Cu targets peaks at ~2 keV with no emission >4 keV and was estimated using images with eight different foil filters. One-dimensional hydrodynamic and spectral calculations using HELIOS-CR provide qualitative agreement with experimental results. Modest intensity lasers can be an excellent source for nanosecond bursts of soft X-rays.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Higher-order harmonic generation and strong field ionization with Bessel–Gauss beams in a thin jet geometry

A promising alternative to Gaussian beams for use in strong field science is Bessel–Gauss (BG or Bessel-like) laser beams, as they are easily produced with readily available optics and provide more flexibility of the spot size and working distances. Here we use BG beams produced with a lens-axicon optical system for higher-order harmonic generation (HHG) in a thin gas jet. The finite size of the interaction region allows for scans of the HHG yield along the propagation axis. Further, by measuring the ionization yield in unison with the extreme ultraviolet (XUV), we are able to distinguish regions of maximum ionization from regions of optimum XUV generation. This distinction is of great importance for BG fields, as the generation of BG beams with axicons often leads to oscillations of the on-axis intensity, which can be exploited for extended phase-matching conditions. We observed such oscillations in the ionization and XUV flux along the propagation axis for the first time. As is the case for Gaussian modes, the harmonic yield is not maximum at the point of highest ionization. Finally, despite Bessel beams having a hole in the center in the far field, the XUV beam is well collimated, making BG modes a great alternative when spatial filtering of the fundamental is desired.

Davino, Michael↗
DOE OSTI2024

Multiscale assessment of North American terrestrial carbon balance

Abstract. Comparisons of carbon uptake estimates from bottom-up terrestrial biosphere models (TBMs) to top-down atmospheric inversions help assess how well we understand carbon dioxide (CO2) exchange between the atmosphere and terrestrial biosphere. Previous comparisons have shown varying levels of agreement between bottom-up and top-down approaches, but they have almost exclusively focused on large, aggregated scales (e.g., global or continental), providing limited insights into reasons for the mismatches. Here we explore how consistency, defined as the spread in net ecosystem exchange (NEE) estimates within an ensemble of TBMs or inversions, varies with at finer spatial scales ranging from 1∘×1∘ to the continent of North America. We also evaluate how well consistency informs accuracy in overall NEE estimates by filtering models based on their agreement with the variability, magnitude, and seasonality in observed atmospheric CO2 drawdowns or enhancements. We find that TBMs produce more consistent estimates of NEE for most regions and at most scales relative to inversions. Filtering models using atmospheric CO2 metrics causes ensemble spread to decrease substantially for TBMs, but not for inversions. This suggests that ensemble spread is likely not a reliable measure of the uncertainty associated with the North American carbon balance at any spatial scale. Promisingly, applying atmospheric CO2 metrics leads to a set of models with converging flux estimates across TBMs and inversions. Overall, we show that multiscale assessment of the agreement between bottom-up and top-down NEE estimates, aided by regional-scale observational constraints is a promising path towards identifying fine-scale sources of uncertainty and improving both ensemble consistency and accuracy. These findings help refine our understanding of biospheric carbon balance, particularly at scales relevant for informing regional carbon-climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Quasi-biennial geomagnetic variation caused by the sun

Clear evidence for the existence of a quasi-biennial geomagnetic variation is shown by an analysis of annual averages of the horizontal (H) component of the geomagnetic field observed at five observatories. The analysis uses a numerical filter, which is equivalent to taking the second order time derivative of the time series. The cause for the variation is external to the earth because its amplitude depends on magnetic activity. The second order time derivative of H is well correlated with the corresponding time derivatives of the relative sunspot number and 10.7 cm solar flux. It is suggested that quasi-biennial oscillations observed in the geomagnetic field, cosmic rays, stratospheric zonal wind and temperature, total ozone, and other meteorological parameters could be produced by a common cause on the sun.

Sugiura, M.↗