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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Plot-scale field experiment of surface hydrologic processes with EOS implications

Plot-scale hydrologic field studies were initiated at NASA Marshall Space Flight Center to a) investigate the spatial and temporal variability of surface and subsurface hydrologic processes, particularly as affected by vegetation, and b) develop experimental techniques and associated instrumentation methodology to study hydrologic processes at increasingly large spatial scales. About 150 instruments, most of which are remotely operated, have been installed at the field site to monitor ground atmospheric conditions, precipitation, interception, soil-water status, and energy flux. This paper describes the nature of the field experiment, instrumentation and sampling rationale, and presents preliminary findings.

Laymon, Charles A.↗
NASA NTRS1972

Satellite observations of temporal terrestrial features

The application of satellite data to earth resources and environmental studies and the effects of resolution of the photographs and imagery are discussed. The nature of the data acquired by manned space flight and unmanned satellites is described. Specific applications of remotely sensed data for oceanography, hydrology, geography, and geology are examined.

Rabchevsky, G. A.↗
NASA NTRS1977

Apollo 14 - Oxide, metal, and olivine mineral chemistries in 14072 with a bearing on the temporal relationships of subsolidus reduction

One of three primary objectives of the reported study is related to the definition of the distribution of troilite and Fe and the evaluation of the role of FeS in subsolidus reduction assemblages. Another objective was concerned with the definition of the lower limit of stabilizing elements such as Mg, Al, and Cr in ulvospinel to determine the terminal compositions at which reduction is inhibited. The third objective involves a comparison of the mineral chemistries of decomposed olivine with unaltered olivine in an attempt to determine the temperature limits. The sample was selected because it is one of the most intensely reduced samples returned from the moon. The model invoked for reduction is a magmatic-deuteric process which requires an environment approximating that of a closed system in which the volatile constituents are contained and in which reduction proceeds continuously with crystallization.

Haggerty, S. E.↗
NASA NTRS2022

Study of the Mass-loss Rate from the Sun

We investigate the temporal evolution of the yearly total mass-loss rate (YTMLR) from the Sun through coronal mass ejections (CMEs) over solar cycles 23 and 24. The mass determination of CMEs can be subject to significant uncertainty. To minimize this problem, we have used extensive statistical analysis. For this purpose, we employed data included in the Coordinated Data Analysis Workshop (CDAW) catalog. We estimated the contributions to mass loss from the Sun from different subsamples of CMEs (selected on the basis of their masses, angular widths, and position angles). The temporal variations of the YTMLR were compared to those of the sunspot number (SSN), X-ray flare flux, and the Disturbance Storm Time (Dst) index. We show that the CME mass included in the CDAW catalog reflects with high accuracy the actual mass-loss rate from the Sun through CMEs. Additionally, it is shown that the CME mass distribution in the log-lin representation reflects the Gaussian distribution very well. This means that the CMEs included in the CDAW catalog form one coherent population of ejections that have been correctly identified. Unlike the CME occurrence rate, it turns out that the YTMLR is a very good indicator of solar activity (e.g., SSN) and space weather (e.g., Dst index) consequences. These results are very important, since the YTMLR, unlike the mass loss through solar wind, significantly depends on solar cycles.

the sun↗
DOE OSTI2025

Direct Study of Changes in Catalyst Structure-Kinetic Properties During Redox Transitions

The Temporal Analysis of Products (TAP) pulse response methodology is a transient technique that provides the time resolution needed to deconvolve reaction steps from the complex networks typical in industrial catalytic processes. Traditionally, TAP measurements observe gas phase dynamics at the reactor exit but lack direct measurements of changes in the catalyst itself. Recently, a new operando technique was developed that couples gas phase transients to dynamic changes in metal centers with the precise TAP methodology for nanomole titration. Using an industrial CrOx/Al2O3 catalyst used for propane dehydrogenation, we demonstrate the capabilities of this unique device to reveal key catalytic processes: 1) total propane oxidation not associated with chromia centers, 2) reduction of Cr6+ to Cr3+ correlated with selective product formation, and 3) subsequent carbon accumulation. By utilizing incremental pulsing in a diffusion-only transport regime, the spectrokinetic device allows us to resolve detailed changes in catalyst structure, composition, and kinetic function that are otherwise indistinguishable in conventional operando devices. The unification of the TAP methodology with time-resolved spectroscopic measurements offers new and unique insights into the complex kinetic phenomena regulated by solid catalyst surfaces.

03 - NATURAL GAS↗
DOE OSTI2023

Hyperspectral and Nanosecond Temporal Resolution Widefield Infrared Photothermal Heterodyne Imaging

Label-free, bond-selective imaging offers new opportunities for fundamental and applied studies in chemistry, biology, and materials science. Preventing its broader application to investigating spectrally congested specimens are issues related to low sensitivity as well as low spatial and temporal resolution. Here, we demonstrate a widefield, mid-infrared (MIR) photothermal imaging technique, called widefield Infrared Photothermal Heterodyne imaging (wIR-PHI), that massively parallelizes acquisition of MIR absorption data through use of a high-speed complementary metal-oxide-semiconductor camera. wIR-PHI possesses notable features that include: spatial resolution significantly below the MIR diffraction limit, hyperspectral imaging capabilities, high sensitivity, and ~100 ns temporal resolution. Here, the first two features are highlighted by hyperspectral imaging of proximally close poly(methyl methacrylate) (PMMA) and polystyrene (PS) nanoparticles where clear, bond-specific imaging of nanoparticles, separated by less than the MIR diffraction limit, is demonstrated. Sensitivity is highlighted by imaging individual PMMA and PS nanoparticles with radii between r = 97-556 nm. This leads to a current, peak absorption cross-section limit-of-detection of σ abs = 1.9× 10 –16 cm 2 . wIR-PHI's 100 ns temporal resolution is simultaneously demonstrated by observing the decay of photothermal contrast on individual nanoparticles on a ~200-6000 ns timescale. In whole, wIR-PHI’s dramatic increase in acquisition speed opens opportunities for future MIR kinetic imaging and spectroscopic studies of important chemical, biological, and material processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Machine Learning Analysis of Hydrologic Exchange Flows and Transit Time Distributions in a Large Regulated River

Hydrologic exchange between river channels and adjacent subsurface environments is a key process that influences water quality and ecosystem function in river corridors. High-resolution numerical models were often used to resolve the spatial and temporal variations of exchange flows, which are computationally expensive. In this study, we adopt Random Forest (RF) and Extreme Gradient Boosting (XGB) approaches for deriving reduced order models of hydrologic exchange flows and associated transit time distributions, with integrated field observations (e.g., bathymetry) and hydrodynamic simulation data (e.g., river velocity, depth). The setup allows an improved understanding of the influences of various physical, spatial, and temporal factors on the hydrologic exchange flows and transit times. The predictors also contain those derived using hybrid clustering, leveraging our previous work on river corridor system hydromorphic classification. The machine learning-based predictive models are developed and validated along the Columbia River Corridor, and the results show that the top parameters are the thickness of the top geological formation layer, the flow regime, river velocity, and river depth; the RF and XGB models can achieve 70% to 80% accuracy and therefore are effective alternatives to the computational demanding numerical models of exchange flows and transit time distributions. Each machine learning model with its favorable configuration and setup have been evaluated. The transferability of the models to other river reaches and larger scales, which mostly depends on data availability, is also discussed.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2011

Interannual Variation in Phytoplankton Concentration and Community in the Pacific Ocean

Climate events such as El Nino have been shown to have an effect on the biology of our ocean. Because of the lack of data, we still have very little knowledge about the spatial and temporal effect these climate events may have on biological marine systems. In this study, we used the NASA Ocean Biogeochemical Model (NOBM) to assess the interannual variability in phytoplankton community in the Pacific Ocean between 1998 and 2005. In the North Central and Equatorial Pacific Ocean, changes in the Multivariate El Nino Index were associated with changes in phytoplankton composition. The model identified an increase in diatoms of approx.33 % in the equatorial Pacific in 1999 during a La Nina event. This increase in diatoms coincided with a decrease of approx.11 % in cyanobacteria concentration. The inverse relationship between cyanobacteria and diatoms concentration was significant (p<0.05) throughout the period of study. The use of a numerical model allows us to assess the impact climate variability has on key phytoplankton groups known to lead to contrasting food chain at a spatial and temporal resolution unachievable when relying solely on in-situ observations.

Rousseaux, C. S.↗
DOE OSTI2016

Frequency modulation and compression of optical pulses in an optical fibre with a travelling refractive-index wave

We have studied the conditions for spectral broadening, frequency modulation and compression (both temporal and spectral) of Gaussian pulses propagating in a fibre with a travelling refractive-index wave. Analytical expressions have been derived for the dependences of pulse duration, chirp and spectral width on the distance travelled through the fibre, parameters of the fibre and radiation launched into it. Based on the numerical analysis we have studied the behaviour of these characteristics by changing the coefficient of the refractive-index modulation and other parameters of the travelling refractive-index wave. (nonlinear optical phenomena)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2022

High-Resolution Imaging of Supraglacial Hydrological Features on the Greenland Ice Sheet with NASA’s Airborne Topographic Mapper (ATM) Instrument Suite

Seasonal meltwater pools on the surface of the Greenland Ice Sheet (GrIS) during late spring and summer in lakes on the surface and transforms the ice sheet's surface into a wet environment in the ablation zone below the equilibrium line. These supraglacial lakes in topographic lows on the ice surface are connected by a dendritic pattern of meandering streams and channels that together form a hydrological system consisting of supra-, en-, and subglacial components. Here, we use lidar data from NASA's Airborne Topographic Mapper (ATM) instrument suite and high-resolution optical imagery collected as part of Operation IceBridge (OIB) in spring 2019 over the GrIS to develop methods for the study of supraglacial hydrological features. While airborne surveys have a limited temporal and spatial coverage compared to imaging spaceborne sensors, their high footprint density and high-resolution imagery reveal a level of detail that is currently not obtainable from spaceborne measurements. The accuracy and resolution of airborne measurements complement spaceborne measurements, can support calibration and validation of spaceborne methods, and provide information necessary for high-resolution process studies of the supraglacial hydrological system on the GrIS that currently cannot be achieved from spaceborne observations alone.

ATM↗
NASA NTRS1998

The Remote Sensing of Mineral Aerosols and Their Impact on Phytoplankton Productivity using Sea WiFS

The main objective of this proposal was to use SeaWiFs data to study the relationship between aerosols found in aeollan dust and photosynthesis of phytoplankton in open ocean surface waters. This project was a collaborative effort between myself and Dr. Neil Tindale at Texas A&M University and followed on our earlier funded proposal which had been designed as a proof-of-concept study to determine if ocean color sensors such as the Coastal Zone Color Scanner (CZCS) could be used to detect and map large-scale mineral aerosol plumes. Despite the large spatial and temporal gaps inherent in the CZCS data coverage, our results from this initial study indicated that an ocean color sensor could indeed be used to detect aerosols. These encouraging results led us to propose in this proposal the use of SeaWiFS data to study mineral aerosol transport and its impact on phytoplankton production. This proposal orignally intended to make use of SeaWiFS images, but as the launch delay of SeaWiFS dragged on, we had to make do with other satellite data sets. Thus, the focus of this proposal became the CSCS image archive instead. I detail my results and accomplishments with this data set.

Stegmann, Petra M.↗
DOE OSTI2024

Multi-Tiered Estimation for Correlation Spectroscopy in 3D (MTECS3D) v0.1

This innovative software estimates rotational diffusion coefficients of particles from X-ray photon correlation spectroscopy (XPCS) data of monodispersed particle systems. It is the first method capable of extracting rotational diffusion information from three-dimensional particle systems using XPCS. Using the angular-temporal cross-correlation of the XPCS images, this software is able to estimate the rotational diffusion coefficients with only a few percent relative errors while requiring minimal prior knowledge of particle structures. This software enhances XPCS analysis capabilities, allowing researchers to study translational and rotational Brownian dynamics of particles in suspension across various temporal and spatial scales.

Hu, Zixi↗
NASA NTRS1993

A technique for deriving column-integrated water content using VAS split-window data

An algorithm is examined that uses VISSR Atmospheric Sounder (VAS) 11- and 12-micron (split-window) data to derive column-integrated water content (IWC) at mesoscale resolution. The algorithm is physically based and derives its first-guess information from radiosonde data. The procedure is applied first to a test case data set and then to the 19 June 1986 study day from the Cooperative Huntsville Meteorological Experiment (COHMEX). Ground truth data for verifying results from the technique include IWC from National Weather Service and COHMEX radiosondes, the Multispectral Atmospheric Mapping Sensor (MAMS), and a special set of VAS soundings (12 channel) using an independent retrieval method. Results from the test case show reasonable accuracy with the rms errors as low as +/- 3.8 mm. On the 19 June case study day IWC analyses depict reasonable gradients and exhibit good spatial and temporal continuity. Furthermore, they provide insight into preferred regions for cumulus cloud and thunderstorm formation. On the average, a mean absolute retrieval error of 2.4 mm (an 8.1 percent error) and a rms error of +/- 2.9 mm are obtained on the case study day. These results compare favorably with those from existing VAS IWC techniques. Overall, the findings indicate that the technique has excellent potential to depict mesoscale moisture variations.

Guillory, Anthony R.↗
DOE OSTI2021

TQEA: Temporal Quantum Error Analysis

For the last few years quantum computers have captured researchers’ interest in solving complicated problems in finance, chemistry, machine learning, and many other NP problems. Quantum computing benefits from parallel computation, entanglement, and calculation speedup compared to classical computing. Even though the operations and number of qubits in quantum computers are limited, previous research showed that using quantum computers can be beneficial. These benefits gained researchers’ interest to work on the improvement of quantum computers and overcome the limitations by building more advanced quantum computers with fault tolerance capability, more physical qubits, and better operational gates. In practice, Quantum applications would be translated into Quantum Circuits and each circuit can contain one or many entanglements (s), single qubits operations, and readouts. The importance of running Quantum applications with controlled errors or without errors is critical to the desired result from Quantum readout. In this paper, we study the characteristics of superconducting quantum machines along with the previously proposed methods of Quantum error detection/correction and in order to build a better error model we propose a temporal method for analyzing the the behavior of qubits errors (T1 and T2), frequency of operation, entanglement errors, and readout errors. In order to detect and predict the behavior of each machine, we use simple exponential smoothing analysis on heuristic calibration data. Finally, based on observation, we show that based on frequency, qubits, readout and single operation errors we can build a temporal based model to study and predict the outcome of runs on each Quantum machine.

Baheri, Betis↗
NASA NTRS2021

Separation at Crossing Waypoints Under Wind Uncertainty in Urban Air Mobility

To enable high-density operations in major metropolitan areas, urban air mobility networks are anticipated to have air traffic management with higher levels of autonomy. To ensure that this type of autonomy is feasible, one of the critical steps from a safety and efficiency perspective is understanding various factors that affect the spatial separation between airborne flights and ensure that these factors can be managed. In terms of separation assurance and scheduling, an important real-world concern is that future states of aircraft cannot be perfectly predicted. The focus of this research paper is to understand how these prediction errors affect separation and scheduling services and to explore mitigation strategies to handle these errors. In this research, we have simulated these types of uncertainty by adding wind-prediction errors to trajectory predictions for separation. With these wind-prediction errors, we decompose the problem into two separate questions. First, using both simulation and analytical methods, we look at conflict-detection-only scenarios to understand how the wind errors affect required minimum temporal separation between crossing flights to ensure a specific spatial separation. Next, we study how trajectory errors effect conflict resolution, and we explore different combinations of scheduling and separation assurance to mitigate the effects of uncertainty between crossing flights. The conflict resolution algorithm aims to minimize necessary temporal separation between crossing flights under uncertainty, still ensuring safety-critical spatial separation. In summary, this research suggests that the required minimum temporal separation at a crossing waypoint is dependent on factors such as inbound crossing angle, the relative angle between wind direction and bearing of each route, wind magnitude, wind magnitude uncertainty, nominal cruise airspeed of aircraft, and look-ahead time of the conflict detection algorithm. This research also suggests that different combinations of scheduling and separation have different qualitative results. Using a combination of strategic, flow-based scheduling, tactical scheduling at crossings, speed control near crossing points, and separation management leads to a system that is insensitive to trajectory prediction errors with high throughput and flexibility for aircraft away from shared resources.

urban air mobility↗
NASA NTRS2021

Separation at Crossing Waypoints Under Wind Uncertainty in Urban Air Mobility

To enable high-density operations in major metropolitan areas, urban air mobility networks are anticipated to have air traffic management with higher levels of autonomy. To ensure that this type of autonomy is feasible, one of the critical steps from a safety and efficiency perspective is understanding various factors that affect the spatial separation between airborne flights and ensure that these factors can be managed. In terms of separation assurance and scheduling, an important real-world concern is that future states of aircraft cannot be perfectly predicted. The focus of this research paper is to understand how these prediction errors affect separation and scheduling services and to explore mitigation strategies to handle these errors. In this research, we have simulated these types of uncertainty by adding wind-prediction errors to trajectory predictions for separation. With these wind-prediction errors, we decompose the problem into two separate questions. First, using both simulation and analytical methods, we look at conflict-detection-only scenarios to understand how the wind errors affect required minimum temporal separation between crossing flights to ensure a specific spatial separation. Next, we study how trajectory errors effect conflict resolution, and we explore different combinations of scheduling and separation assurance to mitigate the effects of uncertainty between crossing flights. The conflict resolution algorithm aims to minimize necessary temporal separation between crossing flights under uncertainty, still ensuring safety-critical spatial separation. In summary, this research suggests that the required minimum temporal separation at a crossing waypoint is dependent on factors such as inbound crossing angle, the relative angle between wind direction and bearing of each route, wind magnitude, wind magnitude uncertainty, nominal cruise airspeed of aircraft, and look-ahead time of the conflict detection algorithm. This research also suggests that different combinations of scheduling and separation have different qualitative results. Using a combination of strategic, flow-based scheduling, tactical scheduling at crossings, speed control near crossing points, and separation management leads to a system that is insensitive to trajectory prediction errors with high throughput and flexibility for aircraft away from shared resources.

urban air mobility↗
DOE OSTI2021

A Graphics Processing Unit (GPU) Approach to Large Eddy Simulation (LES) for Transport and Contaminant Dispersion

Recent advances in the development of large eddy simulation (LES) atmospheric models with corresponding atmospheric transport and dispersion (AT&D) modeling capabilities have made it possible to simulate short, time-averaged, single realizations of pollutant dispersion at the spatial and temporal resolution necessary for common atmospheric dispersion needs, such as designing air sampling networks, assessing pollutant sensor system performance, and characterizing the impact of airborne materials on human health. The high computational burden required to form an ensemble of single-realization dispersion solutions using an LES and coupled AT&D model has, until recently, limited its use to a few proof-of-concept studies. An example of an LES model that can meet the temporal and spatial resolution and computational requirements of these applications is the joint outdoor-indoor urban large eddy simulation (JOULES). A key enabling element within JOULES is the computationally efficient graphics processing unit (GPU)-based LES, which is on the order of 150 times faster than if the LES contaminant dispersion simulations were executed on a central processing unit (CPU) computing platform. JOULES is capable of resolving the turbulence components at a suitable scale for both open terrain and urban landscapes, e.g., owing to varying environmental conditions and a diverse building topology. In this paper, we describe the JOULES modeling system, prior efforts to validate the accuracy of its meteorological simulations, and current results from an evaluation that uses ensembles of dispersion solutions for unstable, neutral, and stable static stability conditions in an open terrain environment.

54 ENVIRONMENTAL SCIENCES↗