Oxidation of PCEA nuclear graphite by low water concentrations in helium
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Contescu, Cristian I.↗
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Results for “Methods: data analysis”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Results from the Atacama B-mode Search (ABS) experiment
We report the Atacama B-mode Search is an experiment designed to measure the cosmic microwave background polarization at large angular scales (0ℓ>4). It observes at 145 GHz from a site at 5,190 m elevation in northern Chile. The noise equivalent polarization temperature, or NEQ, is 41 μK√s. One of the unique features of ABS is its use of a rapidly rotating ambient-temperature half-wave plate (HWP) {as the first optical element}. {The HWP spins} at 2.55 Hz to modulate the incident polarized signal at frequencies above where instrument white noise dominates over atmospheric fluctuations and other sources of low-frequency noise. We report here on the analysis of data from a 2,400 deg 2 region of sky. We perform a blind analysis to reduce potential bias. After unblinding, we find agreement with the Planck TE and EE measurements on the same region of sky, {with a derived calibration factor of 00.89 ± 0.1}. We marginally detect polarized dust emission {(at 3.2 σ for EE and 2.2 σ for BB)} and give an upper limit on the tensor-to-scalar ratio of r<2.3 (95% confidence level) with the equivalent of 100 on-sky days of observation. Finally, we also present a new measurement of the polarization of Tau A and introduce new methods for calibration and data analysis associated with HWP-based observations.
79 ASTRONOMY AND ASTROPHYSICS↗
Online data analysis and reduction: An important co-design motif for extreme-scale computers
A growing disparity between supercomputer computation speeds and I/O rates means that it is rapidly becoming infeasible to analyze supercomputer application output only after that output has been written to a file system. Instead, data-generating applications must run concurrently with data reduction and/or analysis operations, with which they exchange information via high-speed methods such as interprocess communications. The resulting parallel computing motif, online data analysis and reduction (ODAR), has important implications for both application and HPC systems design. Here we introduce the ODAR motif and its co-design concerns, describe a co-design process for identifying and addressing those concerns, present tools that assist in the co-design process, and present case studies to illustrate the use of the process and tools in practical settings.
Data Analysis↗
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.↗
Disaster risk and artificial intelligence: A framework to characterize conceptual synergies and future opportunities
Artificial intelligence (AI) methods have revolutionized and redefined the landscape of data analysis in business, healthcare, and technology. These methods have innovated the applied mathematics, computer science, and engineering fields and are showing considerable potential for risk science, especially in the disaster risk domain. The disaster risk field has yet to define itself as a necessary application domain for AI implementation by defining how to responsibly balance AI and disaster risk. (1) How is AI being used for disaster risk applications; and how are these applications addressing the principles and assumptions of risk science, (2) What are the benefits of AI being used for risk applications; and what are the benefits of applying risk principles and assumptions for AI-based applications, (3) What are the synergies between AI and risk science applications, and (4) What are the characteristics of effective use of fundamental risk principles and assumptions for AI-based applications? This study develops and disseminates an online survey questionnaire that leverages expertise from risk and AI professionals to identify the most important characteristics related to AI and risk, then presents a framework for gauging how AI and disaster risk can be balanced. This study is the first to develop a classification system for applying risk principles for AI-based applications. This classification contributes to understanding of AI and risk by exploring how AI can be used to manage risk, how AI methods introduce new or additional risk, and whether fundamental risk principles and assumptions are sufficient for AI-based applications.
97 MATHEMATICS AND COMPUTING↗
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.↗
Improved accuracy of quantitative parameter estimates in dynamic contrast-enhanced CT study with low temporal resolution
Purpose: A previously proposed method to reduce radiation dose to patient in dynamic contrast-enhanced (DCE) CT is enhanced by principal component analysis (PCA) filtering which improves the signal-to-noise ratio (SNR) of time-concentration curves in the DCE-CT study. The efficacy of the combined method to maintain the accuracy of kinetic parameter estimates at low temporal resolution is investigated with pixel-by-pixel kinetic analysis of DCE-CT data. Methods: The method is based on DCE-CT scanning performed with low temporal resolution to reduce the radiation dose to the patient. The arterial input function (AIF) with high temporal resolution can be generated with a coarsely sampled AIF through a previously published method of AIF estimation. To increase the SNR of time-concentration curves (tissue curves), first, a region-of-interest is segmented into squares composed of 3 × 3 pixels in size. Subsequently, the PCA filtering combined with a fraction of residual information criterion is applied to all the segmented squares for further improvement of their SNRs. The proposed method was applied to each DCE-CT data set of a cohort of 14 patients at varying levels of down-sampling. The kinetic analyses using the modified Tofts’ model and singular value decomposition method, then, were carried out for each of the down-sampling schemes between the intervals from 2 to 15 s. The results were compared with analyses done with the measured data in high temporal resolution (i.e., original scanning frequency) as the reference. Results: The patients’ AIFs were estimated to high accuracy based on the 11 orthonormal bases of arterial impulse responses established in the previous paper. In addition, noise in the images was effectively reduced by using five principal components of the tissue curves for filtering. Kinetic analyses using the proposed method showed superior results compared to those with down-sampling alone; they were able to maintain the accuracy in the quantitative histogram parameters of volume transfer constant [standard deviation (SD), 98th percentile, and range], rate constant (SD), blood volume fraction (mean, SD, 98th percentile, and range), and blood flow (mean, SD, median, 98th percentile, and range) for sampling intervals between 10 and 15 s. Conclusions: The proposed method of PCA filtering combined with the AIF estimation technique allows low frequency scanning for DCE-CT study to reduce patient radiation dose. The results indicate that the method is useful in pixel-by-pixel kinetic analysis of DCE-CT data for patients with cervical cancer.
61 RADIATION PROTECTION AND DOSIMETRY↗
Simulations of a PSD Plastic Neutron Collar for Assaying Fresh Fuel
The potential performance of a notional active coincidence collar for assaying uranium fuel based on segmented detectors constructed from the new PSD plastic fast organic scintillator with pulse shape discrimination capability was investigated in simulation. Like the International Atomic Energy Agency's present Uranium Neutron Collar for LEU (UNCL), the PSD plastic collar would also function by stimulating fission in the 235 U content of the fuel with a moderated 241 Am/Li neutron source and detecting instances of induced fission via neutron coincidence counting. In contrast to the moderated detectors of the UNCL, the fast time scale of detection in the scintillator eliminates statistical errors due to accidental coincidences that limit the performance of the UNCL. However, the potential to detect a single neutron multiple times historically has been one of the properties of organic scintillator detectors that has prevented their adoption for international safeguards applications. Consequently, as part of the analysis of simulated data, a method was developed by which true neutron-neutron coincidences can be distinguished from inter-detector scatter that takes advantage of the position and timing resolution of segmented detectors. Then, the performance of the notional simulated coincidence collar was evaluated for assaying a variety of fresh fuels, including some containing burnable poisons and partial defects. In these simulations, particular attention was paid to the analysis of fast mode measurements. In fast mode, a Cd liner is placed inside the collar to shield the fuel from the interrogating source and detector moderators, thereby eliminating the thermal neutron flux that is most sensitive to the presence of burnable poisons that are ubiquitous in modern nuclear fuels. The simulations indicate that the predicted precision of fast mode measurements is similar to what can be achieved by the present UNCL in thermal mode. For example, the statistical accuracy of a ten-minute measurement of fission coincidences collected in fast mode will be approximately 1% for most fuels of interest, yielding a ~1.4% error after subtraction of a five minute measurement of the spontaneous fissions from 238 U in the fuel, a ~2% error in analyzed linear density after accounting for the slope of the calibration curve, and a ~2.9% total error after addition of an assumed systematic error of 2%.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
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 ↗
AUTOMATIC CLASSIFICATION OF VARIABLE STARS IN CATALOGS WITH MISSING DATA
We present an automatic classification method for astronomical catalogs with missing data. We use Bayesian networks and a probabilistic graphical model that allows us to perform inference to predict missing values given observed data and dependency relationships between variables. To learn a Bayesian network from incomplete data, we use an iterative algorithm that utilizes sampling methods and expectation maximization to estimate the distributions and probabilistic dependencies of variables from data with missing values. To test our model, we use three catalogs with missing data (SAGE, Two Micron All Sky Survey, and UBVI) and one complete catalog (MACHO). We examine how classification accuracy changes when information from missing data catalogs is included, how our method compares to traditional missing data approaches, and at what computational cost. Integrating these catalogs with missing data, we find that classification of variable objects improves by a few percent and by 15% for quasar detection while keeping the computational cost the same.
79 ASTRONOMY AND ASTROPHYSICS↗
Beam Based RF Voltage Measurements and Longitudinal Beam Tomography at the Fermilab Booster
Increasing proton beam power on neutrino production targets is one of the major goals of the Fermilab long term accelerator programs. In this effort, the Fermilab 8 GeV Booster synchrotron plays a critical role for at least the next two decades. Therefore, understanding the Booster in great detail is important as we continue to improve its performance. For example, it is important to know accurately the available RF power in the Booster by carrying out beam-based measurements in order to specify the needed upgrades to the Booster RF system. Since the Booster magnetic field is changing continuously measuring/calibrating the RF voltage is not a trivial task. Here, we present a beam based method for the RF voltage measurements. Data analysis is carried out using computer programs developed in Python and MATLAB. The method presented here is applicable to any RCS which do not have flat-bottom and flat-top in the acceleration magnetic ramps. We have also carried out longitudinal beam tomography at injection and extraction energies with the data used for RF voltage measurements. Beam based RF voltage measurements and beam tomography were never done before for the Fermilab Booster. The results from these investigations will be very useful in future intensity upgrades.
43 PARTICLE ACCELERATORS↗
Cluster spin glass correlations and dynamics in Zn 0.5 Mn 0.5 Te
Here, we present a combined magnetometry, muon spin-relaxation (𝜇SR), 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 𝜇SR 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↗
Improving Thermal Model Prediction Through Statistical Analysis of Irradiation and Post-Irradiation Data from AGR Experiments
As part of the High Temperature Reactors (HTR) R&D program, a series of irradiation tests, designated as Advanced Gas-cooled Reactor (AGR), have been defined to support development and qualification of fuel design, fabrication process, and fuel performance under normal operation and accident conditions. The AGR tests employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule and instrumented with thermocouples (TC) embedded in graphite blocks enabling temperature control. While not possible to obtain by direct measurements in the tests, crucial fuel conditions (e.g., temperature, neutron fast fluence, and burnup) are calculated using core physics and thermal modeling codes. This paper is focused on AGR test fuel temperature predicted by the ABAQUS code's finite element-based thermal models. The work follows up on a previous study, in which several statistical analysis methods were adapted, implemented in the NGNP Data Management and Analysis System (NDMAS), and applied for qualification of AGR-1 thermocouple data. Abnormal trends in measured data revealed by the statistical analysis are traced to either measuring instrument deterioration or physical mechanisms in capsules that may have shifted the system thermal response. The main thrust of this work is to exploit the variety of data obtained in irradiation and post-irradiation examination (PIE) for assessment of modeling assumptions. As an example, the uneven reduction of the control gas gap in Capsule 5 found in the capsule metrology measurements in PIE helps identify mechanisms other than TC drift causing the decrease in TC readings. This suggests a more physics-based modification of the thermal model that leads to a better fit with experimental data, thus reducing model uncertainty and increasing confidence in the calculated fuel temperatures of the AGR-1 test.
99 GENERAL AND MISCELLANEOUS↗
Statistically optimal analysis of state-discretized trajectory data from multiple thermodynamic states
We propose a discrete transition-based reweighting analysis method (dTRAM) for analyzing configuration-space-discretized simulation trajectories produced at different thermodynamic states (temperatures, Hamiltonians, etc.) dTRAM provides maximum-likelihood estimates of stationary quantities (probabilities, free energies, expectation values) at any thermodynamic state. In contrast to the weighted histogram analysis method (WHAM), dTRAM does not require data to be sampled from global equilibrium, and can thus produce superior estimates for enhanced sampling data such as parallel/simulated tempering, replica exchange, umbrella sampling, or metadynamics. In addition, dTRAM provides optimal estimates of Markov state models (MSMs) from the discretized state-space trajectories at all thermodynamic states. Under suitable conditions, these MSMs can be used to calculate kinetic quantities (e.g., rates, timescales). In the limit of a single thermodynamic state, dTRAM estimates a maximum likelihood reversible MSM, while in the limit of uncorrelated sampling data, dTRAM is identical to WHAM. dTRAM is thus a generalization to both estimators.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
High-resolution neutron diffraction study of microstructural changes in nanocrystalline ball-milled niobium carbide NbC{sub 0.93}
High resolution neutron diffraction was applied for elucidating of the microstructural evolution of nanocrystalline niobium carbide NbC{sub 0.93} powders subjected to high-energy ball milling. The diffraction patterns were collected with the high resolution Fourier diffractometer HRFD by using the reverse time-of-flight (RTOF) mode of data acquisition. The traditional single diffraction line analysis, the Rietveld method and more advanced Whole Powder Pattern Modeling technique were applied for the data analysis. The comparison of these techniques was performed. It is established that short-time milling produces a non-uniform powder, in which two distinct fractions with differing microstructure can be identified. Part of the material is in fact milled efficiently, with a reduction in grain size, an increase in the quantity of defects, and a corresponding tendency to decarburize reaching a composition NbC{sub 0.80} after 15 h of milling. The rest of the powder is less efficiently processed and preserves its composition and lower defect content. Larger milling times should have homogenized the system by increasing the efficiently milled fraction, but the material is unable to reach a uniform and homogeneous state. It is definitely shown that RTOF neutron diffraction patterns can provide the very accurate data for microstructure analysis of nanocrystalline powders. - Highlights: • The NbC{sub 0.93} powder was processed by high-energy ball milling. • The microstrain and dislocation density increase with milling time increase. • The corresponding decrease in crystallite size with milling time was observed. • The material exhibits the presence of two fractions after ball milling. • The RTOF neutron diffraction data are suitable for accurate microstructure analysis.
36 MATERIALS SCIENCE↗
SWIFT X-RAY TELESCOPE MONITORING OF FERMI-LAT GAMMA-RAY SOURCES OF INTEREST
We describe a long-term Swift monitoring program of Fermi gamma-ray sources, particularly the 23 gamma-ray ''sources of interest''.We present a systematic analysis of the Swift X-Ray Telescope light curves and hardness ratios of these sources, and we calculate excess variability. We present data for the time interval of 2004 December 22 through 2012 August 31. We describe the analysis methods used to produce these data products, and we discuss the availability of these data in an online repository, which continues to grow from more data on these sources and from a growing list of additional sources. This database should be of use to the broad astronomical community for long-term studies of the variability of these objects and for inclusion in multiwavelength studies.
79 ASTRONOMY AND ASTROPHYSICS↗
Towards scanning nanostructure X-ray microscopy
This article demonstrates spatial mapping of the local and nanoscale structure of thin film objects using spatially resolved pair distribution function (PDF) analysis of synchrotron X-ray diffraction data. This is exemplified in a lab-on-chip combinatorial array of sample spots containing catalytically interesting nanoparticles deposited from liquid precursors using an ink-jet liquid-handling system. A software implementation is presented of the whole protocol, including an approach for automated data acquisition and analysis using the atomic PDF method. The protocol software can handle semi-automated data reduction, normalization and modeling, with user-defined recipes generating a comprehensive collection of metadata and analysis results. By slicing the collection using included functions, it is possible to build images of different contrast features chosen by the user, giving insights into different aspects of the local structure.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗