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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 361 records · Page 20

Application of Support Vector Regression to Derive Crater Depth/Diameter From Satellite Images

Through the study of impact crater shapes, one can draw important conclusions about the nature and evolution of planetary surfaces [e.g., 1-4].In particular, studying the depth (d) to diameter (D)ratio (d/D) of a population of impact craters, in combination with crater count statistics, can yield valuable insights regarding rates of erosion and burial[5]. Motivated by the great abundance of available planetary surface image data, the goal of this project is to develop an efficient way to estimate d/D from satellite images of impact craters for which stereo information is not available [6]. We set out to develop and train a machine learning algorithm to extract d/D from a dataset of synthetic impact crater images for which model d/D is known. The applications of machine learning to planetary science are numerous and diverse [7], including automatic planetary surface mapping [8] and the detection of impact craters [9]. Our algorithm makes use of Support Vector Regression (SVR), which is a type of Support Vector Machine (SVM) [10, 11].SVMs are a branch of supervised machine learning valued for their straightforward implementation and versatility in solving both classification and regression problems. In regression analysis, an SVR algorithm produces a hyperplane function to fit the training data points, as well as an ε-tube that surrounds the hyperplane. Tunable hyperparameters include the width of the ε-tube (ε) and the amount an algorithm is penalized for points which fall outside the ε-tube.

L R Chin↗

Data Transmission Signal Design and Analysis

The error performances of several digital signaling methods are determined as a function of a specified signal-to-noise ratio. Results are obtained for Gaussian noise and impulse noise. Performance of a receiver for differentially encoded biphase signaling is obtained by extending the results of differential phase shift keying. The analysis presented obtains a closed-form answer through the use of some simplifying assumptions. The results give an insight into the analysis problem, however, the actual error performance may show a degradation because of the assumptions made in the analysis. Bipolar signaling decision-threshold selection is investigated. The optimum threshold depends on the signal-to-noise ratio and requires the use of an adaptive receiver.

Moore, J. D.↗

The development of a pseudo-nyquist analysis technique for hybrid sampled-data control systems

The stability characteristics of a launch vehicle, as a function of gain and phase variations at the thrust vector controller, cannot be obtained using classical sampled-data control theory if the launch vehicle attitude control system contains both sampled-data and continuous feedback control loops. A method was developed which can be used to generate a sampled-data pseudo-Nyquist plot for gain and phase variations at the controller. This method was developed and used to determine the stability characteristics of the Saturn 1B launch vehicle in the backup guidance mode.

Burnitt, M. G.↗

The diffuse galactic gamma ray emission

The EGRET (Energetic Gamma-Ray Experiment Telescope) detector will provide a much more detailed view of the diffuse galactic gamma ray intensity in terms of higher resolution, greater statistical significance, and broader energy range than earlier missions. These observations will furnish insight into a number of very important questions related to the dynamics and structure of the Galaxy. A diffuse emission model is being developed that incorporates the latest information on matter distribution and source functions. In addition, it is tailored to the EGRET instrument response functions. The analysis code of the model maintains flexibility to accommodate the quality of the data that is anticipated. The discussion here focuses on the issues of the distributions of matter, cosmic rays, and radiation fields, and on the important source functions that enter into the model calculation of diffuse emission.

Bertsch, David L.↗

Guided Wave Delamination Detection and Quantification With Wavefield Data Analysis

Unexpected damage can occur in aerospace composites due to impact events or material stress during off-nominal loading events. In particular, laminated composites are susceptible to delamination damage due to weak transverse tensile and inter-laminar shear strengths. Developments of reliable and quantitative techniques to detect delamination damage in laminated composites are imperative for safe and functional optimally-designed next-generation composite structures. In this paper, we investigate guided wave interactions with delamination damage and develop quantification algorithms by using wavefield data analysis. The trapped guided waves in the delamination region are observed from the wavefield data and further quantitatively interpreted by using different wavenumber analysis methods. The frequency-wavenumber representation of the wavefield shows that new wavenumbers are present and correlate to trapped waves in the damage region. These new wavenumbers are used to detect and quantify the delamination damage through the wavenumber analysis, which can show how the wavenumber changes as a function of wave propagation distance. The location and spatial duration of the new wavenumbers can be identified, providing a useful means not only for detecting the presence of delamination damage but also allowing for estimation of the delamination size. Our method has been applied to detect and quantify real delamination damage with complex geometry (grown using a quasi-static indentation technique). The detection and quantification results show the location, size, and shape of the delamination damage.

Tian, Zhenhua↗

Ares I-X In-Flight Modal Identification

Operational modal analysis is a procedure that allows the extraction of modal parameters of a structure in its operating environment. It is based on the idealized premise that input to the structure is white noise. In some cases, when free decay responses are corrupted by unmeasured random disturbances, the response data can be processed into cross-correlation functions that approximate free decay responses. Modal parameters can be computed from these functions by time domain identification methods such as the Eigenvalue Realization Algorithm (ERA). The extracted modal parameters have the same characteristics as impulse response functions of the original system. Operational modal analysis is performed on Ares I-X in-flight data. Since the dynamic system is not stationary due to propellant mass loss, modal identification is only possible by analyzing the system as a series of linearized models over short periods of time via a sliding time-window of short time intervals. A time-domain zooming technique was also employed to enhance the modal parameter extraction. Results of this study demonstrate that free-decay time domain modal identification methods can be successfully employed for in-flight launch vehicle modal extraction.

Bartkowicz, Theodore J.↗

Advances in automatic extraction of information from multispectral scanner data

The state-of-the-art of automatic multispectral scanner data analysis and interpretation is reviewed. Sources of system variability which tend to obscure the spectral characteristics of the classes under consideration are discussed, and examples of the application of spatial and temporal discrimination bases are given. Automatic processing functions, techniques and methods, and equipment are described with particular attention to those that are applicable to large land surveys using satellite data. The development and characteristics of the Multivariate Interactive Digital Analysis System (MIDAS) for processing aircraft or satellite multispectral scanning data are discussed in detail. The MIDAS system combines the parallel digital implementation capabilities of a low-cost processor with a general purpose PDP-11/45 minicomputer to provide near-real-time data processing. The preprocessing functions are user-selectable. The input subsystem accepts data stored on high density digital tape, computer compatible tape, and analog tape.

Erickson, J. D.↗

Ares Launch Vehicle Transonic Buffet Testing and Analysis Techniques

It is necessary to define the launch vehicle buffet loads to ensure that structural components and vehicle subsystems possess adequate strength, stress, and fatigue margins when the vehicle structural dynamic response to buffet forcing functions are considered. In order to obtain these forcing functions, the accepted method is to perform wind-tunnel testing of a rigid model instrumented with hundreds of unsteady pressure transducers designed to measure the buffet environment across the desired frequency range. The buffet wind-tunnel test program for the Ares Crew Launch Vehicle employed 3.5 percent scale rigid models of the Ares I and Ares I-X launch vehicles instrumented with 256 unsteady pressure transducers each. These models were tested at transonic conditions at the Transonic Dynamics Tunnel at NASA Langley Research Center. The ultimate deliverable of the Ares buffet test program are buffet forcing functions (BFFs) derived from integrating the measured fluctuating pressures on the rigid wind-tunnel models. These BFFs are then used as input to a multi-mode structural analysis to determine the vehicle response to buffet and the resulting buffet loads and accelerations. This paper discusses the development of the Ares I and I-X rigid buffet model test programs from the standpoint of model design, instrumentation system design, test implementation, data analysis techniques to yield final products, and presents normalized sectional buffet forcing function root-mean-squared levels.

Piatak, David J.↗

Galileo spacecraft modal test and evaluation of testing techniques

The structural configuration, modal test requirements and pre-test activities involved in modeling the expected dynamic environment and responses of the Galileo spacecraft are discussed. The probe will be Shuttle-launched in 1986 and will gather data on the Jupiter system. Loads analysis for the 5300 lb spacecraft were performed with the NASTRAN code, and covered 10,000 static degrees of freedom and 1600 mass degrees of freedom. A modal analysis will be used to verify the predictions for natural frequencies, mode shapes, orthogonality checks, residual mass, modal damping and forces, and generalized forces. Verification of the validity of considering only 70 natural modes in the numerical simulation is being performed by examining the forcing functions of the analysis. The analysis led to requirements that 162 channels of accelerometer data and 118 channels of strain gage data be recorded during shaker tests to reveal areas where design changes will be needed to eliminate vibration peaks.

Chen, J.-C.↗

Free vibration and dynamic response analysis of spinning structures

The proposed effort involved development of numerical procedures for efficient solution of free vibration problems of spinning structures. An eigenproblem solution procedure, based on a Lanczos method employing complex arithmetic, was successfully developed. This task involved formulation of the numerical procedure, FORTRAN coding of the algorithm, checking and debugging of software, and implementation of the routine in the STARS program. A graphics package for the E/S PS 300 as well as for the Tektronix terminals was successfully generated and consists of the following special capabilities: (1) a dynamic response plot for the stresses and displacements as functions of time; and (2) a menu driven command module enabling input of data on an interactive basis. Finally, the STARS analysis capability was further improved by implementing the dynamic response analysis package that provides information on nodal deformations and element stresses as a function of time. A number of test cases were run utilizing the currently developed algorithm implemented in the STARS program and such results indicate that the newly generated solution technique is significantly more efficient than other existing similar procedures.

Source record↗

Machine-learning-enabled on-the-fly analysis of RHEED patterns during thin film deposition by molecular beam epitaxy

Thin film deposition is a fundamental technology for the discovery, optimization, and manufacturing of functional materials. Deposition by molecular beam epitaxy (MBE) typically employs reflection high-energy electron diffraction (RHEED) as a real-time in situ probe of the growing film. However, the state-of-the-art for RHEED analysis during deposition requires human observation. Here, we present an approach using machine learning (ML) methods to monitor, analyze, and interpret RHEED images on-the-fly during thin film deposition. In the analysis workflow, RHEED pattern images are collected at one frame per second and featurized using a pretrained deep convolutional neural network. The feature vectors are then statistically analyzed to identify changepoints; these changepoints can be related to changes in the deposition mode from initial film nucleation to a transition regime, smooth film deposition, and in some cases, an additional transition to a rough, islanded deposition regime. The feature vectors are additionally analyzed via graph analysis and community classification. The graph is quantified as a stabilization plot, and we show that inflection points in the stabilization plot correspond to changes in the growth regime. The full RHEED analysis workflow is termed RHAAPsody and includes data transfer and output to a visual dashboard. We demonstrate the functionality of RHAAPsody by analyzing the precaptured RHEED images from epitaxial depositions of anatase TiO2 on SrTiO3(001) and show that the analysis workflow can be executed in less than 1 s. Our approach shows promise as one component of ML-enabled real-time feedback control of the MBE deposition process.

36 MATERIALS SCIENCE↗

SASS wind ambiguity removal by direct minimization

An objective analysis procedure is presented which combines Seasat-A satellite scatterometer (SASS) data with other available data on wind speeds by minimizing an objective function of gridded wind speed values. The functions are defined as the loss functions for the SASS velocity data, the forecast, the SASS velocity magnitude data, and conventional wind speed data. Only aliases closest to the analysis were included, and a method for improving the first guess while using a minimization technique and slowly changing the parameters of the problem is introduced. The model is employed to predict the wind field for the North Atlantic on Sept. 10, 1978. Dealiased SASS data is compared with available ship readings, showing good agreement between the SASS dealiased winds and the winds measured at the surface. Expansion of the model to take in low-level cloud measurements, pressure data, and convergence and cloud level data correlations is discussed.

Hoffman, R. N.↗

Orbital Debris Engineering Model (ORDEM) v.3

A model of the manmade orbital debris environment is required by spacecraft designers, mission planners, and others in order to understand and mitigate the effects of the environment on their spacecraft or systems. A manmade environment is dynamic, and can be altered significantly by intent (e.g., the Chinese anti-satellite weapon test of January 2007) or accident (e.g., the collision of Iridium 33 and Cosmos 2251 spacecraft in February 2009). Engineering models are used to portray the manmade debris environment in Earth orbit. The availability of new sensor and in situ data, the re-analysis of older data, and the development of new analytical and statistical techniques has enabled the construction of this more comprehensive and sophisticated model. The primary output of this model is the flux [#debris/area/time] as a function of debris size and year. ORDEM may be operated in spacecraft mode or telescope mode. In the former case, an analyst defines an orbit for a spacecraft and "flies" the spacecraft through the orbital debris environment. In the latter case, an analyst defines a ground-based sensor (telescope or radar) in terms of latitude, azimuth, and elevation, and the model provides the number of orbital debris traversing the sensor's field of view. An upgraded graphical user interface (GUI) is integrated with the software. This upgraded GUI uses project-oriented organization and provides the user with graphical representations of numerous output data products. These range from the conventional flux as a function of debris size for chosen analysis orbits (or views), for example, to the more complex color-contoured two-dimensional (2D) directional flux diagrams in local spacecraft elevation and azimuth.

Matney, Mark↗

Iterative Strain-Gage Balance Calibration Data Analysis for Extended Independent Variable Sets

A new method was developed that makes it possible to use an extended set of independent calibration variables for an iterative analysis of wind tunnel strain gage balance calibration data. The new method permits the application of the iterative analysis method whenever the total number of balance loads and other independent calibration variables is greater than the total number of measured strain gage outputs. Iteration equations used by the iterative analysis method have the limitation that the number of independent and dependent variables must match. The new method circumvents this limitation. It simply adds a missing dependent variable to the original data set by using an additional independent variable also as an additional dependent variable. Then, the desired solution of the regression analysis problem can be obtained that fits each gage output as a function of both the original and additional independent calibration variables. The final regression coefficients can be converted to data reduction matrix coefficients because the missing dependent variables were added to the data set without changing the regression analysis result for each gage output. Therefore, the new method still supports the application of the two load iteration equation choices that the iterative method traditionally uses for the prediction of balance loads during a wind tunnel test. An example is discussed in the paper that illustrates the application of the new method to a realistic simulation of temperature dependent calibration data set of a six component balance.

Ulbrich, Norbert Manfred↗

Spatial analysis of cell patterning to aid genetic and phenotypic understanding of grass stomatal density: A case study in maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

59 BASIC BIOLOGICAL SCIENCES↗

Land image data processing requirements for the EOS era

Requirements are proposed for a hybrid approach to image analysis that combines the functionality of a general-purpose image processing system with the knowledge representation and manipulation capabilities associated with expert systems to improve the productivity of scientists in extracting information from remotely sensed image data. The overall functional objectives of the proposed system are to: (1) reduce the level of human interaction required on a scene-by-scene basis to perform repetitive image processing tasks; (2) allow the user to experiment with ad hoc rules and procedures for the extraction, description, and identification of the features of interest; and (3) facilitate the derivation, application, and dissemination of expert knowledge for target recognition whose scope of application is not necessarily limited to the image(s) from which it was derived.

Wharton, Stephen W.↗

Deciphering Reaction Mechanisms of Molecular Proton Reduction Catalysts with Cyclic Voltammetry: Kinetic vs Thermodynamic Control

The kinetics and thermodynamics of elementary reaction steps involved in the catalytic reduction of protons to hydrogen define the reaction landscape for catalysis. The mechanisms can differ in the order of the elementary proton transfer, electron transfer, and bond-forming steps and can be further differentiated by the sites at which protons and electrons localize. Access to fully elucidated mechanistic, kinetic, and thermochemical details of molecular catalysts is crucial to facilitate the development of new catalysts that operate with optimal efficiency, selectivity, and durability. The mechanism by which a catalyst operates, as well as the kinetics and thermodynamics associated with the individual steps, can often be accessed through electroanalytical studies. Here, this Account details the application of cyclic voltammetry to interrogate reaction mechanisms and quantify the kinetics and thermodynamics of elementary reaction steps for a series of molecular catalysts that mediate electrochemical proton reduction. I distinguish the limiting scenarios wherein a catalyst operates under kinetic control vs thermodynamic control, with a focus on detecting how cyclic voltammetry features shift with proton source strength and concentration, as well as scan rate. For systems that operate under kinetic control, catalytic currents are observed at, or slightly positive toward, the formal potential for the redox process that triggers catalysis. Under thermodynamic control, catalytic responses shift as a function of the proton source pKa and effective pH of the solution. After drawing this distinction, we introduce the appropriate voltammetry experiments and accompanying analytical expressions for extracting key metrics from the data. To illustrate analytical strategies to quantify elementary reaction steps of catalysts operating under kinetic control, I describe our studies of proton reduction catalysts Co(dmgBF 2 ) 2 (CH 3 CN) 2 (dmgBF 2 = difluoroboryl-dimethylglyoxime) and [Ni(P 2 Ph N 2 Ph ) 2 ] 2+ (P 2 Ph N 2 Ph = 1,5-phenyl-3,7-phenyl-1,5-diaza-3,7-diphosphacyclooctane). Here, peak shift analysis, foot-of-the-wave analysis, and plateau current analysis are applied to data sets wherein voltammetric response are recorded as a function of catalyst concentration, proton source concentration, proton source strength, and scan rate to quantify rate constants for elementary proton transfer and bond-forming steps in a catalytic cycle. Further, the case study of [Ni(P 2 Ph N 2 Ph ) 2 ] 2+ illustrates how complementary spectroscopic methods can bolster the mechanistic assignment. Collectively, these two studies showcase how detailed mechanistic studies inform on rate-limiting elementary steps in catalysis and other key processes underpinning catalysis. Second, I present analytical strategies to interrogate catalysts operating under thermodynamic control, centered on the case study of [Ni II (P 2 Ph N 2 Bn ) 2 ] 2+ (P 2 Ph N 2 Bn = 1,5-dibenzyl-3,7-diphenyl-1,5-diaza-3,7-diphosphacyclooctane). Here, the application of nonaqueous Pourbaix theory to extract thermodynamic information is introduced, and the construction of a coupled Pourbaix diagram is detailed. This study identifies ligand-based protonation as the key process that places catalysis under thermodynamic control and influences the reaction mechanism. Together, the work detailed in this Account showcases the utility of electroanalytical methods to disentangle complex reaction mechanisms and extract key thermochemical and kinetic parameters for elementary steps of catalysis. Through detailed presentation of the key analytical expressions that underpin these analyses, this Account seeks to facilitate the adoption of cyclic voltammetry by the community to fully extract kinetic, thermochemical, and mechanistic information on electrochemical small-molecule activation.

catalysts↗