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At least 1,279 records · Page 71

A study of the longevity and operational reliability of Goddard Spacecraft, 1960-1980

Compiled data regarding the design lives and lifetimes actually achieved by 104 orbiting satellites launched by the Goddard Spaceflight Center between the years 1960 and 1980 is analyzed. Historical trends over the entire 21 year period are reviewed, and the more recent data is subjected to an examination of several key parameters. An empirical reliability function is derived, and compared with various mathematical models. Data from related studies is also discussed. The results provide insight into the reliability history of Goddard spacecraft an guidance for estimating the reliability of future programs.

Shockey, E. F.↗

Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

Juday, Richard D.↗

Extra Terrestrial Lava Flows

Volcanism has been one of the major processes shaping the surfaces of the terrestrial planets. Lava flows have been identified on the Moon, Mars, Venus, and on Juptier's moon Io. The study of extra-terrestrial lavas has largely relied on the interpretation of remotely acquired imaging, topographic and spectroscopic data. Models relating the final flow morpohology to eruption characteristics and magma chemistry have been important tools in the interpretation of these data.

lava volcanism↗

FE K EMISSION AND ABSORPTION FEATURES IN THE XMM-EPIC SPECTRUM OF THE SEYFERT GALAXY IC 4329A

We present a re-analysis of the XMM-Newton long-look of the X-ray bright Seyfert galaxy IC 4329a. The Fe K bandpass is dominated by two peaks, consistent with emission from neutral or near-neutral Fe Ka and KP. A relativistic diskline model whereby both peaks are the result of one doubly-peaked diskline profile is found to be a poor description of the data. Models using two relativistic disklines are found to describe the emission profile well. A low-inclination, moderately-relativistic dual-diskline model is possible if the contribution from narrow components, due to distant material, is small or absent. A high-inclination, moderately relativistic profile for each peak is possible if there are roughly equal contributions from both the broad and narrow components. Upper limits on Fe XXV and Fe XXVI emission and absorption at the systemic velocity of IC 4329a are obtained. We also present the results of RXTE monitoring of this source obtained so far; the combined XMM-Newton and RXTE data sets allow us to explore the time-resolved spectral behavior of this source on time scales ranging from hours to 2 years. We find no strong evidence for variability of the Fe Ka emission line on any time scale probed, likely due to the minimal level of continuum variability. We detect a narrow absorption line, at a energy of 7.68 keV in the rest frame of the source; its significance has been confirmed using Monte Carlo simulations. This feature is most likely due to absorption from Fe XXVI blueshifted to approximately 0.1c relative to the systemic velocity, making IC 4329a the lowest-redshift AGN known with a high-velocity, highly-ionized outflow component. As is often the case with similar outflows seen in high-luminosity quasars, the estimated mass outflow rate is larger than the inflow accretion rate, signaling that the outflow represents a substantial portion of the total energy budget of the AGN. The outflow could arise from a radiatively-driven disk wind, or it may be in the form of a discrete, transient blob of ejected material.

Markowitz, A.↗

Data-driven causal model discovery and personalized prediction in Alzheimer's disease

Abstract With the explosive growth of biomarker data in Alzheimer’s disease (AD) clinical trials, numerous mathematical models have been developed to characterize disease-relevant biomarker trajectories over time. While some of these models are purely empiric, others are causal, built upon various hypotheses of AD pathophysiology, a complex and incompletely understood area of research. One of the most challenging problems in computational causal modeling is using a purely data-driven approach to derive the model’s parameters and the mathematical model itself, without any prior hypothesis bias. In this paper, we develop an innovative data-driven modeling approach to build and parameterize a causal model to characterize the trajectories of AD biomarkers. This approach integrates causal model learning, population parameterization, parameter sensitivity analysis, and personalized prediction. By applying this integrated approach to a large multicenter database of AD biomarkers, the Alzheimer’s Disease Neuroimaging Initiative, several causal models for different AD stages are revealed. In addition, personalized models for each subject are calibrated and provide accurate predictions of future cognitive status.

Zheng, Haoyang (ORCID:0000000168358242)↗

Efficient high-dimensional variational data assimilation with machine-learned reduced-order models

Abstract. Data assimilation (DA) in geophysical sciences remains the cornerstone of robust forecasts from numerical models. Indeed, DA plays a crucial role in the quality of numerical weather prediction and is a crucial building block that has allowed dramatic improvements in weather forecasting over the past few decades. DA is commonly framed in a variational setting, where one solves an optimization problem within a Bayesian formulation using raw model forecasts as a prior and observations as likelihood. This leads to a DA objective function that needs to be minimized, where the decision variables are the initial conditions specified to the model. In traditional DA, the forward model is numerically and computationally expensive. Here we replace the forward model with a low-dimensional, data-driven, and differentiable emulator. Consequently, gradients of our DA objective function with respect to the decision variables are obtained rapidly via automatic differentiation. We demonstrate our approach by performing an emulator-assisted DA forecast of geopotential height. Our results indicate that emulator-assisted DA is faster than traditional equation-based DA forecasts by 4 orders of magnitude, allowing computations to be performed on a workstation rather than a dedicated high-performance computer. In addition, we describe accuracy benefits of emulator-assisted DA when compared to simply using the emulator for forecasting (i.e., without DA). Our overall formulation is denoted AIEADA (Artificial Intelligence Emulator-Assisted Data Assimilation).

58 GEOSCIENCES↗

A Process for the Creation of T-MATS Propulsion System Models from NPSS Data

A modular thermodynamic simulation package called the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) has been developed for the creation of dynamic simulations. The T-MATS software is designed as a plug-in for Simulink(Trademark) and allows a developer to create system simulations of thermodynamic plants (such as gas turbines) and controllers in a single tool. Creation of such simulations can be accomplished by matching data from actual systems, or by matching data from steady state models and inserting appropriate dynamics, such as the rotor and actuator dynamics for an aircraft engine. This paper summarizes the process for creating T-MATS turbo-machinery simulations using data and input files obtained from a steady state model created in the Numerical Propulsion System Simulation (NPSS). The NPSS is a thermodynamic simulation environment that is commonly used for steady state gas turbine performance analysis. Completion of all the steps involved in the process results in a good match between T-MATS and NPSS at several steady state operating points. Additionally, the T-MATS model extended to run dynamically provides the possibility of simulating and evaluating closed loop responses.

gas path dynamics↗

Paths Forward for Nuclear Energy: Using a Nationwide Post-Stratified Hierarchical Model to Facilitate Matching of New Nuclear Technologies to Receptive Host Communities

This project was a collaboration between the University of Oklahoma (OU) and the University of Michigan (UMich). The overall objective of the project was to address a critical problem facing the siting of nuclear facilities, where there is no mechanism for incorporating public attitudes at a state and local level into decision-making. Utilizing recent advances in data modeling over local spatial scales, the research team created a state and county level map of public attitudes towards nuclear energy. Current estimates for public acceptance of nuclear technologies primarily exists on a national level, and sub-national estimates of public opinion about reactor siting, research facilities, transport routes, or storage and disposal facilities are very scarce. Model results from this project provide a systematic basis for technology developers to evaluate public acceptance across alternative siting options as a critical component for weighing potential benefit-cost tradeoffs for alternative paths to deploy new nuclear facilities. The project utilized data from the largest database of nuclear attitudes in the US, coupled with Census and elections-related data as well as data on social vulnerability and proximity to current nuclear facilities. In addition to modeling public support, the team also developed an interactive map to showcase results, using an online tool called Public and Local Attitudes about Nuclear Energy Technologies (PLANET). The tool allows technology developers and stakeholders to interact with the model results and better understand variation in support for nuclear facility siting on a state and county level. The interactive nature of the tool also allows users to analyze results in a targeted way, by comparing levels of support across different states and/or counties as desired.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A Process for the Creation of T-MATS Propulsion System Models from NPSS Data

A modular thermodynamic simulation package called the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) has been developed for the creation of dynamic simulations. The T-MATS software is designed as a plug-in for Simulink(Registered TradeMark) and allows a developer to create system simulations of thermodynamic plants (such as gas turbines) and controllers in a single tool. Creation of such simulations can be accomplished by matching data from actual systems, or by matching data from steady state models and inserting appropriate dynamics, such as the rotor and actuator dynamics for an aircraft engine. This paper summarizes the process for creating T-MATS turbo-machinery simulations using data and input files obtained from a steady state model created in the Numerical Propulsion System Simulation (NPSS). The NPSS is a thermodynamic simulation environment that is commonly used for steady state gas turbine performance analysis. Completion of all the steps involved in the process results in a good match between T-MATS and NPSS at several steady state operating points. Additionally, the T-MATS model extended to run dynamically provides the possibility of simulating and evaluating closed loop responses.

gas path dynamics↗

A Process for the Creation of T-MATS Propulsion System Models from NPSS data

A modular thermodynamic simulation package called the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) has been developed for the creation of dynamic simulations. The T-MATS software is designed as a plug-in for Simulink (Math Works, Inc.) and allows a developer to create system simulations of thermodynamic plants (such as gas turbines) and controllers in a single tool. Creation of such simulations can be accomplished by matching data from actual systems, or by matching data from steady state models and inserting appropriate dynamics, such as the rotor and actuator dynamics for an aircraft engine. This paper summarizes the process for creating T-MATS turbo-machinery simulations using data and input files obtained from a steady state model created in the Numerical Propulsion System Simulation (NPSS). The NPSS is a thermodynamic simulation environment that is commonly used for steady state gas turbine performance analysis. Completion of all the steps involved in the process results in a good match between T-MATS and NPSS at several steady state operating points. Additionally, the T-MATS model extended to run dynamically provides the possibility of simulating and evaluating closed loop responses.

gas path dynamics↗

A manifold learning perspective on surrogate modeling of nitrate concentration in the Kansas River

Abstract A non-linear surrogate model of nitrate concentration in the Kansas River (USA) is described. The model is an (almost) Piece-wise Linear response surface that provides a mean field approximation to the dynamics of the measured data for nitrate plus nitrite (target product) correlations to turbidity and chlorophyll-a concentrations (input variables). The method extends the United States Geological Survey’s linear procedures for surrogate data modeling allowing for better approximations for river systems exhibiting algal blooms due to nutrient-rich source waters. The model and visualization procedures illustrated in the Kansas River example should be generally applicable to many medium-size rivers in agricultural regions.

Tufillaro, Nicholas (ORCID:0009000628968832)↗

A method for experimental modal separation

A method is described for the numerical simulation of multiple-shaker modal survey testing using simulated experimental data to optimize the shaker force-amplitude distribution for the purpose of isolating individual modes of vibration. Inertia, damping, stiffness, and model data are stored on magnetic disks, available by direct access to the interactive FORTRAN programs which perform all computations required by this relative force amplitude distribution method.

Hallauer, W. L., Jr.↗

Development and validation of an advanced low-order panel method

A low-order potential-flow panel code, PMARC, for modeling complex three-dimensional geometries, is currently being developed at NASA Ames Research Center. The PMARC code was derived from a code named VSAERO that was developed for Ames Research Center by Analytical Methods, Inc. In addition to modeling potential flow over three-dimensional geometries, the present version of PMARC includes several advanced features such as an internal flow model, a simple jet wake model, and a time-stepping wake model. Data management within the code was optimized by the use of adjustable size arrays for rapidly changing the size capability of the code, reorganization of the output file and adopting a new plot file format. Preliminary versions of a geometry preprocessor and a geometry/aerodynamic data postprocessor are also available for use with PMARC. Several test cases are discussed to highlight the capabilities of the internal flow model, the jet wake model, and the time-stepping wake model.

Ashby, Dale L.↗

Design for Vibration Monitoring: A Methodology for Reliable and Cost-Effective Vibration Monitoring

The purpose of health monitoring systems is to detect failures or defects for increased safety and performance and to provide on-condition maintenance with reduced costs. The problems associated with health monitoring systems include high rates of false alarms and missed failures, which make monitoring an unreliable and costly task. The reason for this is that unaccounted variations invalidate signal modeling assumptions. Our approach was to focus on vibration monitoring of rotating components. We analyzed baseline signals to determine statistical variations, identify and model factors that influence vibrations (pre-production vs. post-production variations), determine hit and false alarm rates with baseline flight data, model and predict effects of defects and variations on vibrations, and develop algorithms and metrics for failure and anomaly detection in the presence of variations.

Tumer, Irem Y.↗

NASA Land Information System (LIS) Water Availability to Support Reclamation ET Estimation

The U.S. Bureau of Reclamation identified the remote sensing of evapotranspiration (ET) as an important water flux for study and designated a test site in the Lower Colorado River basin. A consortium of groups will work together with the goal to develop more accurate and cost effective techniques using the enhanced spatial and temporal coverage afforded by remote sensing. ET is a critical water loss flux where improved estimation should lead to better management of Reclamation responsibilities. There are several areas where NASA satellite and modeling data may be useful to meet Reclamation's objectives for improved ET estimation. In this paper we outline one possible contribution to use NASA's data integration capability of the Land Information System (LIS) to provide a merger of observational (in situ and satellite) with physical process models to provide estimates of ET and other water availability outputs (e.g., runoff, soil moisture) retrospectively, in near real-time, and also providing short-term predictions.

Toll, David↗

A-Train Data Depot (ATDD)

ATDD is a web based tool which provides collocated data and display products for a number of A-train instruments Cloudsat, Calipso, OMI, AIRS, MODIS, MLS, POLDER-3, and ECWMF model data. Products provided include Clouds, Aerosols, Water Vapor, Temperatures and trace gases. All input data is online and in HDF4, HDF5 format. Display products include curtain images, horizontal strips, line plot overlays, and GE kmz files. Sample products are shown for two type of events. Hurricane event, Norbert, Oct 8, 2008 and a dust storm event over the Arabian Sea, Nov 13-14, 2008.

Smith, Peter M.↗

Use of Schema on Read in Earth Science Data Archives

Traditionally, NASA Earth Science data archives have file-based storage using proprietary data file formats, such as HDF and HDF-EOS, which are optimized to support fast and efficient storage of spaceborne and model data as they are generated. The use of file-based storage essentially imposes an indexing strategy based on data dimensions. In most cases, NASA Earth Science data uses time as the primary index, leading to poor performance in accessing data in spatial dimensions. For example, producing a time series for a single spatial grid cell involves accessing a large number of data files. With exponential growth in data volume due to the ever-increasing spatial and temporal resolution of the data, using file-based archives poses significant performance and cost barriers to data discovery and access. Storing and disseminating data in proprietary data formats imposes an additional access barrier for users outside the mainstream research community. At the NASA Goddard Earth Sciences Data Information Services Center (GES DISC), we have evaluated applying the schema-on-read principle to data access and distribution. We used Apache Parquet to store geospatial data, and have exposed data through Amazon Web Services (AWS) Athena, AWS Simple Storage Service (S3), and Apache Spark. Using the schema-on-read approach allows customization of indexing spatially or temporally to suit the data access pattern. The storage of data in open formats such as Apache Parquet has widespread support in popular programming languages. A wide range of solutions for handling big data lowers the access barrier for all users. This presentation will discuss formats used for data storage, frameworks with This presentation will discuss formats used for data storage, frameworks with support for schema-on-read used for data access, and common use cases covering data usage patterns seen in a geospatial data archive.

cloud applications↗

Learjet Flight Test Update

The presentation provides an update on progress towards an acoustic test with a Lear 25 aircraft. The intent of the test is to acquire data that will be used to determine the ability to predict jet noise for future supersonic aircraft at takeoff from scale-model data acquired in wind tunnels. Flight and instrumentation details are provided for the flight test planned for 2022.

Electric Motor Noise↗