Search NASA⌕ Search

SEARCH · Search NASA

Results for “parameter subset selection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Long-Term Variations of the EOP and ICRF2

We analyzed the time series of the coordinates of the ICRF radio sources. We show that part of the radio sources, including the defining sources, shows a significant apparent motion. The stability of the celestial reference frame is provided by a no-net-rotation condition applied to the defining sources. In our case this condition leads to a rotation of the frame axes with time. We calculated the effect of this rotation on the Earth orientation parameters (EOP). In order to improve the stability of the celestial reference frame we suggest a new method for the selection of the defining sources. The method consists of two criteria: the first one we call cosmological and the second one kinematical. It is shown that a subset of the ICRF sources selected according to cosmological criteria provides the most stable reference frame for the next decade.

Zharov, Vladimir↗
NASA NTRS1977

Utility of correlation techniques in gravity and magnetic interpretation

Internal correspondence uses Poisson's Theorem in a moving-window linear regression analysis between the anomalous first vertical derivative of gravity and total magnetic field reduced to the pole. The regression parameters provide critical information on source characteristics. The correlation coefficient indicates the strength of the relation between magnetics and gravity. Slope value gives delta j/delta sigma estimates of the anomalous source. The intercept furnishes information on anomaly interference. Cluster analysis consists of the classification of subsets of data into groups of similarity based on correlation of selected characteristics of the anomalies. Model studies are used to illustrate implementation and interpretation procedures of these methods, particularly internal correspondence. Analysis of the results of applying these methods to data from the midcontinent and a transcontinental profile shows they can be useful in identifying crustal provinces, providing information on horizontal and vertical variations of physical properties over province size zones, validating long wavelength anomalies, and isolating geomagnetic field removal problems.

Chandler, V. W.↗
NASA NTRS1988

Orbiter Flying Qualities (OFQ) Workstation user's guide

This project was devoted to the development of a software package, called the Orbiter Flying Qualities (OFQ) Workstation, for working with the OFQ Archives which are specially selected sets of space shuttle entry flight data relevant to flight control and flying qualities. The basic approach to creation of the workstation software was to federate and extend commercial software products to create a low cost package that operates on personal computers. Provision was made to link the workstation to large computers, but the OFQ Archive files were also converted to personal computer diskettes and can be stored on workstation hard disk drives. The primary element of the workstation developed in the project is the Interactive Data Handler (IDH) which allows the user to select data subsets from the archives and pass them to specialized analysis programs. The IDH was developed as an application in a relational database management system product. The specialized analysis programs linked to the workstation include a spreadsheet program, FREDA for spectral analysis, MFP for frequency domain system identification, and NIPIP for pilot-vehicle system parameter identification. The workstation also includes capability for ensemble analysis over groups of missions.

Myers, Thomas T.↗
NASA NTRS2007

Preliminary Performance Analyses of the Constellation Program ARES 1 Crew Launch Vehicle

By the time NASA's Exploration Systems Architecture Study (ESAS) report had been released to the public in December 2005, engineers at NASA's Marshall Space Flight Center had already initiated the first of a series of detailed design analysis cycles (DACs) for the Constellation Program Crew Launch Vehicle (CLV), which has been given the name Ares I. As a major component of the Constellation Architecture, the CLV's initial role will be to deliver crew and cargo aboard the newly conceived Crew Exploration Vehicle (CEV) to a staging orbit for eventual rendezvous with the International Space Station (ISS). However, the long-term goal and design focus of the CLV will be to provide launch services for a crewed CEV in support of lunar exploration missions. Key to the success of the CLV design effort and an integral part of each DAC is a detailed performance analysis tailored to assess nominal and dispersed performance of the vehicle, to determine performance sensitivities, and to generate design-driving dispersed trajectories. Results of these analyses provide valuable design information to the program for the current design as well as provide feedback to engineers on how to adjust the current design in order to maintain program goals. This paper presents a condensed subset of the CLV performance analyses performed during the CLV DAC-1 cycle. Deterministic studies include development of the CLV DAC-1 reference trajectories, identification of vehicle stage impact footprints, an assessment of launch window impacts to payload performance, and the computation of select CLV payload partials. Dispersion studies include definition of input uncertainties, Monte Carlo analysis of trajectory performance parameters based on input dispersions, assessment of CLV flight performance reserve (FPR), assessment of orbital insertion accuracy, and an assessment of bending load indicators due to dispersions in vehicle angle of attack and side slip angle. A short discussion of the various customers for the dispersion results, along with results and ramifications of each study, are also provided.

Phillips, Mark↗
NASA NTRS2016

Initial Navigation Alignment of Optical Instruments on GOES-R

Post-launch alignment errors for the Advanced Baseline Imager (ABI) and Geospatial Lightning Mapper (GLM) on GOES-R may be too large for the image navigation and registration (INR) processing algorithms to function without an initial adjustment to calibration parameters. We present an approach that leverages a combination of user-selected image-to-image tie points and image correlation algorithms to estimate this initial launch-induced offset and calculate adjustments to the Line of Sight Motion Compensation (LMC) parameters. We also present an approach to generate synthetic test images, to which shifts and rotations of known magnitude are applied. Results of applying the initial alignment tools to a subset of these synthetic test images are presented. The results for both ABI and GLM are within the specifications established for these tools, and indicate that application of these tools during the post-launch test (PLT) phase of GOES-R operations will enable the automated INR algorithms for both instruments to function as intended.

geolocation↗
NASA NTRS2005

Surveillance system and method having parameter estimation and operating mode partitioning

A system and method for monitoring an apparatus or process asset including creating a process model comprised of a plurality of process submodels each correlative to at least one training data subset partitioned from an unpartitioned training data set and each having an operating mode associated thereto; acquiring a set of observed signal data values from the asset; determining an operating mode of the asset for the set of observed signal data values; selecting a process submodel from the process model as a function of the determined operating mode of the asset; calculating a set of estimated signal data values from the selected process submodel for the determined operating mode; and determining asset status as a function of the calculated set of estimated signal data values for providing asset surveillance and/or control.

Bickford, Randall L.↗
NASA NTRS1987

On determining important aspects of mathematical models: Application to problems in physics and chemistry

The use of parametric and functional gradient sensitivity analysis techniques is considered for models described by partial differential equations. By interchanging appropriate dependent and independent variables, questions of inverse sensitivity may be addressed to gain insight into the inversion of observational data for parameter and function identification in mathematical models. It may be argued that the presence of a subset of dominantly strong coupled dependent variables will result in the overall system sensitivity behavior collapsing into a simple set of scaling and self similarity relations amongst elements of the entire matrix of sensitivity coefficients. These general tools are generic in nature, but herein their application to problems arising in selected areas of physics and chemistry is presented.

Rabitz, Herschel↗
NASA NTRS1979

NLSCIDNT user's guide maximum likehood parameter identification computer program with nonlinear rotorcraft model

A nonlinear, maximum likelihood, parameter identification computer program (NLSCIDNT) is described which evaluates rotorcraft stability and control coefficients from flight test data. The optimal estimates of the parameters (stability and control coefficients) are determined (identified) by minimizing the negative log likelihood cost function. The minimization technique is the Levenberg-Marquardt method, which behaves like the steepest descent method when it is far from the minimum and behaves like the modified Newton-Raphson method when it is nearer the minimum. Twenty-one states and 40 measurement variables are modeled, and any subset may be selected. States which are not integrated may be fixed at an input value, or time history data may be substituted for the state in the equations of motion. Any aerodynamic coefficient may be expressed as a nonlinear polynomial function of selected 'expansion variables'.

Source record↗
NASA NTRS2003

Surveillance system and method having parameter estimation and operating mode partitioning

A system and method for monitoring an apparatus or process asset including partitioning an unpartitioned training data set into a plurality of training data subsets each having an operating mode associated thereto; creating a process model comprised of a plurality of process submodels each trained as a function of at least one of the training data subsets; acquiring a current set of observed signal data values from the asset; determining an operating mode of the asset for the current set of observed signal data values; selecting a process submodel from the process model as a function of the determined operating mode of the asset; calculating a current set of estimated signal data values from the selected process submodel for the determined operating mode; and outputting the calculated current set of estimated signal data values for providing asset surveillance and/or control.

Bickford, Randall L.↗
NASA NTRS2022

VIPRE: A Tool Aiding the Design for Entry Probe Missions

Exploring planetary atmospheres uncovers important information for how our solar system formed and evolved. While remote sensing is extensively used, some crucial observations require in-situ measurements by an atmospheric probe. Given their scientific importance, probe missions to Saturn, Uranus and Neptune are considered for the coming decades. In anticipation of future probe missions, the software tool VIPRE was developed as proof-of-concept to facilitate selection of probe entry locations. Currently, there is no analytical way to identify which interplanetary trajectory from thousands of feasible launch opportunities is optimal for a considered mission concept. The search and decision process for that solution is complex and relies on the intuition of mission designers, who focus on a subset of trajectories to make the trade space manageable. The idea of VIPRE is to (1) generate a multi-dimensional data cube showing relevant engineering and science parameters simultaneously for thousands of trajectories, and (2) visualize the data for all entry sites over the body's envelope. VIPRE lays the foundation to make the data available for browsing in a 3-D visualization to identify the best family of solutions for a given mission. The paper introduces the validated and verified core algorithms of VIPRE, published on GitHub. VIPRE serves as a basic framework to be used and extended for different purposes. The paper presents the motivation for the development and algorithms. It explains the computation and data visualization strategy, and gives a list of suggested functionalities to extend and further develop VIPRE to fully leverage its potential.

Ice Giants↗
NASA NTRS2011

A Summary of the Flux-Rope CDAW events

In this paper, I summarize some of the results obtained during previous CDAW on the events selected for analysis. The events were selected based on the following criteria: 1. The events must be well observed in the interplanetary medium as shock-driving interplanetary coronal mass ejections (ICMEs), 2. The ICMEs should have corresponding CMEs near the Sun, observed in white-light coronal images, and 3. The heliographic coordinates of the solar sources must be within 15 degrees from the Sun Center. In all, 24 magnetic cloud (MC) events and 35 non-MC evens were analyzed. Of the 35 non-MC events selected for analysis, it was possible to fit flux ropes to 31/35 events if different boundaries and multiple flux ropes are used. The four events without flux rope structure seem to be poor events (short duration, poor magnetic and plasma signatures). Coronal flux rope fitting suggests (at least for a subset) that non-MC events become non-central during propagation. It was also found that MCs have high charge states; half of the non-MC events also have high charge states. The direction parameter of CMEs seems to be high for MCs. All these results are consistent with the idea that alll CMEs may be flux ropes.

Gopalswamy, Natchimuthuk↗
NASA NTRS2007

F-15B Quiet Spike(TradeMark) Aeroservoelastic Flight-Test Data Analysis

System identification is utilized in the aerospace community for development of simulation models for robust control law design. These models are often described as linear, time-invariant processes and assumed to be uniform throughout the flight envelope. Nevertheless, it is well known that the underlying process is inherently nonlinear. Over the past several decades the controls and biomedical communities have made great advances in developing tools for the identification of nonlin ear systems. In this report, we show the application of one such nonlinear system identification technique, structure detection, for the an alysis of Quiet Spike(TradeMark)(Gulfstream Aerospace Corporation, Savannah, Georgia) aeroservoelastic flight-test data. Structure detectio n is concerned with the selection of a subset of candidate terms that best describe the observed output. Structure computation as a tool fo r black-box modeling may be of critical importance for the development of robust, parsimonious models for the flight-test community. The ob jectives of this study are to demonstrate via analysis of Quiet Spike(TradeMark) aeroservoelastic flight-test data for several flight conditions that: linear models are inefficient for modelling aeroservoelast ic data, nonlinear identification provides a parsimonious model description whilst providing a high percent fit for cross-validated data an d the model structure and parameters vary as the flight condition is altered.

Kukreja, Sunil L.↗
NASA NTRS2007

Designing Rolling-Element Bearings

Bearing Analysis Tool (BAT) is a computer program for designing rolling-element bearings for cryogenic turbomachines. BAT provides a graphical user interface (GUI) that guides the entry of data to develop mathematical models of bearings. The GUI breaks model data into logical subsets that are entered through logic-driven input screens. The software generates a threedimensional graphical model of a bearing as the data are entered. Most dataentry errors become immediately obvious in the graphical model. BAT provides for storage of all the data on a shaft/bearing system, enabling the creation of a library of proven designs. Data from the library can be transferred to subsequent projects by use of simple cut-and-paste routines. BAT includes a library of temperature- dependent cryogenic bearing-material properties for use in the mathematical models. BAT implements algorithms that (1) enable the user to select combinations of design and/or operating-condition parameters, and then (2) automatically optimize the design by performing trade studies over all of the parameter combinations. This feature enables optimization over a large trade space in a fraction of the time taken when using prior bearingmodel software.

Moore, James D., Jr.↗
NASA NTRS2018

NASA ACC High Energy Dynamic Impact Methodology and Outcomes

For High Energy Dynamic Impact (HEDI) events, testing to evaluate the structural response of primary aircraft structure for design and certification is both expensive and time consuming. This paper discusses current work seeking to assess, develop, and validate appropriate analytical models that accurately predict physical response, damage, and failure modes for large scale composite structures in HEDI events. Four state-of-the-art Progressive Damage Analysis (PDA) methods were employed for this phased project: LS-DYNA MAT162, LS-DYNA MAT261, Smoothed Particle Galerkin (SPG), and EMU Peridynamics. Multiple material systems were considered, namely T700/5208 textile-infusion triaxial braid, T800/AMD-825 textile-infusion triaxial braid, IM7/8552 uni-directional tape, and SPG 196-PW/8552 plain-weave fabric. Extensive ballistic impact testing was performed to support this activity and measured results were compared to predictive models for assessment using panel delamination, panel displacement, force at the load cells, and threshold velocity as measures. Ultimately, the work under this activity provided significant progress in advancing the state-of-the-art in the use of PDA for HEDI events. Each material model had favorable performance comparing to test in some parameters and needed improvement in others. With the lessons learned from this activity, significant progress was made in the ability to predict panel behavior for a more general case beyond the flat panel in a ballistic impact event. Subsequent Phase II of the NASA ACC HEDI effort will continue to build on the coupon testing, flat panel ballistic impact testing, and analysis performed to-date with application of the PDA methods for intended material selections to test articles with greater complexity of configuration, curvature, and scale. It is not the intention of this paper to present a full set of data, but rather to give an overview of the NASA HEDI effort and show a small representative subset of the test and analysis results.

Hunziker, Kenneth J.↗
NASA NTRS2007

Aeroelastic Model Structure Computation for Envelope Expansion

Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modelling may be of critical importance in the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear aeroelastic systems. The LASSO minimises the residual sum of squares by the addition of an l(sub 1) penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. Applicability of this technique for model structure computation for the F/A-18 Active Aeroelastic Wing using flight test data is shown for several flight conditions (Mach numbers) by identifying a parsimonious system description with a high percent fit for cross-validated data.

Kukreja, Sunil L.↗
NASA NTRS2015

Characterization of Machine Variability and Progressive Heat Treatment in Selective Laser Melting of Inconel 718

The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human‐rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30‐sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post‐processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one‐way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.

Prater, Tracie↗
NASA NTRS2015

Characterization of Machine Variability and Progressive Heat Treatment in Selective Laser Melting of Inconel 718

The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human-rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30-sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post-processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one-way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.

Prater, T.↗
NASA NTRS2005

NASA GES DISC On-line Visualization and Analysis System for Gridded Remote Sensing Data

The ability to use data stored in the current NASA Earth Observing System (EOS) archives for studying regional or global phenomena is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. Gaining this understanding and applying it to data reduction is a time-consuming task that must be undertaken before the core investigation can begin. This is an especially difficult challenge when science objectives require users to deal with large multi-sensor data sets that are usually of different formats, structures, and resolutions. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has taken a major step towards meeting this challenge by developing an infrastructure with a Web interface that allows users to perform interactive analysis online without downloading any data, the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni." Giovanni provides interactive, online, analysis tools for data users to facilitate their research. There have been several instances of this interface created to serve TRMM users, Aerosol scientists, Ocean Color and Agriculture applications users. The first generation of these tools support gridded data only. The user selects geophysical parameters, area of interest, time period; and the system generates an output on screen in a matter of seconds. The currently available output options are: Area plot averaged or accumulated over any available data period for any rectangular area; Time plot time series averaged over any rectangular area; Hovmoller plots image view of any longitude-time and latitude-time cross sections; ASCII output for all plot types; Image animation for area plot. Another analysis suite deals with parameter intercomparison: scatter plots, temporal correlation maps, GIs-compatible outputs, etc. This allow user to focus on data content (i.e. science parameters) and eliminate the need for expensive learning, development and processing tasks that are redundantly incurred by an archive's user community. The current implementation utilizes the GrADS-DODS Server (GDS), and provides subsetting and analysis services across the Internet for any GrADS-readable dataset. The subsetting capability allows users to retrieve a specified temporal and/or spatial subdomain from a large dataset, eliminating the need to download everything simply to access a small relevant portion of a dataset. The analysis capability allows users to retrieve the results of an operation applied to one or more datasets on the server. We use this approach to read pre-processed binary files and/or to read and extract the needed parts directly from HDF or HDF-EOS files. These subsets then serve as inputs into GrADS analysis scripts. It can be used in a wide variety of Earth science applications: climate and weather events study and monitoring; modeling. It can be easily configured for new applications.

Leptoukh, Gregory G.↗