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NASA NTRS1997

Multiresolution and Explicit Methods for Vector Field Analysis and Visualization

This is a request for a second renewal (3d year of funding) of a research project on the topic of multiresolution and explicit methods for vector field analysis and visualization. In this report, we describe the progress made on this research project during the second year and give a statement of the planned research for the third year. There are two aspects to this research project. The first is concerned with the development of techniques for computing tangent curves for use in visualizing flow fields. The second aspect of the research project is concerned with the development of multiresolution methods for curvilinear grids and their use as tools for visualization, analysis and archiving of flow data. We report on our work on the development of numerical methods for tangent curve computation first.

Nielson, Gregory M.↗

NASA NTRSDate not supplied

Proposed Reliability-Based Damage Tolerance Guidelines for Space Systems

Deterministic damage tolerance guidelines for highly reusable and efficiently designed launch systems can be challenging to meet and result in overly conservative assessments for tightly controlled manufacturing processes. Deterministic approaches may be unconservative when the structure is workmanship sensitive and there is a wide spread in fracture properties. Reliability-based damage tolerance assessments targeting a component reliability over the service life commensurate to mission risk posture is a promising alternative. Low production rates, short fleets, and lack of standards or guidance has slowed down widespread adoption of this method. Guidance for the robust application of reliability-based damage tolerance for space systems are proposed. These guidelines cover the treatment of uncertainty in damage tolerance analysis, the collection of data to develop probabilistic distributions, uncertainty propagation methods, and types of hardware.

Reliability-Based Damage Tolerance↗

NASA NTRS2011

Engineering and Scientific Applications: Using MatLab(Registered Trademark) for Data Processing and Visualization

MatLab(TradeMark)(MATrix LABoratory) is a numerical computation and simulation tool that is used by thousands Scientists and Engineers in many countries. MatLab does purely numerical calculations, which can be used as a glorified calculator or interpreter programming language; its real strength is in matrix manipulations. Computer algebra functionalities are achieved within the MatLab environment using "symbolic" toolbox. This feature is similar to computer algebra programs, provided by Maple or Mathematica to calculate with mathematical equations using symbolic operations. MatLab in its interpreter programming language form (command interface) is similar with well known programming languages such as C/C++, support data structures and cell arrays to define classes in object oriented programming. As such, MatLab is equipped with most of the essential constructs of a higher programming language. MatLab is packaged with an editor and debugging functionality useful to perform analysis of large MatLab programs and find errors. We believe there are many ways to approach real-world problems; prescribed methods to ensure foregoing solutions are incorporated in design and analysis of data processing and visualization can benefit engineers and scientist in gaining wider insight in actual implementation of their perspective experiments. This presentation will focus on data processing and visualizations aspects of engineering and scientific applications. Specifically, it will discuss methods and techniques to perform intermediate-level data processing covering engineering and scientific problems. MatLab programming techniques including reading various data files formats to produce customized publication-quality graphics, importing engineering and/or scientific data, organizing data in tabular format, exporting data to be used by other software programs such as Microsoft Excel, data presentation and visualization will be discussed.

Sen, Syamal K.↗

NASA NTRS2013

Measuring and Estimating Normalized Contrast in Infrared Flash Thermography

Infrared flash thermography (IRFT) is used to detect void-like flaws in a test object. The IRFT technique involves heating up the part surface using a flash of flash lamps. The post-flash evolution of the part surface temperature is sensed by an IR camera in terms of pixel intensity of image pixels. The IR technique involves recording of the IR video image data and analysis of the data using the normalized pixel intensity and temperature contrast analysis method for characterization of void-like flaws for depth and width. This work introduces a new definition of the normalized IR pixel intensity contrast and normalized surface temperature contrast. A procedure is provided to compute the pixel intensity contrast from the camera pixel intensity evolution data. The pixel intensity contrast and the corresponding surface temperature contrast differ but are related. This work provides a method to estimate the temperature evolution and the normalized temperature contrast from the measured pixel intensity evolution data and some additional measurements during data acquisition.

Koshti, Ajay M.↗

NASA NTRS1985

Quantitative study on dispersion relations of TIDs observed by an HF Doppler array

A quantitative study on the dispersion relation of traveling ionospheric disturbances (TIDs) was performed by using data obtained by an HF Doppler array. Observed data at three stations are digitized continuously with a sampling period of 10 sec. A schematic illustration of a running analysis method is given. Fourier components omega's and their wave vectors k's of the TIDs are calculated from these subset data from three stations by means of the cross-spectrum analysis. Diagrams of horizontal trace velocity V sub ph versus wave period T were also obtained. From these diagrams one can see clear cutoff periods of the internal mode of the atmospheric gravity waves. A morphological classification of the mode of the omega - k and V sub ph - T obtained through one year was performed. The estimation of the horizontal velocity vectors of the thermospheric wind form their dispersion relations was performed also. A key point of the method of obtaining the vectors is to estimate the tilt, in azimuthally different omega - k diagrams, of a resonant branch ascribed to the Brunt oscillations.

Tsutsui, M.↗

NASA NTRSDate not supplied

INCREASING THE TRANSPARENCY AND REPRODUCIBILITY OF SPACE RADIATION SCIENCE: THE RADIATION BIOLOGY ONTOLOGY

Among the primary objectives of the Open/Open-Source Science paradigm are making scientific investigation data transparent and results reproducible [1], objectives shared by the FAIR principles [2]. To accomplish this, the conceptual framework that includes all the investigation objects needs to be accurately captured and communicated to all data consumers. A large part of this requires using metadata standards to annotate data collected. These standards should be readily accessible, informed by scientific community consensus and sufficiently specific to encompass all of the important aspects of the investigation. Starting in 2020 we have been co-leading an open consortium to develop a new metadata standard, the Radiation Biology Ontology (RBO), through the Open Biological and Biomedical Ontologies (OBO) Foundry [3]. We began by transforming many of the terms from the National Council on Radiation Protection and Measurement into concepts that can be formally related to existing OBO Foundry classes or attributes. We then identified and imported into the RBO existing OBO Foundry classes that have obvious relevance for radiation biomedicine (for example, concepts from the Environment Ontology that describe radiative processes, and concepts from the Gene Ontology dealing with molecular and cellular responses to radiation). Finally, we scrutinized datasets from investigations of radiation effects held in NASA GeneLab and LSDA repositories and added additional classes, instances, and attributes into the RBO that should be used to annotate these data. We developed the RBO using the open-source tools of GitHub and publish the RBO periodically through the NIH/NCBI BioPortal website, so systems worldwide can leverage the knowledge it contains [4]. This initial phase of concept modeling has yielded an RBO that at present has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies. While this first phase has focused on concepts for annotating samples, environments, exposures, and measurements, the next phase will center on supporting annotation of results and findings, such as concept models of molecular, cellular and tissue effects. The value of the RBO will be determined in part by our ability to engage the community in its development, and we have established a Radiobiology Informatics Consortium with unrestricted membership as the owner of the RBO in order to encourage investigators, system owners and other to join in this effort. Anyone can report issues or request new concept modeling or other features directly on GitHub. By using the BioPortal application programming interface, systems can pose dynamic queries to the latest version of the RBO for information on individual classes or entire hierarchies; this design eliminates the need for systems to be updated in order to use newer versions of the RBO. We hope to contribute to the advancement of open radiobiological science through the continued, open development of the RBO, that will provide more precise, machine-interpretable descriptions of investigations, as well as support data meta-analysis through machine learning or other artificial intelligence methods.

knowledge↗

DOE OSTI2025

Low Activity Tritium Detection in CCDs Using Deep Learning Techniques

Here, this study explores the use of charge-coupled devices (CCDs) for detecting low-energy beta particles from tritium decay - a critical signal for nuclear safety, nuclear nonproliferation, and environmental monitoring. We employ a dual approach utilizing both measured CCD data and detailed Geant4 simulations. Our analysis compares classical techniques with advanced deep learning methods, including convolutional neural networks (CNNs), autoencoders trained exclusively on tritium data, and preliminary studies on boosted decision trees (BDTs). The CNN, trained on mixed signal/background datasets, demonstrates superior classification performance, while the autoencoder shows the potential of unsupervised, background-agnostic strategies when background characteristics are poorly defined. These results highlight the excellent sensitivity achievable thanks to the background rejection made possible by information-rich CCD data, paving the way for improved portable tritium monitoring.

Autoencoder↗

NASA NTRS1989

Spectral and correlation analysis with applications to middle-atmosphere radars

The correlation and spectral analysis methods for uniformly sampled stationary random signals, estimation of their spectral moments, and problems arising due to nonstationary are reviewed. Some of these methods are already in routine use in atmospheric radar experiments. Other methods based on the maximum entropy principle and time series models have been used in analyzing data, but are just beginning to receive attention in the analysis of radar signals. These methods are also briefly discussed.

Rastogi, Prabhat K.↗

NASA NTRS2016

Measuring and Modeling Shared Visual Attention

Multi-person teams are sometimes responsible for critical tasks, such as flying an airliner. Here we present a method using gaze tracking data to assess shared visual attention, a term we use to describe the situation where team members are attending to a common set of elements in the environment. Gaze data are quantized with respect to a set of N areas of interest (AOIs); these are then used to construct a time series of N dimensional vectors, with each vector component representing one of the AOIs, all set to 0 except for the component corresponding to the currently fixated AOI, which is set to 1. The resulting sequence of vectors can be averaged in time, with the result that each vector component represents the proportion of time that the corresponding AOI was fixated within the given time interval. We present two methods for comparing sequences of this sort, one based on computing the time-varying correlation of the averaged vectors, and another based on a chi-square test testing the hypothesis that the observed gaze proportions are drawn from identical probability distributions. We have evaluated the method using synthetic data sets, in which the behavior was modeled as a series of "activities," each of which was modeled as a first-order Markov process. By tabulating distributions for pairs of identical and disparate activities, we are able to perform a receiver operating characteristic (ROC) analysis, allowing us to choose appropriate criteria and estimate error rates. We have applied the methods to data from airline crews, collected in a high-fidelity flight simulator (Haslbeck, Gontar & Schubert, 2014). We conclude by considering the problem of automatic (blind) discovery of activities, using methods developed for text analysis.

attention↗

DOE OSTI2019

X-ray analysis methods for sources from self-modulated laser wakefield acceleration driven by picosecond lasers

A versatile set of methods for analyzing x-ray energy spectra and photon flux has been developed for laser plasma accelerator experiments driven by picosecond lasers. Forward fit provides extrapolated broad energy spectrum measurements, while Ross pair and differential average transmission analysis provide directly measured data points using a particular diagnostic. Combining these methods allows the measurement of x-ray energy spectra with improved confidence. We apply here the methods to three diagnostics (filter wheel, stacked image plate spectrometer, and step wedge), each sensitive to a different region of x-ray energies (<40 keV, 35–100 keV, and 60–1000 keV, respectively), to characterize the analysis methods using laser-driven bremsstrahlung x-rays. We then apply the methods to measure three x-ray mechanisms, betatron, inverse Compton scattering, and bremsstrahlung, driven by a laser plasma accelerator. The analysis results in the measurement of x-ray energy spectra ranging from 10 keV to 1 MeV with peak flux greater than 10 10 photons/keV/Sr. The combined analysis methods provide a robust tool to accurately measure broadband x-ray sources (keV to MeV) driven by laser plasma acceleration with picosecond, kilojoule-class lasers.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques

By conservation of mass, the mass of wildland fuel that is pyrolyzed and combusted must equal the mass of smoke emissions, residual char and ash. For a given set of conditions, these amounts are fixed. This places a constraint on smoke emissions data which violates statistical assumptions for many of the methods currently used to analyze these data such as linear regression, analysis of variance, and t-tests. These data are inherently multivariate and non-negative parts of a whole. This paper introduces the field of compositional data analysis to the emissions community and provides examples of appropriate statistical treatment of emissions data. It is shown that modified combustion efficiency should not be used as a predictor variable for other smoke emissions because it is not an independent variable. An alternative method based on compositional linear trends to estimate trace gas composition using CO and CO2 is presented. The data used in this paper resulted from projects the DOD/DOE/EPA Strategic 586 Environmental Research and Development Program projects RC-1648 and 1649. The senior 587 author appreciates the guidance and R scripts provided by Prof. Girty at San Diego State 588 University to estimate linear trends by perturbation. J. P.-A. was supported by the Spanish 589 Ministry of Science, Innovation and Universities under the project CODAMET (RTI2018-590 095518-B-C21, 2019-2021). The data used in this study have been previously published and are 591 available in the original publications. DRW conceived the initial manuscript (70 percent) and 592 performed the bulk of the data analysis. JPA provided statistical guidance and compositional data 593 expertise and contributed 20 percent of the manuscript. TJJ and HJ were extensively involved in 594 the study that provided the data. TJJ provide smoke emissions expertise and HJ provided 595 combustion expertise. The authors declare that they have no conflict of interest. The use of trade 596 or firm names in this publication is for reader information and does not imply endorsement by 597 the U.S. Department of Agriculture of any product or service.

simplex, compositional data analysis, balance, log↗

NASA NTRS1973

A sinusoidal-vibration analysis program for experimental data

A program is described for obtaining resonant frequencies, modal amplitudes, and damping of a structure from a sinusoidal force-controlled vibration test. Presented are the theoretical basis for the analysis (the Kennedy-Pancu method), recommendations for a test procedure based on experience with several earlier test programs, and an outline of the data analysis technique. Although the program was developed for structural vibration problems, variations for processing any sinusoidal data are available.

Schoenster, J. A.↗

NASA NTRS1979

Analysis of regression methods for solar activity forecasting

The paper deals with the potential use of the most recent solar data to project trends in the next few years. Assuming that a mode of solar influence on weather can be identified, advantageous use of that knowledge presumably depends on estimating future solar activity. A frequently used technique for solar cycle predictions is a linear regression procedure along the lines formulated by McNish and Lincoln (1949). The paper presents a sensitivity analysis of the behavior of such regression methods relative to the following aspects: cycle minimum, time into cycle, composition of historical data base, and unnormalized vs. normalized solar cycle data. Comparative solar cycle forecasts for several past cycles are presented as to these aspects of the input data. Implications for the current cycle, No. 21, are also given.

Lundquist, C. A.↗

NASA NTRS1974

A Monte Carlo investigation of experimental data requirements for fitting polynomial functions

This report examines the extent to which sample size affects the accuracy of a low order polynomial approximation of an experimentally observed quantity and establishes a trend toward improvement in the accuracy of the approximation as a function of sample size. The task is made possible through a simulated analysis carried out by the Monte Carlo method, in which data are generated by using several transcendental or algebraic functions as models. Contaminated data of varying amounts are fitted to linear quadratic or cubic polynomials, and the behavior of the mean-squared error of the residual variance is determined as a function of sample size. Results indicate that the effect of the size of the sample is significant only for relatively small sample sizes and diminishes drastically for moderate and large amounts of experimental data.

Canavos, G. C.↗

DOE OSTI2023

High-Fidelity Numerical Investigation on Elucidating Sodium Heat Transfer Characteristics for 37-Pin Wire-Wrapped Fuel Bundle in the PLANDTL Facility

This study involved a Reynolds-averaged Navier-Stokes- (RANS-) based computational fluid dynamics (CFD) analysis of the 37-pin wire-wrapped fuel bundle of the PNC Plant dynamics test loop (PLANDTL) facility. Previously, mainly the hydrodynamic phenomena of the wire-wrapped fuel bundle were analyzed, but the present study additionally included heat transfer analysis through conjugate heat transfer. The main purpose of the study was to benchmark the experimental data of the PLANDTL 37-pin wire-wrapped fuel bundle to investigate the heat transfer phenomena. In addition, the aim was to verify the accuracy of the RANS-based CFD analysis method using the STAR-CCM+ simulation software in comparison with the experimental data. The grid used for verification was an innovative grid system consisting of hexahedra using Fortran-based code. The development of the RANS-based CFD methodology included grid sensitivity analysis, turbulence model sensitivity analysis, and turbulent Prandtl number sensitivity analysis. Information on the temperature, mass flow rate, and area of the CFD results for each subchannel was provided for the top of the heated section and is expected to serve as a reference for future studies aiming to perform the validation and verification of a PLANDTL facility. In addition, the dependence of the peak temperature on the azimuth angle of each pin was analyzed.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1997

Experimental Investigation of Jet Impingement Heat Transfer Using Thermochromic Liquid Crystals

Jet impingement cooling of a hypersonic airfoil leading edge is experimentally investigated using thermochromic liquid crystals (TLCS) to measure surface temperature. The experiment uses computer data acquisition with digital imaging of the TLCs to determine heat transfer coefficients during a transient experiment. The data reduction relies on analysis of a coupled transient conduction - convection heat transfer problem that characterizes the experiment. The recovery temperature of the jet is accounted for by running two experiments with different heating rates, thereby generating a second equation that is used to solve for the recovery temperature. The resulting solution requires a complicated numerical iteration that is handled by a computer. Because the computational data reduction method is complex, special attention is paid to error assessment. The error analysis considers random and systematic errors generated by the instrumentation along with errors generated by the approximate nature of the numerical methods. Results of the error analysis show that the experimentally determined heat transfer coefficients are accurate to within 15%. The error analysis also shows that the recovery temperature data may be in error by more than 50%. The results show that the recovery temperature data is only reliable when the recovery temperature of the jet is greater than 5 C, i.e. the jet velocity is in excess of 100 m/s. Parameters that were investigated include nozzle width, distance from the nozzle exit to the airfoil surface, and jet velocity. Heat transfer data is presented in graphical and tabular forms. An engineering analysis of hypersonic airfoil leading edge cooling is performed using the results from these experiments. Several suggestions for the improvement of the experimental technique are discussed.

Dempsey, Brian Paul↗

NASA NTRS1990

Analytical concepts for health management systems of liquid rocket engines

Substantial improvement in health management systems performance can be realized by implementing advanced analytical methods of processing existing liquid rocket engine sensor data. In this paper, such techniques ranging from time series analysis to multisensor pattern recognition to expert systems to fault isolation models are examined and contrasted. The performance of several of these methods is evaluated using data from test firings of the Space Shuttle main engines.

Williams, Richard↗

NASA NTRS2007

Analysis of Crossflow Transition Flight Experiment aboard the Pegasus Launch Vehicle

The Pegasus wing-glove flight experiment was designed to provide crossflow transition data at high Mach numbers, specifically to help validate stability based predictions for transition onset in a flight environment. This paper provides an analysis of the flight experiment, with emphasis on computational results for crossflow disturbances and the correlation of disturbance growth factors with in-flight transition locations via the e(sup N) method. Implications of the flight data for attachment line stability are also examined. Analysis of the thermocouple data reveals that transition (from turbulent to laminar flow) was first detected during the ascending flight of the rocket when the free stream Mach number exceeded about 4. Therefore, computations have been performed for flight Mach numbers of 4.13, 4.35, 4.56 and 4.99. Due to continually decreasing unit Reynolds number at higher altitudes, the entire wing-glove boundary layer became laminar at the highest flight Mach number computed above. In contrast, the boundary layer flow over the inboard tile region remained transitional up to and somewhat beyond the time of laminarization over the instrumented glove region. Linear stability predictions confirmed that the tile boundary layer is indeed more unstable to crossflow disturbances than the much colder stainless steel glove boundary layer. The transition locations based on thermocouple data from both the glove and the tile regions are found to correlate with stationary-crossflow N-factors within the range of 7 to 12.4 and with traveling mode N-factors between 7.6 and 14.1. Data from the thermocouples and hot film sensors indicates that transition from turbulent to laminar flow (i.e., laminarization) at a fixed point over the glove is generally completed within a flight time interval of 3 seconds. However, the times at which transition begins and ends as inferred from the hot film sensors are found to differ by about 2 seconds from the corresponding estimates based on the thermocouple data.

Malik, Mujeeb R.↗