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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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NASA NTRS2011

Data Analysis And Polarization Measurements With GEMS

The Gravity and Extreme Magnetism SMEX (GEMS) mission was selected by NASA for flight in 2014. GEMS will make the first sensitive survey of X-ray polarization across a wide range of source classes including black hole and neutron star binaries, AGN of different types, rotation and accretion-powered pulsars, magnetars, shell supernova remnants and pulsar wind nebulae. GEMS employs grazing-incidence foil mirrors and novel time-projection chamber (TPC) polarimeters leveraging the photoelectric effect. The GEMS detectors image the charge tracks of photoelectrons produced by 2 - 10 keV X-rays. The initial direction of the photoelectron is determined by the linear polarization of the photon. We present an overview of the data analysis challenges and methods for GEMS, including procedures for producing optimally filtered images of the charge tracks and estimating their initial directions. We illustrate our methods using laboratory measurements of polarized and unpolarized X-rays with flight-like detectors as well as from simulated tracks. We also present detailed simulations exploring the statistics of polarization measurements appropriate for GEMS, and make comparisons with previous work.

Stohmayer, Tod↗
NASA NTRS2011

NASA Instrument Cost/Schedule Model

NASA's Office of Independent Program and Cost Evaluation (IPCE) has established a number of initiatives to improve its cost and schedule estimating capabilities. 12One of these initiatives has resulted in the JPL developed NASA Instrument Cost Model. NICM is a cost and schedule estimator that contains: A system level cost estimation tool; a subsystem level cost estimation tool; a database of cost and technical parameters of over 140 previously flown remote sensing and in-situ instruments; a schedule estimator; a set of rules to estimate cost and schedule by life cycle phases (B/C/D); and a novel tool for developing joint probability distributions for cost and schedule risk (Joint Confidence Level (JCL)). This paper describes the development and use of NICM, including the data normalization processes, data mining methods (cluster analysis, principal components analysis, regression analysis and bootstrap cross validation), the estimating equations themselves and a demonstration of the NICM tool suite.

JCL↗
NASA NTRS2015

Aircraft Engine Noise Research and Testing at the NASA Glenn Research Center

The presentation will begin with a brief introduction to the NASA Glenn Research Center as well as an overview of how aircraft engine noise research fits within the organization. Some of the NASA programs and projects with noise content will be covered along with the associated goals of aircraft noise reduction. Topics covered within the noise research being presented will include noise prediction versus experimental results, along with engine fan, jet, and core noise. Details of the acoustic research conducted at NASA Glenn will include the test facilities available, recent test hardware, and data acquisition and analysis methods. Lastly some of the actual noise reduction methods investigated along with their results will be shown.

Aeroacoustics↗
NASA NTRS2015

Climate-Induced Larch Growth Response Within the Central Siberian Permafrost Zone

Aim: estimation of larch (Larix gmelinii) growth response to current climate changes. Location: permafrost area within the northern part of Central Siberia (approximately 65.8 deg N, 98.5 deg E). Method: analysis of dendrochronological data, climate variables, drought index SPEI, GPP (gross primary production) and EVI vegetation index (both Aqua/MODIS satellite derived), and soil water content anomalies (GRACE satellite measurements of equivalent water thickness anomalies, EWTA). Results: larch tree ring width (TRW) correlated with previous year August precipitation (r = 0.63), snow accumulation (r = 0.61), soil water anomalies (r = 0.79), early summer temperatures and water vapor pressure (r = 0.73 and r = 0.69, respectively), May and June drought index (r = 0.68-0.82). There are significant positive trends of TRW since late 1980s and GPP since the year 2000. Mean TRW increased by about 50%, which is similar to post-Little Ice Age warming. TRW correlated with GPP and EVI of larch stands (r = 0.68-0.69). Main conclusions: within the permafrost zone of central Siberia larch TRW growth is limited by early summer temperatures, available water from snowmelt, water accumulated within soil in the previous year, and permafrost thaw water. Water stress is one of the limiting factors of larch growth. Larch TRW growth and GPP increased during recent decades.

permafrost thaw↗
NASA NTRS2015

Aircraft Engine Noise Research and Testing at the NASA Glenn Research Center

The presentation will begin with a brief introduction to the NASA Glenn Research Center as well as an overview of how aircraft engine noise research fits within the organization. Some of the NASA programs and projects with noise content will be covered along with the associated goals of aircraft noise reduction. Topics covered within the noise research being presented will include noise prediction versus experimental results, along with engine fan, jet, and core noise. Details of the acoustic research conducted at NASA Glenn will include the test facilities available, recent test hardware, and data acquisition and analysis methods. Lastly some of the actual noise reduction methods investigated along with their results will be shown.

Aeroacoustics↗
NASA NTRSDate not supplied

XV-15 Tilt Rotor Research Aircraft Photogrammetry and Metrology Measurement

A new measurement capability was created by combining photogrammetry and metrology techniques to accurately measure one half of the XV-15 Tilt Rotor Research Aircraft at the Smithsonian’s Udvar-Hazy museum. The challenges imposed by the fuselage and surrounding environment at Udvar-Hazy were overcome by careful application of photogrammetry and metrology techniques. Data analyses and processing included the use of multiple reverse engineering programs to accurately generate a complete 3-dimensional water-tight geometry of the aircraft and rotor blade. This paper describes the photogrammetry and metrology measurement systems, technology and hardware set-up, data analysis and processing methods, future work, and lessons learned. In addition, selected measurement results of the fuselage and rotor blade are presented.

XV-15↗
NASA NTRS1994

Topological analysis of chaotic orbits: Revisiting Hyperion

There is emerging interest in the possibility of chaotic evolution in astrophysical systems. To mention just one example, recent well-sampled ground-based observations of the Saturian satellite Hyperion strongly suggest that it is exhibiting chaotic behavior. We present a general technique, the method of close returns, for the analysis of data from astronomical objects believed to be exhibiting chaotic motion. The method is based on the extraction of pieces of the evolution that exhibit nearly periodic behavior-episodes during which the object stays near in phase space to some unstable periodic orbit. Such orbits generally act as skeletal features, tracing the topological organization of the manifold on which the chaotic dynamics takes place. This method does not require data sets as lengthy as other nonlinear analysis techniques do and is therefore well suited to many astronomical observing programs. Well sampled data covering between twenty and forty characteristic periods of the system have been found to be sufficient for the application of this technique. Additional strengths of this method are its robustness in the presence of noise and the ability for a user to clearly distinguish between periodic, random, and chaotic behavior by inspection of the resulting two-dimensional image. As an example of its power, we analyze close returns in a numerically generated data set, based on a model for Hyperion extensively studied in the literature, corresponding to nightly observations of the satellite. We show that with a small data set, embedded unstable periodic orbits can be extracted and that these orbits can be responsible for nearly periodic behavior lasting a substantial fraction of the observing run.

Boyd, Patricia T.↗
NASA NTRS2003

Fixed Pattern Correction and Rapid Analysis Procedures for He I 1083 nm Imaging Spectroscopy with the NASA/NSO Spectromagnetograph

Imaging spectroscopy in the He 1083 nm lines is a powerful tool for probing the top of the chromosphere and bottom of the transition region. A method for spectral flat-fielding using a uniform solar exposure with spectral lines in place is presented and illustrated with 1083 nm data obtained with the NASA/NSO Spectromagnetograph at the National Solar Observatory Kitt Peak Vacuum Telescope. An efficient method for analysis of the data producing images in continuum intensity, line-of-sight velocity, equivalent width, central line depth, Doppler width, and line asymmetry is also presented and illustrated.

Jones, Harrison P.↗
NASA NTRS1972

Determination of stability derivatives from flight data using a Newton-Raphson minimization technique

A modified Newton-Raphson or quasilinearization minimization technique for determining stability derivatives from flight data was developed and compared with simple-equations, analog-matching, least-squares, and Shinbrot methods of analysis. For the data analyzed, the solutions computed by using the estimates obtained from the Newton-Raphson technique fit the data and determined coefficients adequately. A further modification to include a priori information was found to be useful. A model statistically similar to the flight data was analyzed using the same methods (excluding analog matching), and the Newton-Raphson technique was found to yield superior estimates. An approximate Cramer-Rao bound was compared with the error covariance matrix of the model and was found to provide information about the reliability of the individual estimates obtained. The technique was successfully applied to data obtained from a light airplane, a large supersonic airplane, and a lifting body vehicle. It was shown that the reliability of the estimates of a given coefficient obtained from these vehicles depends upon the data analyzed.

Iliff, K. W.↗
NASA NTRS1986

Test versus analysis: A discussion of methods

Some techniques for comparing structural vibration data determined from test and analysis are discussed. Orthogonality is a general category of one group, correlation is a second, synthesis is a third and matrix improvement is a fourth. Advantages and short-comings of the methods are explored with suggestions as to how they can complement one another. The purpose for comparing vibration data from test and analysis for a given structure is to find out whether each is representing the dynamic properties of the structure in the same way. Specifically, whether: mode shapes are alike; the frequencies of the modes are alike; modes appear in the same frequency sequence; and if they are not alike, how to judge which to believe.

Butler, T. G.↗
NASA NTRS1995

Hierarchical analysis of spatial pattern and processes of Douglas-fir forests

There has been an increased interest in the quantification of pattern in ecological systems over the past years. This interest is motivated by the desire to construct valid models which extend across many scales. Spatial methods must quantify pattern, discriminate types of pattern, and relate hierarchical phenomena across scales. Wavelet analysis is introduced as a method to identify spatial structure in ecological transect data. The main advantage of the wavelet transform over other methods is its ability to preserve and display hierarchical information while allowing for pattern decomposition. Two applications of wavelet analysis are illustrated, as a means to: (1) quantify known spatial patterns in Douglas-fir forests at several scales, and (2) construct spatially-explicit hypotheses regarding pattern generating mechanisms. Application of the wavelet variance, derived from the wavelet transform, is developed for forest ecosystem analysis to obtain additional insight into spatially-explicit data. Specifically, the resolution capabilities of the wavelet variance are compared to the semi-variogram and Fourier power spectra for the description of spatial data using a set of one-dimensional stationary and non-stationary processes. The wavelet cross-covariance function is derived from the wavelet transform and introduced as a alternative method for the analysis of multivariate spatial data of understory vegetation and canopy in Douglas-fir forests of the western Cascades of Oregon.

Bradshaw, G. A.↗
NASA NTRS2010

Affordability Engineering: Bridging the Gap Between Design and Cost

Affordability is a commonly used term that takes on numerous meanings depending on the context used. Within conceptual design of complex systems, the term generally implies comparisons between expected costs and expected resources. This characterization is largely correct, but does not convey the many nuances and considerations that are frequently misunderstood and underappreciated. In the most fundamental sense, affordability and cost directly relate to engineering and programmatic decisions made throughout development programs. Systems engineering texts point out that there is a temporal aspect to this relationship, for decisions made earlier in a program dictate design implications much more so than those made during latter phases. This paper explores affordability engineering and its many sub-disciplines by discussing how it can be considered an additional engineering discipline to be balanced throughout the systems engineering and systems analysis processes. Example methods of multidisciplinary design analysis with affordability as a key driver will be discussed, as will example methods of data visualization, probabilistic analysis, and other ways of relating design decisions to affordability results.

Reeves, J. D.↗
NASA NTRS2021

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal (<90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Machine Learning↗
NASA NTRS1985

Analysis/forecast experiments with a multivariate statistical analysis scheme using FGGE data

A three-dimensional, multivariate, statistical analysis method, optimal interpolation (OI) is described for modeling meteorological data from widely dispersed sites. The model was developed to analyze FGGE data at the NASA-Goddard Laboratory of Atmospherics. The model features a multivariate surface analysis over the oceans, including maintenance of the Ekman balance and a geographically dependent correlation function. Preliminary comparisons are made between the OI model and similar schemes employed at the European Center for Medium Range Weather Forecasts and the National Meteorological Center. The OI scheme is used to provide input to a GCM, and model error correlations are calculated for forecasts of 500 mb vertical water mixing ratios and the wind profiles. Comparisons are made between the predictions and measured data. The model is shown to be as accurate as a successive corrections model out to 4.5 days.

Baker, W. E.↗
NASA NTRS1935

Spinning characteristics of wings II : rectangular Clark Y biplane cellule: 25 percent stagger; 0 degree decalage; gap/chord 1.0

General methods of theoretical analysis of airplane spinning characteristics have been available for some time. Some of these methods of analysis might be used by designers to predict the spinning characteristics of proposed airplane designs if the necessary aerodynamic data were known. The present investigation, to determine the spinning characteristics of wings, is planned to include variations in airfoil sections, plan forms, and tip shapes of monoplane wings and variations in stagger, gap, and decalage for biplane cellules. The first series of tests, made on a rectangular Clark Y monoplane wing, are reported in reference 1. That report also gives an analysis of the data for predicting the probable effects of various important parameters on the spin for normal airplanes using such a wing. The present report is the second of the series. It gives the aerodynamic characteristics of a rectangular Clark Y biplane cellule in spinning attitudes and includes a discussion of the data, using the method of analysis given in reference 1.

Bamber, M J↗
NASA NTRS1998

In-Flight System Identification

A method is proposed and studied whereby the system identification cycle consisting of experiment design and data analysis can be repeatedly implemented aboard a test aircraft in real time. This adaptive in-flight system identification scheme has many advantages, including increased flight test efficiency, adaptability to dynamic characteristics that are imperfectly known a priori, in-flight improvement of data quality through iterative input design, and immediate feedback of the quality of flight test results. The technique uses equation error in the frequency domain with a recursive Fourier transform for the real time data analysis, and simple design methods employing square wave input forms to design the test inputs in flight. Simulation examples are used to demonstrate that the technique produces increasingly accurate model parameter estimates resulting from sequentially designed and implemented flight test maneuvers. The method has reasonable computational requirements, and could be implemented aboard an aircraft in real time.

Morelli, Eugene A.↗