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At least 451 records · Page 25

Performance Risk Model Validation with Operationally Relevant Tasks

Human Research Program aims to develop methods to support astronauts’ health and productivity during spaceflight. The Crew Health and Performance Probabilistic Risk Assessment (CHP-PRA) team uses powerful computational methods to predict mission risk in both domains: medical and performance. Here, we show how CHP-PRA uses the Performance Risk Model (PRisM) to quantify the performance risk and show an application of the model on operationally relevant tasks. There are various metrics adopted across performance researchers that PRisM can accommodate. For data analysis, interpretation, and integration, we use a method of unifying data from multiple sources by converting each to a single metric. We consult subject matter experts prior to integrating the converted data into PRisM. The method we use is inspired by the Cooper-Harper rating scale [1]. Using this unified metric, we can easily combine data from various tests and lab groups. We explain our conversion method in detail and show how it pertains to the process of testing and validation of PRisM on operational tasks. We conducted an initial validation in collaboration with the Behavioral Health and Performance (BHP) lab. We test PRisM using data on their operationally relevant task ROBoT-r, a track-and-capture task for grappling incoming resupply vehicles [2]. Several other labs at NASA Johnson Space Center worked together to design 7 Functional Task Tests (FTTs) in pursuit of simulating the tasks required after landing on a planetary surface and after return to Earth [3]. Here we use the results from both ROBoT-r and the 7 FTTs and compare their experiment data to PRisM’s computational output to demonstrate how PRisM can support operations by predicting crew performance on future missions.

performance modeling↗

Improved method of analyzing hot-wire measurements in supersonic turbulence

The present analysis method for hot-wire data in supersonic turbulence takes sound field effects into account and yields greater accuracy in its treatment of flow variable fluctuations than existing methods despite requiring only a moderately accurate estimate of static pressure fluctuations. The method demonstrates the way in which neglecting pressure fluctuations will affect hot-wire data analysis, as well as indicating the probable direction the errors will take.

Logan, Pamela↗

The Application of Time-Frequency Methods to HUMS

This paper reports the study of four time-frequency transforms applied to vibration signals and presents a new metric for comparing them for fault detection. The four methods to be described and compared are the Short Time Frequency Transform (STFT), the Choi-Williams Distribution (WV-CW), the Continuous Wavelet Transform (CWT) and the Discrete Wavelet Transform (DWT). Vibration data of bevel gear tooth fatigue cracks, under a variety of operating load levels, are analyzed using these methods. The new metric for automatic fault detection is developed and can be produced from any systematic numerical representation of the vibration signals. This new metric reveals indications of gear damage with all of the methods on this data set. Analysis with the CWT detects mechanical problems with the test rig not found with the other transforms. The WV-CW and CWT use considerably more resources than the STFT and the DWT. More testing of the new metric is needed to determine its value for automatic fault detection and to develop methods of setting the threshold for the metric.

Pryor, Anna H.↗

Bayesian Inference for NASA Probabilistic Risk and Reliability Analysis

This document, Bayesian Inference for NASA Probabilistic Risk and Reliability Analysis, is intended to provide guidelines for the collection and evaluation of risk and reliability-related data. It is aimed at scientists and engineers familiar with risk and reliability methods and provides a hands-on approach to the investigation and application of a variety of risk and reliability data assessment methods, tools, and techniques. This document provides both: A broad perspective on data analysis collection and evaluation issues. A narrow focus on the methods to implement a comprehensive information repository. The topics addressed herein cover the fundamentals of how data and information are to be used in risk and reliability analysis models and their potential role in decision making. Understanding these topics is essential to attaining a risk informed decision making environment that is being sought by NASA requirements and procedures such as 8000.4 (Agency Risk Management Procedural Requirements), NPR 8705.05 (Probabilistic Risk Assessment Procedures for NASA Programs and Projects), and the System Safety requirements of NPR 8715.3 (NASA General Safety Program Requirements).

Dezfuli, Homayoon↗

Overview of the Space Launch System Transonic Buffet Environment Test Program

Fluctuating aerodynamic loads are a significant concern for the structural design of a launch vehicle, particularly while traversing the transonic flight environment. At these trajectory conditions, unsteady aerodynamic pressures can excite the vehicle dynamic modes of vibration and result in high structural bending moments and vibratory environments. To ensure that vehicle structural components and subsystems possess adequate strength, stress, and fatigue margins in the presence of buffet and other environments, buffet forcing functions are required to conduct the coupled load analysis of the launch vehicle. The accepted method to obtain these buffet forcing functions is to perform wind-tunnel testing of a rigid model that is heavily instrumented with unsteady pressure transducers designed to measure the buffet environment within the desired frequency range. Two wind-tunnel tests of a 3 percent scale rigid buffet model have been conducted at the Langley Research Center Transonic Dynamics Tunnel (TDT) as part of the Space Launch System (SLS) buffet test program. The SLS buffet models have been instrumented with as many as 472 unsteady pressure transducers to resolve the buffet forcing functions of this multi-body configuration through integration of the individual pressure time histories. This paper will discuss test program development, instrumentation, data acquisition, test implementation, data analysis techniques, and several methods explored to mitigate high buffet environment encountered during the test program. Preliminary buffet environments will be presented and compared using normalized sectional buffet forcing function root-meansquared levels along the vehicle centerline.

Piatak, David J.↗

Archetype-based Redshift Estimation for the Dark Energy Spectroscopic Instrument Survey

We present a computationally efficient galaxy archetype-based redshift estimation and spectral classification method for the Dark Energy Survey Instrument (DESI) survey. The DESI survey currently relies on a redshift fitter and spectral classifier using a linear combination of principal component analysis–derived templates, which is very efficient in processing large volumes of DESI spectra within a short time frame. However, this method occasionally yields unphysical model fits for galaxies and fails to adequately absorb calibration errors that may still be occasionally visible in the reduced spectra. Our proposed approach improves upon this existing method by refitting the spectra with carefully generated physical galaxy archetypes combined with additional terms designed to absorb data reduction defects and provide more physical models to the DESI spectra. We test our method on an extensive data set derived from the survey validation (SV) and Year 1 (Y1) data of DESI. Our findings indicate that the new method delivers marginally better redshift success for SV tiles while reducing catastrophic redshift failure by 10%–30%. At the same time, results from millions of targets from the main survey show that our model has relatively higher redshift success and purity rates (0.5%–0.8% higher) for galaxy targets while having similar success for QSOs. These improvements also demonstrate that the main DESI redshift pipeline is generally robust. Additionally, it reduces the false-positive redshift estimation by 5%–40% for sky fibers. We also discuss the generic nature of our method and how it can be extended to other large spectroscopic surveys, along with possible future improvements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Cluster spin glass correlations and dynamics in Zn 0.5⁢ Mn 0.5⁢ Te

Here, we present a combined magnetometry, muon spin-relaxation (𝜇⁢SR), and neutron-scattering study of the insulating spin glass Zn 0.5 ⁢Mn 0.5 ⁢Te, for which magnetic Mn 2+ and nonmagnetic Zn 2+ ions are randomly distributed on a face-centered cubic lattice. The magnetometry and 𝜇⁢SR results confirm a spin freezing transition around 𝑇 𝑓 ≈ 23 K, with the spin-fluctuation rate decreasing gradually and somewhat inhomogeneously through the sample volume as the temperature decreases toward 𝑇 𝑓 . Characteristic spin-correlation times well above 𝑇 𝑓 are on the order of 10 −10 s, much slower than typically observed in canonical spin glasses but in line with expectations for a cluster spin glass. Using magnetic pair distribution function (mPDF) analysis and reverse Monte Carlo (RMC) modeling of the magnetic diffuse neutron-scattering data, we show that the spin-glass ground state consists of clusters of spins exhibiting short-range-ordered type-III antiferromagnetic correlations with a locally ordered moment of 3.1⁢(1)⁢𝜇 B between nearest-neighbor spins. The type-III correlations decay exponentially as a function of spin separation distance with a correlation length of approximately 5 Å. The diffuse magnetic scattering and corresponding mPDF show no significant changes across 𝑇 𝑓 , indicating that the dynamically fluctuating short-range spin correlations in the paramagnetic state retain the same basic type-III configuration that characterizes the spin-glass state; the only change apparent from the neutron-scattering data is a gradual reduction of the correlation length and locally ordered moment with increasing temperature. Taken together, these results paint a unique and detailed picture of the local magnetic structure and dynamics in Zn 0.5 ⁢Mn 0.5⁢ Te and provide strong evidence that this material is best described as a cluster spin glass. In addition, this work showcases a statistical method for extracting diffuse scattering signals from neutron powder diffraction data, which we developed to facilitate the mPDF and RMC analysis of the neutron data. This method has the potential to be broadly useful for neutron powder diffraction experiments on a variety of materials with short-range atomic or magnetic order.

magnetism↗

Interpretation of gamma-ray burst source count statistics

Ever since the discovery of gamma-ray bursts, the so-called log N-log S relation has been used for determination of their distances and distribution. This task has not been straightforward because of varying thresholds for the detection of bursts. Most of the current analyses of these data are couched in terms of ambiguous distributions, such as the distribution of Cp/Clim, the ratio of peak to threshold photon count rates, or the distribution of V/Vmax = (Cp/Clim) exp -3/2. It is shown that these distributions are not always a true reflection of the log N-log S relation. Some kind of deconvolution is required for obtaining the true log N-log S. Therefore, care is required in the interpretation of results of such analyses. A new method of analysis of these data is described, whereby the bivariate distribution of Cp and Clim is obtained directly from the data.

Petrosian, Vahe↗

Lessons Learned in the Application of Machine Learning Techniques to Air Traffic Management

There is an increasing interest in applying methods based on Machine Learning Techniques (MLT) to problems in Air Traffic Management (ATM). The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large databases. This paper reviews the current-state-of-the art in applying MLT to aviation operations, its promises and challenges. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for analysis using data-driven methods. The promises and challenges in applying MLT to ATM is traced through three examples based on the authors’ experience, each separated by a decade, to show the influence of data and feature selection in the successful application of MLT to ATM. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Machine Learning Techniques↗

Environmental dynamics at orbital altitudes

The influence of real satellite aerodynamics on the determination of upper atmospheric density was investigated. A method of analysis of satellite drag data is presented which includes the effect of satellite lift and the variation in aerodynamic properties around the orbit. The studies indicate that satellite lift may be responsible for the observed orbit precession rather than a super rotation of the upper atmosphere. The influence of simplifying assumptions concerning the aerodynamics of objects in falling sphere analysis were evaluated and an improved method of analysis was developed. Wind tunnel data was used to develop more accurate drag coefficient relationships for studying altitudes between 80 and 120 Km. The improved drag coefficient relationships revealed a considerable error in previous falling sphere drag interpretation. These data were reanalyzed using the more accurate relationships. Theoretical investigations of the drag coefficient in the very low speed ratio region were also conducted.

Karr, G. R.↗

On-Line Loss of Control Detection Using Wavelets

Wavelet transforms are used for on-line detection of aircraft loss of control. Wavelet transforms are compared with Fourier transform methods and shown to more rapidly detect changes in the vehicle dynamics. This faster response is due to a time window that decreases in length as the frequency increases. New wavelets are defined that further decrease the detection time by skewing the shape of the envelope. The wavelets are used for power spectrum and transfer function estimation. Smoothing is used to tradeoff the variance of the estimate with detection time. Wavelets are also used as front-end to the eigensystem reconstruction algorithm. Stability metrics are estimated from the frequency response and models, and it is these metrics that are used for loss of control detection. A Matlab toolbox was developed for post-processing simulation and flight data using the wavelet analysis methods. A subset of these methods was implemented in real time and named the Loss of Control Analysis Tool Set or LOCATS. A manual control experiment was conducted using a hardware-in-the-loop simulator for a large transport aircraft, in which the real time performance of LOCATS was demonstrated. The next step is to use these wavelet analysis tools for flight test support.

Brenner, Martin J.↗

A Data Matrix Method for Improving the Quantification of Element Percentages of SEM/EDX Analysis

A simple 2D M N matrix involving sample preparation enables the microanalyst to peer below the noise floor of element percentages reported by the SEM/EDX (scanning electron microscopy/ energy dispersive x-ray) analysis, thus yielding more meaningful data. Using the example of a 2 3 sample set, there are M = 2 concentration levels of the original mix under test: 10 percent ilmenite (90 percent silica) and 20 percent ilmenite (80 percent silica). For each of these M samples, N = 3 separate SEM/EDX samples were drawn. In this test, ilmenite is the element of interest. By plotting the linear trend of the M sample s known concentration versus the average of the N samples, a much higher resolution of elemental analysis can be performed. The resulting trend also shows how the noise is affecting the data, and at what point (of smaller concentrations) is it impractical to try to extract any further useful data.

Lane, John↗

NASA Goddard Space Flight Center

The contribution of the Goddard Space Flight Center to the National Geodetic Satellite Program is reported. All of the major types of tracking systems, including those employing optical, electronic, range-and-range-rate, and laser technologies, which were developed and operated by Goddard, are described. The MINITRACK data were used to derive geodetic results. The methods used for the analysis of these data are presented.

Berbert, J. H.↗

Buckling analysis and test correlation of high temperature structural panels

This paper focuses on the design, analysis, and test of a high temperature structural panel, constructed of Ti-6-4, subjected to a variety of thermal and mechanical load conditions. A follow-on panel, constructed of TMC, is also discussed in less detail. The design constraints and test set-up are discussed, as well as the test methods that were used: the grid shadow moire method and a single gage force stiffness method. The agreement between the test data and analysis for this test program provides confidence in the methods that are currently being used to design structures for hypersonic vehicles. The agreement also suggests that postbuckled strength may potentially be used to reduce the vehicle weight.

Teare, Wendy P.↗

A method for the measurement and analysis of ride vibrations of transportation systems

The measurement and recording of ride vibrations which affect passenger comfort in transportation systems and the subsequent data-reduction methods necessary for interpreting the data present exceptional instrumentation requirements and necessitate the use of computers for specialized analysis techniques. A method is presented for both measuring and analyzing ride vibrations of the type encountered in ground and air transportation systems. A portable system for measuring and recording low-frequency, low-amplitude accelerations and specialized data-reduction procedures are described. Sample vibration measurements in the form of statistical parameters representative of typical transportation systems are also presented to demonstrate the utility of the techniques.

Catherines, J. J.↗

Determination of a Two-Phase Structure of Nanocrystals: GaN and SiC

The properties of nano-crystalline materials are critically dependent on the structure of the constituent grains. Experimental conditions necessary to perform structural analysis of nanocrystalline materials as a two-phase core-surface shell system are discussed. It is shown, that a standard X-ray diffraction measurements and analysis are insufficient and may lead to incorrect conclusions as to the real structure of the materials. A new method of evaluation of powder diffraction data based on the analysis of the shift of the Bragg reflections from their perfect-lattice positions was developed. "Apparent lattice parameters" quantity, alp, was introduced and calculated from the actual positions of each individual Bragg reflection. The alp values plotted versus diffraction vector (Q) show characteristic features that are used for evaluation of the experimental results. The study was based on modeling of nano-grains and simulations of theoretical intensity profiles using the Debye functions. The method was applied to the analysis of synchrotron X-ray diffraction data of GaN and SiC nanocrystals. A presence of strained surface shell and a considerable internal pressure (GaN) in the nanoparticles was concluded.

Palosz, W.↗

Time Distribution Analysis for Task Primitives to Support Dynamic Human Reliability Analysis

To support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method and Human Reliability data EXtraction (HuREX). GOMS-HRA was developed to provide cognition-based time and human error probability (HEP) information for dynamic HRA calculations within the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework, while HuREX is a comprehensive HRA data collection method developed by the Korea Atomic Energy Research Institute (KAERI). In this paper, we examine time distributions by using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which proposes an HRA data collection framework to complement full-scope simulator research and gather input data for dynamic HRA by using simplified simulators such as the Rancor Microworld simulator. This paper investigates whether the time required for GOMS-HRA and HuREX task primitives fits 13 statistical distributions. Additionally, we compare and discuss the time distributions obtained from both student operators and professional operators. The result was that this study identified several time distributions for five GOMS-HRA and four HuREX task primitives. In the future, the results of this study are expected to provide objective reference data on the elapsed time for task primitives and aid in realistically simulating scenarios within dynamic HRA.

Dynamic Human Reliability Analysis↗