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NASA NTRS1997

Probabilistic Approaches: Composite Design

Probabilistic composite design is described in terms of a computational simulation. This simulation tracks probabilistically the composite design evolution from constituent materials, fabrication process through composite mechanics, and structural component. Comparisons with experimental data are provided to illustrate selection of probabilistic design allowables, test methods/specimen guidelines, and identification of in situ versus pristine strength. For example, results show that: in situ fiber tensile strength is 90 percent of its pristine strength; flat-wise long-tapered specimens are most suitable for setting ply tensile strength allowables; a composite radome can be designed with a reliability of 0.999999; and laminate fatigue exhibits wide spread scatter at 90 percent cyclic-stress to static-strength ratios.

Chamis, Christos C.↗

NASA NTRS1997

Probabilistic Composite Design

Probabilistic composite design is described in terms of a computational simulation. This simulation tracks probabilistically the composite design evolution from constituent materials, fabrication process, through composite mechanics and structural components. Comparisons with experimental data are provided to illustrate selection of probabilistic design allowables, test methods/specimen guidelines, and identification of in situ versus pristine strength, For example, results show that: in situ fiber tensile strength is 90% of its pristine strength; flat-wise long-tapered specimens are most suitable for setting ply tensile strength allowables: a composite radome can be designed with a reliability of 0.999999; and laminate fatigue exhibits wide-spread scatter at 90% cyclic-stress to static-strength ratios.

Chamis, Christos C.↗

NASA NTRS1999

Cosmic Ray Telescope Experiment (CRT), Pioneer 10/11 Program

In May 1996 the electrical power on Pioneer 10 was no longer adequate to support the Cosmic Ray Telescope Experiment (CRT). In March 1997 ground based operations for the mission were terminated. The 25 years of Pioneer 10 were a remarkable voyage of discovery as it ventured into a vast new unexplored region of space. These observations by the Pioneer experiments led in the development of a new discipline of space science - heliospheric physics. For cosmic ray studies it was an incredible era, leading to the identification of new energetic particle populations and processes and initiating the study of the dynamics and large-scale structure and began the study of the dynamics and large-scale structure of the outer heliosphere. A summary of some of the principal scientific findings of the CRT experiment over this period is given in the next section. Even with the cessation of data from the Pioneer 10/11 mission there remained a great deal of scientific analysis and data archiving that required on the order of an additional three years of effort on the part of the CRT team. We have tried to select those tasks where the P10/11 CRT data have an important role to play. Special emphasis is placed on long-term synoptic studies that make use of the extended temporal and spatial coverage of the missions and the full capabilities of the CRT experiment. The major scientific objectives of this study are: (1) A phenomenological study of the modulation process in the heliosphere, thereby laying the foundation for developing a unified model of cosmic ray modulation over a complete 22 year heliomagnetic cycle; (2) These modulation studies and the temporal changes in the cosmic ray intensities also provide information on the large-scale structure and dynamics of the outer heliosphere; (3) use the galactic and anomalous cosmic ray data from Pioneer 10 to obtain a more accurate estimate of the distance to the modulation boundary and to the termination shock; (4) Use the results from (2) and from temporal variations to determine whether significant modulation occurs in the region of the heliosphere; (5)study the acceleration and transport of low energy solar interplanetary energetic particles and their relation to solar activity and interplanetary phenomena.

McDonald, Frank B.↗

NASA NTRS1999

Optimized System Identification

In system identification, one usually cares most about finding a model whose outputs are as close as possible to the true system outputs when the same input is applied to both. However, most system identification algorithms do not minimize this output error. Often they minimize model equation error instead, as in typical least-squares fits using a finite-difference model, and it is seen here that this distinction is significant. Here, we develop a set of system identification algorithms that minimize output error for multi-input/multi-output and multi-input/single-output systems. This is done with sequential quadratic programming iterations on the nonlinear least-squares problems, with an eigendecomposition to handle indefinite second partials. This optimization minimizes a nonlinear function of many variables, and hence can converge to local minima. To handle this problem, we start the iterations from the OKID (Observer/Kalman Identification) algorithm result. Not only has OKID proved very effective in practice, it minimizes an output error of an observer which has the property that as the data set gets large, it converges to minimizing the criterion of interest here. Hence, it is a particularly good starting point for the nonlinear iterations here. Examples show that the methods developed here eliminate the bias that is often observed using any system identification methods of either over-estimating or under-estimating the damping of vibration modes in lightly damped structures.

Juang, Jer-Nan↗

NASA NTRS2003

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/~ge/gedihome.html Supplementary information: http://www.chip.org/~ge/gedihome.html.

Database Management Systems↗

NASA NTRS2011

Organic Carbon Features Identified in the Nakhla Martian Meteorite

We report, for the first time, the identification of specific carbonaceous phases, present within iddingsite alteration zones of the Nakhla meteorite that possess discrete, well defined, structurally coherent morphologies. These structures bear superficial similarity to the carbonaceous nanoglobules [1] found in primitive chondrites interplanetary dust particles, although they are an order-of-magnitude larger in size. Introduction: It has been known for many years that some members of the Martian meteorite clan contain organic matter [e.g., 2-4]. Based on both isotopic measurements [5] and circumstantial observations [4] (e.g., the similarity organic signatures present in both Antarctic finds and non-Antarctic falls) a credible argument has been made for a preterrestrial origin for the majority of these organics. The Nakhla meteorite is of particular interest in that it has been shown to contain both an acid-labile organic fraction as well as an acid-insoluble high molecular weight organic component [4]. Pyrolysis-gas chromatography-mass spectrometry of the latter component indicates it to be composed of aromatic and alkyl-aromatic functionalities bound into a macromolecule phase through ether linkages [4]. However, the spatial, textural and mineralogical associations of this carbonaceous macromolecular material have remained elusive [6].

Mckay, D. S.↗

NASA NTRS2012

Topographic Rise in the Northern Smooth Plains of Mercury: Characteristics from Messenger Image and Altimetry Data and Candidate Modes of Origin

MESSENGER observations from orbit around Mercury have revealed that a large contiguous area of smooth plains occupies much of the high northern latitudes and covers an area in excess of approx.6% of the surface of the planet [1] (Fig. 1). Smooth surface morphology, embayment relationships, color data, candidate flow fronts, and a population of partly to wholly buried craters provide evidence for the volcanic origin of these plains and their emplacement in a flood lava mode to depths at least locally in excess of 1 km. The age of these plains is similar to that of plains associated with and postdating the Caloris impact basin, confirming that volcanism was a globally extensive process in the post-heavy bombardment history of Mercury [1]. No specific effusive vent structures, constructional volcanic edifices, or lava distributary features (leveed flow fronts or sinuous rilles) have been identified in the contiguous plains, although vent structures and evidence of high-effusion-rate flood eruptions are seen in adjacent areas [1]. Subsequent to the identification and mapping of the extensive north polar smooth plains, data from the Mercury Laser Altimeter (MLA) on MESSENGER revealed the presence of a broad topographic rise in the northern smooth plains that is ~1,000 km across and rises more than 1.5 km above the surrounding smooth plains [2] (Fig. 2). The purpose of this contribution is to characterize the northern plains rise and to outline a range of hypotheses for its origin.

Dickson, James L.↗

NASA NTRS2017

New Flutter Analysis Technique for Time-Domain Computational Aeroelasticity

A new time-domain approach for computing flutter speed is presented. Based on the time-history result of aeroelastic simulation, the unknown unsteady aerodynamics model is estimated using a system identification technique. The full aeroelastic model is generated via coupling the estimated unsteady aerodynamic model with the known linear structure model. The critical dynamic pressure is computed and used in the subsequent simulation until the convergence of the critical dynamic pressure is achieved. The proposed method is applied to a benchmark cantilevered rectangular wing.

HWB aircraft↗

NASA NTRSDate not supplied

Uncertainty Quantification of Inducer Natural Frequency using Conditional Assessment of Modeling and Modal Testing of Simpler Systems

The low pressure fuel pump inducer of the new Space Launch System RS25 core stage engine operates in a highly complex environment that substantially affects its modal characteristics. Some of the more important effects are fluid-added mass resulting from operation within a light liquid (Hydrogen), and the magnification of this effect due to tight tip clearance. Since higher order cavitation has been identified as a significant harmonic driver, knowledge of the natural frequency of potentially excitable modes is critical for safe operation, but this frequency cannot be measured during the severe operational environment. A comprehensive testing and analysis program has therefore been performed over the last four years to identify the nominal value and uncertainty of the frequency by modeling and testing four simpler structures which share some of the characteristics of the operational inducer. This testing was used to assess and adjust modeling techniques and excellent correlation was achieved. Identification of the uncertainty in the inducer frequency itself was still problematic, however. This difficulty led to an investigation of Bayesian uncertainty quantification techniques, and to the application of the relatively simple technique of Multi-Variate Normal conditional distributions to calculate the inducer natural frequency uncertainty. Assumptions on prior distributions of uncertainty of the fluid-added mass and tip clearance effect are initially applied to models of each of the simple structures and the inducer itself, and these uncertainties are propagated to generate natural frequencies using design of experiments. Simple response surfaces are then created from this data in order to calculate a Covariance Matrix relating all of these natural frequencies. Finally, the results from modal test of the simple structures are considered to be observations and used to calculate the conditional variance of the desired inducer frequencies. As this method is less rigorous than more complicated Bayesian methods reported in the literature, a conservative factor is applied to the result, but the resulting uncertainty is still significantly less than originally estimated and will greatly assist certification of the inducer for use in the engine.

Uncertainty Quantification↗

NASA NTRSDate not supplied

Uncertainty Quantification of Inducer Eigenvalues using Conditional Assessment of Models and Modal Test of Simpler Systems

Uncertainty Quantification↗

NASA NTRS1988

A unified process for systems identification based on performance assessment

Many modern spacecraft are complex multi-body dynamic systems where the bodies are connected by several active control systems for pointing and isolation. Mission requirements indicate that many structural modes and possibly some nonlinear effects will require characterization. Thus, even characterization at the subsystem level will become more difficult than usual. System level characterization difficulties will be compounded by the fact that only limited ground testing will be possible on the full up system, and flight testing will be restricted by an extremely limited measurements set. The object of the present discussion is the application of matrix majorant theory to the problem of assessing dynamic system performance when knowledge of the system is uncertain. We show how majorants provide an effective tool to relate required performance output to system identification test quality in terms of residual uncertainty in input-output relations, parameter values, nonlinearities, and interactions. The underlying machinery consists of the block-norm matrix which is a nonnegative matrix each of whose elements is the norm of a block of a suitably partitioned matrix. A matrix which bounds the block-norm matrix in the sense of nonnegative matrices, i.e., element by element is known as a majorant.

Hyland, C.↗

DOE OSTI2024

FY24 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

Algorithms for Machine Learning (ML) and data analysis for the 3013 Surveillance Program have been developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). The objective of the algorithms is to automate the identification of corrosion and crack formation in the Inner Container Closure Weld Region (ICCWR) of the canister system used to store Pu-bearing material. Data for corrosion and cracking is collected from large binary files generated by a Laser Confocal Microscope (LCM), the Wide Area 3D Measurement System (WAMS), or,in a recent proposal, by a Scanning Electron Microscope (SEM). The ML software uses the physical attributes in the data files (e.g., one or more of: height, color, and 16-bit grayscale values as functions of position in a plane projection) to detect signs of surface corrosion and cracking after being trained on similar data, with the features to be detected. Although the initial scope included screening for broader indicators of corrosion, e.g., pitting, identification of potential cracks was prioritized for the past several years at the request of program leadership. Labeled training data is essential to developing the ML algorithm, and 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 large volume of data required to train ML algorithms and the relative rarity of cracks in the ICCWR data set. The updated program will read binary data from either LCM, WAMS or SEM files, interrogate data attributes, facilitate user labeling of data for training ML algorithms, execute ML algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. In FY24, hourglass neural networks (HNNs) that were initiated in FY22 were further developed and tested using available LCM data, and their performance was tested against that of the alternative U-Net Neural Network algorithm structure. HNNs along with previously developed Convolutional Neural Networks (CNNs) and Deep Neural Networks (DNNs) comprise a suite of ML tools for identification of cracks in the ICCWR

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1993

Dynamic test results for the CASES ground experiment

The Controls, Astrophysics, and Structures Experiment in Space (CASES) Ground Test Facility (GTF) has been developed at Marshall Space Flight Center (MSFC) to provide a facility for the investigation of Controls/Structures Interaction (CSI) phenomena, to support ground testing of a potential shuttle-based CASES flight experiment, and to perform limited boom deployment and retraction dynamics studies. The primary objectives of the ground experiment are to investigate CSI on a test article representative of a Large Space Structure (LSS); provide a platform for Guest Investigators (GI's) to conduct CSI studies; to test and evaluate LSS control methodologies, system identification (ID) techniques, failure mode analysis; and to compare ground test predictions and flight results. The proposed CASES flight experiment consists of a 32 meter deployable/retractable boom at the end of which is an occulting plate. The control objective of the experiment is to maintain alignment of the tip plate (occulter) with a detector located at the base of the boom in the orbiter bay. The tip plate is pointed towards a star, the sun, or the galactic center to collect high-energy X-rays emitted by these sources. The tip plate, boom, and detector comprise a Fourier telescope. The occulting holes in the tip plate are approximately one millimeter in diameter making the alignment requirements quite stringent. Control authority is provided by bidirectional linear thrusters located at the boom tip and Angular Momentum Exchange Devices (AMED's) located at mid-boom and at the tip. The experiment embodies a number of CSI control problems including vibration suppression, pointing a long flexible structure, and disturbance rejection. The CASES GTF is representative of the proposed flight experiment with identical control objectives.

Bukley, Angelia P.↗

NASA NTRS1990

Infrared images of merging galaxies

Infrared imaging of interacting galaxies is especially interesting because their optical appearance is often so chaotic due to extinction by dust and emission from star formation regions, that it is impossible to locate the nuclei or determine the true stellar distribution. However, at near-infrared wavelengths extinction is considerably reduced, and most of the flux from galaxies originates from red giant stars that comprise the dominant stellar component by mass. Thus near infrared images offer the opportunity to study directly components of galactic structure which are otherwise inaccessible. Such images may ultimately provide the framework in which to understand the activity taking place in many of the mergers with high Infrared Astronomy Satellite (IRAS) luminosities. Infrared images have been useful in identifying double structures in the nuclei of interacting galaxies which have not even been hinted at by optical observations. A striking example of this is given by the K images of Arp 220. Graham et al. (1990) have used high resolution imaging to show that it has a double nucleus coincident with the radio sources in the middle of the dust lane. The results suggest that caution should be applied in the identification of optical bright spots as multiple nuclei in the absence of other evidence. They also illustrate the advantages of using infrared imaging to study the underlying structure in merging galaxies. The authors have begun a program to take near infrared images of galaxies which are believed to be mergers of disk galaxies because they have tidal tails and filaments. In many of these the merger is thought to have induced exceptionally luminous infrared emission (cf. Joseph and Wright 1985, Sanders et al. 1988). Although the optical images of the galaxies show spectacular dust lanes and filaments, the K images all have a very smooth distribution of light with an apparently single nucleus.

Wright, G. S.↗

DOE OSTI2024

Harnessing graph convolutional neural networks for identification of glassy states in metallic glasses

Graph Convolutional Neural Networks (GCNNs) have emerged as powerful tools for analyzing materials. In this study, we employ GCNNs to examine structural characteristics of CuZr metallic glasses (MGs) and identify their states. We use molecular dynamics to simulate the quenching process of CuZr, using cooling rates ranging from 10 9 to 10 15 K/s, to produce six unique glassy states. For each state, we create a dataset comprising 1,800 distinct samples. We evaluate the effectiveness of various GCNNs, including Graph Attention Neural Network (GANN), Graph Sample and AggreGatE (GraphSAGE), Graph Isomorphism Network (GIN), and Relational Graph Convolutional Neural Network (RGCN). GANN and GraphSAGE demonstrate comparable performance, achieving an overall accuracy of 81% in classifying the MG states. Furthermore, these results underscore the potential of GCNNs to detect subtle structural variances in disordered materials and point to broader application of deep learning in the analysis of MGs and other amorphous substances.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Automated Defect Identification For Triso Fuels

The developed code is to be used to identify manufacturing defects of nuclear fuel kernels using image processing methods. Past batches of TRi-structural ISOtropic particle (TRISO) fuel kernels have on occasion contained fissures that result in the fuel batch not meeting specifications. The developed code automates the inspection process of these kernels. The code analyzes micrographs of TRISO fuel kernels and outputs a count of total kernels in the sample, a count of the number of defective particles in the sample, as well as processed images for more effective manual inspection. This information output will be used to help identify if defective kernels are present in a fuel batch and quantify the countable fissure fraction.

Oncken, JosephE.↗

DOE OSTI2023

A Machine Learning–Based Approach to Time-series Wave Identification in the Solar Wind

The Wind spacecraft has yielded several decades of high-resolution magnetic field data, a large fraction of which displays small-scale structures. In particular, the solar wind is full of wavelike fluctuations that appear in both the field magnitude and its components. The nature of these fluctuations can be tied to the properties of other structures in the solar wind, such as shocks, that have implications for the time evolution of the solar wind. As such, having a large collection of wave events would facilitate further study of the effects that these fluctuations have on solar wind evolution. Given the large volume of magnetic field data available, machine learning is the most practical approach to classifying the myriad small-scale structures observed. To this end, a subset of Wind data is labeled and used as a training set for a multibranch 1D convolutional neural network aimed at classifying circularly polarized wave modes. Using this algorithm, a preliminary statistical study of 1 yr of data is performed, yielding about 300,000 wave intervals out of about 5,000,000 solar wind intervals. The wave intervals come about more often in the fast solar wind and at higher temperatures, and the number of waves per day is highly periodic. This machine learning–based approach to wave detection has the potential to be a powerful, inexpensive way to catalog waves throughout decades of spacecraft data.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1985

Bending waves and the structure of Saturn's rings

The surface mass density profiles at four locations within Saturn's rings are calculated using Voyager spacecraft images of spiral bending waves. The identification of a feature in Saturn's outer B ring as Mimas's 4:2 bending waves is confirmed, and these 4:2 waves are analyzed to determine the surface density in Saturn's B ring. A fourth set of bending waves, the Mimas 7:4, located in the inner A ring, is identified and analyzed. Mimas's 5:3 and 8:5 bending waves, observed in the middle and outer A ring respectively, are reanalyzed.

Lissauer, J. J.↗