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At least 37 records · Page 2

River streamflow, remotely-sensed water quality, and benthic composition of previously undescribed nearshore coral reefs in northern Puerto Rico

Land-based sediment stress represents a threat to many coral reefs in Puerto Rico primarily as a result of unrestricted land cover/land use changes and poor best management practices. The effects of such stresses have been documented along most coasts around the island. However, little attention has been paid to reefs located on the north coast, and very little is known about their composition and current state. Here, we present a study characterizing riverine inputs, water quality conditions, and benthic composition of two previously undescribed coral reefs (Tómbolo and Machuca reefs) located just eastward of the Río Grande de Manatí outlet in north-central Puerto Rico. This study utilizes a time series of remotely sensed ocean color products (diffuse vertical attenuation coefficient at 490 nm [Kd490] and chlorophyll-a concentration [Chl-a] estimated with data from the Visible Infrared Imaging Radiometer Suite [VIIRS]) to characterize water quality in this coastal region. In general, the months with relatively high mean daily river streamflow also coincide with months having the highest proportion of eastward wave direction, which can promote the eastward influence of river waters towards the two coral reefs sites. Kd490 and Chl-a showed a higher riverine influence closer to the watershed outlet. Kd490 and Chl-a monthly peaks also coincide with river streamflow highs, particularly at those pixels closer to shore. Tómbolo Reef, located farther eastward of the river outlet, shows a well-developed primary reef framework mainly composed of threatened reef-building species (Acropora palmata, Pseudodiploria) and high coral cover (19-51%). The benthos of Machuca Reef, located closer to the river outlet, is dominated by macroalgae with a significantly lower coral cover (0.2-2.7%) mainly composed of “weedy” coral species (Porites astroides, and S. radians). Cover of major benthic components correlates with distance from the river outlet, and with gradients in Kd490 and Chl-a, with higher coral cover and lower macroalgal cover farther from the river outlet. Coral cover at Tómbolo Reef is higher than what has been reported for similar sites around Puerto Rico and other Caribbean islands showing its ecological importance and, as up until now, an unrecognized potential refuge of reef-building threatened coral species.

benthic cover

Electrostatic Regolith Interaction Experiment (ERIE) Electrometer Instrument Development

The Electrostatic Regolith Interaction Experiment (ERIE) is a joint venture between the University of Central Florida (UCF) Center for Microgravity Research (CMR) and the NASA Kennedy Space Center (KSC) Electrostatics and Surface Physics Laboratory (ESPL) seeking to examine charged dust grain behavior in a microgravity environment. Two separate systems have been combined for this suborbital flight experiment: the COLLisions Into Dust Experiment (COLLIDE) developed by the UCF CMR and the Wheel Electrostatic Spectrometer (WES) developed by the NASA KSC ESPL. This combination will advance the understanding of the natural and induced charged grain behavior on the Moon, asteroids, and other low gravity bodies comprised of charged dust particles. COLLIDE retains granular material under vacuum in a shallow tray behind a metal door, which then opens and releases the particles into a larger open volume when microgravity is achieved. The experiment is observed with a high-speed camera, such that the motions of these particles can then be tracked so the kinematics of each grain may be analyzed. The original application for this apparatus was to study cratering events into granular beds, but electrostatic repulsion was detected in the early frames of the video data returned from completed experiments, so a re-flight with a focus on these events was proposed. Agitation of the grains during launch combined with the frictional charge transfer between the grains and the door as it slides open provides an opportunity to use this setup to observe material tribocharging and charged particle behaviors in microgravity. In this updated version, the charged particles released into the chamber will traverse through an electric field produced by high voltage parallel plates and their resulting trajectories will be determined by their net charges. WES was originally developed to characterize the triboelectric properties of the Martian regolith through the contact of a rover wheel with the surface as it rotates. Improvements were made upon this legacy system to develop a sensor suite that will be installed within the COLLIDE door to measure charge transferred between the granular material and insulating disks protruding through the door. These insulator disks span the triboelectric series so, as they slide across the particulate matter when the door opens, each will accumulate a charge consistent with its relative position to the grains within the series. This charge on each insulator is distributed between two capacitances in series with an electrometer amplifier returning an analog voltage proportional to the charge accumulated. Calibration of this system has been performed using applications of known charge to the inputs and characterization of the frictional charge transfer between various regolith simulants and the sensor insulators is currently being examined in the lab.

Electrostatics

Layered recognition networks that pre-process, classify, and describe

A brief overview is presented of six types of pattern recognition programs that: (1) preprocess, then characterize; (2) preprocess and characterize together; (3) preprocess and characterize into a recognition cone; (4) describe as well as name; (5) compose interrelated descriptions; and (6) converse. A computer program (of types 3 through 6) is presented that transforms and characterizes the input scene through the successive layers of a recognition cone, and then engages in a stylized conversation to describe the scene.

Uhr, L.

Rare earth elements in river waters

To characterize the input to the oceans of rare earth elements (REE) in the dissolved and the suspended loads of rivers, the REE concentrations were measured in samples of Amazon, Indus, Mississippi, Murray-Darling, and Ohio rivers and in samples of smaller rivers that had more distinct drainage basin lithology and water chemistry. It was found that, in the suspended loads of small rivers, the REE pattern was dependent on drainage basin geology, whereas the suspended loads in major rivers had relatively uniform REE patterns and were heavy-REE depleted relative to the North American Shale composite (NASC). The dissolved loads in the five major rivers had marked relative heavy-REE enrichments, relative to the NASC and the suspended material, with the (La/Yb)N ratio of about 0.4 (as compared with the ratio of about 1.9 in suspended loads).

Goldstein, Steven J.

A representational framework and user-interface for an image understanding workstation

Problems in image understanding involve a wide variety of data (e.g., image arrays, edge maps, 3-D shape models) and processes or algorithms (e.g., convolution, feature extraction, rendering). The underlying structure of an Image Understanding Workstation designed to support mulitple levels and types of representations for both data and processes is described, also the user-interface. The Image Understanding Workstation consists of two parts: the Image Understanding (IU) Framework, and the user-interface. The IU Framework is the set of data and process representations. It includes multiple levels of representation for data such as images (2-D), sketches (2-D), surfaces (2 1/2 D), and models (3-D). The representation scheme for processes characterizes their inputs, outputs, and parameters. Data and processes may reside on different classes of machines. The user-interface to the IU Workstation gives the user convenient access for creating, manipulating, transforming, and displaying image data. The user-interface follows the structure of the IU Framework and gives the user control over multiple types of data and processes. Both the IU Framework and user-interface are implemented on a LISP machine.

Schroeder, Joyce D.

Automated synthesis of sequence invariant state machines

A computer aided design (CAD) tool for the design of very large scale integration (VLSI) synchronous sequential controllers is presented. Both the design and layout of the state machine are automatically generated. The program is process independent allowing a choice of design rules to base generation upon. An incremental layout creation approach was implemented which makes the tool useful in a wide range of layout applications. Flow table descriptions are input to characterize the desired machine and a layout archive is output.

Buehler, D.

NASA Stennis Space Center V and V Capabilities Overview

The objective are provide independent field measurement ground capability for satellite and aircraft mounted in-flight sensor validation. NASA Stennis is considering expanding its Verification and Validation (V&V) range to support LIDAR and digital camera characterization. Soliciting input for requirements and suggestion.

Ryan, Robert

An Abstract Interpretation Framework for the Round-Off Error Analysis of Floating-Point Programs

This paper presents an abstract interpretation framework for the round-off error analysis of floating-point programs. This framework defines a parametric abstract analysis that computes, for each combination of ideal and floating-point execution path of the program, a sound over-approximation of the accumulated floating-point round-off error that may occur. In addition, a Boolean expression that characterizes the input values leading to the computed error approximation is also computed. An abstraction on the control flow of the program is proposed to mitigate the explosion of the number of elements generated by the analysis. Additionally, a widening operator is defined to ensure the convergence of recursive functions and loops. An instantiation of this framework is implemented in the prototype tool PRECiSA that generates formal proof certificates stating the correctness of the computed round-off errors.

Titolo, Laura

Advancement of Entry System Modeling to Support Exploration of Giant Planets

This paper describes NASA’s efforts to advance entry system modeling and simulation capabilities to support future exploration of Giant planets. The Giant planets are key destinations of interest to the planetary science community for their potential to provide insight into the formation and evolution of our Solar System, as well as extrasolar planetary systems. To date, the Galileo atmospheric probe is the only purpose-built entry probe to a Giant planet. Post-flight analysis of Galileo’s performance showed that there was significant recession of the thermal protection system (TPS), well beyond what was anticipated on the flank, and this was due in part to insufficiently accurate capability for estimating the flight environment and TPS response. While Galileo ultimately survived its flight, the example serves to highlight the great challenge of designing successful missions for environments that are poorly understood or where models have not yet been validated. An important means to reduce mission risks is the incorporation of physics-based modeling with well-quantified uncertainties. The emphasis on physics-based modeling – in contrast to empirically-driven models – is motivated by the fact that it is impossible to completely replicate entry environments through ground tests and, therefore, extrapolation to the flight environment is required. Basing analysis in fundamental physics removes the bias of ground test limitations, though one must then be careful to properly characterize model inputs, simplifying assumptions, and the limits wherein the model is valid. NASA’s Entry Systems Modeling (ESM) Project is tasked with investigating such considerations for planetary science missions across the Solar System, and in recent years has begun to do so for Giant planets. The most distinctive features of the Giant planets, from an entry system perspective, are the atmospheres composed primarily of hydrogen and helium. The entry velocities of proposed missions are generally very large and can therefore be expected to result in significant convective and radiative heating generated by the vehicle’s shock layer. Yet thermochemical behavior of the hydrogen-helium system is not well understood under such conditions. The ESM project is leading efforts to develop accurate thermochemical databases based on state-of-the-art measurements in the Electric Arc Shock Tube and detailed computational chemistry. The large heat fluxes anticipated by missions has driven interest in new TPS materials, in particular woven materials, which may be enabling but have never been flown before. Consequently, multiscale models are in development to describe properties and performance of the materials from micro- to system-scale. The goal is to not only provide accurate thermal response but also to inform thermostructural reliability predictions for extreme entries. Additionally, new computational models have been developed to evaluate performance of non-destructive evaluation techniques which are vital to establishing acceptance of systems to be free of manufacturing faults like material cracking, voids, and debonding. Finally, in the area of guidance and control, aerocapture has been shown conceptually to provide a number of mission benefits, including reducing transit time and increasing payload fraction. The ESM project is building a launch-to-landing trajectory simulation capability to enable detailed studies of aerocapture maneuvers in the context of Giant planets missions. The final presentation and paper will describe each of these topics in detail, including discussion of specific gaps and the technical approach to solving them. In addition, the final paper will briefly discuss ongoing coordination between ESM project work and an ESA-funded technology development activity comprised of validation testing in the Oxford T6, IRS PWK and IST ESTHER tunnels, as well as state-to-state modeling of the shock layer to better represent non-Boltzmann energy distributions leading to non-equilibrium radiation.

Entry systems

Sources of Uncertainty in the Prediction of LAI / fPAR from MODIS

To explicate the sources of uncertainty in the prediction of biophysical variables over space, consider the general equation: where z is a variable with values on some nominal, ordinal, interval or ratio scale; y is a vector of input variables; u is the spatial support of y and z ; x and u are the spatial locations of y and z , respectively; f is a model and B is the vector of the parameters of this model. Any y or z has a value and a spatial extent which is called its support. Viewed in this way, categories of uncertainty are from variable (e.g. measurement), parameter, positional. support and model (e.g. structural) sources. The prediction of Leaf Area Index (LAI) and the fraction of absorbed photosynthetically active radiation (fPAR) are examples of z variables predicted using model(s) as a function of y variables and spatially constant parameters. The MOD15 algorithm is an example of f, called f(sub 1), with parameters including those defined by one of six biome types and solar and view angles. The Leaf Canopy Model (LCM)2, a nested model that combines leaf radiative transfer with a full canopy reflectance model through the phase function, is a simpler though similar radiative transfer approach to f(sub 1). In a previous study, MOD15 and LCM2 gave similar results for the broadleaf forest biome. Differences between these two models can be used to consider the structural uncertainty in prediction results. In an effort to quantify each of the five sources of uncertainty and rank their relative importance for the LAI/fPAR prediction problem, we used recent data for an EOS Core Validation Site in the broadleaf biome with coincident surface reflectance, vegetation index, fPAR and LAI products from the Moderate Resolution Imaging Spectrometer (MODIS). Uncertainty due to support on the input reflectance variable was characterized using Landsat ETM+ data. Input uncertainties were propagated through the LCM2 model and compared with published uncertainties from the MOD15 algorithm.

Dungan, Jennifer L.

Urban Landscape Characterization Using Remote Sensing Data For Input into Air Quality Modeling

The urban landscape is inherently complex and this complexity is not adequately captured in air quality models that are used to assess whether urban areas are in attainment of EPA air quality standards, particularly for ground level ozone. This inadequacy of air quality models to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well these models predict ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to meteorological and air quality models focusing on the Atlanta, Georgia metropolitan area as a case study. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality.

Quattrochi, Dale A.

Leveraging explainable AI to characterize floating-point exceptions in linear solvers

Linear solver packages are central to many scientific, engineering, and machine learning applications. When floating-point exceptions occur in these solvers, e.g., division by zero or overflow, numerical results are compromised and become unreliable. Existing static and dynamic analysis tools can detect such exceptions, but they do not explain why the exceptions occur in terms of the solver inputs. Here, we present a study to characterize the inputs that cause numerical exceptions in linear solver packages. Our approach uses explainable AI (XAI) to find the most relevant characteristics of input matrices that explain the occurrence of exceptions in the solvers. Since training data in this domain is scarce, we perform extensive data gathering and data augmentation to obtain exception-inducing inputs. Our approach uses a repair strategy on the features blamed by XAI to validate that such features indeed explain the exceptions. We compare the LIME and SHAP XAI techniques using a dozen matrix features with three classifiers. We evaluate the approach on three widely used linear solver packages and find that some input characteristics can explain the occurrence of exceptions 100% of the time, in specific solvers and preconditioners.

Explainable AI

Layered 'recognition cone' networks that pre-process, classify, and describe.

A sequence of six types of pattern recognition system is examined. A program is described to illustrate some of the features developed. The first type (similar to many of the programs currently used) preprocesses by applying layers of local averaging and differencing transforms to smooth, fill in gaps and heighten contours, curves, and angles. It then applies a set of characterizers, each of which implies a set of names. The program chooses the single most high implied name. The second type combines the preprocessing transforms and the characterizers into a single operation of general type. Transforms build up a next representation of the input, while the characterizers imply the output name. The third type erases the distinction between a transform and an implication. Now all outputs are stored in the next transform layer. As the program averages information, its layers shrink, so that the system builds a cone of layers. When the program reaches the apex (a layer of only one cell that contains all the information), it chooses the single name with which it classifies the input. The fourth type is capable of choosing more than one name and, therefore, can both describe and classify the scene. The fifth type examines the interrelations among the set of names chosen. The sixth step can be taken to converse about the scene, developing an appropriate description in response to suggestions and queries. This allows the program to perform more computations and to look again on demand.

Uhr, L.

Frequency domain synthesis of optimal inputs for adaptive identification and control

The input design problem of selecting appropriate inputs for use in SISO adaptive identification and model reference adaptive control algorithms is considered. Averaging theory is used to characterize the optimal inputs in the frequency domain. The design problem is formulated as an optimization problem which maximizes the smallest eigenvalue of the average information matrix over power constrained signals, and the global optimal solution is obtained using a convergent numerical algorithm. A bound on the frequency search range required in the design algorithm has been determined in terms of the desired performance.

Fu, Li-Chen

Estimated performance and future potential of solar dynamic and photovoltaic power systems for selected LEO and HEO missions

Solar Photo Voltaic (PV) and thermal dynamic power systems for application to selected Low Earth Orbit (LEO) and High Eccentric Orbit (Energy) (HEO) missions are characterized in the regime 7 to 35 kWe. Input parameters to the characterization are varied corresponding to anticipated introduction of improved or new technologies. Comparative assessment is made between the two power system types utilizing newly emerging technologies in cells and arrays, energy storage, optical surfaces, heat engines, thermal energy storage, and thermal management. The assessment is made to common ground rules and assumptions. The four missions (space station, sun-synchronous, Van Allen belt and GEO) are representative of the anticipated range of multi-kWe earth orbit missions. System characterizations include all required subsystems, including power conditioning, cabling, structure, to deliver electrical power to the user. Performance is estimated on the basis of three different levels of component technology: (1) state-of-art, (2) near-term, and (3) advanced technologies. These range from planar array silicon/IPV nickel hydrogen batteries and Brayton systems at 1000 K to thin film GaAs with high energy density secondary batteries or regenerative fuel cells and 1300 K Stirling systems with ultra-lightweight concentrators and radiators. The system estimates include design margin for performance degradations from the known environmental mechanisms (micrometeoroids and space debris, atomic oxygen, electron and proton flux) which are modeled and applied depending on the mission. The results give expected performance, mass and drag of multi-kWe earth orbiting solar power systems and show how overall system figures of merit will improve as new component technologies are incorporated.

Bents, David J.

Estimated performance and future potential of solar dynamic and photovoltaic power systems for selected LEO and HEO missions

Solar photovoltaic and thermal dynamic power systems for application to selected low-earth-orbit (LEO) and high-earth-orbit (HEO) missions are characterized in the regime 7 to 35 kWe. Input parameters to the characterization are varied to correspond to anticipated introduction of improved or new technologies. A comparative assessment is made of the two power system types for emerging technologies in cells and arrays, energy storage, optical surfaces, heat engines, thermal energy storage and thermal management. The assessment is made to common ground rules and assumptions. The four missions (Space Station, sun-synchronous, Van Allen belt, and GEO) are representative of the anticipated range of multikilowatt earth-orbit missions. The results give the expected performance, mass and drag of multikilowatt earth-orbiting solar power systems and show how the overall system figure of merit will improve as new component technologies are incorporated.

Bents, David J.

A comparison of operationally determined atmospheric densities from satellite orbit solutions and the exospheric temperature from the Jacchia-Roberts model

Operational orbit determination by the Flight Dynamics Division at the Goddard Space Flight Center has yielded a data base of orbit solutions covering the onset of solar cycle 22. Solutions for nine satellites include an estimated drag adjustment parameter (rho sub 1) determined by the Goddard Trajectory Determination System (GTDS). The rho sub 1 is used to evaluate correlations between density variations and changes in the following: 10.7-centimeter wavelength solar flux (F sub 10.7), the geomagnetic index A sub p, and two exospheric temperatures (T sub c and T sub infinity) adapted from the Jacchia-Roberts atmospheric density model in GTDS. T sub c depends on the daily and 81-day centered mean F sub 10.7; T sub infinity depends on T sub c and the geomagnetic index K sub p values. The highest correlations are between density and T sub infinity. Correlations with T sub c and F sub 10.7 are lower by 9 and 10 percent, respectively. For most cases, correlations with A sub p are considerably lower; however, significant correlations with A sub p were found for some high-inclination, moderate-altitude orbits. Results from this analysis enhance the understanding of the drag model and the accommodation of atmospheric density variations in the operational orbit determination support. The degree of correlation demonstrates the sensitivity of the orbit determination process to drag variations and to the input parameters that characterize aspects of the atmospheric density model. To this extent, the degree of correlation provides a measure of performance for methods of selecting or modeling the thermospheric densities using the solar F sub 10.7 and geomagnetic data as input to the process.

Ward, D. T.

Analytical ultrasonics for evaluation of composite materials response. Part 2: Generation and detection

To evaluate the response of composite materials, it is imperative that the input excitation as well as the observed output be well characterized. This characterization ideally should be in terms of displacements as a function of time with high spatial resolution. Additionally, the ability to prescribe these features for the excitation is highly desirable. Various methods for generating and detecting ultrasound in advanced composite materials are examined. Characterization and tailoring of input excitation is considered for contact and noncontact, mechanical, and electromechanical devices. Type of response as well as temporal and spatial resolution of detection methods are discussed as well. Results of investigations at Virginia Tech in application of these techniques to characterizing the response of advanced composites are presented.

Duke, J. C., Jr.