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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 235 records · Page 13

Comparing Ice Jam Hindcasting Models with Tree Scar Data

Hindcasting models can use historic ice jam observations and hydroclimatic data to identify conditions that form ice jams.However, historic ice jam records are often sparse or incomplete. New sources of historic ice jam data could improve hindcasting models, leading to better ice jam forecasting and flood warning systems. Because ice jams damage riparian trees, marker rings associated with historic scars include information about ice jam frequency and severity. This study examined marker rings from 56 trees along the Muskegon River to supplement the historic ice jam data on this system. The study team compared tree ring data to results from hindcasting models, which were independently validated with newspaper reports on 1,500 separate days. Logistic regression converted the marker ring data into annual ice jam probabilities. Ice jam dates from the dendrochronology data were too noisy to train or validate a hindcasting model. However, the marker ring data did confirm that ice jams on the Muskegon are nonstationary. Ice jams are significantly more likely now than they were before 1966.The marker rings also helped to distinguish between false-negatives and nondetects in the hindcasting model.

Stanford Gibson↗

Aeroservoelastic Uncertainty Model Identification from Flight Data

Uncertainty modeling is a critical element in the estimation of robust stability margins for stability boundary prediction and robust flight control system development. There has been a serious deficiency to date in aeroservoelastic data analysis with attention to uncertainty modeling. Uncertainty can be estimated from flight data using both parametric and nonparametric identification techniques. The model validation problem addressed in this paper is to identify aeroservoelastic models with associated uncertainty structures from a limited amount of controlled excitation inputs over an extensive flight envelope. The challenge to this problem is to update analytical models from flight data estimates while also deriving non-conservative uncertainty descriptions consistent with the flight data. Multisine control surface command inputs and control system feedbacks are used as signals in a wavelet-based modal parameter estimation procedure for model updates. Transfer function estimates are incorporated in a robust minimax estimation scheme to get input-output parameters and error bounds consistent with the data and model structure. Uncertainty estimates derived from the data in this manner provide an appropriate and relevant representation for model development and robust stability analysis. This model-plus-uncertainty identification procedure is applied to aeroservoelastic flight data from the NASA Dryden Flight Research Center F-18 Systems Research Aircraft.

Brenner, Martin J.↗

Using data with models - Ill-posed problems

An attempt is made to show that the combination of data with models leads to a sequence of conventionally ill-posed problems which can be treated in a systematic and practical way by control-theory techniques. The illustrative approach is to exploit the very great mathematical simplifications which result when the methods of finite dimensional vector spaces are used, thus reducing a lot of difficult mathematics to classical least squares. The immediate motivation for this study comes from ocean acoustic tomography.

Wunsch, C.↗

Technical report series on global modeling and data assimilation. Volume 1: Documentation of the Goddard Earth Observing System (GEOS) General Circulation Model, version 1

This technical report documents Version 1 of the Goddard Earth Observing System (GEOS) General Circulation Model (GCM). The GEOS-1 GCM is being used by NASA's Data Assimilation Office (DAO) to produce multiyear data sets for climate research. This report provides a documentation of the model components used in the GEOS-1 GCM, a complete description of model diagnostics available, and a User's Guide to facilitate GEOS-1 GCM experiments.

Suarez, Max J.↗

Super high compression of line drawing data

Models which can be used to accurately represent the type of line drawings which occur in teleconferencing and transmission for remote classrooms and which permit considerable data compression were described. The objective was to encode these pictures in binary sequences of shortest length but such that the pictures can be reconstructed without loss of important structure. It was shown that exploitation of reasonably simple structure permits compressions in the range of 30-100 to 1. When dealing with highly stylized material such as electronic or logic circuit schematics, it is unnecessary to reproduce configurations exactly. Rather, the symbols and configurations must be understood and be reproduced, but one can use fixed font symbols for resistors, diodes, capacitors, etc. Compression of pictures of natural phenomena such as can be realized by taking a similar approach, or essentially zero error reproducibility can be achieved but at a lower level of compression.

Cooper, D. B.↗

A Robust Schema for Storing and Managing Machine Learning Data and Models

- Machine Learning (ML) has enabled models that can improve efficiency and decrease computational cost - ML models are crucial in enabling Integrated Computational Materials Engineering (ICME) - Large data sets require robust means of storing ML data and models

Brandon L. Hearley↗

A Comparison of the Age-Spectra from Data Assimilation Models

We use kinematic and diabatic back trajectory calculations, driven by winds from a general circulation model (GCM) and two different data assimilation systems (DAS), to compute the age spectrum at three latitudes in the lower stratosphere. The age-spectra are compared to chemical transport model (CTM) calculations, and the mean ages from all of these studies are compared to observations. The age spectra computed using the GCM winds show a reasonably well-isolated tropics in good agreement with observations; however, the age spectra determined from the DAS differ from the GCM spectra. For the diabatic trajectory calculations, the age spectrum is too broad as a result of too much exchange between the tropics and mid-latitudes. The age spectrum determined using the kinematic trajectory calculation is less broad and lacks an age offset; both of these features are due to excessive vertical dispersion of parcels. The tropical and mid-latitude mean age difference between the diabatically and kinematically determined age-spectra is about one year, the former being older. The CTM calculation of the age spectrum using the DAS winds shows the same dispersive characteristics of the kinematic trajectory calculation. These results suggest that the current DAS products will not give realistic trace gas distributions for long integrations; they also help explain why the mean ages determined in a number of previous DAS driven CTM's are too young compared with observations. Finally, we note trajectory-generated age spectra show significant age anomalies correlated with the seasonal cycles, and these anomalies can be linked to year-to-year variations in the tropical heating rate. These anomalies are suppressed in the CTM spectra suggesting that the CTM transport is too diffusive.

Schoeberl, Mark R.↗

Eight Year Climatologies from Observational (AIRS) and Model (MERRA) Data

We examine climatologies derived from eight years of temperature, water vapor, cloud, and trace gas observations made by the Atmospheric Infrared Sounder (AIRS) instrument flying on the Aqua satellite and compare them to similar climatologies constructed with data from a global assimilation model, the Modern Era Retrospective-Analysis for Research and Applications (MERRA). We use the AIRS climatologies to examine anomalies and trends in the AIRS data record. Since sampling can be an issue for infrared satellites in low earth orbit, we also use the MERRA data to examine the AIRS sampling biases. By sampling the MERRA data at the AIRS space-time locations both with and without the AIRS quality control we estimate the sampling bias of the AIRS climatology and the atmospheric conditions where AIRS has a lower sampling rate. While the AIRS temperature and water vapor sampling biases are small at low latitudes, they can be more than a few degrees in temperature or 10 percent in water vapor at higher latitudes. The largest sampling biases are over desert. The AIRS and MERRA data are available from the Goddard Earth Sciences Data and Information Services Center (GES DISC). The AIRS climatologies we used are available for analysis with the GIOVANNI data exploration tool. (see, http://disc.gsfc.nasa.gov).

Hearty, Thomas↗

Analysis of Forest Foliage Using a Multivariate Mixture Model

Data with wet chemical measurements and near infrared spectra of ground leaf samples were analyzed to test a multivariate regression technique for estimating component spectra which is based on a linear mixture model for absorbance. The resulting unmixed spectra for carbohydrates, lignin, and protein resemble the spectra of extracted plant starches, cellulose, lignin, and protein. The unmixed protein spectrum has prominent absorption spectra at wavelengths which have been associated with nitrogen bonds.

Hlavka, C. A.↗

Analyzing System on A Chip Single Event Upset Responses using Single Event Upset Data, Classical Reliability Models, and Space Environment Data

We are investigating the application of classical reliability performance metrics combined with standard single event upset (SEU) analysis data. We expect to relate SEU behavior to system performance requirements. Our proposed methodology will provide better prediction of SEU responses in harsh radiation environments with confidence metrics. single event upset (SEU), single event effect (SEE), field programmable gate array devises (FPGAs)

single event effect (SEE)↗

Analysis of Skylab/Apollo Telescope Mount S-056 observations based on a force-free magnetic field model

Data obtained from the S-056 X-ray experiment on Skylab/ATM have been analyzed based on the assumption that the magnetic fields in the chromosphere and lower corona are force-free. Underlying the analysis is the hypothesis that the observed X-ray filaments coincide with magnetic field lines. The photographic recording of the filaments can then be compared with the projection along the line of sight of the computed magnetic field lines of the model. Ground-based observations of the longitudinal magnetic field component complement the X-ray data and are used in the theoretical interpretation.

Meyer, R. X.↗

Analysis of Sting Balance Calibration Data Using Optimized Regression Models

Calibration data of a wind tunnel sting balance was processed using a candidate math model search algorithm that recommends an optimized regression model for the data analysis. During the calibration the normal force and the moment at the balance moment center were selected as independent calibration variables. The sting balance itself had two moment gages. Therefore, after analyzing the connection between calibration loads and gage outputs, it was decided to choose the difference and the sum of the gage outputs as the two responses that best describe the behavior of the balance. The math model search algorithm was applied to these two responses. An optimized regression model was obtained for each response. Classical strain gage balance load transformations and the equations of the deflection of a cantilever beam under load are used to show that the search algorithm s two optimized regression models are supported by a theoretical analysis of the relationship between the applied calibration loads and the measured gage outputs. The analysis of the sting balance calibration data set is a rare example of a situation when terms of a regression model of a balance can directly be derived from first principles of physics. In addition, it is interesting to note that the search algorithm recommended the correct regression model term combinations using only a set of statistical quality metrics that were applied to the experimental data during the algorithm s term selection process.

Ulbrich, N.↗

An overview of the NASA electronic components information management system

The NASA Parts Project Office (NPPO) comprehensive data system to support all NASA Electric, Electronic, and Electromechanical (EEE) parts management and technical data requirements is described. A phase delivery approach is adopted, comprising four principal phases. Phases 1 and 2 support Space Station Freedom (SSF) and use a centralized architecture with all data and processing kept on a mainframe computer. Phases 3 and 4 support all NASA centers and projects and implement a distributed system architecture, in which data and processing are shared among networked database servers. The Phase 1 system, which became operational in February of 1990, implements a core set of functions. Phase 2, scheduled for release in 1991, adds functions to the Phase 1 system. Phase 3, to be prototyped beginning in 1991 and delivered in 1992, introduces a distributed system, separate from the Phase 1 and 2 system, with a refined semantic data model. Phase 4 extends the data model and functionality of the Phase 3 system to provide support for the NASA design community, including integration with Computer Aided Design (CAD) environments. Phase 4 is scheduled for prototyping in 1992 to 93 and delivery in 1994.

Kramer, G.↗

An Extensible, Interchangeable and Sharable Database Model for Improving Multidisciplinary Aircraft Design

Crucial to an efficient aircraft simulation-based design is a robust data modeling methodology for both recording the information and providing data transfer readily and reliably. To meet this goal, data modeling issues involved in the aircraft multidisciplinary design are first analyzed in this study. Next, an XML-based. extensible data object model for multidisciplinary aircraft design is constructed and implemented. The implementation of the model through aircraft databinding allows the design applications to access and manipulate any disciplinary data with a lightweight and easy-to-use API. In addition, language independent representation of aircraft disciplinary data in the model fosters interoperability amongst heterogeneous systems thereby facilitating data sharing and exchange between various design tools and systems.

Lin, Risheng↗

Weather Intelligent Navigation Data and Models for Aviation Planning (WINDMAP)

WINDMAP addresses the emerging needs in the aviation community of providing real-time weather forecasting to improve the safety of low altitude aircraft operations. This is accomplished through the integration of real-time observations from autonomous systems, such as drones and urban air taxis, with numerical weather prediction models and flight management and safety systems. To solve this problem, several technical challenges have been identified. These include (1) developing autonomous UAS capable of conducting observations accurately and reliably; (2) determining the number and frequency of required observations and the sensitivity of these observations in data sparse regions of the lower atmosphere;(3) assimilating dense observational data into models in real-time with sufficient resolution and accuracy; (4) developing novel physics-based reduced order models capable of incorporating diverse data sets; and (5)integrating real-time forecasting into UTM and DAA (detect-and-avoid) architectures for path planning and navigation. The goal of this proposed effort is to demonstrate the value of using small UAS to collect measurements of the dynamic and thermodynamic properties of the lower atmosphere at scales that match or exceed the spatio-temporal resolution of today’s best numerical weather prediction models

Koushik Datta↗

The interior structure of Jupiter (Consequences of Pioneer 10 data)

Models of the Jovian interiors based on theoretical equations of state of hydrogen and helium supported by a few experimental points and on observed parameters such as oblateness, gravitational coefficients, heat emission, magnetic fields, are discussed. The models fall into three categories: (1) those that assume a uniform and rather low H2/He ratio throughout the planet; (2) those in which this ratio is solar and thus higher; and (3) those that take into account the lack of complete miscibility of the two elements in the condensed state. It appears now also that within the limits of error the planet is in a hydrostatic equilibrium. The large heat emission and the need for an efficient source of internal heat are confirmed, but the results do not indicate which one of the various possible mechanisms is favored, although new evolutionary models suggest that the primordial heat may be insufficient. A new red spot has been discovered. Finally, the presence of a highly eccentric and inclined magnetic field poses new problems related to the pattern of internal convection and to the possibility of a north-south asymmetry of the interior. Further analysis of the available data may throw additional light on these questions.

Smoluchowski, R.↗

A Large-Grain Mapping Approach for Multiprocessor Systems Through Data Flow Model Ph.D. Thesis

A large-grain level mapping method is presented of numerical oriented applications onto multiprocessor systems. The method is based on the large-grain data flow representation of the input application and it assumes a general interconnection topology of the multiprocessor system. The large-grain data flow model was used because such representation best exhibits inherited parallelism in many important applications, e.g., CFD models based on partial differential equations can be presented in large-grain data flow format, very effectively. A generalized interconnection topology of the multiprocessor architecture is considered, including such architectural issues as interprocessor communication cost, with the aim to identify the 'best matching' between the application and the multiprocessor structure. The objective is to minimize the total execution time of the input algorithm running on the target system. The mapping strategy consists of the following: (1) large-grain data flow graph generation from the input application using compilation techniques; (2) data flow graph partitioning into basic computation blocks; and (3) physical mapping onto the target multiprocessor using a priority allocation scheme for the computation blocks.

Kim, Hwa-Soo↗

Evaluation of Vertical Patterns in Chlorophyll-A Derived From A Data Assimilating Model of Satellite-Based Ocean Color

Satellite-based sensors of ocean color have become the primary tool to infer changes in surface chlorophyll, while BGC-Argo floats are now filling the information gap at depth. Here we use BGC-Argo data to assess depth-resolved information on chlorophyll-a derived from an ocean biogeochemical model constrained by the assimilation of surface ocean color remote sensing. The data-assimilating model replicates well the general seasonality and meridional gradients in surface and depth-resolved chlorophyll-a inferred from the float array in the Southern Ocean. On average, the model tends to overestimate float-based chlorophyll, particularly at times and locations of high productivity such as the beginning of the spring bloom, subtropical deep chlorophyll maxima, and non-iron limited regions of the Southern Ocean. The highest model RMSE in the upper 50 m with respect to the float array is of 0.6 mg Chl m −3 , which should allow the detection of seasonal changes in float-based biomass (varying between 0.01 and >1 mg Chl m −3 ) but might hinder the identification of subtle changes in chlorophyll at narrow local scales. Both model and float profiling data show good agreement with in situ data from station ALOHA, with model estimates showing a slight accuracy edge in inferring depth-resolved observations. Uncertainties in float bio-optical estimates impede their use as a reliable benchmark for validation, but the general qualitative agreement between model and float data provides confidence in the ability of model to replicate biogeochemical features below the surface, where data is not directly constrained by the assimilation of satellite ocean color.

Lionel A Quintero↗