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DOE OSTI2019

Caveat regarding CMS Merit-based Incentive Payment Systems incidental adrenal nodule measure

Current Medicare MIP measures encourage radiologists not to recommend follow-up for ≤ 1 cm adrenal nodules. However, a radiologist may be the first to discover a small, subclinical pheochromocytoma. As such, recognition of the enhancement pattern of pheochromocytoma is important to ensure detection and properly guide management, which begins with clinical and laboratory assessment for elevated catecholamines.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2019

On the measurement of dislocations and dislocation substructures using EBSD and HRSD techniques

The accumulation of the dislocations and development of dislocation structures in plastically deformed Ni201 is examined using dedicated analyses of Electron Back-Scatter Diffraction (EBSD) acquired orientation maps, and High-Resolution Synchrotron Diffraction (HRSD) acquired patterns. The results show that the minimum detectable microstructure-averaged (bulk) total dislocation density ($ρ_T$) measured via HRSD is approximately 1E13 m -2 , while the minimum GND density ($ρ_G$) measured via EBSD is approximately 2E12 m -2 - the EBSD technique being more sensitive at low plastic strain. This highlights complementarity of the two techniques when attempting to quantify amount of plastic deformation (damage) in a material via a measurement of present dislocations and their structures. Furthermore, a relationship between EBSD-measured $ρ_G$ and the size of HRSD-measured Coherently Scattering Domains (CSDs) has been mathematically derived - this allows for an estimation of the size of CSDs from EBSD-acquired orientation maps, and conversely an estimation of $ρ_G$ from HRSD-measured size of CSDs. The measured evolution of ($ρ_T$), and $ρ_G$ is compared with plasticity theory models - the current results suggest that Ashby's single-slip model underestimates the amount of ONDs ($ρ_G$), while Taylor's model is correctly predicting the total amount of dislocation ($ρ_T$) present in the material as a function of imparted plastic strain.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Thirty-four years of Hawaii wave hindcast from downscaling of climate forecast system reanalysis

The complex wave climate of Hawaii includes a mix of seasonal swells and wind waves from all directions across the Pacific. Numerical hindcasting from surface winds provides essential space-time information to complement buoy and satellite observations for studies of the marine environment. We utilize WAVEWATCH III and SWAN (Simulating WAves Nearshore) in a nested grid system to model basin-wide processes as well as high-resolution wave conditions around the Hawaiian Islands from 1979 to 2013. The wind forcing includes the Climate Forecast System Reanalysis (CFSR) for the globe and downscaled regional winds from the Weather Research and Forecasting (WRF) model. Long-term in-situ buoy measurements and remotely-sensed wind speeds and wave heights allow thorough assessment of the modeling approach and data products for practical application. The high-resolution WRF winds, which include orographic and land-surface effects, are validated with QuickSCAT observations from 2000 to 2009. The wave hindcast reproduces the spatial patterns of swell and wind wave events detected by altimeters on multiple platforms between 1991 and 2009 as well as the seasonal variations recorded at 16 offshore and nearshore buoys around the Hawaiian Islands from 1979 to 2013. The hindcast captures heightened seas in interisland channels and around prominent headlands, but tends to overestimate the heights of approaching northwest swells and give lower estimates in sheltered areas. Finally, the validated high-resolution hindcast sets a baseline for future improvement of spectral wave models.

16 TIDAL AND WAVE POWER↗

DOE OSTI2022

First Synoptic Images of FUV Discrete Aurora and Discovery of Sinuous Aurora at Mars by EMM EMUS

Abstract We present the first measurements of Mars discrete aurora in the extreme ultraviolet (<110 nm) and the first synoptic aurora images in the far ultraviolet (110–180 nm). Auroral emission is detected in >75% of nightside images, with patterns shifting visibly over 15–20 min. Aurora is observed most frequently in regions of open magnetic topology (where crustal magnetic fields are very weak and/or vertical), with the brightest aurora where crustal fields are strongest. We present the first disk‐averaged spectrum of discrete aurora, with several O, C, and CO features as expected for electron impact primarily on CO 2 . We categorize discrete auroral morphology into three types: crustal field aurora, non‐crustal field patchy aurora, and a new type we call “sinuous” aurora, an elongated serpentine structure that stretches thousands of kilometers into the nightside from near midnight in the northern hemisphere. These observations point to a highly dynamic environment in Mars' magnetotail.

Lillis, Robert J.↗

DOE OSTI2017

Efficient laser-driven proton acceleration from cylindrical and planar cryogenic hydrogen jets

We report on recent experimental results deploying a continuous cryogenic hydrogen jet as a debris-free, renewable laser-driven source of pure proton beams generated at the 150 TW ultrashort pulse laser Draco. Efficient proton acceleration reaching cut-off energies of up to 20 MeV with particle numbers exceeding 109 particles per MeV per steradian is demonstrated, showing for the first time that the acceleration performance is comparable to solid foil targets with thicknesses in the micrometer range. Two different target geometries are presented and their proton beam deliverance characterized: cylindrical (Ø 5 μm) and planar (20 μm × 2 μm). In both cases typical Target Normal Sheath Acceleration emission patterns with exponential proton energy spectra are detected. Significantly higher proton numbers in laser-forward direction are observed when deploying the planar jet as compared to the cylindrical jet case. As a result, this is confirmed by two-dimensional Particle-in-Cell (2D3V PIC) simulations, which demonstrate that the planar jet proves favorable as its geometry leads to more optimized acceleration conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

First step toward a synthetic diagnostic for magnetic fluctuation measurements using cross-polarization scattering on DIII-D

Cross-polarization scattering (CPS) provides localized magnetic fluctuation ($\tilde{B}$) measurements in fusion plasmas based on the process where $\tilde{B}$ scatters electromagnetic radiation into the orthogonal polarization. The CPS system on DIII-D utilizes the probe beam of a Doppler backscattering (DBS) diagnostic combined with a cross-view CPS receiver system, which allows simultaneous density and $\tilde{B}$ measurements with good spatial and wavenumber coverage. The interpretation of the signals is challenging due to the complex plasma propagation of the DBS probe beam and CPS receive beams. A synthetic diagnostic for CPS is therefore essential to interpret data and perform detailed validation tests of non-linear turbulence simulations. This work reports a first step toward a synthetic diagnostic for CPS utilizing GENRAY, a 3-D ray tracing code, to simulate the propagation of the probe and scattered rays. The local $\tilde{B}$ wavenumber is calculated from the local O- and X-mode wavenumbers using the wave vector matching scattering condition. The CPS wavenumber values and spatial locations are determined by a complex consideration that includes the local density and $\tilde{B}$ level, receive antenna pattern and orientation, scattering volume, wavenumber values detected at the various scattering centers, and alignment of the magnetic wave vector with the plane perpendicular to the magnetic field. The issue of a spurious CPS signal due to polarization mismatches for launch and receive is also discussed. It is suggested that simultaneous O- and X-mode DBS measurements should be utilized for better understanding of the CPS signal contamination when the cutoff locations for both polarizations are close.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

A GENERAL RELATIVISTIC NULL HYPOTHESIS TEST WITH EVENT HORIZON TELESCOPE OBSERVATIONS OF THE BLACK HOLE SHADOW IN Sgr A*

The half opening angle of a Kerr black hole shadow is always equal to (5 ± 0.2)GM/Dc{sup 2}, where M is the mass of the black hole and D is its distance from the Earth. Therefore, measuring the size of a shadow and verifying whether it is within this 4% range constitutes a null hypothesis test of general relativity. We show that the black hole in the center of the Milky Way, Sgr A*, is the optimal target for performing this test with upcoming observations using the Event Horizon Telescope (EHT). We use the results of optical/IR monitoring of stellar orbits to show that the mass-to-distance ratio for Sgr A* is already known to an accuracy of ∼4%. We investigate our prior knowledge of the properties of the scattering screen between Sgr A* and the Earth, the effects of which will need to be corrected for in order for the black hole shadow to appear sharp against the background emission. Finally, we explore an edge detection scheme for interferometric data and a pattern matching algorithm based on the Hough/Radon transform and demonstrate that the shadow of the black hole at 1.3 mm can be localized, in principle, to within ∼9%. All these results suggest that our prior knowledge of the properties of the black hole, of scattering broadening, and of the accretion flow can only limit this general relativistic null hypothesis test with EHT observations of Sgr A* to ≲10%.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Genomic Signatures of a Major Adaptive Event in the Pathogenic Fungus Melampsora larici-populina

The recent availability of genome-wide sequencing techniques has allowed systematic screening for molecular signatures of adaptation, including in nonmodel organisms. Host–pathogen interactions constitute good models due to the strong selective pressures that they entail. We focused on an adaptive event which affected the poplar rust fungus Melampsora larici-populina when it overcame a resistance gene borne by its host, cultivated poplar. Based on 76 virulent and avirulent isolates framing narrowly the estimated date of the adaptive event, we examined the molecular signatures of selection. Using an array of genome scan methods based on different features of nucleotide diversity, we detected a single locus exhibiting a consistent pattern suggestive of a selective sweep in virulent individuals (excess of differentiation between virulent and avirulent samples, linkage disequilibrium, genotype–phenotype statistical association, and long-range haplotypes). Our study pinpoints a single gene and further a single amino acid replacement which may have allowed the adaptive event. Although our samples are nearly contemporary to the selective sweep, it does not seem to have affected genome diversity further than the immediate vicinity of the causal locus, which can be explained by a soft selective sweep (where selection acts on standing variation) and by the impact of recombination in mitigating the impact of selection. Therefore, it seems that properties of the life cycle of M. larici-populina, which entails both high genetic diversity and outbreeding, has facilitated its adaptation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Pushing the limits of electron ptychography

Here, ptychographic imaging in transmission electron microscopy is based on the detection of a huge number of diffraction patterns generated as an electron-beam probe scans the sample. Unlike conventional diffraction experiments where information about the phase of the scattered beam is lost, by scanning the entire sample and recording the diffraction patterns, an inversion analysis can reconstruct the complex amplitude of the beam and ultimately the atomic positions. Probe beams continue to decrease in size and can be much smaller than the distance between scatterers. The diffraction spots also broaden and interfere with one another (see the figure). Analysis of this interference allows more information to be extracted, such as minute details of nuclei position and electronic structure that define physical properties and enable visualization of subtle details of electric fields, orbital orderings, ferroic behavior, and perhaps local spins. Ptychography and related techniques are poised to revolutionize the field of electron microscopy, in much the same way as they have in x-ray crystallography (1), and as aberration correction has achieved for imaging, provided that some key challenges can be met.

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

Quantum Cascade Laser Infrared Spectroscopy for Online Monitoring of Hydroxylamine Nitrate

We describe a new approach for high sensitivity and real-time online measurements to monitor the kinetics in the processing of nuclear materials and other chemical reactions. Mid infrared (Mid-IR) quantum cascade laser (QCL) high-resolution spectroscopy was used for rapid and continuous sampling of nitrates in aqueous and organic reactive systems, using pattern recognition analysis and high sensitivity to detect and identify chemical species. In this standoff or off-set method, the collection of a sample for analysis is not required. To perform the analysis, a flow cell was used for in situ sampling of a liquid slipstream. A prototype was designed based on attenuated total reflection (ATR) coupled with the QCL beam to detect and identify chemical changes and be deployed in hostile environments, either radiological or chemical. The limit of detection (LOD) and the limit of quantification (LOQ) at 3 σ for hydroxylamine nitrate ranged from 0.3 to 3 and from 3.5 to 10 g·L −1 , respectively, for the nitrate system at three peaks with wavelengths between 3.8 and 9.8 μ m.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Investigating Biochemical and Developmental Dependencies of Lignification with a Click-Compatible Monolignol Analog in Arabidopsis thaliana Stems

Lignin is a key structural component of plant cell walls that provides rigidity, strength, and resistance against microbial attacks. This hydrophobic polymer also serves a crucial role in water transport. Despite its abundance and essential functions, several aspects of lignin biosynthesis and deposition remain cryptic. Lignin precursors are known to be synthesized in the cytoplasm by complex biosynthetic pathways, after which they are transported to the apoplastic space, where they are polymerized via free radical coupling reactions into polymeric lignin. However, the lignin deposition process and the factors controlling it are unclear. In this study, the biochemical and developmental dependencies of lignification were investigated using a click-compatible monolignol analog, 3-O-propargylcaffeyl alcohol (3-OPC), which can incorporate into both in vitro polymerized lignin and Arabidopsis thaliana tissues. Fluorescence labeling of 3-OPC using click chemistry followed by confocal fluorescence microscopy enabled the detection and imaging of 3-OPC incorporation patterns. These patterns were consistent with endogenous lignification observed in different developmental stages of Arabidopsis stems. However, the concentration of supplied monolignols influenced where lignification occurred at the subcellular level, with low concentrations being deposited in cell corners and middle lamellae and high concentrations also being deposited in secondary walls. Experimental inhibition of multiple lignification factors confirmed that 3-OPC incorporation proceeds via a free radical coupling mechanism involving peroxidases/laccases and reactive oxygen species (ROS). Finally, the presence of peroxide-producing enzymes determined which cell walls lignified: adding exogenous peroxide and peroxidase caused cells that do not naturally lignify in Arabidopsis stems to lignify. In conclusion, 3-OPC accurately mimics natural lignification patterns in different developmental stages of Arabidopsis stems and allows for the dissection of key biochemical and enzymatic factors controlling lignification.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

An approach to online network monitoring using clustered patterns

Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regard to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Gravitational wave signals of electroweak phase transition triggered by dark matter

We study in this work a scenario that the universe undergoes a two step phase transition with the first step happened to the dark matter sector and the second step being the transition between the dark matter and the electroweak vacuums, where the barrier between the two vacuums, that is necessary for a strongly first order electroweak phase transition (EWPT) as required by the electroweak baryogenesis mechanism, arises at the tree-level. We illustrate this idea by working with the standard model (SM) augmented by a scalar singlet dark matter and an extra scalar singlet which mixes with the SM Higgs boson. We study the conditions for such pattern of phase transition to occur and especially for the strongly first order EWPT to take place, as well as its compatibility with the basic requirements of a successful dark matter, such as observed relic density and constraints of direct detections. We further explore the discovery possibility of this pattern EWPT by searching for the gravitational waves generated during this process in spaced based interferometer, by showing a representative benchmark point of the parameter space that the generated gravitational waves fall within the sensitivity of eLISA, DECIGO and BBO.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Exploring Continuous Seismic Data at an Industry Facility Using Unsupervised Machine Learning

Seismic data recorded at industrial sites contain valuable information on anthropogenic activities. With advances in machine learning and computing power, new opportunities have emerged to explore the seismic wavefield in these complex environments. We applied two unsupervised machine learning algorithms to analyze continuous seismic data collected from an industrial facility in Texas, United States. The Uniform Manifold Approximation and Projection for Dimension Reduction algorithm was used to reduce the dimensionality of the data and generate 2D embeddings. Then, the Hierarchical Density-Based Spatial Clustering of Applications with Noise method was employed to automatically group these embeddings into distinct signal clusters. Our analysis of over 1400 hr (around 59 days) of continuous seismic data revealed five and seven signal clusters at two separate stations. At both stations, we identified clusters associated with background noise and vehicle traffic, with the latter’s temporal patterns aligning closely with the facility’s work schedule. Furthermore, the algorithms detected signal clusters from unknown sources and underline the ability of unsupervised machine learning for uncovering previously unrecognized patterns. Our analysis demonstrates the effectiveness of unsupervised approaches in examining continuous seismic data without requiring prior knowledge or pre-existing labels.

58 GEOSCIENCES↗

DOE OSTI2018

Pattern-based Modeling of Multiresilience Solutions for High-Performance Computing

Resiliency is the ability of large-scale high-performance computing (HPC) applications to gracefully handle errors, and recover from failures. In this paper, we propose a pattern-based approach to constructing resilience solutions that handle multiple error modes. Using resilience patterns, we evaluate the performance and reliability characteristics of detection, containment and mitigation techniques for transient errors that cause silent data corruptions and techniques for fail-stop errors that result in process failures. We demonstrate the design and implementation of the multiresilience solution based on patterns instantiated across multiple layers of the system stack. The patterns are integrated to work together to achieve resiliency to different error types in a performance-efficient manner.

Ashraf, Rizwan↗

DOE OSTI2022

A Qualitative Strategy for Fusion of Physics into Empirical Models for Process Anomaly Detection

To facilitate the automated online monitoring of power plants, a systematic and qualitative strategy for anomaly detection is presented. This strategy is essential to provide credible reasoning on why and when an empirical versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. Empirical methods are usually based on pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The presented strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability, and suitability for training and testing, cause-effect, entropy inference, and model fitting. The strategy is demonstrated through a pilot use case for the application of anomaly detection to capture a valve packing leak at the high-pressure coolant injection system of a nuclear power plant.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Nonlocal metasurface for circularly polarized light detection

Modern-day sensing and imaging applications increasingly rely on accurate measurements of the primary physical quantities associated with light waves: intensity, wavelength, directionality, and polarization. These are conventionally performed with a series of bulky optical elements, but recently, it has been recognized that optical resonances in nanostructures can be engineered to achieve selective photodetection of light waves with a specific set of predetermined properties. Here, we theoretically illustrate how a thin silicon layer can be patterned into a dislocated nanowire-array that affords detection of circularly polarized light with an efficiency that reaches the theoretical limit for circular dichroism of a planar detector in a symmetric external environment. The presence of a periodic arrangement of dislocations is essential in achieving such unparalleled performance as they enable selective excitation of nonlocal, guided-mode resonances for one handedness of light. We also experimentally demonstrate compact, high-performance chiral photodetectors created from these dislocated nanowire-arrays. This work highlights the critical role defects can play in enabling new nanophotonic functions and devices.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Performance of Advanced Signal Processing and Pattern Recognition Algorithms Using Raw Data from Ultrasonic Guided Waves and Fiber Optics Transducers

The Light Water Reactor Sustainability Program was initiated to evaluate technologies that could be used to perform online monitoring of piping and other secondary system structural components in commercial nuclear power plants. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real-time measurements, rather than at a pre-determined inspection interval. This transition to condition-based, risk-informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for most nuclear power generation costs. This report describes the current state of research related to ultrasonic guided wave testing and its application to detecting defects in commercial nuclear power plants. The report analyzes the applicability of the guided wave technology to secondary piping systems, as well as studying the potential for expanding the range of guided wave technology to include bent piping and other piping components. The ultrasonic guided waves can inspect long stretches of straight piping; however, more complex geometries such as elbows, welds, and tees are causing spurious reflections and coherent noise, which significantly decreases the sensitivity of the technique. To deal with these limitations, high-definition fiber optic sensors are applied to complex piping geometries, and advanced machine learning algorithms are used to detect deviations from healthy states. This report also analyzes the performance of advanced signal processing and machine learning-based pattern recognition algorithms in detecting defects in secondary structures. It is demonstrated on guided wave data collected at nuclear power plants that the independent component analysis can separate different coherent noise components and segregate them from useful signals. It also demonstrates that advanced machine learning techniques, such as neural networks, support vector machines, and deep learning networks, can detect minor defects present in inspected structures. Recommendation about the applicability of advanced machine learning techniques to online piping monitoring are also given.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗