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NASA NTRS2018

Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations

Earth Observation data are a vital resource for studying long term changes, but the large data volumes can be challenging to analyze. Time series analysis in particular is hampered by the typical thin-time-slice file organization. We examine several potential solutions inspired in large part by the data-parallel methods that have arisen with cloud computing. These solutions include various combinations of data re-organization, spatial indexing, distributed storage and pre-computation that we term "Analytics Optimized Data Stores" (AODS). We find that even simple solutions (such as a data cube) produce more than an order of magnitude improvement; the best provide two to three orders of magnitude improvement. The most performant solutions have tradeoffs in terms of generality or storage footprint, but may nonetheless be useful components in data analytics frameworks where performance is critical.

parallel processing (computers)↗

NASA NTRS1973

Application of the hydrogen-bubble technique for velocity measurements in thin liquid films.

A unique adaptation of the hydrogen-bubble flow visualization method was applied to measure velocity profiles and film thicknesses of very thin films on an inclined plane wall. Data were obtained in the three flow regions for a developing falling film with an initially uniform velocity profile and thickness less than or equal to 0.1 in. The measured profiles compared more favorably with parabolic profiles in the intermediate fully developed region than in the initial developing region. However, measured film thicknesses compared favorably with a simplified solution of the integral momentum equation based on parabolic velocity profiles. The results confirm the theoretical prediction that a relatively long distance may be required even for a thin film before nonaccelerating flow with a constant film thickness is obtained and Nusselt's classical analysis applies. The experimental technique was shown to be a practical experimental method for obtaining data for the two-dimensional laminar flow of thin liquid films.

Thomas, W. C.↗

NASA NTRS1998

Neural Network and Regression Approximations in High Speed Civil Transport Aircraft Design Optimization

Nonlinear mathematical-programming-based design optimization can be an elegant method. However, the calculations required to generate the merit function, constraints, and their gradients, which are frequently required, can make the process computational intensive. The computational burden can be greatly reduced by using approximating analyzers derived from an original analyzer utilizing neural networks and linear regression methods. The experience gained from using both of these approximation methods in the design optimization of a high speed civil transport aircraft is the subject of this paper. The Langley Research Center's Flight Optimization System was selected for the aircraft analysis. This software was exercised to generate a set of training data with which a neural network and a regression method were trained, thereby producing the two approximating analyzers. The derived analyzers were coupled to the Lewis Research Center's CometBoards test bed to provide the optimization capability. With the combined software, both approximation methods were examined for use in aircraft design optimization, and both performed satisfactorily. The CPU time for solution of the problem, which had been measured in hours, was reduced to minutes with the neural network approximation and to seconds with the regression method. Instability encountered in the aircraft analysis software at certain design points was also eliminated. On the other hand, there were costs and difficulties associated with training the approximating analyzers. The CPU time required to generate the input-output pairs and to train the approximating analyzers was seven times that required for solution of the problem.

Patniak, Surya N.↗

NASA NTRS1991

Application of software technology to automatic test data analysis

The verification process for a major software subsystem was partially automated as part of a feasibility demonstration. The methods employed are generally useful and applicable to other types of subsystems. The effort resulted in substantial savings in test engineer analysis time and offers a method for inclusion of automatic verification as a part of regression testing.

Stagner, J. R.↗

NASA NTRS1987

Contributions of numerical simulation data bases to the physics, modeling and measurement of turbulence

The use of simulation data bases for the examination of turbulent flows is an effective research tool. Studies of the structure of turbulence have been hampered by the limited number of probes and the impossibility of measuring all desired quantities. Also, flow visualization is confined to the observation of passive markers with limited field of view and contamination caused by time-history effects. Computer flow fields are a new resource for turbulence research, providing all the instantaneous flow variables in three-dimensional space. Simulation data bases also provide much-needed information for phenomenological turbulence modeling. Three dimensional velocity and pressure fields from direct simulations can be used to compute all the terms in the transport equations for the Reynolds stresses and the dissipation rate. However, only a few, geometrically simple flows have been computed by direct numerical simulation, and the inventory of simulation does not fully address the current modeling needs in complex turbulent flows. The availability of three-dimensional flow fields also poses challenges in developing new techniques for their analysis, techniques based on experimental methods, some of which are used here for the analysis of direct-simulation data bases in studies of the mechanics of turbulent flows.

Moin, Parviz↗

NASA NTRS1985

Implementation of design sensitivity analysis with existing finite element codes

A numerical method is presented to implement structural design sensitivity analysis theory, using the versatility and convenience of existing finite element structural analysis programs. Design variables such as thickness and cross-sectional areas of components of individual members and built-up structures are considered. Structural performance functionals considered include displacement and stress. The method is also applicable for eigenvalue problem design sensitivity analysis. It is shown that calculations can be carried out outside existing finite element codes, using postprocessing data only. Thus, design sensitivity analysis software does not have to be embedded in an existing finite element code. Feasability of the method is shown through analysis of several problems, including a built-up structure. Accurate design sensitivity results are obtained without the uncertainty of numerical accuracy associated with selection of finite difference perturbations.

Choi, Kyung K.↗

NASA NTRS1975

Thermal desorption of metals from tungsten single crystal surfaces

After a short review of experimental methods used to determine desorption energies and frequencies the assumptions underlying the theoretical analysis of experimental data are discussed. Recent experimental results on the flash desorption of Cu, Ag, and Au from clean, well characterized W (110) and (100) surfaces are presented and analyzed in detail with respect to the coverage dependence. The results obtained clearly reveal the limitations of previous analytical methods and of the experimental technique per se (such as structure and phase changes below and in the temperature region in which desorption occurs).

Bauer, E.↗

NASA NTRS1994

Adding intelligent services to an object oriented system

As today's software becomes increasingly complex, the need grows for intelligence of one sort or another to becomes part of the application, often an intelligence that does not readily fit the paradigm of one's software development. There are many methods of developing software, but at this time, the most promising is the object oriented (OO) method. This method involves an analysis to abstract the problem into separate 'objects' that are unique in the data that describe them and the behavior that they exhibit, and eventually to convert this analysis into computer code using a programming language that was designed (or retrofitted) for OO implementation. This paper discusses the creation of three different applications that are analyzed, designed, and programmed using the Shlaer/Mellor method of OO development and C++ as the programming language. All three, however, require the use of an expert system to provide an intelligence that C++ (or any other 'traditional' language) is not directly suited to supply. The flexibility of CLIPS permitted us to make modifications to it that allow seamless integration with any of our applications that require an expert system. We illustrate this integration with the following applications: (1) an after action review (AAR) station that assists a reviewer in watching a simulated tank battle and developing an AAR to critique the performance of the participants in the battle; (2) an embedded training system and over-the-shoulder coach for howitzer crewmen; and (3) a system to identify various chemical compounds from their infrared absorption spectra.

Robideaux, Bret R.↗

NASA NTRS2018

Increasing the Statistical Rigor of Cross-Species Differential Expression Analysis

Microgravity inflicts substantial, but undercharacterized, pressure on organisms that induces metabolic responses such as increased microbial virulence and antibiotic resistance, altered organ weights in developing rats, and loss of bone tissue in astronauts. Numerous studies have analyzed the effects of microgravity on specific organisms, tissues, or test conditions, but these projects are necessarily limited by the small sample size of space research. Increasing the sample size of spaceflight studies is non-trivial; however, pooling data from numerous studies can greatly increase the statistical rigor of comparative analyses. The GeneLab houses datasets from 73 spaceflight studies that performed transcription profiling assays. These data encompass a diverse array of organisms ranging from Escherichia coli to Mus musculus to Homo sapiens and comprise studies analyzing ionizing radiation, mammalian pregnancy, etc. Collectively, the GeneLab database contains a large quantity of transcription assays and RNA sequence data analyzing Differential Gene Expression (DGE) between microand normogravity. Xspecies, a cross-species analysis method for DGE developed by Kristiansson, et al. in 2012, identifies homologous genes between species that are universally up- or downregulated in response to test conditions. Previous work by an intern at GeneLab applied Xspecies to 19 datasets containing seven different species and identified 14 homologous groups differentially expressed under spaceflight conditions including several heat shock proteins and cytoskeletal components. Unfortunately, these results may be biased by the disproportionate number of studies on Arabidopsis thaliana (5) and Mus musculus (6) and the results are not normalized by evolutionary distances. Here, we present modifications to the Xspecies algorithm that permits incorporation of multi-omic data and normalizes data for effect size, directionality, and evolutionary distances. We then apply this algorithm to all currently available GeneLab studies

Xspecies↗

NASA NTRS2009

Determining the Detection Efficiency and Background Level of ATIC Electron Observation from Flight Data

Observations of Cosmic-ray electrons are difficult due to the large flux of cosmic ray hadrons. The event selection efficiency and background levels can be estimated from flight data for the ATIC instrument. This reduces the dependence upon Monte Carlo simulations, which show differences between different codes, thereby reducing the systematic errors resulting from analyses that only use simulations. This paper discusses some of the methods used in the ATIC analysis to determine the detection efficiency and background level for the flight data.

Chang, J.↗

NASA NTRS1991

On the estimation of jet-induced fountain lift and additional suckdown in hover for two-jet configurations

Currently available methods for estimating the net suckdown induced on jet V/STOL aircraft hovering in ground effect are based on a correlation of available force data and are, therefore, limited to configurations similar to those in the data base. Experience with some of these configurations has shown that both the fountain lift and additional suckdown are overestimated but these effects cancel each other for configurations within the data base. For other configurations, these effects may not cancel and the net suckdown could be grossly overestimated or underestimated. Also, present methods do not include the prediction of the pitching moments associated with the suckdown induced in ground effect. An attempt to develop a more logically based method for estimating the fountain lift and suckdown based on the jet-induced pressures is initiated. The analysis is based primarily on the data from a related family of three two-jet configurations (all using the same jet spacing) and limited data from two other two-jet configurations. The current status of the method, which includes expressions for estimating the maximum pressure induced in the fountain regions, and the sizes of the fountain and suckdown regions is presented. Correlating factors are developed to be used with these areas and pressures to estimate the fountain lift, the suckdown, and the related pitching moment increments.

Kuhn, Richard E.↗

NASA NTRS1990

A high temperature thermal diffusivity determination procedure for solids and liquids

A new method for measuring the thermal diffusivity of materials at high temperatures is presented. The method is applicable to solids on Earth, and to liquids in the reduced gravity environment of space. It is especially suited to levitated liquid metals at elevated temperatures where thermal diffusivity data is not available. The method is applied in two parts, such that lumped analysis is valid in the first part, and Fourier's law of conduction is valid in the second. In both parts, the spherical specimen is assumed to have been heated to a desired temperature and cooled. An inverse conduction problem is then formulated and solved using Laplace transformation techniques. Using this solution, sample sizes, and experimentally obtained surface temperature history, the thermal diffusivity is determined by minimizing a function that satisifies the heat balance at the surface. Minimization is performed using a modified quasilinearization algorithm. Accuracy is very sensitive to error in the temperature data and increases with better curve fits to the temperature data. An error analysis is also performed, and the effect of errors in the various parameters on the evaluated thermal diffusivity is determined. An experimental study for solids on Earth is suggested, before development for implementation in space.

Bayazitoglu, Yildiz↗

NASA NTRS1992

Methodology issues concerning the accuracy of kinematic data collection and analysis using the ariel performance analysis system

Kinematics, the study of motion exclusive of the influences of mass and force, is one of the primary methods used for the analysis of human biomechanical systems as well as other types of mechanical systems. The Anthropometry and Biomechanics Laboratory (ABL) in the Crew Interface Analysis section of the Man-Systems Division performs both human body kinematics as well as mechanical system kinematics using the Ariel Performance Analysis System (APAS). The APAS supports both analysis of analog signals (e.g. force plate data collection) as well as digitization and analysis of video data. The current evaluations address several methodology issues concerning the accuracy of the kinematic data collection and analysis used in the ABL. This document describes a series of evaluations performed to gain quantitative data pertaining to position and constant angular velocity movements under several operating conditions. Two-dimensional as well as three-dimensional data collection and analyses were completed in a controlled laboratory environment using typical hardware setups. In addition, an evaluation was performed to evaluate the accuracy impact due to a single axis camera offset. Segment length and positional data exhibited errors within 3 percent when using three-dimensional analysis and yielded errors within 8 percent through two-dimensional analysis (Direct Linear Software). Peak angular velocities displayed errors within 6 percent through three-dimensional analyses and exhibited errors of 12 percent when using two-dimensional analysis (Direct Linear Software). The specific results from this series of evaluations and their impacts on the methodology issues of kinematic data collection and analyses are presented in detail. The accuracy levels observed in these evaluations are also presented.

Wilmington, R. P.↗

NASA NTRS1993

Processing parameters associated with scale-up of balloon film production

A method is set forth for assessing strain-rate profiles that can be used to develop a scale-up theory for blown-film extrusion. Strain rates are evaluated by placing four ink dots on the stalk of an extruded bubble to follow the displacements of the dots as a function of time. The instantaneous Hencky strain is obtained with the displacement data and plotted for analysis. Specific attention is given to potential sources of error in the distance measurements and corrections for these complex bubble geometries. The method is shown to be effective for deriving strain-rate data related to different processing parameters for the production of balloon film. The strain rates can be compared to frostline height, blow-up ratio, and take-up ratio to optimize these processing variables.

Simpson, D. M.↗

NASA NTRS2005

Faults Discovery By Using Mined Data

Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

Lee, Charles↗

NASA NTRS1995

Determination of stability and control derivatives from the NASA F/A-18 HARV from flight data using the maximum likelihood method

This report is a compilation of PID (Proportional Integral Derivative) results for both longitudinal and lateral directional analysis that was completed during Fall 1994. It had earlier established that the maneuvers available for PID containing independent control surface inputs from OBES were not well suited for extracting the cross-coupling static (i.e., C(sub N beta)) or dynamic (i.e., C(sub Npf)) derivatives. This was due to the fact that these maneuvers were designed with the goal of minimizing any lateral directional motion during longitudinal maneuvers and vice-versa. This allows for greater simplification in the aerodynamic model as far as coupling between longitudinal and lateral directions is concerned. As a result, efforts were made to reanalyze this data and extract static and dynamic derivatives for the F/A-18 HARV (High Angle of Attack Research Vehicle) without the inclusion of the cross-coupling terms such that more accurate estimates of classical model terms could be acquired. Four longitudinal flights containing static PID maneuvers were examined. The classical state equations already available in pEst for alphadot, qdot and thetadot were used. Three lateral directional flights of PID static maneuvers were also examined. The classical state equations already available in pEst for betadot, p dot, rdot and phi dot were used. Enclosed with this document are the full set of longitudinal and lateral directional parameter estimate plots showing coefficient estimates along with Cramer-Rao bounds. In addition, a representative time history match for each type of meneuver tested at each angle of attack is also enclosed.

Napolitano, Marcello R.↗

NASA NTRSDate not supplied

Enabling Intelligent Data Downlink Prioritization of In-Situ Observations through Generalizable and Computationally Inexpensive Anomaly Detection

High-fidelity measurements of magnetic fields and other observed properties, such as energetic particle fluxes, are a necessary component to our understanding of the highly dynamic near-Earth space environment. As our desire to study smaller-scale phenomena such as shocks and dipolorizations has increased, we have been driven to take and telemeter measurements at higher cadences. Unfortunately, many missions are unable to downlink all their captured data due to the well-known data transmission bottleneck at the DSN. These missions must then prioritize their high-cadence data such that the most scientifically useful intervals are transmitted. One simple prioritization technique uses the spacecraft position to telemeter data from only the region of interest. Although easy to implement, this method does not leverage the available scientific data and can omit intervals of useful scientific data when they lie outside the region of interest. The Magnetospheric Multiscale Mission (MMS) uses mission-specific parameterization of several data products to automatically prioritize scientifically useful intervals. Then, MMS verifies the automatically selected intervals by having a domain expert manually select intervals for downlink. The overall complexity required by this technique make it prohibitive for deployment on low-cost platforms (i.e., CubeSats) or on future missions featuring large constellations of satellites such as the Geospace Dynamics Constellation (GDC). We present preliminary results for a simple, generic, and data-driven method of downlink prioritization for magnetic field (and other) measurements. Specifically, Principal Components Analysis (PCA) and One-Class Support Vector Machines (OC-SVMs) are used to detect intervals containing anomalous activity, which can then be prioritized for subsequent downlink. The computational simplicity of this algorithm makes it an excellent candidate for implementation on spaceflight hardware, as well as provide generalizability to a broad range of missions and data products. Initial analysis of this technique has been performed using magnetic field measurements from the Magnetospheric Multiscale Mission and CASSIOP, where it automatically identified scientifically interesting intervals containing Alfvén waves and EMIC activity.

Matthew G. Finley↗

NASA NTRSDate not supplied

Enabling Intelligent Data Downlink Prioritization of In-Situ Observations through Generalizable and Computationally Inexpensive Anomaly Detection

Matthew G. Finley↗