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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Reconstructing porous media using generative flow networks

One area of intense scientific interest for the study of sandstones, carbonates, and shale at the pore scale is the use of limited image and petrophysical data to generate multiple realizations of a rock’s pore structure. Such images aid efforts to quantify uncertainty in petrophysical properties, including porosity–permeability transforms. We develop and evaluate a deep learning-based method to synthesize porous media volumes using a so-called generative flow model trained on x-ray microscope images of rock texture and pore structure. These models are optimized on a log-likelihood objective and they synthesize large and realistic three-dimensional images. Further, we demonstrate the rapid generation of sandstone image volumes that display realism as gauged by quantitative comparison of topological features using Minkowski functionals of porosity, specific surface area, and the Euler–Poincaré characteristic (i.e., pore connectivity). We also evaluate the single-phase permeability using Navier–Stokes and lattice Boltzmann methods and show that transport properties of the generated samples match measured trends.

58 GEOSCIENCES↗
DOE OSTI2024

Augmented Human Analysis (AHA)

Radio frequency (RF) signal monitoring generally emphasizes intentionally generated signals, such as WiFi, Bluetooth, or cellular transmissions. However, electronic devices also produce unintended radiated emissions (UREs), which could also be useful in RF spectrum analysis. In either case, deriving intelligence from RF signals is typically a human-intensive process requiring significant domain knowledge. In the Augmented Human Analysis (AHA) project, we investigate the utility of dimensionally aligned signal projection (DASP) and machine learning (ML) algorithms for accelerating RF analysis workflows. We find that while DASP algorithms can indeed highlight signal characteristics relevant for classification tasks, the choice of algorithmic hyperparameters greatly affects performance. To address this challenge, we evaluate the quality of DASP outputs using the silhouette score, which measures how well data points cluster; high silhouette scores indicate good clustering, and thus good hyperparameter values. This approach is critical for machine learning pipelines as the DASP parameters cannot be directly optimized during model training. By identifying good DASP parameters, and thus good DASP outputs, as a preprocessing step, we can decrease the amount of effort required for downstream ML model training. We demonstrate our workflow using a dataset of UREs from common household devices, showing that even without the aid of ML, proper selection of DASP parameters enables clustering by device type.

42 ENGINEERING↗
DOE OSTI2017

CRISTAL V2: New package for criticality calculations

A new release of the CRISTAL French criticality calculation package, named CRISTAL V2, has been developed and intensively validated by IRSN and CEA, in collaboration with AREVA. This package was designed to cover the needs of criticality practitioners in the fields of nuclear fuel cycle facilities and transportation of fissile materials. Based on an optimized modular architecture in an updated software development environment, the design of CRISTAL package V2 integrates new generation of cross-section libraries, new calculation schemes consistent with new applications, and up-to-date calculation codes capabilities. Four calculation routes are currently available allowing multi-group and continuous energy calculations. The validation database is composed of more than 3000 critical experiments, in order to cover a wide range of configurations. The CRISTAL V2 package also includes customer services covering a large scope of activities like documentations, hotline, maintenance and training courses. A significant promotion and an increased recognition referred both nationally and internationally are foreseen, including the provision of the CRISTAL V2 package to the OECD / NEA Data Bank. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Automated detection of part quality during two-photon lithography via deep learning

Two-photon lithography (TPL) is an additive manufacturing technique for fabricating three-dimensional objects with nanoscale features. A main challenge of TPL is the routine and labor-intensive task of finding suitable light dosage parameters, i.e. writing speed and laser intensity that induce photo-polymerization within a wide variety of candidate photo-curing polymers. Another challenge is the monitoring required during fabrication. In this work, we apply machine learning (ML) models to accelerate the process of identifying optimal light dosage parameters and automate the detection of part quality. We curate TPL videos of different parts fabricated under a range of light dosage parameters using different resins and train spatial-temporal ML models on this data. Our results show that ML models can detect TPL part quality with a 95.1% accuracy in milliseconds. We also evaluate classification failures and identify two operating modes: parameter optimization and part quality detection. Last but not least, we publicly release this labelled dataset so that it may serve as a useful benchmark to the community. Our approach to process optimization and part quality detection addresses important aspects of TPL industrialization, is applicable beyond TPL and should benefit other additive manufacturing techniques with similar barriers to operating at industrial scale.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Neutrino Interactions

The neutrino group of the University of Tennessee, Knoxville was involved from 05/01/2013 to 04/30/2015 in the neutrino physics research funded by DOE-HEP grant DE-SC0009861. Contributions were made to the Double Chooz nuclear reactor experiment in France where second detector was commissioned during this period and final series of measurements has been started. Although Double Chooz was smaller experimental effort than competitive Daya Bay and RENO experiments, its several advantages make it valuable for understanding of systematic errors in measurements of neutrino oscillations. Double Chooz was the first experiment among competing three that produced initial result for neutrino angle θ 13 measurement, giving other experiments the chance to improve measured value statistically. Graduate student Ben Rybolt defended his PhD thesis on the results of Double Chooz experiment in 2015. UT group has fulfilled all the construction and analysis commitments to Double Chooz experiment, and has withdrawn from the collaboration by the end of the mentioned period to start another experiment. Larger effort of UT neutrino group during this period was devoted to the participation in another DOE-HEP project - NOvA experiment. The 14,000-ton "FAR" neutrino detector was commissioned in northern Minnesota in 2014 together with 300-ton "NEAR" detector located at Fermilab. Following that, the physics measurement program has started when Fermilab accelerator complex produced the high-intensity neutrino beam propagating through Earth to detector in MInnessota. UT group contributed to NOvA detector construction and developments in several aspects. Our Research Associate Athanasios Hatzikoutelis was managing (Level 3 manager) the construction of the Detector Control System. This work was successfully accomplished in time with the commissioning of the detectors. Group was involved in the development of the on-line software and study of the signatures of the cosmic ray backgrounds. Flumerfelt and another graduate student Philip Mason were also studying the non-linearity properties of the NOvA liquid scintillator - information that will be essential at the final stages of NOvA data analysis. Philip Mason also studied the response of the FAR NOvA detector in correlation with solar flares. Flumerfelt and Mason successfully defended their PhD in 2015. Also, undergraduate student Cameron Blake Erickson has defended his undergraduate thesis on the NOvA liquid scintillator studies with Compton gamma spectrometer at UT.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Scaling comb-driven resonator-based DWDM silicon photonic links to multi-Tb/s in the multi-FSR regime

The use of chip-based micro-resonator Kerr frequency combs in conjunction with dense wavelength-division multiplexing (DWDM) enables massively parallel intensity-modulated direct-detection data transmission with low energy consumption. Resonator-based modulators and filters used in such systems can limit the number of usable wavelength channels due to practical constraints on the maximum achievable free spectral range (FSR). In this work, we introduce the design of multi-Tb/s comb-driven resonator-based silicon photonic links by leveraging the multi-FSR regime. We demonstrate the viability of the link architecture with yield estimates that are supported by extensive wafer-scale measurements of 704 micro-resonators fabricated in a commercial complementary metal–oxide–semiconductor foundry. We show that a 2.80 Tb/s link is realizable with a ≥6 σ yield (∼99.999%), and that aggregate bandwidths of 3.76 Tb/s and 4.72 Tb/s are possible if yield targets are relaxed (3 σ and 1 σ , respectively). All designs represent a 1.94−3.28× boost to aggregate link bandwidth while maintaining BER≤10 −10 performance, with a theoretical bandwidth of 10.51 Tb/s being possible for sufficiently robust resonators. We use high-speed BER measurements to inform co-optimization of data rate and aggressor spacing ( λ ag ), limiting any additional loss-based power penalties to off-resonance insertion loss (IL) and routing loss. This work demonstrates that, through the multi-FSR regime, there is a clear path toward Kerr comb-driven ultra-broadband, high bandwidth silicon photonic links that can support next-generation data centers and high-performance computers.

James, Aneek (ORCID:0000000262527807)↗
DOE OSTI2020

Retrieving functional pathways of biomolecules from single-particle snapshots

Abstract A primary reason for the intense interest in structural biology is the fact that knowledge of structure can elucidate macromolecular functions in living organisms. Sustained effort has resulted in an impressive arsenal of tools for determining the static structures. But under physiological conditions, macromolecules undergo continuous conformational changes, a subset of which are functionally important. Techniques for capturing the continuous conformational changes underlying function are essential for further progress. Here, we present chemically-detailed conformational movies of biological function, extracted data-analytically from experimental single-particle cryo-electron microscopy (cryo-EM) snapshots of ryanodine receptor type 1 (RyR1), a calcium-activated calcium channel engaged in the binding of ligands. The functional motions differ substantially from those inferred from static structures in the nature of conformationally active structural domains, the sequence and extent of conformational motions, and the way allosteric signals are transduced within and between domains. Our approach highlights the importance of combining experiment, advanced data analysis, and molecular simulations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) Winter Intensive Operational Period: Aerodynamic Particle Sizer Field Campaign Report

An aerodynamic particle sizer spectrometer (APS, model 3321 by TSI Inc., Shoreview, Minnesota) was deployed at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility Eastern North Atlantic (ENA) observatory during the second (winter) intensive operational period (IOP) of the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. Data were collected from January 9 through February 26, 2018, covering the second deployment of the ARM Aerial Facility (AAF) aircraft within ACE-ENA. The standard ENA instrument suite does not provide measurements of aerosol particle size distribution for diameters greater than one micron. Properties of coarse-mode (super-micron) aerosols are rarely measured, although super-micron particles can play an important role in the aerosol life cycle, affecting aerosol optical properties and cloud nuclei activity (e.g., Clarke et al. 2003). The APS was deployed to fill this gap in particle size measurements: it is capable of measuring size-resolved concentration of the aerosols in the 0.5-20 μm range (aerodynamic diameter). The APS was installed in the aerosol trailer to sample through the main stack. Special attention was given to selection of the instrument location (just below the main stack) to minimize particle losses in the connecting lines. Most atmospheric aerosols are hygroscopic, so the measurement of the aerosol size distributions should either be performed in a controlled humidity environment or accompanied by concurrent measurement of the temperature and humidity of the sample air. The latter strategy was used during this deployment: a high-precision humidity/temperature transmitter (model EE08 by E+E Elektonik GMBH, Engerwitzdorf, Germany) was mounted in the APS sampling line immediately upstream of the APS inlet. A dedicated laptop computer was used for data collection and communications. The APS was controlled with vendor-supplied software (Aerosol Instrument Manager, ver. 10.1, TSI); aerosol size distribution data were collected over a period of 55 seconds and converted to one-minute averages. Temperature and humidity analog signals were acquired via analog-to-digital converter (ADC) module (model WTAIN-M by Weeder Technologies, Fort Walton Beach, Florida) using vendor-supplied software (ModCom) with 1- sec resolution. In post-processing, the APS data were exported from TSI proprietary format into “comma-separated value” American Standard Code for Information Interchange (ASCII) files and matched with appropriately averaged temperature and humidity data. Two significant periods of missing data were caused by local power outages. Vendor-supplied software was not designed for unattended operation: it needs to be manually restarted including sensor configuration setup.

ACE-ENA, Azores, ultra-high-sensitivity aerosol sp↗
DOE OSTI2015

Consensus Guidelines and Contouring Atlas for Pelvic Node Delineation in Prostate and Pelvic Node Intensity Modulated Radiation Therapy

Purpose: The purpose of this study was to establish reproducible guidelines for delineating the clinical target volume (CTV) of the pelvic lymph nodes (LN) by combining the freehand Royal Marsden Hospital (RMH) and Radiation Therapy Oncology Group (RTOG) vascular expansion techniques. Methods and Materials: Seven patients with prostate cancer underwent standard planning computed tomography scanning. Four different CTVs (RMH, RTOG, modified RTOG, and Prostate and pelvIs Versus prOsTate Alone treatment for Locally advanced prostate cancer [PIVOTAL] trial) were created for each patient, and 6 different bowel expansion margins (BEM) were created to assess bowel avoidance by the CTV. The resulting CTVs were compared visually and by using Jaccard conformity indices. The volume of overlap between bowel and planning target volume (PTV) was measured to aid selection of an appropriate BEM to enable maximal LN yet minimal normal tissue coverage. Results: In total, 84 nodal contours were evaluated. LN coverage was similar in all groups, with all of the vascular-expansion techniques (RTOG, modified RTOG, and PIVOTAL), resulting in larger CTVs than that of the RMH technique (mean volumes: 287.3 cm{sup 3}, 326.7 cm{sup 3}, 310.3 cm{sup 3}, and 256.7 cm{sup 3}, respectively). Mean volumes of bowel within the modified RTOG PTV were 19.5 cm{sup 3} (with 0 mm BEM), 17.4 cm{sup 3} (1-mm BEM), 10.8 cm{sup 3} (2-mm BEM), 6.9 cm{sup 3} (3-mm BEM), 5.0 cm{sup 3} (4-mm BEM), and 1.4 cm{sup 3} (5-mm BEM) in comparison with an overlap of 9.2 cm{sup 3} seen using the RMH technique. Evaluation of conformity between LN-CTVs from each technique revealed similar volumes and coverage. Conclusions: Vascular expansion techniques result in larger LN-CTVs than the freehand RMH technique. Because the RMH technique is supported by phase 1 and 2 trial safety data, we proposed modifications to the RTOG technique, including the addition of a 3-mm BEM, which resulted in LN-CTV coverage similar to that of the RMH technique, with reduction in bowel and planning target volume overlap. On the basis of these findings, recommended guidelines including a detailed pelvic LN contouring atlas have been produced and implemented in the PIVOTAL trial.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

WE-G-204-07: Automated Characterization of Perceptual Quality of Clinical Chest Radiographs: Improvements in Lung, Spine, and Hardware Detection

Purpose: To develop and validate more robust methods for automated lung, spine, and hardware detection in AP/PA chest images. This work is part of a continuing effort to automatically characterize the perceptual image quality of clinical radiographs. [Y. Lin et al. Med. Phys. 39, 7019–7031 (2012)] Methods: Our previous implementation of lung/spine identification was applicable to only one vendor. A more generalized routine was devised based on three primary components: lung boundary detection, fuzzy c-means (FCM) clustering, and a clinically-derived lung pixel probability map. Boundary detection was used to constrain the lung segmentations. FCM clustering produced grayscale- and neighborhood-based pixel classification probabilities which are weighted by the clinically-derived probability maps to generate a final lung segmentation. Lung centerlines were set along the left-right lung midpoints. Spine centerlines were estimated as a weighted average of body contour, lateral lung contour, and intensity-based centerline estimates. Centerline estimation was tested on 900 clinical AP/PA chest radiographs which included inpatient/outpatient, upright/bedside, men/women, and adult/pediatric images from multiple imaging systems. Our previous implementation further did not account for the presence of medical hardware (pacemakers, wires, implants, staples, stents, etc.) potentially biasing image quality analysis. A hardware detection algorithm was developed using a gradient-based thresholding method. The training and testing paradigm used a set of 48 images from which 1920 51×51 pixel{sup 2} ROIs with and 1920 ROIs without hardware were manually selected. Results: Acceptable lung centerlines were generated in 98.7% of radiographs while spine centerlines were acceptable in 99.1% of radiographs. Following threshold optimization, the hardware detection software yielded average true positive and true negative rates of 92.7% and 96.9%, respectively. Conclusion: Updated segmentation and centerline estimation methods in addition to new gradient-based hardware detection software provide improved data integrity control and error-checking for automated clinical chest image quality characterization across multiple radiography systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Improving signal strength in serial crystallography with DIALS geometry refinement

The DIALS diffraction-modeling software package has been applied to serial crystallography data. Diffraction modeling is an exercise in determining the experimental parameters, such as incident beam wavelength, crystal unit cell and orientation, and detector geometry, that are most consistent with the observed positions of Bragg spots. These parameters can be refined by nonlinear least-squares fitting. In previous work, it has been challenging to refine both the positions of the sensors (metrology) on multipanel imaging detectors such as the CSPAD and the orientations of all of the crystals studied. Since the optimal models for metrology and crystal orientation are interdependent, alternate cycles of panel refinement and crystal refinement have been required. To simplify the process, a sparse linear algebra technique for solving the normal equations was implemented, allowing the detector panels to be refined simultaneously against the diffraction from thousands of crystals with excellent computational performance. Separately, it is shown how to refine the metrology of a second CSPAD detector, positioned at a distance of 2.5 m from the crystal, used for recording low-angle reflections. With the ability to jointly refine the detector position against the ensemble of all crystals used for structure determination, it is shown that ensemble refinement greatly reduces the apparent nonisomorphism that is often observed in the unit-cell distributions from still-shot serial crystallography. In addition, it is shown that batching the images by timestamp and re-refining the detector position can realistically model small, time-dependent variations in detector position relative to the sample, and thereby improve the integrated structure-factor intensity signal and heavy-atom anomalous peak heights.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Compilation of the ``Atlas of Gamma-rays from the Inelastic Scattering of Reactor Fast Neutrons'' (1978DE41) by A.M. Demidov, L.I. Govor, Yu. K. Cherepantsev, M.R. Ahmed, S. Al-Najjar, M.A. Al-Amili, N. Al-Assafi, and N. Rammo

A Structured Query Language (SQL) relational database has been developed based on the original (n,n'gamma) work carried out by A.M. Demidov et al., at the Nuclear Research Institute in Baghdad, Iraq [``Atlas of Gamma-Ray Spectra from the Inelastic Scattering of Reactor Fast Neutrons'', Nuclear Research Institute, Baghdad, Iraq (Moscow, Atomizdat 1978)] for 105 independent measurements comprising 76 elemental samples of natural composition and 29 isotopically-enriched samples. The information from this ATLAS includes: gamma-ray energies and intensities; nuclide and level data corresponding to where the gamma-ray originated from; target (sample) experimental-measurement data. Taken together, this information allows for the extraction of the flux-weighted (n,n'gamma) cross sections for a given transition relative to a defined value. Currently, we are using the fast-neutron flux-weighted partial gamma-ray cross section from ENDF/B-VII.1 for the production of the 847-keV transition from the first excited 2+ state to the 0+ ground state in 56Fe, 468 mb. This value also takes into account contributions to the 847-keV transition following beta(-) decay of 56Mn formed in the 56Fe(n,p) reaction. However, this value can easily be adjusted to accommodate the user preference. The (n,n'gamma) data has been compiled into a series of ASCII comma separated value tables and a suite of Python scripts and C modules are provided to build the database. Upon building, the database can then be interacted with directly via the SQLite engine or accessed via the Jupyter Notebook Python-browser interface. Several examples exploiting these utilities are also provided with the complete software package.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

TU-AB-BRA-06: Texture Feature Reproducibility Between PET/CT and PET/MR Imaging Modalities

Purpose: Radiomics involves the extraction of texture features from different imaging modalities with the purpose of developing models to predict patient treatment outcomes. The purpose of this study is to investigate texture feature reproducibility across [18F]FDG PET/CT and [18F]FDG PET/MR imaging in patients with primary malignancies. Methods: Twenty five prospective patients with solid tumors underwent clinical [18F]FDG PET/CT scan followed by [18F]FDG PET/MR scans. In all patients the lesions were identified using nuclear medicine reports. The images were co-registered and segmented using an in-house auto-segmentation method. Fifty features, based on the intensity histogram, second and high order matrices, were extracted from the segmented regions from both image data sets. One-way random-effects ANOVA model of the intra-class correlation coefficient (ICC) was used to establish texture feature correlations between both data sets. Results: Fifty features were classified based on their ICC values, which were found in the range from 0.1 to 0.86, in three categories: high, intermediate, and low. Ten features extracted from second and high-order matrices showed large ICC ≥ 0.70. Seventeen features presented intermediate 0.5 ≤ ICC ≤ 0.65 and the remaining twenty three presented low ICC ≤ 0.45. Conclusion: Features with large ICC values could be reliable candidates for quantification as they lead to similar results from both imaging modalities. Features with small ICC indicates a lack of correlation. Therefore, the use of these features as a quantitative measure will lead to different assessments of the same lesion depending on the imaging modality from where they are extracted. This study shows the importance of the need for further investigation and standardization of features across multiple imaging modalities.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

General approaches for shear-correcting coordinate transformations in Bragg coherent diffraction imaging. Part II

X-ray Bragg coherent diffraction imaging (BCDI) has been demonstrated as a powerful 3D microscopy approach for the investigation of sub-micrometre-scale crystalline particles. The approach is based on the measurement of a series of coherent Bragg diffraction intensity patterns that are numerically inverted to retrieve an image of the spatial distribution of the relative phase and amplitude of the Bragg structure factor of the diffracting sample. This 3D information, which is collected through an angular rotation of the sample, is necessarily obtained in a non-orthogonal frame in Fourier space that must be eventually reconciled. To deal with this, the approach currently favored by practitioners (detailed in Part I) is to perform the entire inversion in conjugate non-orthogonal real- and Fourier-space frames, and to transform the 3D sample image into an orthogonal frame as a post-processing step for result analysis. In this article, which is a direct follow-up of Part I, two different transformation strategies are demonstrated, which enable the entire inversion procedure of the measured data set to be performed in an orthogonal frame. The new approaches described here build mathematical and numerical frameworks that apply to the cases of evenly and non-evenly sampled data along the direction of sample rotation ( i.e. the rocking curve). The value of these methods is that they rely on the experimental geometry, and they incorporate significantly more information about that geometry into the design of the phase-retrieval Fourier transformation than the strategy presented in Part I. Finally, two important outcomes are (1) that the resulting sample image is correctly interpreted in a shear-free frame and (2) physically realistic constraints of BCDI phase retrieval that are difficult to implement with current methods are easily incorporated. Computing scripts are also given to aid readers in the implementation of the proposed formalisms.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Complex-valued universal linear transformations and image encryption using spatially incoherent diffractive networks

As an optical processor, a diffractive deep neural network (D2NN) utilizes engineered diffractive surfaces designed through machine learning to perform all-optical information processing, completing its tasks at the speed of light propagation through thin optical layers. With sufficient degrees of freedom, D2NNs can perform arbitrary complex-valued linear transformations using spatially coherent light. Similarly, D2NNs can also perform arbitrary linear intensity transformations with spatially incoherent illumination; however, under spatially incoherent light, these transformations are nonnegative, acting on diffraction-limited optical intensity patterns at the input field of view. Here, we expand the use of spatially incoherent D2NNs to complex-valued information processing for executing arbitrary complex-valued linear transformations using spatially incoherent light. Through simulations, we show that as the number of optimized diffractive features increases beyond a threshold dictated by the multiplication of the input and output space-bandwidth products, a spatially incoherent diffractive visual processor can approximate any complex-valued linear transformation and be used for all-optical image encryption using incoherent illumination. The findings are important for the all-optical processing of information under natural light using various forms of diffractive surface-based optical processors.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Stride search: A general algorithm for storm detection in high-resolution climate data

This study discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared: the commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. The Stride Search algorithm is defined independently of the spatial discretization associated with a particular data set. Results from the two algorithms are compared for the application of tropical cyclone detection, and shown to produce similar results for the same set of storm identification criteria. Differences between the two algorithms arise for some storms due to their different definition of search regions in physical space. The physical space associated with each Stride Search region is constant, regardless of data resolution or latitude, and Stride Search is therefore capable of searching all regions of the globe in the same manner. Stride Search's ability to search high latitudes is demonstrated for the case of polar low detection. Wall clock time required for Stride Search is shown to be smaller than a grid point search of the same data, and the relative speed up associated with Stride Search increases as resolution increases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Application of Multivariate Data Analysis Techniques for the Portable Isotopic Neutron Spectroscopy system

The Portable Isotopic Neutron Spectroscopy (PINS) is a commercialized system developed by Idaho National Laboratory (INL) to examine chemical compounds non-destructively, utilizing Prompt Gamma Neutron Activation Analysis (PGNAA) techniques. The PINS systems have been successfully deployed around the world to identify chemical munitions and containers. The PINS system takes advantage of a high-resolution gamma-ray spectrum from a high-purity germanium (HPGe) detector, and gamma-ray peak analysis provides input to its chemical identification logic with the probabilistic decision tree (PDT). Gamma-ray peak analyses, however, require knowledge of pre-selected gamma-ray peaks whose energies, intensities, and origins are well studied, and some peaks might be excluded from the decision making processes due to lack of current nuclear data. In contrast, Multivariate Analysis (MVA) treats a whole gamma-ray spectrum as a collection of multiple variables or a pattern. The effectiveness of chemical identification algorithm is determined by the availability of a wide range of data to train an algorithm to identify chemical fills with accuracy. INL has a collection of gamma-ray spectra of various chemical-fills from the field-deployed PINS systems over the years, and it was envisaged to combine such a database with the principle of multivariate statistics. Therefore, in parallel with the current decision tree algorithm, an MVA-based chemical identification algorithm was developed as an independent verification of the current results. The Principal Component Analysis (PCA) method was adopted to build an MVA-based identification algorithm, using the collected field data to refine and validate the algorithm. A benchmarking study of the MVA-based algorithm’s performance was conducted alongside the current algorithm, with the results presented and discussed in this study.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Global Carbon Budget 2018

Accurate assessment of anthropogenic carbon dioxide ( CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components ofthe global carbon budget and their uncertainties. Fossil CO 2 emissions ( E FF ) are based on energy statistics and cement production data, while emissions from land use and land-use change ( E LUC ), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO 2 concentration is measured directly and its growth rate ( G ATM ) is computed from the annual changes in concentration. The ocean CO 2 sink ( S OCEAN ) and terrestrial CO 2 sink ( S LAND ) are estimated with global process models constrained by observations. The resulting carbon budget imbalance ( B IM ), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1 σ . For the last decade available (2008–2017), E FF was 9.4±0.5 GtC yr -1 , E LUC 1.5±0.7 GtC yr -1 , G ATM 4.7±0.02 GtC yr -1 , S OCEAN 2.4±0.5 GtC yr -1 , and S LAND 3.2±0.8 GtC yr -1 , with a budget imbalance B IM of0.5 GtC yr -1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in E FF was about 1.6 %and emissions increased to 9.9±0.5 GtC yr -1 . Also for 2017, E LUC was 1.4±0.7 GtC yr -1 , G ATM was 4.6±0.2 GtC yr -1 , S OCEAN was 2.5±0.5 GtC yr -1 , and S LAND was 3.8±0.8 GtC yr -1 ,with a B IM of 0.3 GtC. The global atmospheric CO 2 concentration reached 405.0±0.1 ppm averaged over 2017.For 2018, preliminary data for the first 6–9 months indicate a renewed growth in E FF of + 2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017,but discrepancies of up to 1 GtC yr -1 persist for the representation of semi-decadal variability in CO 2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO 2 flux in the northern extra-tropics,and (3) an apparent underestimation of the CO 2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016,2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018 .

54 ENVIRONMENTAL SCIENCES↗