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NASA NTRS1972

Unsupervised classification of earth resources data.

A new clustering technique is presented. It consists of two parts: (a) a sequential statistical clustering which is essentially a sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. This unsupervised composite technique was employed for automatic classification of two sets of remote multispectral earth resource observations. The classification accuracy by the unsupervised technique is found to be comparable to that by existing supervised maximum liklihood classification technique.

Su, M. Y.↗

NASA NTRS1986

An overview of data acquisition, signal coding and data analysis techniques for MST radars

An overview is given of the data acquisition, signal processing, and data analysis techniques that are currently in use with high power MST/ST (mesosphere stratosphere troposphere/stratosphere troposphere) radars. This review supplements the works of Rastogi (1983) and Farley (1984) presented at previous MAP workshops. A general description is given of data acquisition and signal processing operations and they are characterized on the basis of their disparate time scales. Then signal coding, a brief description of frequently used codes, and their limitations are discussed, and finally, several aspects of statistical data processing such as signal statistics, power spectrum and autocovariance analysis, outlier removal techniques are discussed.

Rastogi, P. K.↗

NASA NTRS2016

Comparison of Atmospheric Delay Statistics from Deep Space Network Arrays and Nearby Test Interferometers

Several techniques have been explored and demonstrated that allow for greater data return on space-to-ground links. Among these techniques, arraying several smaller diameter dish antennas together is one method used in several arenas. These arrays can achieve larger effective area and gain than are available from a single larger antenna. This technique is routinely used by the NASA Deep Space Network (DSN) at 8.4 GHz where the incoming signals are much weaker than those experienced by the near-Earth satellite community. When considering arraying at much higher frequencies such as 32 GHz deep-space Ka-band, the phase alignment of the individual antenna signals is significantly disrupted by atmospheric turbulence. Since 2012, several downlink array demonstrations have been conducted using 32 GHz carrier signals emitted by the deep space probes Cassini and Kepler. Site test interferometers (STIs) that receive signals from geostationary satellites have been deployed at all three DSN tracking complexes for long-term monitoring of atmospheric delay fluctuations. In a previous DSN array demonstration study involving the Cassini spacecraft, it was shown that statistics of the adjusted STI phase fluctuations matched the statistics of concurrent array demonstration phase fluctuations. These adjustments accounted for differences in antenna separation, elevation angle and spacecraft frequencies. The STI antenna separations were about 200 m and the DSN antenna separations were about 300 m. These adjustments made use of the thick-layer turbulence model that was applicable to the Goldstone desert climate during the summer months for which the data were acquired. In this paper, we report on the results of additional array demonstrations involving the Kepler spacecraft and compare the adjusted STI phase fluctuations with those seen by a nearby two-element array of 34 m diameter antennas tracking Kepler’s 32 GHz signal at the Goldstone, California and Madrid, Spain DSN sites. We also discuss results from a demonstration using an array over a longer 12.5 km baseline. The Cassini and Kepler array demonstrations were found to validate the long term statistics acquired from several years of STI data as well as the models used to adjust the statistics for the conditions of an array. These statistics represent reliable estimates of the phase fluctuations that would be seen by an array tracking a deep space signal after applying appropriate adjustments for a given array configuration, elevation angle profile and observing frequency.

Morabito, David D.↗

DOE OSTI2021

Collaborative Exploration of Scientific Datasets Using Immersive and Statistical Visualization

We discuss the value of collaborative, immersive visualization for the exploration of scientific datasets and review techniques and tools that have been developed and deployed at the National Renewable Energy Laboratory (NREL). We believe that collaborative visualizations linking statistical interfaces and graphics on laptops and high-performance computing (HPC) with 3D visualizations on immersive displays (head-mounted displays and large-scale immersive environments) enable scientific workflows that further rapid exploration of large, high-dimensional datasets by teams of analysts. We present a framework, PlottyVR, that blends statistical tools, general-purpose programming environments, and simulation with 3D visualizations. To contextualize this framework, we propose a categorization and loose taxonomy of collaborative visualization and analysis techniques. Finally, we describe how scientists and engineers have adopted this framework to investigate large, complex datasets.

collaborative visualization↗

DOE OSTI2014

MO-C-18A-01: Advances in Model-Based 3D Image Reconstruction

Recent years have seen the emergence of CT image reconstruction techniques that exploit physical models of the imaging system, photon statistics, and even the patient to achieve improved 3D image quality and/or reduction of radiation dose. With numerous advantages in comparison to conventional 3D filtered backprojection, such techniques bring a variety of challenges as well, including: a demanding computational load associated with sophisticated forward models and iterative optimization methods; nonlinearity and nonstationarity in image quality characteristics; a complex dependency on multiple free parameters; and the need to understand how best to incorporate prior information (including patient-specific prior images) within the reconstruction process. The advantages, however, are even greater – for example: improved image quality; reduced dose; robustness to noise and artifacts; task-specific reconstruction protocols; suitability to novel CT imaging platforms and noncircular orbits; and incorporation of known characteristics of the imager and patient that are conventionally discarded. This symposium features experts in 3D image reconstruction, image quality assessment, and the translation of such methods to emerging clinical applications. Dr. Chen will address novel methods for the incorporation of prior information in 3D and 4D CT reconstruction techniques. Dr. Pan will show recent advances in optimization-based reconstruction that enable potential reduction of dose and sampling requirements. Dr. Stayman will describe a “task-based imaging” approach that leverages models of the imaging system and patient in combination with a specification of the imaging task to optimize both the acquisition and reconstruction process. Dr. Samei will describe the development of methods for image quality assessment in such nonlinear reconstruction techniques and the use of these methods to characterize and optimize image quality and dose in a spectrum of clinical applications. Learning Objectives: Learn the general methodologies associated with model-based 3D image reconstruction. Learn the potential advantages in image quality and dose associated with model-based image reconstruction. Learn the challenges associated with computational load and image quality assessment for such reconstruction methods. Learn how imaging task can be incorporated as a means to drive optimal image acquisition and reconstruction techniques. Learn how model-based reconstruction methods can incorporate prior information to improve image quality, ease sampling requirements, and reduce dose.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Polynomial meta-models with canonical low-rank approximations: Numerical insights and comparison to sparse polynomial chaos expansions

The growing need for uncertainty analysis of complex computational models has led to an expanding use of meta-models across engineering and sciences. The efficiency of meta-modeling techniques relies on their ability to provide statistically-equivalent analytical representations based on relatively few evaluations of the original model. Polynomial chaos expansions (PCE) have proven a powerful tool for developing meta-models in a wide range of applications; the key idea thereof is to expand the model response onto a basis made of multivariate polynomials obtained as tensor products of appropriate univariate polynomials. The classical PCE approach nevertheless faces the “curse of dimensionality”, namely the exponential increase of the basis size with increasing input dimension. To address this limitation, the sparse PCE technique has been proposed, in which the expansion is carried out on only a few relevant basis terms that are automatically selected by a suitable algorithm. An alternative for developing meta-models with polynomial functions in high-dimensional problems is offered by the newly emerged low-rank approximations (LRA) approach. By exploiting the tensor–product structure of the multivariate basis, LRA can provide polynomial representations in highly compressed formats. Through extensive numerical investigations, we herein first shed light on issues relating to the construction of canonical LRA with a particular greedy algorithm involving a sequential updating of the polynomial coefficients along separate dimensions. Specifically, we examine the selection of optimal rank, stopping criteria in the updating of the polynomial coefficients and error estimation. In the sequel, we confront canonical LRA to sparse PCE in structural-mechanics and heat-conduction applications based on finite-element solutions. Canonical LRA exhibit smaller errors than sparse PCE in cases when the number of available model evaluations is small with respect to the input dimension, a situation that is often encountered in real-life problems. By introducing the conditional generalization error, we further demonstrate that canonical LRA tend to outperform sparse PCE in the prediction of extreme model responses, which is critical in reliability analysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Direct comparison of using a Z -transformation instead of the traditional $Q^2$ for extraction of the proton radius from $e-p$ scattering data

A discrepancy in the determination of the proton’s charge radius, r p , between muonic hydrogen spectroscopy versus classic atomic spectroscopy and electron scattering data has become known as the proton radius puzzle. Extractions of r p from electron scattering data require determination of the slope of the proton’s charge form factor, $G$$^{p}_{E}$, in the limit of Q 2 → 0 through fitting and extrapolation. Some works have presented the Z-transformation fitting technique as the best choice for this type of extraction due to the true functional form of $G$$^{p}_{E}$ being mathematically guaranteed to exist within the parameter-space of the fit function. In this work, we test this claim by examining the mathematical bias and variances introduced by this technique as compared to the more traditional Q 2 fits using statistically sampled $G$$^{p}_{E}$ parameterizations with known input radii. Furthermore, our tests conclude that the quality of the Z-transformation technique depends on the range of data used. In the case of new experiments, the fit function and technique should be selected in advance by generating realistic pseudodata and assessing the power of different techniques.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2015

Development and application of a standardized flow measurement uncertainty analysis framework to various low-head short-converging intake types across the United States federal hydropower fleet

Turbine discharges at low-head short converging intakes are difficult to measure accurately. The proximity of the measurement section to the intake entrance admits large uncertainties related to asymmetry of the velocity profile, swirl, and turbulence. Existing turbine performance codes [10, 24] do not address this special case and published literature is largely silent on rigorous evaluation of uncertainties associated with this measurement context. The American Society of Mechanical Engineers (ASME) Committee investigated the use of Acoustic transit time (ATT), Acoustic scintillation (AS), and Current meter (CM) in a short converging intake at the Kootenay Canal Generating Station in 2009. Based on their findings, a standardized uncertainty analysis (UA) framework for velocity-area method (specifically for CM measurements) is presented in this paper given the fact that CM is still the most fundamental and common type of measurement system. Typical sources of systematic and random errors associated with CM measurements are investigated, and the major sources of uncertainties associated with turbulence and velocity fluctuations, numerical velocity integration technique (bi-cubic spline), and the number and placement of current meters are being considered for an evaluation. Since the velocity measurements in a short converging intake are associated with complex nonlinear and time varying uncertainties (e.g., Reynolds stress in fluid dynamics), simply applying the law of propagation of uncertainty is known to overestimate the measurement variance while the Monte Carlo method does not. Therefore, a pseudo-Monte Carlo simulation method (random flow generation technique [8]) which was initially developed for the purpose of establishing upstream or initial conditions in the Large-Eddy Simulation (LES) and the Direct Numerical Simulation (DNS) is used to statistically determine uncertainties associated with turbulence and velocity fluctuations. This technique is then combined with a bi-cubic spline interpolation method which converts point velocities into a continuous velocity distribution over the measurement domain. Subsequently the number and placement of current meters are simulated to investigate the accuracy of the estimated flow rates using the numerical velocity-area integration method outlined in ISO 3354 [12]. The authors herein consider that statistics on generated flow rates processed with bi-cubic interpolation and sensor simulations are the combined uncertainties which already accounted for the effects of all those three uncertainty sources. A preliminary analysis based on the current meter data obtained through an upgrade acceptance test of a single unit located in a mainstem plant has been presented.

Smith, Brennan T↗

DOE OSTI2014

Signal/noise enhancement strategies for stochastically estimated correlation functions

We develop here strategies for enhancing the signal/noise ratio for stochastically sampled correlation functions. The techniques are general and offer a wide range of applicability. We demonstrate the potential of the approach with a generic two-state system and then explore the practical applicability of the method for single hadron correlators in lattice quantum chromodynamics. In the latter case, we determine the ground state energies of the pion, proton, and delta baryon, as well as the ground and first excited state energy of the rho meson using matrices of correlators computed on an exemplary ensemble of anisotropic gauge configurations. In the majority of cases, we find a modest reduction in the statistical uncertainties on extracted energies compared to conventional variational techniques. However, in the case of the delta baryon, we achieve a factor of 3 reduction in statistical uncertainties. The variety of outcomes achieved for single hadron correlators illustrates an inherent dependence of the method on the properties of the system under consideration and the operator basis from which the correlators are constructed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1988

Statistical error analysis in CCD time-resolved photometry with applications to variable stars and quasars

Differential photometric time series obtained from CCD frames are tested for intrinsic variability using a newly developed analysis of variance technique. In general, the objects used for differential photometry will not all be of equal magnitude, so the techniques derived here explicitly correct for differences in the measured variances due to photon statistics. Other random-noise terms are also considered. The technique tests for the presence of intrinsic variability without regard to its random or periodic nature. It is then applied to observations of the variable stars ZZ Ceti and US 943 and the active extragalactic objects OQ 530, US 211, US 844, LB 9743, and OJ 287.

Howell, Steve B.↗

DOE OSTI2017

Bladder radiotherapy treatment: A retrospective comparison of 3-dimensional conformal radiotherapy, intensity-modulated radiation therapy, and volumetric-modulated arc therapy plans

To examine tumor's and organ's response when different radiotherapy plan techniques are used. Ten patients with confirmed bladder tumors were first treated using 3-dimensional conformal radiotherapy (3DCRT) and subsequently the original plans were re-optimized using the intensity-modulated radiation treatment (IMRT) and volumetric-modulated arc therapy (VMAT)-techniques. Targets coverage in terms of conformity and homogeneity index, TCP, and organs' dose limits, including integral dose analysis were evaluated. In addition, MUs and treatment delivery times were compared. Better minimum target coverage (1.3%) was observed in VMAT plans when compared to 3DCRT and IMRT ones confirmed by a statistically significant conformity index (CI) results. Large differences were observed among techniques in integral dose results of the femoral heads. Even if no statistically significant differences were reported in rectum and tissue, a large amount of energy deposition was observed in 3DCRT plans. In any case, VMAT plans provided better organs and tissue sparing confirmed also by the normal tissue complication probability (NTCP) analysis as well as a better tumor control probability (TCP) result. Our analysis showed better overall results in planning using VMAT techniques. Furthermore, a total time reduction in treatment observed among techniques including gantry and collimator rotation could encourage using the more recent one, reducing target movements and patient discomfort.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2017

The Calibration System of the E989 Experiment at Fermilab

The muon anomaly aµ is one of the most precise quantity known in physics experimentally and theoretically. The high level of accuracy permits to use the measurement of aµ as a test of the Standard Model comparing with the theoretical calculation. After the impressive result obtained at Brookhaven National Laboratory in 2001 with a total accuracy of 0.54 ppm, a new experiment E989 is under construction at Fermilab, motivated by the diff of aexp SM µ − aµ ∼ 3σ. The purpose of the E989 experiment is a fourfold reduction of the error, with a goal of 0.14 ppm, improving both the systematic and statistical uncertainty. With the use of the Fermilab beam complex a statistic of × 21 with respect to BNL will be reached in almost 2 years of data taking improving the statistical uncertainty to 0.1 ppm. Improvement on the systematic error involves the measurement technique of ωa and ωp, the anomalous precession frequency of the muon and the Larmor precession frequency of the proton respectively. The measurement of ωp involves the magnetic field measurement and improvements on this sector related to the uniformity of the field should reduce the systematic uncertainty with respect to BNL from 170 ppb to 70 ppb. A reduction from 180 ppb to 70 ppb is also required for the measurement of ωa; new DAQ, a faster electronics and new detectors and calibration system will be implemented with respect to E821 to reach this goal. In particular the laser calibration system will reduce the systematic error due to gain fl of the photodetectors from 0.12 to 0.02 ppm. The 0.02 ppm limit on systematic requires a system with a stability of 10−4 on short time scale (700 µs) while on longer time scale the stability is at the percent level. The 10−4 stability level required is almost an order of magnitude better than the existing laser calibration system in particle physics, making the calibration system a very challenging item. In addition to the high level of stability a particular environment, due to the presence of a 14 m diameter storage ring, a highly uniform magnetic field and the detector distribution around the storage ring, set specific guidelines and constraints. This thesis will focus on the final design of the Laser Calibration System developed for the E989 experiment. Chapter 1 introduces the subject of the anomalous magnetic moment of the muon; chapter 2 presents previous measurement of g-2, while chapter 3 discusses the Standard Model prediction and possible new physics scenario. Chapter 4 describes the E989 experiment. In this chapter will be described the experimental technique and also will be presented the experimental apparatus focusing on the improvements necessary to reduce the statistical and systematic errors. The main item of the thesis is discussed in the last two chapters: chapter 5 is focused on the Laser Calibration system while chapter 6 describes the Test Beam performed at the Beam Test Facility of Laboratori Nazionali di Frascati from the 29th February to the 7th March as a final test for the full calibrations system. An introduction explain the physics motivation of the system and the diff t devices implemented. In the final chapter the setup used will be described and some of the results obtained will be presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1985

Signal analysis techniques for incipient failure detection in turbomachinery

Signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery were developed, implemented and evaluated. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques were implemented on a computer and applied to dynamic signals. A laboratory evaluation of the methods with respect to signal detection capability is described. Plans for further technique evaluation and data base development to characterize turbopump incipient failure modes from Space Shuttle main engine (SSME) hot firing measurements are outlined.

Coffin, T.↗

NASA NTRS1986

Signal Detection Techniques for Diagnostic Monitoring of Space Shuttle Main Engine Turbomachinery

An investigation to develop, implement, and evaluate signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery is reviewed. A brief description of the Space Shuttle Main Engine (SSME) test/measurement program is presented. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques have been implemented on a computer and applied to dynamc signals. A laboratory evaluation of the methods with respect to signal detection capability is described. A unique coherence function (the hyper-coherence) was developed through the course of this investigation, which appears promising as a diagnostic tool. This technique and several other non-linear methods of signal analysis are presented and illustrated by application. Software for application of these techniques has been installed on the signal processing system at the NASA/MSFC Systems Dynamics Laboratory.

Coffin, Thomas↗

DOE OSTI2024

Highly accelerated life testing (HALT): A review from a statistical perspective

Despite its use in one form or another for at least four decades, HALT and related techniques [e.g., highly accelerated-stress screening (HASS) and stress audits (HASA)] are not well understood within the statistical community and remain controversial. This largely reflects a conflict in motivation between engineers, testing under harsh conditions to discover and eliminate failure modes, and statisticians, taking a more cautious approach to develop quantitative estimates of parameters such as mean time between failures (MTBF). Here, this review article will clarify HALT concepts and methods and explain where it fits within the universe of methods that involve the application of accelerating factors to compress the time required to evaluate or enhance product reliability. A major distinction is between methods such as HALT, a high-stress test-analyze-fix-test iterative process directed at improving reliability by discovering and fixing weak points in a design, and quantitative accelerated life testing (QALT), whose goal is the estimation of product life for a fixed design. We discuss methods such as physics of failure that offer some hope of bridging the gap between the qualitative nature of HALT, and purely quantitative statistical methods. We present a variety of engineering applications of HALT including metal fatigue, piping and pressure vessels, structural damage, radiation damage, and rotating machinery. We also discuss potential synergies between HALT and QALT, such as rapid identification, through HALT, of failure modes requiring quantitative analysis. For further study, extensive references to the applicable literature are provided as well as an appendix that describes related methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Smart Sampling and HPC-based Probabilistic Look-ahead Contingency Analysis Implementation and its Evaluation with Real-world Data

This paper describes a probabilistic look-ahead contingency analysis application that incorporates smart sampling and high-performance computing (HPC) techniques. Smart sampling techniques are implemented to effectively represent the structure and statistical characteristics of uncertainty introduced by different sources in the power system. They can significantly reduce the data set size required for multiple look-ahead contingency analyses, and therefore reduce the time required to compute them. High-performance-computing (HPC) techniques are used to further reduce computational time. These two techniques enable a predictive capability that forecasts the impact of various uncertainties on potential transmission limit violations. The developed package has been tested with real world data from the Bonneville Power Administration. Case study results are presented to demonstrate the performance of the applications developed.

high performance computing↗

DOE OSTI2020

Collaborative Exploration of Scientific Datasets Using Immersive and Statistical Visualization: Preprint

collaborative visualization↗

DOE OSTI2018

Geometry tagging for heavy ions at JLEIC

Geometry tagging is an experimental analysis technique for selecting event samples where one can, on a statistical basis, control the geometry of the collision in order to make more incisive physics measurements. Several physics measurements at the EIC would benefit significantly from the use of this technique, including studies of gluon anti-shadowing, studies of parton propagation, attenuation and hadronization in the nucleus, and ultimately the search for parton saturation. The JLEIC full-acceptance detector, with full acceptance to forward-going neutrons, protons and nuclear fragments and a high data-taking rate is ideally suited to such geometry tagging. We improve, tune, and apply existing modeling codes, BeAGLE, Sartre, and GEMC, and detector descriptions to study this physics.

Morozov, Vasiliy↗