Results for “Multivariate Analysis” — Page 73

NASA NTRS2005

Multivariable Parametric Cost Model for Ground Optical Telescope Assembly

A parametric cost model for ground-based telescopes is developed using multivariable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction-limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature are examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e., multi-telescope phased-array systems). Additionally, single variable models Based on aperture diameter are derived.

Stahl, H. Philip↗

NASA NTRS2007

Physical Interpretation of the Correlation Between Multi-Angle Spectral Data and Canopy Height

Recent empirical studies have shown that multi-angle spectral data can be useful for predicting canopy height, but the physical reason for this correlation was not understood. We follow the concept of canopy spectral invariants, specifically escape probability, to gain insight into the observed correlation. Airborne Multi-Angle Imaging Spectrometer (AirMISR) and airborne Laser Vegetation Imaging Sensor (LVIS) data acquired during a NASA Terrestrial Ecology Program aircraft campaign underlie our analysis. Two multivariate linear regression models were developed to estimate LVIS height measures from 28 AirMISR multi-angle spectral reflectances and from the spectrally invariant escape probability at 7 AirMISR view angles. Both models achieved nearly the same accuracy, suggesting that canopy spectral invariant theory can explain the observed correlation. We hypothesize that the escape probability is sensitive to the aspect ratio (crown diameter to crown height). The multi-angle spectral data alone therefore may not provide enough information to retrieve canopy height globally

Schull, M. A.↗

NASA NTRS2016

System and Method for Outlier Detection via Estimating Clusters

An efficient method and system for real-time or offline analysis of multivariate sensor data for use in anomaly detection, fault detection, and system health monitoring is provided. Models automatically derived from training data, typically nominal system data acquired from sensors in normally operating conditions or from detailed simulations, are used to identify unusual, out of family data samples (outliers) that indicate possible system failure or degradation. Outliers are determined through analyzing a degree of deviation of current system behavior from the models formed from the nominal system data. The deviation of current system behavior is presented as an easy to interpret numerical score along with a measure of the relative contribution of each system parameter to any off-nominal deviation. The techniques described herein may also be used to "clean" the training data.

Iverson, David J.↗

NASA NTRS2019

Measurement of CH3D on Titan at Submillimeter Wavelengths

We present the first radio/submillimeter detection of monodeuterated methane (CH3D) in Titan's atmosphere, using archival data from of the Atacama Large Millimeter/submillimeter Array (ALMA). The J (sub K) equals 2 (sub 1) minus 1 (sub 1) and J (sub K) equals 2 (sub 0) minus 1 (sub 0) transitions at 465.235 and 465.250 gigahertz (approximately 0.644 millimeters) were measured at significance levels of 4.6 sigma and 5.7 sigma, respectively. These two lines were modeled using the Non-linear optimal Estimator for MultivariatE spectral analySIS (NEMESIS) radiative transfer code to determine the disk-averaged CH3D volume mixing ratio equals 6.157 times 10 (sup minus 6) in Titan's stratosphere (at altitudes greater than 130 kilometers). By comparison with the CH4 vertical abundance profile measured by Cassini-Huygens mass spectrometry, the resulting value for D/H in CH4 is (1.033 plus or minus 0.081) times 10 (sup minus 4). This is consistent with previous ground-based and in situ measurements from the Cassini-Huygens mission, though slightly lower than the average of the previous values. Additional CH3D observations at higher spatial resolution will be required to determine a value truly comparable with the Cassini-Huygens CH4 measurements, by measuring CH3D with ALMA close to Titan's equator. In the post-Cassini era, spatially resolved observations of CH3D with ALMA will enable the latitudinal distribution of methane to be determined, making this an important molecule for further studies.

Thelen, Alexander E.↗

NASA NTRS2022

New Constraints on Titan's Stratospheric n-Butane Abundance

Curiously, n-butane has yet to be detected at Titan, though it is predicted to be present in a wide range of abundances that span over 2.5 orders of magnitude. We have searched infrared spectroscopic observations of Titan for signals from n-butane (n-C4H10) in Titan's stratosphere. Three sets of Cassini Composite Infrared Spectrometer Focal Plane 4 (1050–1500 cm−1) observations were selected for modeling, having been collected from different flybys and pointing latitudes. We modeled the observations with the Nonlinear Optimal Estimator for MultivariatE Spectral AnalySIS radiative transfer tool. Temperature profiles were retrieved for each of the data sets by modeling the ν4 emission from methane near 1305 cm−1. Then, incorporating the temperature profiles, we retrieved abundances of all of Titan's known trace gases that are active in this spectral region, reliably reproducing the observations. We then systematically tested a set of models with varying abundances of n-butane, investigating how the addition of this gas affected the fits. We did this for several different photochemically predicted abundance profiles from the literature, as well as for a constant-with-altitude profile. Ultimately, though we did not produce any firm detection of n-butane, we derived new upper limits on its abundance specific to the use of each profile and to multiple different ranges of stratospheric altitudes. These results will tightly constrain the C4 chemistry of future photochemical modeling of Titan's atmosphere and also motivate the continued search for n-butane and its isomer, isobutane.

Brendan L. Steffens↗

DOE OSTI2012

Moving from Descriptive to Causal Analytics: Case Study of the Health Indicators Warehouse

The KDD community has described a multitude of methods for knowledge discovery on large datasets. We consider some of these methods and integrate them into an analyst s workflow that proceeds from the data-centric descriptive level to the model-centric causal level. Examples of the workflow are shown for the Health Indicators Warehouse, which is a public database for community health information that is a potent resource for conducting data science on a medium scale. We demonstrate the potential of HIW as a source of serious visual analytics efforts by showing correlation matrix visualizations, multivariate outlier analysis, multiple linear regression of Medicare costs, and scatterplot matrices for a broad set of health indicators. We conclude by sketching the first steps toward a causal dependence hypothesis.

Schryver, Jack C.↗

DOE OSTI2011

On-Line Monitoring for Control and Safeguarding of Radiochemical Streams at Spent Fuel Reprocessing Plant

There is a renewed interest worldwide to promote the use of nuclear power and close the nuclear fuel cycle. The long term successful use of nuclear power is critically dependent upon adequate and safe processing and disposition of the spent nuclear fuel Liquid-liquid extraction is a separation technique commonly employed for the processing of the dissolved spent nuclear fuel. Our approach is based on prerequisite that real time monitoring of the solvent extraction flowsheets provides unique capability to quickly detect unwanted manipulations with fissile isotopes present in the radiochemical streams during reprocessing activities. The instrumentation used to monitor these processes must be robust, require little or no maintenance, and be able to withstand harsh environments such as high radiation fields and aggressive chemical matrices. In addition, the ability for continuous on-line monitoring allows for numerous benefits. Our team experimentally assessed the potential of Raman and vis-NIR spectrophotometric techniques for on-line real-time monitoring of the U(VI)/nitrate ion/nitric acid and Pu(IV)/Np(V)/Nd(III), respectively, in solutions relevant to spent fuel reprocessing. Both techniques demonstrated robust performance in the repetitive batch measurements of each analyte in a wide concentration range using simulant and commercial dissolved spent fuel solutions. Static spectroscopic measurements served as training sets for the multivariate data analysis to obtain partial least squares predictive models, which were validated using on-line centrifugal contactor extraction tests. The corresponding spectrometers used under the laboratory conditions are easily convertible to the process-friendly configurations allowing remote measurements under the flow conditions. A fiber optic Raman probe allows monitoring of the high concentration species encountered in both aqueous and organic phases within the PUREX suite of flowsheets, including metal oxide ions, such as uranyl, components of the organic solvent, inorganic oxo-anions, and water. The actinides and lanthanides are monitored remotely by UV-vis-NIR spectroscopy in aqueous and organic phases. This paper summarizes our methodology and shows results of specific examples.

Bryan, Samuel A↗

DOE OSTI2011

SPECTROSCOPIC ON-LINE MONITORING FOR PROCESS CONTROL AND SAFEGUARDING OF RADIOCHEMICAL STREAMS

There is a renewed interest worldwide to promote the use of nuclear power and close the nuclear fuel cycle. The long term successful use of nuclear power is critically dependent upon adequate and safe processing and disposition of the spent nuclear fuel. Liquid-liquid extraction is a separation technique commonly employed for the processing of the dissolved spent nuclear fuel. The instrumentation used to monitor these processes must be robust, require little or no maintenance, and be able to withstand harsh environments such as high radiation fields and aggressive chemical matrices. In addition, the ability for continuous online monitoring allows for numerous benefits. Our team experimentally assessed the potential of Raman and spectrophotometric techniques for on-line real-time monitoring of the U(VI)/nitrate ion/nitric acid and Pu(IV)/Np(V)/Nd(III), respectively, in solutions relevant to spent fuel reprocessing. Both techniques demonstrated robust performance in the repetitive batch measurements of each analyte in a wide concentration range using simulant and commercial dissolved spent fuel solutions. Static spectroscopic measurements served as training sets for the multivariate data analysis to obtain partial least squares predictive models, which were validated using on-line centrifugal contactor extraction tests. This paper summarizes or methodology and results of the U(VI)/nitrate system as a specific example.

separations, PUREX, U, Pu, Np, nitic acid, TBP dod↗

DOE OSTI2014

Aberration-corrected X-ray spectrum imaging and Fresnel contrast to differentiate nanoclusters and cavities in helium-irradiated alloy 14YWT

Helium accumulation negatively impacts structural materials used in neutron-irradiated environments, such as fission and fusion reactors. Next-generation fission and fusion reactors will require structural materials, such as steels, resistant to large neutron doses yet see service temperatures in the range most affected by helium embrittlement. Previous work has indicated the difficulty of experimentally differentiating nanometer-sized helium bubbles from the Ti-Y-O rich nanoclustsers (NCs) in radiation-tolerant nanostructured ferritic alloys (NFAs). Because the NCs are expected to sequester helium away from grain boundaries and reduce embrittlement, experimental methods to study simultaneously the NC and bubble populations are needed. In this study, aberration-corrected scanning transmission electron microscopy (STEM) results combining high-collection-efficiency X-ray spectrum images (SIs), multivariate statistical analysis (MVSA), and Fresnel-contrast bright-field STEM imaging have been used for such a purpose. Results indicate that Fresnel-contrast imaging, with careful attention to TEM-STEM reciprocity, differentiates bubbles from NCs, and MVSA of X-ray SIs unambiguously identifies NCs. Therefore, combined Fresnel-contrast STEM and X-ray SI is an effective STEM-based method to characterize helium-bearing NFAs.

Miller, Michael K↗

DOE OSTI2015

Hybrid Statistical Testing for Nuclear Material Accounting Data and/or Process Monitoring Data

The two tests employed in the hybrid testing scheme are Page’s cumulative sums for all streams within a Balance Period (maximum of the maximums and average of the maximums) and Crosier’s multivariate cumulative sum applied to incremental cumulative sums across Balance Periods. The role of residuals for both kinds of data is discussed.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2013

Spectroscopic Online Monitoring for Process Control and Safeguarding of Radiochemical Fuel Reprocessing Streams

There is a renewed interest worldwide to promote the use of nuclear power and close the nuclear fuel cycle. The long term successful use of nuclear power is critically dependent upon adequate and safe processing and disposition of the spent nuclear fuel. Liquid-liquid extraction is a separation technique commonly employed for the processing of the dissolved spent nuclear fuel. The instrumentation used to monitor these processes must be robust, require little or no maintenance, and be able to withstand harsh environments such as high radiation fields and aggressive chemical matrices. In addition, the ability for continuous online monitoring allows for numerous benefits. This paper reviews application of the absorption and vibrational spectroscopic techniques supplemented by physicochemical measurements for radiochemical process monitoring. In this context, our team experimentally assessed the potential of Raman and spectrophotometric techniques for on-line real-time monitoring of the U(VI)/nitrate ion/nitric acid and Pu(IV)/Np(V)/Nd(III), respectively, in solutions relevant to spent fuel reprocessing. Both techniques demonstrated robust performance in the repetitive batch measurements of each analyte in a wide concentration range using simulant and commercial dissolved spent fuel solutions. Static spectroscopic measurements served as training sets for the multivariate data analysis to obtain partial least squares predictive models, which were validated using on-line centrifugal contactor extraction tests. Satisfactory prediction of the analytes concentrations in these preliminary experiments warrants further development of the spectroscopy-based methods for radiochemical safeguards and process control.

spectroscopic process monitoring, Pu, U, Np↗

DOE OSTI2015

qFeature

This package contains statistical routines for extracting features from multivariate time-series data which can then be used for subsequent multivariate statistical analysis to identify patterns and anomalous behavior. It calculates local linear or quadratic regression model fits to moving windows for each series and then summarizes the model coefficients across user-defined time intervals for each series. These methods are domain agnostic-but they have been successfully applied to a variety of domains, including commercial aviation and electric power grid data.

Source record↗

DOE OSTI2015

Experimental and Data Analytical Approaches to Automating Multivariate Curve Resolution in the Analysis of Hyperspectral Images.

Abstract not provided.

Timlin, Jerilyn A.↗

DOE OSTI2013

SPECTROSCOPIC ONLINE MONITORING FOR PROCESS CONTROL AND SAFEGUARDING OF RADIOCHEMICAL STREAMS

There is a renewed interest worldwide to promote the use of nuclear power and close the nuclear fuel cycle. The long term successful use of nuclear power is critically dependent upon adequate and safe processing and disposition of the used nuclear fuel. Liquid-liquid extraction is a separation technique commonly employed for the processing of the dissolved used nuclear fuel. The instrumentation used to monitor these processes must be robust, require little or no maintenance, and be able to withstand harsh environments such as high radiation fields and aggressive chemical matrices. This paper summarizes application of the absorption and vibrational spectroscopic techniques supplemented by physicochemical measurements for radiochemical process monitoring. In this context, our team experimentally assessed the potential of Raman and spectrophotometric techniques for online real-time monitoring of the U(VI)/nitrate ion/nitric acid and Pu(IV)/Np(V)/Nd(III), respectively, in solutions relevant to spent fuel reprocessing. These techniques demonstrate robust performance in the repetitive batch measurements of each analyte in a wide concentration range using simulant and commercial dissolved spent fuel solutions. Spectroscopic measurements served as training sets for the multivariate data analysis to obtain partial least squares predictive models, which were validated using on-line centrifugal contactor extraction tests. Satisfactory prediction of the analytes concentrations in these preliminary experiments warrants further development of the spectroscopy-based methods for radiochemical process control and safeguarding. Additionally, the ability to identify material intentionally diverted from a liquid-liquid extraction contactor system was successfully tested using on-line process monitoring as a means to detect the amount of material diverted. A chemical diversion and detection from a liquid-liquid extraction scheme was demonstrated using a centrifugal contactor system operating with the simulant PUREX extraction system of Nd(NO3)3/nitric acid aqueous phase and TBP/n-dodecane organic phase. During a continuous extraction experiment, a portion of the feed from a counter-current extraction system was diverted while the spectroscopic on-line process monitoring system was simultaneously measuring the feed, raffinate and organic products streams. The amount observed to be diverted by on-line spectroscopic process monitoring was in excellent agreement with values based from the known mass of sample directly taken (diverted) from system feed solution.

fuel reprocessing↗

DOE OSTI2021

Fusing Quantitative-Phase Imaging with Airy Light- Sheet Microscopy

We report the integration of quantitative-phase imaging (QPI) with light-sheet (LS) fluorescent microscopy on to a standard inverted microscope that retains compatibility with microfluidics. QPI enables label-free imaging and number-density quantification of single cells and their organelles. Conversely, LS yields considerable speed and phototoxicity gains in quantifying the 4D dynamics of gene-encoded fluorescent biomarkers. We will detail the system design that relied on spatial light interferometry for QPI and an accelerating Airy- beam light-sheet for fluorescence, its performance, as well as results of a representative multivariate imaging analysis of single-cell metabolism.

imaging, lattice light sheet, Yarrowia lipolytica,↗

DOE OSTI2022

Accurate and Timely Forecasts of Geologic Carbon Storage using Machine Learning Methods

Carbon capture and storage is one strategy to reduce greenhouse gas emissions. One approach to storing the captured CO2 is to inject it into deep saline aquifers. However, dynamics of the injected CO2 plume is uncertain and the potential for leakage back to the atmosphere must be assessed. Thus, accurate and timely forecasts of CO2 storage via real-time measurements integration becomes very crucial. This study proposes a learning-based, inverse-free prediction method that can accurately and rapidly forecast CO2 movement and distribution with uncertainty quantification based on limited simulation and observation data. The machine learning techniques include dimension reduction, multivariate data analysis, and Bayesian learning. The outcome is expected to provide CO2 storage site operators with an effective tool for real-time decision making.

Lu, Dan↗

DOE OSTI2013

Spectroscopic online monitoring for process control and safeguarding of radiochemical streams

This paper summarizes application of the absorption and vibrational spectroscopic techniques supplemented by physicochemical measurements for radiochemical process monitoring. In this context, our team experimentally assessed the potential of Raman and spectrophotometric techniques for online real-time monitoring of the U(VI)/nitrate ion/nitric acid and Pu(IV)/Np(V)/Nd(III), respectively, in solutions relevant to spent fuel reprocessing. These techniques demonstrate robust performance in the repetitive batch measurements of each analyte in a wide concentration range using simulant and commercial dissolved spent fuel solutions. Spectroscopic measurements served as training sets for the multivariate data analysis to obtain partial least squares predictive models, which were validated using on-line centrifugal contactor extraction tests. Satisfactory prediction of the analytes concentrations in these preliminary experiments warrants further development of the spectroscopy-based methods for radiochemical process control and safeguarding. Additionally, the ability to identify material intentionally diverted from a liquid-liquid extraction contactor system was successfully tested using on-line process monitoring as a means to detect the amount of material diverted. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

Radiological Performance Modeling: Platform Comparison

Zapadnoe Uranium Mill Tailings Site, Pridneprovsky Chemical Plant Ukraine: Two exposure scenarios were utilized to develop performance assessment models in GoldSim and NORMALYSA. The first scenario is an onsite worker exposed to radioactivity through external ground irradiation as well as radon and radioactive dust inhalation. The second being an offsite Resident 300 years after institutional control exposed through the ingestion of garden vegetables irrigated by contaminated ground water, ingestion of fish from Konoplyanka River, and agricultural activities in contaminated garden. NORMALYSA utilizes a modular interface to connect extensive pre-created modules to develop contaminant transport and risk assessment models for safety assessments and performance assessments at NORM and legacy sites. Developed by Facilia AB, the program was tested with the creation of the Zapadnoe model under the International Atomic Energy Agency MODARIA Il Working Group 1 (WG1). Default values are provided for input parameters where site specific data and distributions lack. Probabilistic simulations and inputs are limited to parameters with assigned Gaussian probability functions. Similar results for transient worker inhalation dose were found in comparison with the Zapadnoe GoldSim model. However, the NORMALYSA model has results larger by an order of magnitude for external radiation in the transient worker and for aquatic food ingestion, inhalation, and garden food ingestion to the resident. Performance Assessment Modeling: Radiological performance models promote good management and support in remediation and environmental decision making by optimizing radioactive waste disposal site performance. a performance assessment model of the Zapadnoe uranium mill tailings site and a model for calculating authorized limits at Los Alamos National Laboratory are created to demonstrate and highlight the respective capabilities of three modeling platforms: GoldSim, NORMALYSA, and RESRAD-Onsite. GoldSim is a general-purpose modeling platform with the ability to simulate site-specific FT radionuclide transport and risk assessment using a graphical interface to create and link elements that act as indivisible building blocks of the model. The Zapadnoe performance assessment model created in GoldSim is composed of input parameters collected from site specific parameters from WG1 as well as standard assumptions seen in the Generic PA Model from Neptune and Company. The multivariate Zapadnoe simulation contains both deterministic and probabilistic simulation capabilities with the ability to quantitatively represent the uncertainty and associated risks of the site via the Monte Carlo simulation method. Model parameters, documentation, and assumptions are built directly into the model creating a transparent, reproducible, and more purposeful site specific model. To demonstrate this, an ingestion of water pathway was included in addition to the exposure pathways included in the NORMALYSA model. GoldSim offers a wide variety of probability distributions to choose from as well as many tools to visualize the uncertainty of the models and explore which pathways and radionuclides dominate dose. In contrast to the NORMALYSA model, the GoldSim model uses dynamic simulation to calculate tritium concentrations. Authorized limits support the evaluation of radiological health effects from radionuclides present in bulk contaminated soil in order to assist in the process of clearing land for release under different uses. Calculations of authorized limits in RESRAD-Onsite and GoldSim models support the evaluation for 15 radionuclides using a residential exposure scenario, indoor and outdoor inhalation of dust and vapor phase radionuclides (tritium), incidental soil ingestion, and ingestion grown fruits and Vegetables. RESRAD-Onsite, developed by Argonne National Laboratory is a dedicated computer code for calculating radiation doses and cancer risks to an individual located on top of radioactively contaminated soils. It can also be used to provide guidelines for deriving radionuclide soil levels corresponding to a specific dose criterion. The menu driven user interface facilitates selection of radionuclides and soil concentrations, as well as defines parameter values related to materials, environmental factors, and exposure pathways. The program contains radionuclide-specific data such as dose conversion factors and risk coefficients, as well as soil-water partition coefficients and transfer factors for biotic media. The GoldSim model successfully emulates the RESRAD-Onsite code using identical radiological decay and ingrowth factors, radiation dose conversion factors, and other input parameters. DE EEDE ETS Each model supports dynamic modeling of radionuclide ingrowth and decay over time, and integrate this capability with the transport of radionuclides in the environment via processes such as advection and/or diffusion in fluids, or within porous solid media, The applicability of each program is heavily dependent on project context. In the context of developing Authorized Limits, RESRAD-Onsite may be a more desirable option as it was developed for this particular application. For simple disposal or legacy sites or sites that do not need site-specific model structure, NORMALYSA may be a desirable modeling platform, GoldSim can be used to model any problem for which RESRAD or NORMALYSA is applicable, but its strength lies in its flexibility, analytical, and probabilistic capabilities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗