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NASA NTRS1994

(abstract) Synthesis of Speaker Facial Movements to Match Selected Speech Sequences

We are developing a system for synthesizing image sequences the simulate the facial motion of a speaker. To perform this synthesis, we are pursuing two major areas of effort. We are developing the necessary computer graphics technology to synthesize a realistic image sequence of a person speaking selected speech sequences. Next, we are developing a model that expresses the relation between spoken phonemes and face/mouth shape. A subject is video taped speaking an arbitrary text that contains expression of the full list of desired database phonemes. The subject is video taped from the front speaking normally, recording both audio and video detail simultaneously. Using the audio track, we identify the specific video frames on the tape relating to each spoken phoneme. From this range we digitize the video frame which represents the extreme of mouth motion/shape. Thus, we construct a database of images of face/mouth shape related to spoken phonemes. A selected audio speech sequence is recorded which is the basis for synthesizing a matching video sequence; the speaker need not be the same as used for constructing the database. The audio sequence is analyzed to determine the spoken phoneme sequence and the relative timing of the enunciation of those phonemes. Synthesizing an image sequence corresponding to the spoken phoneme sequence is accomplished using a graphics technique known as morphing. Image sequence keyframes necessary for this processing are based on the spoken phoneme sequence and timing. We have been successful in synthesizing the facial motion of a native English speaker for a small set of arbitrary speech segments. Our future work will focus on advancement of the face shape/phoneme model and independent control of facial features.

graphics audio digitizing morphing enunciation pho↗

NASA NTRS2012

General MACOS Interface for Modeling and Analysis for Controlled Optical Systems

The General MACOS Interface (GMI) for Modeling and Analysis for Controlled Optical Systems (MACOS) enables the use of MATLAB as a front-end for JPL s critical optical modeling package, MACOS. MACOS is JPL s in-house optical modeling software, which has proven to be a superb tool for advanced systems engineering of optical systems. GMI, coupled with MACOS, allows for seamless interfacing with modeling tools from other disciplines to make possible integration of dynamics, structures, and thermal models with the addition of control systems for deformable optics and other actuated optics. This software package is designed as a tool for analysts to quickly and easily use MACOS without needing to be an expert at programming MACOS. The strength of MACOS is its ability to interface with various modeling/development platforms, allowing evaluation of system performance with thermal, mechanical, and optical modeling parameter variations. GMI provides an improved means for accessing selected key MACOS functionalities. The main objective of GMI is to marry the vast mathematical and graphical capabilities of MATLAB with the powerful optical analysis engine of MACOS, thereby providing a useful tool to anyone who can program in MATLAB. GMI also improves modeling efficiency by eliminating the need to write an interface function for each task/project, reducing error sources, speeding up user/modeling tasks, and making MACOS well suited for fast prototyping.

Sigrist, Norbert↗

NASA NTRS1981

MPS Solidification Model. Volume 2: Operating guide and software documentation for the unsteady model

The operation of solidification Model 2 is described and documentation of the software associated with the model is provided. Model 2 calculates the macrosegregation in a rectangular ingot of a binary alloy as a result of unsteady horizontal axisymmetric bidirectional solidification. The solidification program allows interactive modification of calculation parameters as well as selection of graphical and tabular output. In batch mode, parameter values are input in card image form and output consists of printed tables of solidification functions. The operational aspects of Model 2 that differ substantially from Model 1 are described. The global flow diagrams and data structures of Model 2 are included. The primary program documentation is the code itself.

Maples, A. L.↗

NASA NTRS1972

Satellite broadcasting system study

The study to develop a system model and computer program representative of broadcasting satellite systems employing community-type receiving terminals is reported. The program provides a user-oriented tool for evaluating performance/cost tradeoffs, synthesizing minimum cost systems for a given set of system requirements, and performing sensitivity analyses to identify critical parameters and technology. The performance/ costing philosophy and what is meant by a minimum cost system is shown graphically. Topics discussed include: main line control program, ground segment model, space segment model, cost models and launch vehicle selection. Several examples of minimum cost systems resulting from the computer program are presented. A listing of the computer program is also included.

Source record↗

DOE OSTI2017

Examining robustness of model selection with half-normal and LASSO plots for unreplicated factorial designs

When there are constraints on resources, an unreplicated factorial or fractional factorial design can allow efficient exploration of numerous factor and interaction effects. A half-normal plot is a common graphical tool used to compare the relative magnitude of effects and to identify important effects from these experiments when no estimate of error from the experiment is available. An alternative is to use a least absolute shrinkage and selection operation plot to examine the pattern of model selection terms from an experiment. We examine how both the half-normal and least absolute shrinkage and selection operation plots are impacted by the absence of individual observations or an outlier, and the robustness of conclusions obtained from these 2 techniques for identifying important effects from factorial experiments. As a result, the methods are illustrated with 2 examples from the literature.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1999

High Pressure Water Stripping Using Multi-Orifice Nozzles

The use of multi-orifice rotary nozzles greatly increases the speed and stripping effectiveness of high pressure water blasting systems, but also greatly increases the complexity of selecting and optimizing the operating parameters. The rotational speed of the nozzle must be coupled with its transverse velocity as it passes across the surface of the substrate being stripped. The radial and angular positions of each orifice must be included in the analysis of the nozzle configuration. Orifices at the outer edge of the nozzle head move at a faster rate than the orifices located near the center. The energy transmitted to the surface from the impact force of the water stream from an outer orifice is therefore spread over a larger area than energy from an inner orifice. Utilizing a larger diameter orifice in the outer radial positions increases the total energy transmitted from the outer orifice to compensate for the wider distribution of energy. The total flow rate from the combination of all orifices must be monitored and should be kept below the pump capacity while choosing orifice to insert in each position. The energy distribution from the orifice pattern is further complicated since the rotary path of all the orifices in the nozzle head pass through the center section. All orifices contribute to the stripping in the center of the path while only the outer most orifice contributes to the stripping at the edge of the nozzle. Additional orifices contribute to the stripping from the outer edge toward the center section. With all these parameters to configure and each parameter change affecting the others, a computer model was developed to track and coordinate these parameters. The computer simulation graphically indicates the cumulative affect from each parameter selected. The result from the proper choices in parameters is a well designed, highly efficient stripping system. A poorly chosen set of parameters will cause the nozzle to strip aggressively in some areas while leaving the coating untouched in adjacent sections. The high pressure water stripping system can be set to extremely aggressive conditions allowing stripping of hard to remove adhesives, paint systems, and even cladding and chromate conversion coatings. The energy force can also be reduced to strip coatings from thin aluminum substrates without causing any damage or deterioration to the substrate's surface. High pressure water stripping of aerospace components has thus proven to be an efficient and cost effective method for cleaning and removing coatings.

Hoppe, David↗

NASA NTRS1989

Definition of NASTRAN sets by use of parametric geometry

Many finite element preprocessors describe finite element model geometry with points, lines, surfaces and volumes. One method for describing these basic geometric entities is by use of parametric cubics which are useful for representing complex shapes. The lines, surfaces and volumes may be discretized for follow on finite element analysis. The ability to limit or selectively recover results from the finite element model is extremely important to the analyst. Equally important is the ability to easily apply boundary conditions. Although graphical preprocessors have made these tasks easier, model complexity may not lend itself to easily identify a group of grid points desired for data recovery or application of constraints. A methodology is presented which makes use of the assignment of grid point locations in parametric coordinates. The parametric coordinates provide a convenient ordering of the grid point locations and a method for retrieving the grid point ID's from the parent geometry. The selected grid points may then be used for the generation of the appropriate set and constraint cards.

Baughn, Terry V.↗

NASA NTRS2000

An Architecture for Real-Time Interpretation and Visualization of Structural Sensor Data in a Laboratory Environment

A visualization system is being developed out of the need to monitor, interpret, and make decisions based on the information from several thousand sensors during experimental testing to facilitate development and validation of structural health monitoring algorithms. As an added benefit the system will enable complete real-time sensor assessment of complex test specimens. Complex structural specimens are routinely tested that have hundreds or thousands of sensors. During a test, it is impossible for a single researcher to effectively monitor all the sensors and subsequently interesting phenomena occur that are not recognized until post-test analysis. The ability to detect and alert the researcher to these unexpected phenomena as the test progresses will significantly enhance the understanding and utilization of complex test articles. Utilization is increased by the ability to halt a test when the health monitoring algorithm response is not satisfactory or when an unexpected phenomenon occurs, enabling focused investigation potentially through the installation of additional sensors. Often if the test continues, structural changes make it impossible to reproduce the conditions that exhibited the phenomena. The prohibitive time and costs associated with fabrication, sensoring, and subsequent testing of additional test articles generally makes it impossible to further investigate the phenomena. A scalable architecture is described to address the complex computational demands of structural health monitoring algorithm development and laboratory experimental test monitoring. The researcher monitors the test using a photographic quality 3D graphical model with actual sensor locations identified. In addition, researchers can quickly activate plots displaying time or load versus selected sensor response along with the expected values and predefined limits. The architecture has several key features. First, distributed dissimilar computers may be seamlessly integrated into the information flow. Second, virtual sensors may be defined that are complex functions of existing sensors or other virtual sensors. Virtual sensors represent a calculated value not directly measured by particular physical instrument. They can be used, for example, to represent the maximum difference in a range of sensors or the calculated buckling load based on the current strains. Third, the architecture enables autonomous response to preconceived events, where by the system can be configured to suspend or abort a test if a failure is detected in the load introduction system. Fourth, the architecture is designed to allow cooperative monitoring and control of the test progression from multiple stations both remote and local to the test system. To illustrate the architecture, a preliminary implementation is described monitoring the Stitched Composite Wing recently tested at LaRC.

Doggett, William↗

NASA NTRS1998

High Pressure Water Stripping Using Multi-Orifice Nozzles

The use of multi-orifice rotary nozzles not only increases the speed and stripping effectiveness of high pressure water blasting systems, but also greatly increases the complexity of selecting and optimizing the operating parameters. The rotational speed of the nozzle must be coupled with the transverse velocity of the nozzle as it passes across the surface of the substrate being stripped. The radial and angular positions of each orifice must be included in the analysis of the nozzle configuration. Since orifices at the outer edge of the nozzle head move at a faster rate than the orifice located near the center, the energy impact force of the water stream from the outer orifice is spread over a larger area than the water streams from the inner orifice. Utilizing a larger diameter orifice in the outer radial positions increases the energy impact to compensate for its wider force distribution. The total flow rate from the combination of orifices must be monitored and kept below the pump capacity while choosing an orifice to insert in each position. The energy distribution from the orifice pattern is further complicated since the rotary path of all orifices in the nozzle head pass through the center section, contributing to the stripping in this area while only the outer most orifice contributes to the stripping in the shell area at the extreme outside edge of the nozzle. From t he outer most shell to the center section, more orifices contribute to the stripping in each progressively reduced diameter shell. With all these parameters to configure and each parameter change affecting the others, a computer model was developed to track and coordinate these parameters. The computer simulation responds by graphically indicating the cumulative affect from each parameter selected. The results from the proper choices in parameters is a well designed, highly efficient stripping system. A poorly chosen set of parameters will cause the nozzle to strip aggressively in some areas while leaving the coating untouched in adjacent sections. The high pressure water stripping system can be set to extremely aggressive conditions allowing stripping of hard to remove adhesives, paint systems, cladding and chromate conversion coatings. The energy force can be reduced to strip coatings from thin aluminum substrates without causing damage or deterioration to the substrate's surface. High pressure water stripping of aerospace components have thus proven to be an efficient and cost effective method for cleaning and removing coatings.

Hoppe, David T.↗

DOE OSTI2021

FY21 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

The development of algorithms for machine learning and data analysis for the 3013 Surveillance Program is a collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). For corrosion detection, Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS) data is extracted from large binary files, with software written to convert the data to physical attributes (e.g., height, color and grayscale values; all as functions of a location in a plane projection). A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data, flag significant features, execute Machine Learning (ML) algorithms, output parameters for trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Features can be called out by user-specified thresholds, manual labeling or machine learning algorithms when they have been completed. The ability to rapidly label data is important because of the volume of data required for training machine learning algorithms. The GUI has the flexibility to allow addition of improved ML algorithms, methods for data visualization, and statistical computations. Statistical analyses via the GUI include areas of pits within a defined range of pit depths, correlations between Red-Green-Blue (RGB) or grayscale intensity and relative surface height, covariances between values associated with features, and feature histograms. The development of supervised machine learning algorithms, however, has been hindered by a lack of training data. The machine learning algorithms for crack identification are being refined but require improvements to the true positive rate for crack detection. This shortcoming is an artifact of the limited training data currently available, perhaps more so than the structure of the neural networks. At present, the best results are had from a consensus over an ensemble of randomly generated Deep Neural Network (DNN) or Convolutional Neural Network (CNN) algorithms. Although the consensus accuracy method has yielded optimum true positive and true negative rates in excess of 80%, additional validation testing is necessary. In addition to the suite of LCM data that was initially used, and which represents the majority of the work presented in this report, WAMS image data was also reviewed at a preliminary level. The review included a comparison between image resolution and dynamic range for each method. WAMS (ZON file) image data was found to have a pixel pitch of 3.69μm compared to 1 μm for the LCM (vk4 file) data, which implies a lower resolution for the WAMS images. Conversely, the ratio of dynamic range of the WAMS data to the LCM data was approximately 41:20 for height data, suggesting that information from WAMS should more accurately determine the depth of pits. At present, the significance of the greater dynamic range of the WAMS data relative to the LCM data has not yet been evaluated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Thermal expansion of mullite-type Bi{sub 2}Al{sub 4}O{sub 9}: A study by X-ray diffraction, vibrational spectroscopy and density functional theory

Polycrystalline Bi{sub 2}Al{sub 4}O{sub 9} powder samples were synthesized using the glycerine method. Single crystals were produced from the powder product in a Bi{sub 2}O{sub 3} melt. The lattice thermal expansion of the mullite-type compound was studied using X-ray diffraction, Raman spectroscopy and density functional theory (DFT). The metric parameters were modeled using Grüneisen approximation for the zero pressure equation of state, where the temperature-dependent vibrational internal energy was calculated from the Debye characteristic frequency. Both the first-order and second-order Grüneisen approximations were applied for modeling the volumetric expansion, and the second-order approach provided physically meaningful axial parameters. The phonon density of states as well as phonon dispersion guided to set the characteristic frequency for simulation. The experimental infrared and Raman phonon bands were compared with those calculate from the DFT calculations. Selective Raman modes were analyzed for the thermal anharmonic behaviors using simplified Klemens model. The respective mode Grüneisen parameters were calculated from the pressure-dependent Raman spectra. - Graphical abstract: Crystal structure of mullite-type Bi{sub 2}Al{sub 4}O{sub 9} showing the edge-sharing AlO{sub 6} octahedra running parallel to the c-axis. - Highlights: • Thermal expansion of Bi{sub 2}Al{sub 4}O{sub 9} was studied using XRD, FTIR, Raman and DFT. • Metric parameters were modeled using Grüneisen approximation. • Phonon DOS and phonon dispersion helped to set the Debye frequency. • Mode Grüneisen parameters were calculated from the pressure-dependent Raman spectra. • Anharmonicity was analyzed for some selective Raman modes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1999

Scientific Programming Using Java and C: A Remote Sensing Example

This paper presents results of a project to port code for processing remotely sensed data from the UNIX environment to Windows. Factors considered during this process include time schedule, cost, resource availability, reuse of existing code, rapid interface development, ease of integration, and platform independence. The approach selected for this project used both Java and C. By using Java for the graphical user interface and C for the domain model, the strengths of both languages were utilized and the resulting code can easily be ported to other platforms. The advantages of this approach are discussed in this paper.

Prados, Donald↗

NASA NTRS1985

Electroencephalogram (EEG) and Magnetoencephalogram (MEG) as Tools for Evaluation of Cognitive Function

We have developed computerized analysis and display techniques to help identify the origins of visually evoked scalped potentials (VESP). The potentials are recorded simultaneously from many electrodes (usually 40 to 48) spaced over the region of the scalp where appreciable evoked potentials are found in response to particular stimulus. Contour mapping algorithms are then used to display the time behavior of equipotential surfaces on the scalp during the VESP. We then use an optimization technique to select the parameters of arrays of current dipole sources within the model until the model equipotential field distribution closely fits the measured data. Computer graphics are then used to display, as a movie, the actual and model scalp potential fields and the parameters of the dipole generators within the model head during the course of VESP activity. We have devised reaction time tests that involve potentially separable stages of cognitive processing and utilize stimuli that produce measurable cognition-related features in the late component of the evoked potential. We have used these techniques to determine the loci in the brain where known cognition-related features in the evoked potential are generated and we have explored the extent to which each of these features can be related to the reaction time tasks. We have also examined the temporal-spatial aspects of their cerebral involvement. Our current work is planned to characterize the age-related changes in the processes performed by such sources. We also use a neuromagnetometer to measure the evoked magnetic fields in similar circumstances; we will discuss the relative merits of the two methodologies.

Fender, Derek H.↗

DOE OSTI2020

SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking (FY2020 Progress Report)

3013 corrosion↗

NASA NTRS1999

Aerothermo-Structural Analysis of Low Cost Composite Nozzle/Inlet Components

This research is a cooperative effort among the Turbomachinery and Propulsion Division of NASA Glenn, CCMR of NC A&T State University, and the Tuskegee University. The NC A&T is the lead center and Tuskegee University is the participating institution. Objectives of the research were to develop an integrated aerodynamic, thermal and structural analysis code for design of aircraft engine components, such as, nozzles and inlets made of textile composites; conduct design studies on typical inlets for hypersonic transportation vehicles and setup standards test examples and finally manufacture a scaled down composite inlet. These objectives are accomplished through the following seven tasks: (1) identify the relevant public domain codes for all three types of analysis; (2) evaluate the codes for the accuracy of results and computational efficiency; (3) develop aero-thermal and thermal structural mapping algorithms; (4) integrate all the codes into one single code; (5) write a graphical user interface to improve the user friendliness of the code; (6) conduct test studies for rocket based combined-cycle engine inlet; and finally (7) fabricate a demonstration inlet model using textile preform composites. Tasks one, two and six are being pursued. Selected and evaluated NPARC for flow field analysis, CSTEM for in-depth thermal analysis of inlets and nozzles and FRAC3D for stress analysis. These codes have been independently verified for accuracy and performance. In addition, graphical user interface based on micromechanics analysis for laminated as well as textile composites was developed. Demonstration of this code will be made at the conference. A rocket based combined cycle engine was selected for test studies. Flow field analysis of various inlet geometries were studied. Integration of codes is being continued. The codes developed are being applied to a candidate example of trailblazer engine proposed for space transportation. A successful development of the code will provide a simpler, faster and user-friendly tool for conducting design studies of aircraft and spacecraft engines, applicable in high speed civil transport and space missions.

Shivakumar, Kuwigai↗

DOE OSTI2022

FY22 Progress Report: SRNL Analysis of ICCWR LCM and WAMS Data for Corrosion and Cracking

Algorithms for machine learning and data analysis for the 3013 Surveillance Program are being developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). To detect the presence of corrosion and cracking, data is collected from large binary files generated by a Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS). Software is being developed to use the physical attributes in the data files (e.g., height, color, and grayscale values; all as functions of a location in a plane projection) to detect the presence of surface corrosion and cracking. A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data for training ML algorithms, flag significant features, execute Machine Learning (ML) algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Surface defects can be called out by setting user-specified thresholds, feature based analysis or machine learning algorithms. Enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the very large volume of data required to train ML algorithms.

3013 Corrosion↗

NASA NTRS1996

The Integrated Mode Management Interface

Mode management is the processes of understanding the character and consequences of autoflight modes, planning and selecting the engagement, disengagement and transitions between modes, and anticipating automatic mode transitions made by the autoflight system itself. The state of the art is represented by the latest designs produced by each of the major airframe manufacturers, the Boeing 747-400, the Boeing 777, the McDonnell Douglas MD-11, and the Airbus A320/A340 family of airplanes. In these airplanes autoflight modes are selected by manipulating switches on the control panel. The state of the autoflight system is displayed on the flight mode annunciators. The integrated mode management interface (IMMI) is a graphical interface to autoflight mode management systems for aircraft equipped with flight management computer systems (FMCS). The interface consists of a vertical mode manager and a lateral mode manager. Autoflight modes are depicted by icons on a graphical display. Mode selection is accomplished by touching (or mousing) the appropriate icon. The IMMI provides flight crews with an integrated interface to autoflight systems for aircraft equipped with flight management computer systems (FMCS). The current version is modeled on the Boeing glass-cockpit airplanes (747-400, 757/767). It runs on the SGI Indigo workstation. A working prototype of this graphics-based crew interface to the autoflight mode management tasks of glass cockpit airplanes has been installed in the Advanced Concepts Flight Simulator of the CSSRF of NASA Ames Research Center. This IMMI replaces the devices in FMCS equipped airplanes currently known as mode control panel (Boeing), flight guidance control panel (McDonnell Douglas), and flight control unit (Airbus). It also augments the functions of the flight mode annunciators. All glass cockpit airplanes are sufficiently similar that the IMMI could be tailored to the mode management system of any modern cockpit. The IMMI does not replace the functions of the FMCS control and display unit. The purpose of the INMI is to provide flight crews with a shared medium in which they can assess the state of the autoflight system, take control actions on it, reason about its behavior, and communicate with each other about its behavior. The design is intended to increase mode awareness and provide a better interface to autoflight mode management. This report describes the IMMI, the methods that were used in designing and developing it, and the theory underlying the design and development processes.

Hutchins, Edwin↗

NASA NTRS1985

NPLOT: an Interactive Plotting Program for NASTRAN Finite Element Models

The NPLOT (NASTRAN Plot) is an interactive computer graphics program for plotting undeformed and deformed NASTRAN finite element models. Developed at NASA's Goddard Space Flight Center, the program provides flexible element selection and grid point, ASET and SPC degree of freedom labelling. It is easy to use and provides a combination menu and command driven user interface. NPLOT also provides very fast hidden line and haloed line algorithms. The hidden line algorithm in NPLOT proved to be both very accurate and several times faster than other existing hidden line algorithms. A fast spatial bucket sort and horizon edge computation are used to achieve this high level of performance. The hidden line and the haloed line algorithms are the primary features that make NPLOT different from other plotting programs.

Jones, G. K.↗