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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
NASA NTRS2023

The James Webb Space Telescope Mission: Optical Telescope Element Design, Development, and Performance

The James Webb Space Telescope (JWST) is a large, infrared space telescope that has recently started its science program which will enable breakthroughs in astrophysics and planetary science. Notably, JWST will provide the very first observations of the earliest luminous objects in the universe and start a new era of exoplanet atmospheric characterization. This transformative science is enabled by a 6.6 m telescope that is passively cooled with a 5 layer sunshield. The primary mirror is comprised of 18 controllable, low areal density hexagonal segments, that were aligned and phased relative to each other in orbit using innovative image-based wave front sensing and control algorithms. This revolutionary telescope took more than two decades to develop with a widely distributed team across engineering disciplines. We present an overview of the telescope requirements, architecture, development, superb on-orbit performance, and lessons learned. JWST successfully demonstrates a segmented aperture space telescope and establishes a path to building even larger space telescopes.

Infrared observatories↗
DOE OSTI2013

A general stochastic approach to unavailability analysis of standby safety systems

The paper presents a general analytical framework to analyze unavailability caused by latent failures in standby safety systems used in nuclear plants. The proposed approach is general in a sense that it encompasses a variety of inspection and maintenance policies and relaxes restrictive assumptions regarding the distributions of time to failure (or aging) and duration of repair. A key result of the paper is a general integral equation for point unavailability, which can be tailored to any specific maintenance policy. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Residuals-based distributionally robust optimization with covariate information

We consider data-driven approaches that integrate a machine learning prediction model within distributionally robust optimization (DRO) given limited joint observations of uncertain parameters and covariates. Our framework is flexible in the sense that it can accommodate a variety of regression setups and DRO ambiguity sets. We investigate asymptotic and finite sample properties of solutions obtained using Wasserstein, sample robust optimization, and phi-divergence-based ambiguity sets within our DRO formulations, and explore cross-validation approaches for sizing these ambiguity sets. Through numerical experiments, we validate our theoretical results, study the effectiveness of our approaches for sizing ambiguity sets, and illustrate the benefits of our DRO formulations in the limited data regime even when the prediction model is misspecified.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

Enabling Technologies for High-accuracy Multiangle Spectropolarimetric Imaging from Space

Satellite remote sensing plays a major role in measuring the optical and radiative properties, environmental impact, and spatial and temporal distribution of tropospheric aerosols. In this paper, we envision a new generation of spaceborne imager that integrates the unique strengths of multispectral, multiangle, and polarimetric approaches, thereby achieving better accuracies in aerosol optical depth and particle properties than can be achieved using any one method by itself. Design goals include spectral coverage from the near-UV to the shortwave infrared; global coverage within a few days; intensity and polarimetric imaging simultaneously at multiple view angles; kilometer to sub-kilometer spatial resolution; and measurement of the degree of linear polarization for a subset of the spectral complement with an uncertainty of 0.5% or less. The latter requirement is technically the most challenging. In particular, an approach for dealing with inter-detector gain variations is essential to avoid false polarization signals. We propose using rapid modulation of the input polarization state to overcome this problem, using a high-speed variable retarder in the camera design. Technologies for rapid retardance modulation include mechanically rotating retarders, liquid crystals, and photoelastic modulators (PEMs). We conclude that the latter are the most suitable.

photoelastic modulators (PEMs)↗
DOE OSTI2015

Elastic-Waveform Inversion with Compressive Sensing for Sparse Seismic Data

Accurate velocity models of compressional- and shear-waves are essential for geothermal reservoir characterization and microseismic imaging. Elastic-waveform inversion of multi-component seismic data can provide high-resolution inversion results of subsurface geophysical properties. However, the method requires seismic data acquired using dense source and receiver arrays. In practice, seismic sources and/or geophones are often sparsely distributed on the surface and/or in a borehole, such as 3D vertical seismic profiling (VSP) surveys. We develop a novel elastic-waveform inversion method with compressive sensing for inversion of sparse seismic data. We employ an alternating-minimization algorithm to solve the optimization problem of our new waveform inversion method. We validate our new method using synthetic VSP data for a geophysical model built using geologic features found at the Raft River enhanced-geothermal-system (EGS) field. We apply our method to synthetic VSP data with a sparse source array and compare the results with those obtained with a dense source array. Our numerical results demonstrate that the velocity models produced with our new method using a sparse source array are almost as accurate as those obtained using a dense source array.

58 GEOSCIENCES↗
DOE OSTI2022

Internal 2-D Surface Temperature Measurements for Large Complex Geometries

For 2D-temperature monitoring applications, a variant of EIT (Electrical Impedance Tomography) is evaluated computationally in this work. Literature examples of poor sensor performance in the center of the 2D domains away from the side electrodes motivated this study which seeks to overcome some of the previously noted shortcomings. In particular, the use of ‘sensing skins’ with novel tailored baseline conductivities were examined using the EIDORS package for EIT. It was found that the best approach for detecting a hot spot depends on several factors such as the current injection (stimulation) patterns, the measurement patterns, and the reconstruction algorithms. For a well-performing combination of these factors, tailored baseline conductivities were assessed and compared to the baseline uniform conductivity. It was discovered that for some EIT applications, a tailored distribution needs to be smooth and that sudden changes in the conductivity gradients should be avoided. Still, the benefits in terms of improved EIT performance were small for conditions for which the EIT measurements had been ‘optimized’ for the uniform baseline case. Within the limited scope of this study, only two specific cases showed benefits from tailored distributions. For one case, a smooth tailored distribution with increased baseline conductivity in the center provided a better separation of two centrally located hot spots. For another case, a smooth tailored distribution with reduced conductivity in the center provided better estimates of the magnitudes of two hot spots near the center of the sensing skin.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Vegetation biogeography is a main source of uncertainty in modelling the land carbon cycle

The terrestrial biosphere exchanges a large amount of CO 2 with the atmosphere through photosynthesis and respiration, determining the magnitude of land carbon sink and consequently influencing the rate of global warming. The magnitudes of global photosynthesis and respiration, however, vary widely across models (100-200 PgC/year), constituting a key and persistent source of uncertainty in carbon cycle and climate modelling. Here, we argue that the uncertainty in the land carbon cycle modelling is largely attributable to the uncertainty in biogeography – the distribution of plant functional types (PFTs). Using an ensemble of dynamic global vegetation models (DGVMs), we find a strong dependence of total photosynthesis on total area for each PFT. The dependence allows us to reduce the spread of land carbon cycle estimates by ~75% using remote sensing-based PFT maps. We further find that 56 ± 21% of climate-driven changes in global photosynthesis modelled by DGVMs are caused by changes in PFT distribution in the last two decades. Our study identifies vegetation biogeography as a main controlling factor of uncertainty in land carbon cycle modelling and highlights the importance of biogeography-climate interactions in carbon cycle and climate studies.

Zhao, Ruiying [National Univ. of Singapore (Singap↗
NASA NTRS1999

Cloud Thickness from Diffusion of Lidar Pulses in Clouds

Measurements of the distribution of reflected light from a laser beam incident on an aqueous suspension of particles or "cloud" with known thickness and particle size distribution are reported. The distribution is referred to as the "cloud radiative Green's function", G. In the diffusion domain, G is sensitive to cloud thickness, allowing that important quantity to be retrieved. The goal of the laboratory simulation is to provide preliminary estimates of sensitivity of G to cloud thickness,for use in the optimal design of an offbeam Lidar instrument for remote sensing of cloud thickness (THOR, Thickness from Offbeam Returns). These clouds of polystyrene microspheres suspended in water are analogous to real clouds of water droplets suspended in air. The microsphere size distribution is roughly lognormal, from 0.5 microns to 25 microns, similar to real clouds. Density of suspended spheres is adjusted so mean-free-path of visible photons is about 10 cm, approximately 1000 times smaller than in real clouds. The light source is a ND:YAG laser at 530 nm. Detectors are flux and photon-counting Photomultiplier Tube (PMTS), with a glass probe for precise positioning. A Labview 5 VI controls positioning, and data acquisition, via an NI Motion Control board connected to a stepper motor driving an Edmund linear slider, and a 16-channel 16-bit NI-DAQ board. The stepper motor is accurate to 10 microns, and step size is selectable from the VI software. Far from the incident beam, the rate of exponential increase as the direction of the incident beam is approached scales as expected from diffusion theory, linearly with the cloud thickness, and inversely as the square root of the reduced optical thickness, and is independent of particle size. Near the beam the signal begins to increase faster than exponential, due to single and low-order scattering near the backward direction, and here the distribution depends on particle size. Results are being used to verify 3D Monte Carlo radiative transfer simulations, used to estimate signal-to-noise ratios for remotely sensed off beam returns, for both homogeneous and inhomogeneous clouds. Signal-to-noise estimates show that unfiltered observations are straight forward at night, while narrow band pass filters are being studied for day.

Cahalan, Robert F.↗
NASA NTRSDate not supplied

Sensitivity of Single-Scattering Properties to Precipitation Particle Meltwater Geometry for GPM Passive Microwave and Radar Remote Sensing Applications

The objective of the current work is to describe the microwave single-scattering properties of partially melted ice-phase precipitation particles using physically-based computational methods, taking into full account the varied geometries of the initially “dry” ice particles and the distributions of liquid water that develop during the melting process. Ultimately, the bulk properties of ensembles of these partially-melted particles will be included in “scattering tables” to support radar and combined radar-radiometer remote sensing of precipitation. A meshless Lagrangian melting procedure (snowMELT) based on smoothed-particle hydrodynamics is applied to both spherical and finely-structured ice particle models to describe the full evolution of the particles from dry ice particles to liquid drops. The melting of spherical ice particles using snowMELT is compared to an alternative continuum physics model to validate melt times and internal thermodynamics. The discrete dipole approximation is then utilized to calculate the single-scattering properties of different mixed-phase particles throughout the melting process. The sensitivities of particle single-scattering properties to thermodynamic and hydrodynamic assumptions in snowMELT are explored, and the implications for combined radar-radiometer precipitation remote sensing from GPM are discussed.

William S Olson↗
DOE OSTI2017

A Dynamic Landsat Derived Normalized Difference Vegetation Index (NDVI) Product for the Conterminous United States

Satellite derived vegetation indices (VIs) are broadly used in ecological research, ecosystem modeling, and land surface monitoring. The Normalized Difference Vegetation Index (NDVI), perhaps the most utilized VI, has countless applications across ecology, forestry, agriculture, wildlife, biodiversity, and other disciplines. Calculating satellite derived NDVI is not always straight-forward, however, as satellite remote sensing datasets are inherently noisy due to cloud and atmospheric contamination, data processing failures, and instrument malfunction. Readily available NDVI products that account for these complexities are generally at coarse resolution; high resolution NDVI datasets are not conveniently accessible and developing them often presents numerous technical and methodological challenges. Here, we address this deficiency by producing a Landsat derived, high resolution (30 m), long-term (30+ years) NDVI dataset for the conterminous United States. We use Google Earth Engine, a planetary-scale cloud-based geospatial analysis platform, for processing the Landsat data and distributing the final dataset. We use a climatology driven approach to fill missing data and validate the dataset with established remote sensing products at multiple scales. We provide access to the composites through a simple web application, allowing users to customize key parameters appropriate for their application, question, and region of interest.

42 ENGINEERING↗
NASA NTRS1997

Entropy Masking

This paper details two projects that use the World Wide Web (WWW) for dissemination of curricula that focus on remote sensing. 1) Presenting grade-school students with the concepts used in remote sensing involves educating the teacher and then providing the teacher with lesson plans. In a NASA-sponsored project designed to introduce students in grades 4 through 12 to some of the ideas and terminology used in remote sensing, teachers from local grade schools and middle schools were recruited to write lessons about remote sensing concepts they could use in their classrooms. Twenty-two lessons were produced and placed in seven modules that include: the electromagnetic spectrum, two- and three-dimensional perception, maps and topography, scale, remote sensing, biotic and abiotic concepts, and landscape chi rise. Each lesson includes a section that evaluates what students have learned by doing the exercise. The lessons, instead of being published in a workbook and distributed to a limited number of teachers, have been placed on a WWW server, enabling much broader access to the package. This arrangement also allows for the lessons to be modified after feedback from teachers accessing the package. 2) Two-year colleges serve to teach trade skills, prepare students for enrollment in senior institutions of learning, and more and more, retrain students who have college degrees in new technologies and skills. A NASA-sponsored curriculum development project is producing a curriculum using remote sensing analysis an Earth science applications. The project has three major goals. First, it will implement the use of remote sensing data in a broad range of community college courses. Second, it will create curriculum modules and classes that are transportable to other community colleges. Third, the project will be an ongoing source of data and curricular materials to other community colleges. The curriculum will have these course pathways to a certificate; a) a Science emphasis, b) an Arts and Letters emphasis, and c) a Computer Science emphasis Each pathway includes course work in remote sensing, geographical information systems (GIS), computer science, Earth science, software and technology utilization, and communication. Distribution of products from this project to other two-year colleges will be accomplished using the WWW.

Watson, Andrew B.↗
NASA NTRS2000

Sensor Needs for Advanced Life Support

Sensors and feedback systems are critical to life support flight systems and life support systems research. New sensor capabilities can allow for new system architectures to be considered, and can facilitate dramatic improvements in system performance. This paper will describe three opportunities for biosensor researchers to develop sensors that will enable life support system improvements. The first opportunity relates to measuring physical, chemical, and biological parameters in the Space Station Water Processing System. Measuring pH, iodine, total organic carbon, microbiological activity, total dissolved solids, or conductivity with a safe, effective, stable, reliable microsensor could benefit the water processing system considerably. Of special interest is a sensor which can monitor biological contamination rapidly. The second opportunity relates to sensing microbiological contamination and water condensation on the surface of large inflatable structures. It is the goal of large inflatable structures used for habitation to take advantage of the large surface area of the structure and reject waste heat passively through the walls of the structure. Too much heat rejection leads to a cold spot with water condensation, and eventually microbiological contamination. A distributed sensor system that can measure temperature, humidity, and microbiological contamination across a large surface would benefit designers of large inflatable habitable structures. The third opportunity relates to sensing microbial bioreactors used for waste water processing and reuse. Microbiological bioreactors offer considerable advantages in weight and power compared to adsorption bed based systems when used for long periods of time. Managing and controlling bioreactors is greatly helped if distributed microsensors measured the biological populations continuously in many locations within the bioreactor. Nitrifying bacteria are of special interest to bioreactor designers, and any sensors that could measure the populations of these types of bacteria would help the control and operation of bioreactors. J

Graf, John C.↗
DOE OSTI2023

Residuals-based distributionally robust optimization with covariate information

We consider data-driven approaches that integrate a machine learning prediction model within distributionally robust optimization (DRO) given limited joint observations of uncertain parameters and covariates. Our framework is flexible in the sense that it can accommodate a variety of regression setups and DRO ambiguity sets. We investigate asymptotic and finite sample properties of solutions obtained using Wasserstein, sample robust optimization, and phi-divergence-based ambiguity sets within our DRO formulations, and explore cross-validation approaches for sizing these ambiguity sets. Through numerical experiments, we validate our theoretical results, study the effectiveness of our approaches for sizing ambiguity sets, and illustrate the benefits of our DRO formulations in the limited data regime even when the prediction model is misspecified.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Microwave Properties of Ice-Phase Hydrometeors for Radar and Radiometers: Sensitivity to Model Assumptions

A simplied framework is presented for assessing the qualitative sensitivities of computed microwave properties, satellite brightness temperatures, and radar reflectivities to assumptions concerning the physical properties of ice-phase hydrometeors. Properties considered included the shape parameter of a gamma size distribution andthe melted-equivalent mass median diameter D0, the particle density, dielectric mixing formula, and the choice of complex index of refraction for ice. We examine these properties at selected radiometer frequencies of 18.7, 36.5, 89.0, and 150.0 GHz; and radar frequencies at 2.8, 13.4, 35.6, and 94.0 GHz consistent with existing and planned remote sensing instruments. Passive and active microwave observables of ice particles arefound to be extremely sensitive to the melted-equivalent mass median diameter D0 ofthe size distribution. Similar large sensitivities are found for variations in the ice vol-ume fraction whenever the geometric mass median diameter exceeds approximately 1/8th of the wavelength. At 94 GHz the two-way path integrated attenuation is potentially large for dense compact particles. The distribution parameter mu has a relatively weak effect on any observable: less than 1-2 K in brightness temperature and up to 2.7 dB difference in the effective radar reflectivity. Reversal of the roles of ice and air in the MaxwellGarnett dielectric mixing formula leads to a signicant change in both microwave brightness temperature (10 K) and radar reflectivity (2 dB). The choice of Warren (1984) or Warren and Brandt (2008) for the complex index of refraction of ice can produce a 3%-4% change in the brightness temperature depression.

Microwave properties↗
NASA NTRS2000

Calibrating Atmospheric Delay for the Cassini Gravitational Wave Experiment

The Cassini spacecraft together with one of the stations of the Deep Space Network (DSN) have been instrumented to carry out extremely precise Doppler tracking that will be used to search for the direct evidence of Gravitational radiation passing through our solar system. The two-way communications link between the ground antenna and the spacecraft constitute an "antenna" for gravitational waves that would perturb the phase of the RF signal in the link. The experiments will be carried out during the long cruise phase of the spacecraft on its journey to Saturn and will be sensitive to gravitational wave perturbations larger than the noise level fluctuations of 3 x 10(exp -15) as measured in the Allan Standard Deviation domain. The use of simultaneous, coherent X- and Ka-Band up and down signals will reduce the errors associated with charged particle fluctuations in the interplanetary medium and Earth's ionosphere to a negligible level. The primary fluctuations in the phase of the signals both to and from the spacecraft are expected to be caused by fluctuations in water vapor in the Earth's atmosphere We have designed and are testing a new atmospheric calibration system (with duplicate components) to sense line-of-sight water vapor and its physical temperature with a goal of calibrating 95% or more of tropospheric path delay fluctuations during the Cassini Gravitational Wave Experiment (GWE). The critical component of the calibration system consists of a newly designed water vapor radiometer having a I degree sensing beamwidth and 0.01 K brightness temperature stability over hour time scales. Auxiliary instrumentation includes a microwave temperature profiler to retrieve the vertical distribution of the vapor physical temperature, and surface meteorology. A detailed error budget has been developed to account for all of the possible sources of error during calibration of the GWE and will be discussed. Two identical calibration systems have been constructed in order to provide capability as well as backup during the actual GWE experiment. We will report on side-by-side testing of the vapor and temperature sensing components of this calibrations system as well as a comparison with a short baseline radio interferometric measurement at our Goldstone complex.

Resch, G. M.↗
NASA NTRS2010

NATO Human View Architecture and Human Networks

The NATO Human View is a system architectural viewpoint that focuses on the human as part of a system. Its purpose is to capture the human requirements and to inform on how the human impacts the system design. The viewpoint contains seven static models that include different aspects of the human element, such as roles, tasks, constraints, training and metrics. It also includes a Human Dynamics component to perform simulations of the human system under design. One of the static models, termed Human Networks, focuses on the human-to-human communication patterns that occur as a result of ad hoc or deliberate team formation, especially teams distributed across space and time. Parameters of human teams that effect system performance can be captured in this model. Human centered aspects of networks, such as differences in operational tempo (sense of urgency), priorities (common goal), and team history (knowledge of the other team members), can be incorporated. The information captured in the Human Network static model can then be included in the Human Dynamics component so that the impact of distributed teams is represented in the simulation. As the NATO militaries transform to a more networked force, the Human View architecture is an important tool that can be used to make recommendations on the proper mix of technological innovations and human interactions.

Handley, Holly A. H.↗
DOE OSTI2011

The effects of digital elevation model resolution on the calculation and predictions of topographic wetness indices.

One of the largest exports in the Southeast U.S. is forest products. Interest in biofuels using forest biomass has increased recently, leading to more research into better forest management BMPs. The USDA Forest Service, along with the Oak Ridge National Laboratory, University of Georgia and Oregon State University are researching the impacts of intensive forest management for biofuels on water quality and quantity at the Savannah River Site in South Carolina. Surface runoff of saturated areas, transporting excess nutrients and contaminants, is a potential water quality issue under investigation. Detailed maps of variable source areas and soil characteristics would therefore be helpful prior to treatment. The availability of remotely sensed and computed digital elevation models (DEMs) and spatial analysis tools make it easy to calculate terrain attributes. These terrain attributes can be used in models to predict saturated areas or other attributes in the landscape. With laser altimetry, an area can be flown to produce very high resolution data, and the resulting data can be resampled into any resolution of DEM desired. Additionally, there exist many maps that are in various resolutions of DEM, such as those acquired from the U.S. Geological Survey. Problems arise when using maps derived from different resolution DEMs. For example, saturated areas can be under or overestimated depending on the resolution used. The purpose of this study was to examine the effects of DEM resolution on the calculation of topographic wetness indices used to predict variable source areas of saturation, and to find the best resolutions to produce prediction maps of soil attributes like nitrogen, carbon, bulk density and soil texture for low-relief, humid-temperate forested hillslopes. Topographic wetness indices were calculated based on the derived terrain attributes, slope and specific catchment area, from five different DEM resolutions. The DEMs were resampled from LiDAR, which is a laser altimetry remote sensing method, obtained from the USDA Forest Service at Savannah River Site. The specific DEM resolutions were chosen because they are common grid cell sizes (10m, 30m, and 50m) used in mapping for management applications and in research. The finer resolutions (2m and 5m) were chosen for the purpose of determining how finer resolutions performed compared with coarser resolutions at predicting wetness and related soil attributes. The wetness indices were compared across DEMs and with each other in terms of quantile and distribution differences, then in terms of how well they each correlated with measured soil attributes. Spatial and non-spatial analyses were performed, and predictions using regression and geostatistics were examined for efficacy relative to each DEM resolution. Trends in the raw data and analysis results were also revealed.

09 BIOMASS FUELS↗
DOE OSTI2016

Facile and high spatial resolution ratio-metric luminescence thermal mapping in microfluidics by near infrared excited upconversion nanoparticles

A local area temperature monitor is important for precise control of chemical and biological processes in microfluidics. In this work, we developed a facile method to realize micron spatial resolution of temperature mapping in a microfluidic channel quickly and cost effectively. Based on the temperature dependent fluorescence emission of NaYF{sub 4}:Yb{sup 3+}, Er{sup 3+} upconversion nanoparticles (UCNPs) under near-infrared irradiation, ratio-metric imaging of UCNPs doped polydimethylsiloxane can map detailed temperature distribution in the channel. Unlike some reported strategies that utilize temperature sensitive organic dye (such as Rhodamine) to achieve thermal sensing, our method is highly chemically inert and physically stable without any performance degradation in long term operation. Moreover, this method can be easily scaled up or down, since the spatial and temperature resolution is determined by an optical imaging system. Our method supplied a simple and efficient solution for temperature mapping on a heterogeneous surface where usage of an infrared thermal camera was limited.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗