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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Extracting Damping Ratio from Dynamic Data and Numerical Solutions

There are many ways to extract damping parameters from data or models. This Technical Memorandum provides a quick reference for some of the more common approaches used in dynamics analysis. Described are six methods of extracting damping from data: the half-power method, logarithmic decrement (decay rate) method, an autocorrelation/power spectral density fitting method, a frequency response fitting method, a random decrement fitting method, and a newly developed half-quadratic gain method. Additionally, state-space models and finite element method modeling tools, such as COMSOL Multiphysics (COMSOL), provide a theoretical damping via complex frequency. Each method has its advantages which are briefly noted. There are also likely many other advanced techniques in extracting damping within the operational modal analysis discipline, where an input excitation is unknown; however, these approaches discussed here are objective, direct, and can be implemented in a consistent manner.

Casiano, M. J.↗
NASA NTRS2012

Structural Element Testing in Support of the Design of the NASA Composite Crew Module

In January 2007, the NASA Administrator and Associate Administrator for the Exploration Systems Mission Directorate chartered the NASA Engineering and Safety Center (NESC) to design, build, and test a full-scale Composite Crew Module (CCM). For the design and manufacturing of the CCM, the team adopted the building block approach where design and manufacturing risks were mitigated through manufacturing trials and structural testing at various levels of complexity. Following NASA's Structural Design Verification Requirements, a further objective was the verification of design analysis methods and the provision of design data for critical structural features. Test articles increasing in complexity from basic material characterization coupons through structural feature elements and large structural components, to full-scale structures were evaluated. This paper discusses only four elements tests three of which include joints and one that includes a tapering honeycomb core detail. For each test series included are specimen details, instrumentation, test results, a brief analysis description, test analysis correlation and conclusions.

Kellas, Sotiris↗
NASA NTRS1975

A discussion of dynamic stability measurement techniques

Techniques for the measurement of the dynamic stability of linear systems are discussed. Particular attention is given to an analysis of the errors in the procedures, and to methods for calculating the system damping from the data. The techniques discussed include: transient decay, moving block analysis, spectral analysis, random decrement signatures, transfer function analysis, and parameter identification methods. The special problems of rotorcraft dynamic stability testing are discussed.

Johnson, W.↗
NASA NTRS1993

Surface hot-film method for the measurement of transition, separation and reattachment points

A real-time method of determining positions of laminar-to-turbulent transition region, separation and reattachment points and stagnation points using an array of simultaneously operated surface-mounted hot-film sensors has been developed and applied to a wind-tunnel test of a multielement airfoil model. Determination of various types of transitions and flow directions in various regimes of flows seen on multielement airfoils are possible without precise sensor calibration or laborious post-test data analysis. The results agree with established method and theoretical methods, but determination of turbulent reattachment points are not yet satisfactory.

Nakayama, Akihiko↗
NASA NTRS1999

Analysis and Application of Airborne Thermal Data at the Local Level Salt Lake City, Utah

Expanding cities are transforming periurban environments such as agricultural land, natural grasslands, forests, wetlands, and and land, into urban surfaces, such as asphalt and concrete. This transformation is part of a process defined as "urban heat island". The urban surfaces get much hotter during the daylight hours in the summer than the natural or vegetated environment. The heat builds up creating a dome effect over the city making it many degrees hotter than it's surrounding area. The impacts from this, which include higher usage of air conditioners, water, etc., are numerous and costly. As cities expand, this problem is exacerbated. It is necessary to incorporate better quality data into urban analysis and for establishing methods that systematically and objectively monitor growth and change due to increased urbanization. NASA initiated Project Atlanta in 1997 "as an interdisciplinary remote sensing study to observe and measure the growth and development of the urban heat island effect over Atlanta, and its associated impacts". This project has recently included Salt Lake City, among others, in the study of the development and effects of "urban heat islands". NASA has made available to Salt Lake City, high resolution, 10 meter, multispectral thermal data collected in June 1998. The data collection was part of a special NASA over-flight, a mission supported by the U.S. EPA in conjunction with their Urban Heat Island (UHI) Mitigation Initiative. Salt Lake City is one of three pilot cities selected to participate in this unique initiative. Hence, this project constitutes a rare opportunity to capitalize upon state-of-the-art NASA technology and link it to an urban community very concerned about rapid growth and development. This data will enhance existing data and be used for improving technical tools used to plan for Utah's future.

Dudley-Murphy, Elizabeth A.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-17943-DND

SAGE II used the solar occultation technique to measure atmospheric ozone for 21 years between 1984 and 2005 and has continued to play a key role in numerous international assessments. Traditionally, the determination of trends in ozone using SAGE II data has been done via time series analysis of monthly mean data within specific latitude bands. However, given the sparse sampling of SAGE II data, this will introduce temporal and/or spatial biases, particularly in the period after late 2000 when the instrument operated at half-duty cycle. Herein we present a new method for performing time series analysis of unevenly sampled data (in particular SAGE II); namely, we utilize the daily mean data and perform a simultaneous temporal and spatial analysis, making use of a Fourier series to constrain latitudinal variation. This methodology is applied to both the previous (v6.2) and current (v7.0) versions of the SAGE II data. Results are discussed that show the improvements to the data between versions 6.2 and 7.0 that make time series analysis produce reduced residuals as well as the preliminary results of the time series itself, which reveal some of the limitations in currently used proxies for the regression.

Robert P Damadeo↗
NASA NTRS1990

Primary reference cell calibrations at SERI - History and methods

The tabular calibration method used at the Solar Energy Research Institute (SERI) for primary reference cells is derived and described in detail. An uncertainty analysis shows that the tabular method should have a total uncertainty of + or - 1.0 percent; data from five years of calibrations are then shown to support this analysis. Results from SERI's tabular method are compared with terrestrial calibrations performed by the NASA Lewis Research Center in the late 1970s.

Osterwald, C. R.↗
NASA NTRS2001

On-Line Mu Method for Robust Flutter Prediction in Expanding a Safe Flight Envelope for an Aircraft Model Under Flight Test

A structured singular value (mu) analysis method of computing flutter margins has robust stability of a linear aeroelastic model with uncertainty operators (Delta). Flight data is used to update the uncertainty operators to accurately account for errors in the computed model and the observed range of aircraft dynamics of the aircraft under test caused by time-varying aircraft parameters, nonlinearities, and flight anomalies, such as test nonrepeatability. This mu-based approach computes predict flutter margins that are worst case with respect to the modeling uncertainty for use in determining when the aircraft is approaching a flutter condition and defining an expanded safe flight envelope for the aircraft that is accepted with more confidence than traditional methods that do not update the analysis algorithm with flight data by introducing mu as a flutter margin parameter that presents several advantages over tracking damping trends as a measure of a tendency to instability from available flight data.

Lind, Richard C.↗
NASA NTRSDate not supplied

Quantitative Phenotypic Analysis of Arabidopsis Thaliana Grown in Microgravity Using Soap, an Applied Artificial Intelligence

Phenotypic analysis is an essential step in studying the gravitropic responses and gravitational stress experienced by plants grown in microgravity. Many of the phenotypic traits analyzed in gravitropism studies, such as root length, leaf area, secondary root count, and number of root hairs, currently rely upon manual measurement methods for quantification. However, new advances in data analysis technology using artificial intelligence offer an opportunity for more efficient phenotypic analysis and a reduction of time spent in the data collection phase. In this project, the ability of a new artificially intelligent data collection software, SOAP (Simple Object Access Protocol), to collect and quantify phenotypic traits of Arabidopsis thaliana will be assessed. This project will test the measurements taken by an initial draft of the software. SOAP will take measurements of shoot length, a key phenotype used to assess A. thaliana stress response when grown in microgravity conditions. Shoot length measurements made by SOAP will be compared against a series of manual shoot length measurements. The comparison between the two methods of data measurement will provide valuable insight into the relative accuracy of SOAP and the margin of human error when conducting lab measurements.

Arabidopsis↗
NASA NTRS1987

An algorithmic approach to crustal deformation analysis

In recent years the analysis of crustal deformation measurements has become important as a result of current improvements in geodetic methods and an increasing amount of theoretical and observational data provided by several earth sciences. A first-generation data analysis algorithm which combines a priori information with current geodetic measurements was proposed. Relevant methods which can be used in the algorithm were discussed. Prior information is the unifying feature of this algorithm. Some of the problems which may arise through the use of a priori information in the analysis were indicated and preventive measures were demonstrated. The first step in the algorithm is the optimal design of deformation networks. The second step in the algorithm identifies the descriptive model of the deformation field. The final step in the algorithm is the improved estimation of deformation parameters. Although deformation parameters are estimated in the process of model discrimination, they can further be improved by the use of a priori information about them. According to the proposed algorithm this information must first be tested against the estimates calculated using the sample data only. Null-hypothesis testing procedures were developed for this purpose. Six different estimators which employ a priori information were examined. Emphasis was put on the case when the prior information is wrong and analytical expressions for possible improvements under incompatible prior information were derived.

Iz, Huseyin Baki↗
NASA NTRS1999

Global Seasonal Climatologies of Ocean Chlorophyll: Blending In situ and Satellite Data for the CZCS Era

The historical archives of in situ (National Oceanographic Data Center) and satellite (Coastal Zone Color Scanner) chlorophyll data were combined using the blended analysis method of Reynolds [1988] in an attempt to construct an improved climatological seasonal representation of global chlorophyll distributions. The results of the blended analysis differed dramatically from the CZCS representation: global chlorophyll estimates increased 8-35% in the blended analysis depending upon season. Regional differences were even larger, up to 140% in the equatorial Indian Ocean in summer (during the southwest monsoon). Tropical Pacific chlorophyll values increased 25-41%. The results suggested that the CZCS generally underestimates chlorophyll. Regional and seasonal differences in the blended analysis were sufficiently large as to produce a different representation of global chlorophyll distributions than otherwise inferred from CZCS data alone. Analyses of primary production and biogeochemical cycles may be substantially impacted by these results.

Gregg, Watson W.↗
NASA NTRSDate not supplied

Evaluation of CFD as a Surrogate for Wind Tunnel Testing - Experimental Uncertainty Quantification

A series of wind tunnel tests is being performed at the Unitary Plan Wind Tunnel at Langley Research Center to assess the validity of using computational fluid dynamics (CFD) as a surrogate for wind tunnel testing. In order to make proper comparisons, uncertainties in CFD results and experimental data must be well understood. The material presented will highlight the methods, assumptions, and elemental inputs used to achieve experimental uncertainty estimates for several variables of interest.The work performed to date has focused on gaining insight into random uncertainty via statistical analysis of repeat data and systematic uncertainty via Monte Carlo propagation analysis. These methods were combined using a second-order Monte Carlo propagation, resulting in a probability box (P-box) for each variable and at all conditions of interest. Figure 1 provides an example of one such P-box, showing the experimental uncertainty in a locally determined dynamic pressure (QC10) for one of many tunnel conditions evaluated during the Flow Survey experiment. This particular condition (Condition 27) has nominal set points of Mach number = 3.85, Reynolds number = 3x10(exp 6) ft(exp -1), total pressure = 5160 psfa, and total temperature = 150°F. The uncertainty in dynamic pressure at this condition is now well defined by this plot. Armed with this experimental data uncertainty, meaningful comparisons can be made with computational results, when their associated uncertainties are also considered.

Heather P Houlden↗
NASA NTRSDate not supplied

Multiscale Modeling of Thermoplastics Using Atomistic-informed Micromechanics

A multiscale model was developed for predicting the thermoelastic behavior of semi-crystalline thermoplastic materials for composite aerospace applications. At the highest scale containing the semi-crystalline spherulite in an amorphous matrix, the generalized method of cells, or high fidelity method of cells, was used to perform the homogenization calculations to obtain the effective properties. Models were developed assuming a cubic, or spherical shape, for the spherulite to understand if the morphology of the spherulite affects the effective thermoelastic properties. The generalized method of cells was used to model at the repeating unit cells at the subscales of the microstructure including the lamellae stacks and granular crystal blocks. The scales are integrated using the multiscale micromechanics method in the NASA Multiscale Analysis Tool. Data from molecular dynamics simulations were used as inputs for the amorphous and crystalline constituents. Convergence studies were performed to determine the best level of discretization for the repeating unit cell at the highest scale. Effective Young’s modulus, shear modulus, Poisson’s ratio, coefficient of thermal expansion, and thermal conductivity were predicted for polyether ether ketone and polyether ketone ketone, and very good agreement between the model utilizing the cubic spherulite and the experimental data, where available, was observed for polyether ketone ketone. Normalization of the data for the bulk polyether ketone ketone, against amorphous data, improved the predictions as compared to experimental data. Overall, the high fidelity method of cells predicted a stiffer response then the generalized method of cells as the crystallinity was increased. The shape of the spherulite had a minimal effect on the predicted bulk properties of the polymers.

thermoplastics↗
NASA NTRS2019

Application of a Temperature-Dependent Load Prediction Method to a RUAG Six-Component Block-Type Balance

Temperature-dependent data of a RUAG six-component block-type balance was analyzed to assess the accuracy of two load prediction methods for temperature-dependent balance data. The supplied data was prepared for the analysis by splitting it into calibration and check load data subsets. The first calibration data subset was obtained at a temperature of 294 Kelvin. The second calibration data subset was obtained at a temperature of 315 Kelvin. A subset of 38 points was extracted from the second data set and used as check loads so that the accuracy of the two load prediction methods could be tested. First, the Iterative Method in combination with an extended independent and dependent variable set was used for the balance load prediction. This approach fits electrical outputs as a function of loads and the temperature and, afterwards, constructs a load iteration scheme from the regression coefficients so that loads can be predicted from outputs and the temperature during a wind tunnel test. The Non-Iterative Method was also used for the load prediction. This alternate method can more easily be implemented in a data system as loads are directly fitted as a function of electrical outputs and the temperature. Analysis results for the axial force are only discussed in the paper as similar results were obtained for the other five load components. Results for both methods clearly show that the cross-product term constructed from either a primary gage load or a primary gage output and the temperature explains the majority of the temperature-dependent part of the predicted balance load. This term models the temperature dependent nature of the gage sensitivity. Therefore, it is recommended to apply primary gage loadings at different temperatures during a balance calibration whenever temperature effects need to be described. These loadings will contain information about the temperature-dependent nature of the gage sensitivities that can be quantified by related cross-product terms in regression models of the data.

strain-gage balance↗
NASA NTRS2012

Refinement of a Method for Identifying Probable Archaeological Sites from Remotely Sensed Data

To facilitate locating archaeological sites before they are compromised or destroyed, we are developing approaches for generating maps of probable archaeological sites, through detecting subtle anomalies in vegetative cover, soil chemistry, and soil moisture by analyzing remotely sensed data from multiple sources. We previously reported some success in this effort with a statistical analysis of slope, radar, and Ikonos data (including tasseled cap and NDVI transforms) with Student's t-test. We report here on new developments in our work, performing an analysis of 8-band multispectral Worldview-2 data. The Worldview-2 analysis begins by computing medians and median absolute deviations for the pixels in various annuli around each site of interest on the 28 band difference ratios. We then use principle components analysis followed by linear discriminant analysis to train a classifier which assigns a posterior probability that a location is an archaeological site. We tested the procedure using leave-one-out cross validation with a second leave-one-out step to choose parameters on a 9,859x23,000 subset of the WorldView-2 data over the western portion of Ft. Irwin, CA, USA. We used 100 known non-sites and trained one classifier for lithic sites (n=33) and one classifier for habitation sites (n=16). We then analyzed convex combinations of scores from the Archaeological Predictive Model (APM) and our scores. We found that that the combined scores had a higher area under the ROC curve than either individual method, indicating that including WorldView-2 data in analysis improved the predictive power of the provided APM.

Tilton, James C.↗
NASA NTRS1991

Systematic methods for knowledge acquisition and expert system development

Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base and to assess the cooperation between the rule bases. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy INS was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm. ANOVA results show that statistically different position accuracies are obtained when different navaids are used, the number of navaids aiding the INS is varied, the aircraft's trajectory is varied, and the performance history is varied. The ID3 algorithm determines the NSM expert's classification rules in the form of decision trees. The performance of these decision trees was assessed on two arbitrary trajectories, and the results demonstrate that the NSM expert adapts to new situations and provides reasonable estimates of the expected hybrid performance.

Belkin, Brenda L.↗
NASA NTRSDate not supplied

Features for a Modern Strain-Gage Balance Data Analysis Software Tool

Required, recommended, and optional features are discussed that benefit preparation and evaluation of the load prediction equations in a strain-gage balance data analysis tool. First, milestones in the evolution of load prediction methods are reviewed so that suggested features can be put into a historical context. Afterwards, independent and dependent variable choices for the balance data analysis are discussed. Then, it is illustrated how three different metrics may be used for the identification of the root cause of an unwanted divergence of the load iterations that may be observed during an iterative load prediction. Finally, a list of features is provided to guide software development efforts.

wind tunnel test↗
NASA NTRS1977

Results of a remote multiplexer/digitizer unit accuracy and environmental study

A remote multiplexer/digitizer unit (RMDU), a part of the airborne integrated flight test data system, was subjected to an accuracy study. The study was designed to show the effects of temperature, altitude, and vibration on the RMDU. The RMDU was subjected to tests at temperatures from -54 C (-65 F) to 71 C (160 F), and the resulting data are presented here, along with a complete analysis of the effects. The methods and means used for obtaining correctable data and correcting the data are also discussed.

Wilner, D. O.↗