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At least 1,225 records · Page 68

Retrospective Imaging and Characterization of Nuclear Material

Modern techniques for detection of covert nuclear ma-terial requires some combination of real time measurement and/or sampling of the material. More common is real time measure-ment of the ionizing emission caused by radioactive decay or through the materials measured in response to external interroga-tion radiation. One can expose the suspect material with various radiation types, including high energy photons such as x rays or with larger particles such as neutrons and muons, to obtain images or measure nuclear reactions induced in the material. Stand-off detection using imaging modalities similar to those in the medical field can be accomplished, or simple collimated detec-tors can be used to localize radioactive materials. In all such cases, the common feature is that some or all of the nuclear materials have to be present for the measurement, which makes sense; as one might ask, “How you can measure something that is not there?” The current work and results show how to do exactly that: characterize nuclear materials after they have been removed from an area leaving no chemical trace. This new approach is demon-strated to be fully capable of providing both previous source spa-tial distribution and emission energy grouping. The technique uses magnetic resonance for organic insulators and/or lumines-cence techniques on ubiquitous refractory materials similar in theory to the way the nuclear industry carries out worker person-nel dosimetry. Spatial information is obtained by acquiring gridded samples for dosimetric measurements, while energy infor-mation comes through dose depth profile results that are func-tions of the incident radiation energies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Workflow for Visual Diagnostics of Binary Classifiers using Instance-Level Explanations

In this paper, we propose a visual analytics workflow to help data scientists explore, diagnose, and understand the decisions made by a binary classifier. The approach leverages “instance-level explanations”, measures of local feature relevance that explain single instances and uses them to build a set of visual representations that guide the users in their investigation. The workflow is based on three main visual representations and steps: one based on aggregate statistics to see how data distributes across correct or incorrect decisions; one based on explanations to understand which features are used to make these decisions; and one based on raw data, to derive insights on potential root causes for the observed patterns. The work is validated through a long-term collaboration with a group of healthcare professionals who used our method to make sense of machine learning models they developed. The case studies from this collaboration demonstrate that the proposed method helps experts derive useful knowledge about the model and the phenomena it describes and also generates useful hypotheses on how a model can be improved.

Krause, Josua↗

System and method for identifying, reporting, and evaluating presence of substance

A system and method for identifying, reporting, and evaluating a presence of a solid, liquid, gas, or other substance of interest, particularly a dangerous, hazardous, or otherwise threatening chemical, biological, or radioactive substance. The system comprises one or more substantially automated, location self-aware remote sensing units; a control unit; and one or more data processing and storage servers. Data is collected by the remote sensing units and transmitted to the control unit; the control unit generates and uploads a report incorporating the data to the servers; and thereafter the report is available for review by a hierarchy of responsive and evaluative authorities via a wide area network. The evaluative authorities include a group of relevant experts who may be widely or even globally distributed.

47 OTHER INSTRUMENTATION↗

Time-fractional Gardner equation for ion-acoustic waves in negative-ion-beam plasma with negative ions and nonthermal nonextensive electrons

Nonlinear propagation of ion-acoustic waves is investigated in a one-dimensional, unmagnetized plasma consisting of positive ions, negative ions, and nonthermal electrons featuring Tsallis distribution that is penetrated by a negative-ion-beam. The classical Gardner equation is derived to describe nonlinear behavior of ion-acoustic waves in the considered plasma system via reductive perturbation technique. We convert the classical Gardner equation into the time-fractional Gardner equation by Agrawal's method, where the time-fractional term is under the sense of Riesz fractional derivative. Employing variational iteration method, we construct solitary wave solutions of the time-fractional Gardner equation with initial condition which depends on the nonlinear and dispersion coefficients. The effect of the plasma parameters on the compressive and rarefactive ion-acoustic solitary waves is also discussed in detail.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Additional Data Focused on Phase 1 Geared Toward Computational Fluid Dynamics (CFD) validation

A new validation campaign was developed within the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) to better understand the complex interactions between components of a floating wind system (e.g., columns, pontoons, etc.) in a more generic sense, and to validate modeling approaches for a variety of floating designs. A set of cylinders based on the Offshore Code Comparison Collaboration Continuation (OC4)-DeepCwind semidesign were tested under wave loading, both individually and in different combinations (including the attachment of heave plates of different sizes). The cylinders were held rigid, and pressure sensors were used to measure the distributed loading on the structures, while load cells measured the total integrated hydrodynamic loads.

17 WIND ENERGY↗

A Physical Protection Systems Test Bed for International Counter-Trafficking System Development

Physical protection systems have a widespread impact on the nuclear industry in areas such as nuclear safeguards, arms control, and trafficking of illicit goods (e.g., nuclear materials) across international borders around the world. Many challenges must be overcome in design and deployment of foreign border security systems such as lack of infrastructure, extreme environmental conditions, limited knowledge of terrain, insider threats, and occasional cultural resistance. Successful security systems, whether it be a system designed to secure a single facility or a whole border security system, rely on the entire integrated system composed of multiple subsystems. This test bed is composed of many unique sensors and subsystems, including wireless unattended ground sensors, a buried fiber-optic acoustic sensor, a lossy coaxial distributed sensor, wireless links, pan-tilt-zoom cameras, mobile power generation systems, unmanned aerial vehicles, and fiber-optic-fence intrusion detection systems. A Common Operating Picture software architecture is utilized to integrate a number of these subsystems. We are currently performance testing each system for border security and perimeter security applications by examining metrics such as probability of sense and a qualitative understanding of the sensor s vulnerability of defeat. The testing process includes different soil conditions for buried sensors (e.g., dry, wet, and frozen) and an array of different tests including walking, running, stealth detection, and vehicle detection. Also, long term sustainability of systems is tested including performance differences due to seasonal variations (e.g. summer versus winter, while raining, in foggy conditions). The capabilities of the test bed are discussed. Performance testing results, both at the individual component level and integrated into a larger system for a specific deployment (in situ), help illustrate the usefulness and need for integrated testing facilities to carry out this mission. The test bed provides access to grassy fields, wooded areas, and a large waterway three distinct testing environments. The infrastructure supporting deployment of systems at the test bed includes grid power, renewable power systems, climate controlled enclosures, high bandwidth wireless links, and a fiber optic communications backbone. With over 10 acres of dedicated area and direct waterway access, the test bed is well suited for long term test and evaluation of physical protection and security systems targeting a wide range of applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Method and apparatus for controlling LCL converters using asymmetric voltage cancellation techniques

A method and apparatus for LCL resonant converter control utilizing Asymmetric Voltage Cancellation is described. The methods to determine the optimal trajectory of the control variables are discussed. Practical implementations of sensing load parameters are included. Simple PI, PID and fuzzy logic controllers are included with AVC for achieving good transient response characteristics with output current regulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Simple and Accurate Energy-Detector-Based Transient Waveform Detection for Smart Grids: Real-World Field Data Performance

Integration of distributed energy sources, advanced meshed operation, sensors, automation, and communication networks all contribute to autonomous operations and decision-making processes utilized in the grid. Therefore, smart grid systems require sophisticated supporting structures. Furthermore, rapid detection and identification of disturbances and transients are a necessary first step towards situationally aware smart grid systems. This way, high-level monitoring is achieved and the entire system kept operational. Even though smart grid systems are unavoidably sophisticated, low-complexity algorithms need to be developed for real-time sensing on the edge and online applications to alert stakeholders in the event of an anomaly. In this study, the simplest form of anomaly detection mechanism in the absence of any a priori knowledge, namely, the energy detector (also known as radiometer in the field of wireless communications and signal processing), is investigated as a triggering mechanism, which may include automated alerts and notifications for grid anomalies. In contrast to the mainstream literature, it does not rely on transform domain tools; therefore, utmost design and implementation simplicity are attained. Performance results of the proposed energy detector algorithm are validated by real power system data obtained from the DOE/EPRI National Database of power system events and the Grid Signature Library.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Mechanical Actuation via Homeomorphic Transformations of Topological Solitons within Polymer Coatings

Abstract Topological solitons are currently under investigation for their exotic properties, especially in nonlinear physics, optics, and material sciences. However, challenges of robust generation and limited stability over time have hindered their practical uses. To address this issue, an approach is developed to form structured arrays of solitons in films of polymerizable liquid crystals. Their complex molecular architecture is preserved by in situ photopolymerization forming a stable liquid crystal network. Most excitingly, their properties are advanced to include responsiveness functions. When thermally actuated, these topological solitons mediate the reconfiguration of surface topographies. Complex shape changes occur depending on the intrinsic complex spatial distribution of the director, which may even lead to full shape inversion and topographical changes as high as ≈40% of the initial thickness. Conversely, the shape changes provide information on the initial director profile, which is consistent with the mathematical model. The soliton‐containing polymer coatings are applicable in multiple domains, ranging from tunable optics to haptics, and from shape‐coupled sensing systems to temperature‐coupled heat management.

36 MATERIALS SCIENCE↗

PSelInv – A distributed memory parallel algorithm for selected inversion: The non-symmetric case

This paper generalizes the parallel selected inversion algorithm called PSelInv to sparse non-symmetric matrices. We assume a general sparse matrix A has been decomposed as $PAQ$ = $LU$ on a distributed memory parallel machine, where L, U are lower and upper triangular matrices, and P, Q are permutation matrices, respectively. The PSelInvmethod computes selected elements of $A$ -1 . The selection is confined by the sparsity pattern of the matrix A T . Here our algorithm does not assume any symmetry properties of A, and our parallel implementation is memory efficient, in the sense that the computed elements of $A$ -T overwrites the sparse matrix $L + U$ in situ . PSelInv involves a large number of collective data communication activities within different processor groups of various sizes. In order to minimize idle time and improve load balancing, tree-based asynchronous communication is used to coordinate all such collective communication. Numerical results demonstrate that PSelInv can scale efficiently to 6,400 cores for a variety of matrices.

97 MATHEMATICS AND COMPUTING↗

Cryo-STEM Tomography with Inpainting

Traditionally, microscopists have worked with the Nyquist-Shannon theory of sampling, which states that to be able to reconstruct the image fully it needs to be sampled at a rate of at least twice the highest spatial frequency in the image. This sampling rate assumes that the image is sampled at regular intervals and that every pixel contains information that is crucial for the image (it even assumes that noise is important). Images in general, and especially low dose S/TEM images, contain significantly less information than can be encoded by a grid of pixels (which is why image compression works). Mathematically speaking, the image data has a low dimensional or sparse representation. Through the application of compressive sensing methods [1,2,3] this representation can be found using pre-designed measurements that are usually random for implementation simplicity. These measurements and the compressive sensing reconstruction algorithms have the added benefit of reducing noise. This reconstruction approach can be extended into higher dimensions, whereby the random sampling in each 2-D image can be extended into: a sequence of tomographic projections (i.e. tilt images); a sequence of video frames (i.e. incorporating temporal resolution and dynamics); spectral resolution (i.e. energy filtering an image to see the distribution of elements); and ptychography (i.e. sampling a full diffraction image at each location in a 2-D grid across the sample). This approach has been employed experimentally for materials science samples requiring low-dose imaging [2], and can be readily applied to biological samples. Figure 1 shows the resolution possible in a complex biological system, mouse pancreatic islet beta cells [4], when tomogram slices are reconstructed using subsampling. Reducing the number of pixels (1/6 pix and 1/3*1/3) shows minimal degradation compared to the reconstructions using all pixels (all data and 1/3 tilt). Although subsampling 1/6 of the tilts (1/6 of overall dose) degrades the reconstruction to the point that the cellular structures cannot be identified. Using 1/3 of both the pixels and the tilts provides a high quality image at 1/9 the overall dose even for this most basic and rapid demonstration of the CS methods. Figure 2 demonstrates the theoretical tomogram reconstruction quality (vertical axis) as undersampling (horizontal axis) is increased; we examined subsampling pixels and tilt-angles individually and a combined approach in which both pixels and tilts are sub-sampled. Note that subsampling pixels maintains high quality reconstructions (solid lines). Using the inpainting algorithm to obtain tomograms can automatically reduce the dose applied to the system by an order of magnitude. Perhaps the best way to understand the impact is to consider that by using inpainting (and with minimal hardware changes), a sample that can normally withstand a dose of ~10 e/Å2 can potentially be imaged with an “equivalent quality” to a dose level of 103 e/Å2. To put this in perspective, this is approaching the dose level used for the most advanced images, in terms of spatial resolution, for inorganic systems. While there are issues for biological specimens beyond dose (structural complexity being the most important one), this sampling approach allows the methods that are traditionally used for materials science to be applied to biological systems [5]. References: [1] A Stevens, H Yang, L Carin et al. Microscopy 63(1), (2014), pp. 41. [2] L Kovarik, A Stevens, A Liyu et al. Appl. Phys. Lett. 109, 164102 (2016) [3] A Stevens, L Kovarik, P Abellan et al. Adv. Structural and Chemical Imaging 1(10), (2015), pp. 1. [4] MD Guay, W Czaja, MA Aronova et al. Scientific Reports 6, 27614 (2016) [5] Supported by the Chemical Imaging, Signature Discovery, and Analytics in Motion Initiatives at PNNL. PNNL is operated by Battelle Memorial Inst. for the US DOE; contract DE-AC05-76RL01830.

Stevens, Andrew↗

Absolute magneto-optical measurement of magnetic field on a long pulse high electrical current driven solenoid

We describe a direct absolute magneto-optical approach to measuring the magnetic field driven by long pulse width (>5 ms) and high electrical current (∼kA) in a solenoidal coil. The magnetic field and electrical current are among the most important operating parameters in lightning research and electrical power distribution and are essential to understanding the properties of the radiation output in pulsed energy accelerators as well as other research platforms. However, accurately measuring these magnetic fields and electrical currents using conventional electrical diagnostics is difficult due to the strength of ionizing radiation and electromagnetic interference. Our approach uses a fiber coupled laser beam with a rare earth element material sensing crystal that is highly resistant to electromagnetic interference, allows for absolute measurement, and does not require an external calibration. Here, we focus on device theory, operating parameters, magneto-optical results from an experiment on a high current solenoid, and comparison with a calculation of the magnetic field and reference electrical current flowing downstream of the solenoid.

Owens, Israel [Sandia National Laboratories (SNL-N↗

Mastering Uncertainty and Risk at Multiple Time Scales in the Future Electrical Grid

Today's electrical grids enjoy a relatively clean separation of spatio-temporal scales yielding a compartmentalization of grid design, optimization, control and risk assessment allowing for the use of conventional mathematical tools within each area. In contrast, the future grid will incorporate time-intermittent renewable generation, operate via faster electrical markets, and tap the latent control capability at finer grid modeling scales; creating a fundamentally new set of couplings across spatiotemporal scales and requiring revolutionary advances in mathematics techniques to bridge these scales. One example is found in decade-scale grid expansion planning in which today's algorithms assume accurate load forecasts and well-controlled generation. Incorporating intermittent renewable generation creates fluctuating network flows at the hourly time scale, inherently linking the ability of a transmission line to deliver electrical power to hourly operational decisions. New operations-based planning algorithms are required, creating new mathematical challenges. Spatio-temporal scales are also crossed when the future grid's minute-scale fluctuations in network flows (due to intermittent generation) create a disordered state upon which second-scale transient grid dynamics propagate effectively invalidating today's on-line dynamic stability analyses. Addressing this challenge requires new on-line algorithms that use large data streams from new grid sensing technologies to physically aggregate across many spatial scales to create responsive, data-driven dynamic models. Here, we sketch the mathematical foundations of these problems and potential solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Defining the layers of a sensory cilium with STORM and cryoelectron nanoscopy

Primary cilia carry out numerous signaling and sensory functions, and defects in them, “ciliopathies,” cause a range of symptoms, including blindness. Understanding of their nanometer-scale ciliary substructures and their disruptions in ciliopathies has been hindered by limitations of conventional microscopic techniques. In this work, we have combined cryoelectron tomography, enhanced by subtomogram averaging, with superresolution stochastic optical reconstruction microscopy (STORM) to define subdomains within the light-sensing rod sensory cilium of mouse retinas and reveal previously unknown substructures formed by resident proteins. Domains are demarcated by structural features such as the axoneme and its connections to the ciliary membrane, and are correlated with molecular markers of subcompartments, including the lumen and walls of the axoneme, the membrane glycocalyx, and the intervening cytoplasm. Within this framework, we report spatial distributions of key proteins in wild-type (WT) mice and the effects on them of genetic deficiencies in 3 models of Bardet–Biedl syndrome.

59 BASIC BIOLOGICAL SCIENCES↗

Photo-exfoliation of MoS 2 quantum dots from nanosheets: an in-situ transmission electron microscopy study

Fabrication of transition metal dichalcogenide (TMD) quantum dots (QDs) is complex and requires submerging of powders in binary solvents and the constant tuning of wavelength and pulsed frequency of light to achieve a desired reaction. Here,iInstead of liquid state photoexfoliation, we utilize infrared laser irradiation of free-standing MoS 2 flakes in transmission electron microscope (TEM) to achieve solid-state multi-level photoexfoliation of QDs. By investigating the steps involved in photochemical reaction between the surface of MoS 2 and the laser beam, we gain insight into each step of the photoexfoliation mechanism and observe high yield production of QDs, led by an inhomogeneous crystalline size distribution. Additionally, by using a laser with a lower energy than the indirect optical transition of bulk MoS 2 , we conclude that the underlying phenomena behind the photoexfoliation is from multi-photon absorption achieved at high optical outputs from the laser source. These findings provide an environmentally friendly synthesis method to fabricate QDs for potential applications in biomedicine, optoelectronics, and fluorescence sensing.

36 MATERIALS SCIENCE↗

Mariprofundus ferrooxydans PV-1 the First Genome of a Marine Fe(II) Oxidizing Zetaproteobacterium

Mariprofundus ferrooxydans PV-1 has provided the first genome of the recently discovered Zetaproteobacteria subdivision. Genome analysis reveals a complete TCA cycle, the ability to fix CO2, carbon-storage proteins and a sugar phosphotransferase system (PTS). The latter could facilitate the transport of carbohydrates across the cell membrane and possibly aid in stalk formation, a matrix composed of exopolymers and/or exopolysaccharides, which is used to store oxidized iron minerals outside the cell. Two-component signal transduction system genes, including histidine kinases, GGDEF domain genes, and response regulators containing CheY-like receivers, are abundant and widely distributed across the genome. Most of these are located in close proximity to genes required for cell division, phosphate uptake and transport, exopolymer and heavy metal secretion, flagellar biosynthesis and pilus assembly suggesting that these functions are highly regulated. Similar to many other motile, microaerophilic bacteria, genes encoding aerotaxis as well as antioxidant functionality (e.g., superoxide dismutases and peroxidases) are predicted to sense and respond to oxygen gradients, as would be required to maintain cellular redox balance in the specialized habitat where M. ferrooxydans resides. Comparative genomics with other Fe(II) oxidizing bacteria residing in freshwater and marine environments revealed similar content, synteny, and amino acid similarity of coding sequences potentially involved in Fe(II) oxidation, signal transduction and response regulation, oxygen sensation and detoxification, and heavy metal resistance. This study has provided novel insights into the molecular nature of Zetaproteobacteria.

59 BASIC BIOLOGICAL SCIENCES↗

Integrating Radio-Over-Fiber Communication System and BOTDR Sensor System

In this paper, we propose and experimentally demonstrate for the first time, the integration of a radio-over-fiber (RoF) communication system and a Brillouin optical time-domain reflectometry (BOTDR) distributed sensor system using a single optical fiber link. In this proof-of-concept integrated system, the communication system is composed of three modulation formats of quadrature phase-shift keying (QPSK), 16-quadrature amplitude modulation (16-QAM) and 64-QAM, which are modulated onto an orthogonal frequency division multiplexing (OFDM) signal. Whereas, the BOTDR sensor system is used for strain and/or temperature monitoring over the fiber distance with a spatial resolution of 5 m using a 25 km single-mode silica fiber. The error vector magnitude (EVM) is analyzed in three modulation formats in the presence of various BOTDR input pump powers. Using QPSK modulation, optimized 18 dBm sensing and 10 dBm data power, the measured EVM values with and without bandpass filter are 3.5% and 14.5%, respectively. The proposed system demonstrates a low temperature measurement error (±0.49 °C at the end of 25 km) and acceptable EVM values, which were within the 3GPP requirements. The proposed integrated system can be effectively applied for practical applications, which significantly reduces the fiber infrastructure cost by effective usage of a single optical fiber link.

42 ENGINEERING↗

A General N -Moment Normalization Method for Deriving Raindrop Size Distribution Scaling Relationships

A general drop size distribution (DSD) normalization method is formulated in terms of generalized power series relating any DSD moment to any number and combination of reference moments. This provides a consistent framework for comparing the variability of normalized DSD moments using different sets of reference moments, with no explicit assumptions about the DSD functional form (e.g., gamma). It also provides a method to derive any unknown moment plus an estimate of its uncertainty from one or more known moments, which is relevant to remote sensing retrievals and bulk microphysics schemes in weather and climate models. Herein, the approach is applied to a large dataset of disdrometer-observed and bin microphysics-modeled DSDs. As expected, the spread of normalized moments decreases as the number of reference moments is increased, quantified by the logarithmic standard deviation of the normalized moments, σ. Averaging σ for all combinations of reference moments and normalized moments of integer order 0–10, 42.9%, 81.3%, 93.7%, and 96.9% of spread are accounted for applying one-, two-, three-, and four-moment normalizations, respectively. Thus, DSDs can be well characterized overall using three reference moments, whereas adding a fourth reference moment contributes little independent information. The spread of disdrometer-observed DSD moments from uncertainty associated with drop count statistics generally lies between values of σ using two- and three-moment normalizations. However, this uncertainty has little impact on the derived DSD scaling relationships or σ when considered.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗