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At least 901 records · Page 50

BCS (Beamline Control System) v2

The software is a flexible architecture used to integrate motors, analog data, digital signals, and instruments together to control scientific experiments and collect data during an experiment. The architecture supports features needed by scientists to quickly add new hardware to an experiment and to take and view data in a meaningful way. It does not perform analysis of the data, but provides basic visualization needed to evaluate the quality of the data as well as the calibration of the system.

Cornell, Earl↗

In situ visualization of multicomponents coevolution in a battery pouch cell

Lithium-ion battery (LIB) is a broadly adopted technology for energy storage. With increasing demands to improve the rate capability, cyclability, energy density, safety, and cost efficiency, it is crucial to establish an in-depth understanding of the detailed structural evolution and cell-degradation mechanisms during battery operation. Here, we present a laboratory-based high-resolution and high-throughput X-ray micro–computed laminography approach, which is capable of in situ visualizing of an industry-relevant lithium-ion (Li-ion) pouch cell with superior detection fidelity, resolution, and reliability. This technique enables imaging of the pouch cell at a spatial resolution of 0.5 μm in a laboratory system and permits the identification of submicron features within cathode and anode electrodes. We also demonstrate direct visualization of the lithium plating in the imaged pouch cell, which is an important phenomenon relevant to battery fast charging and low-temperature cycling. Our development presents an avenue toward a thorough understanding of the correlation among multiscale structures, chemomechanical degradation, and electrochemical behavior of industry-scale battery pouch cells.

25 ENERGY STORAGE↗

Human Factors Design for Particle Accelerator Control Room Interfaces

Fermilab, the birthplace of many scientific discoveries in physics and particle accelerator sciences, is in the midst of a widescale modernization effort. The Accelerator Control Operations Research Network (ACORN project’s goal is to modernize the accelerator control system by replacing end-of-life power supplies and enhance future operations of the Fermilab accelerator complex with megawatt particle beams. Within ACORN, opportunities for process improvement concerning software development, human-system interface design, and task performance are also being considered. Human factors researchers from Idaho National Laboratory in collaboration with usability experts from Fermilab, are currently investigating human-centered design improvements for the accelerator control system. For example, substantial tribal knowledge and memory recall are required to effectively operate the accelerator system. This contributes to high cognitive workload and potential burnout of accelerator operators. Developing guidance for consistent visual and functional design enables a more intuitive interaction and relieves operators of cognitive burden. Additionally, developing more intuitive and integrated interfaces can also lead to improved accelerator efficacy by empowering operators with greater understanding and control of the systems. The challenge in developing such interfaces is in designing for a wide variety of user goals, system specifications, and level of experience in users. The challenges need to be met while e also considering the maintainability of the control system. The purpose of this paper is to detail the human factors process and design within the ACORN project, describe results gathered thus far, and discuss the larger implications for this work.

43 PARTICLE ACCELERATORS↗

A KELT–TESS Eclipsing Binary in a Young Triple System Associated with the Local “Stellar String” Theia 301

HD 54236 is a nearby, wide common-proper-motion visual pair that has been previously identified as likely being very young by virtue of strong X-ray emission and lithium absorption. Here, we report the discovery that the brighter member of the wide pair, HD 54236A, is itself an eclipsing binary (EB), comprising two near-equal solar-mass stars on a 2.4 days orbit. It represents a potentially valuable opportunity to expand the number of benchmark-grade EBs at young stellar ages. Using new observations of Ca ii H and K emission and lithium absorption in the wide K-dwarf companion, HD 54236B, we obtain a robust age estimate of 225 ± 50 Myr for the system. This age estimate and Gaia proper motions show HD 54236 is associated with Theia 301, a newly discovered local “stellar string,” which itself may be related to the AB Dor moving group through shared stellar members. Applying this age estimate to AB Dor itself alleviates reported tension between observation and theory that arises for the luminosity of AB Dor C when younger age estimates are used.

79 ASTRONOMY AND ASTROPHYSICS↗

SU-C-18C-03: Dual-Energy X-Ray Fluoroscopy Imaging System

Purpose: This work studies the clinical utility of dual energy (DE) subtraction fluoroscopy for fiducial-free tumor tracking in lung radiation therapy (RT). Improvement in tumor visualization and quantification of tumor shift within a breathing cycle were analyzed. Methods: Twenty subjects who were undergoing RT for lung cancer were recruited following institutional review board approval. The subjects had a range of tumor sizes, locations in the lungs, and body sizes. An x-ray imaging system was setup with the following components: (a) x-ray tube (Varian G-242, Varian Medical Systems (VMS), CA) (b) flat panel detector (4030CB, VMS, CA) and (c) x-ray generator (EPS 50RF, EMD, Canada). Firmware and software modifications were made to the generator to allow 10 x-ray pulse pairs with alternating low/high kV, 100 ms apart for ∼4s (one breathing cycle). Images were obtained at 4 angles: 0°, 45°, 90° and 135°. Weighted subtraction of a kV-pair image set was used to create a “bone-free” image of the lungs. The 2D tumor-shift in each subtracted image and the 3D shift during a breathing cycle was calculated using all views. Results: The subjects enrolled had the following statistics: average age 62.3±7.1 years, 5 female/15 male, 11 had tumors on the right and 9 on the left and the average tumor size was ∼31.4±10.8 mm. X-ray imaging conditions for the pulse pairs were: 70/120 kVp, 280/221 mA and 65/8 ms. For views where these parameters were insufficient 80/130 kVp, 280/221 mA and 60/12 ms was used. Tumor visibility improved for 0°, 45°, 90° and 135° in 100%, 55%, 75% and 80% of the cases respectively. Tumor shift during a breathing cycle was: 2.4±1.0 mm AP, 2.7±1.4 mm LR and 7.6±4.8 mm IS. Conclusion: DE subtraction fluoroscopy allowed improved visualization and quantification of movement of tumors in the lungs during a breathing cycle. This study was entirely funded by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

Cardiovascular findings on cross-sectional imaging: spectrum of incidental and critical findings and clinical relevance for the abdominal radiologist

Although not the primary focus of the exams, cardiovascular structures are included to some extent on all abdominal or whole-body cross-sectional studies. Cardiovascular findings often present incidentally and may range from chronic to acute and emergent pathologies. Among the most common cardiovascular findings are the presence of cardiac calcifications, most commonly coronary, which correlate with the presence of coronary artery and valvular disease. Signs of myocardial ischemia, both acute and chronic, and its complications may also be visualized. Cardiac filling defects most commonly represent thrombus and are associated with systemic arterial embolic complications. Pericardial findings often manifest as effusion or thickening, which may lead to hemodynamic consequences visible at imaging. Incidental pulmonary emboli and systemic venous thrombi may be incidentally detected, particularly in hospitalized and oncologic patients, and warrant immediate attention. This review will highlight the appearance of common and important incidental cardiovascular findings and related pitfalls and discuss reporting and follow-up recommendations relevant to the abdominal radiologist.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Preprocessing Prediction of Advanced Algorithms for Medical Imaging

Advanced medical imaging algorithms (such as bone removal, vessel segmentation, or a lung nodule detection) can provide extremely valuable information to the radiologists, but they might sometimes be very time consuming. Being able to run the algorithms in advance can be a possible solution. However, we do not know which algorithm to run on a given dataset before it is actually used. It is possible to manually insert matching rules for preprocessing algorithms, but it requires high maintenance and does not work well in practice. This paper presents a dynamic machine learning solution for predicting which advanced visualization (AV) algorithm needs to be applied on a given series. The system gets a handful of free text DICOM tags as an input and builds a model in the clinical setting. It incorporates a Bag of Words (BOW) feature extractor and a Random Forest classifier. The approach was tested on two datasets from clinical sites which use different languages and varying scanner models. We show that even without feature extraction, sensitivity of above 90% can be reached on both of them. By using BOW feature extractor, precision and sensitivity can usually be further improved. Even on a noisy and highly unbalanced dataset, only around 100 samples were needed to reach sensitivity of above 80% and specificity of above 97%. We show how the solution can be part of a Smart Preprocessing mechanism in a viewing software. Using such a system will ultimately minimize the time to launch studies and improve radiologists reading time efficiency.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Imaging the square of the correlated two-electron wave function of a hydrogen molecule

The toolbox for imaging molecules is well-equipped today. Some techniques visualize the geometrical structure, others the electron density or electron orbitals. Molecules are many-body systems for which the correlation between the constituents is decisive and the spatial and the momentum distribution of one electron depends on those of the other electrons and the nuclei. Such correlations have escaped direct observation by imaging techniques so far. Here, we implement an imaging scheme which visualizes correlations between electrons by coincident detection of the reaction fragments after high energy photofragmentation. With this technique, we examine the H 2 two-electron wave function in which electron-electron correlation beyond the mean-field level is prominent. We visualize the dependence of the wave function on the internuclear distance. High energy photoelectrons are shown to be a powerful tool for molecular imaging. Finally, our study paves the way for future time resolved correlation imaging at FELs and laser based X-ray sources.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stable, high-performance, dendrite-free, seawater-based aqueous batteries

Metal anode instability, including dendrite growth, metal corrosion, and hetero-ions interference, occurring at the electrolyte/electrode interface of aqueous batteries, are among the most critical issues hindering their widespread use in energy storage. Herein, a universal strategy is proposed to overcome the anode instability issues by rationally designing alloyed materials, using Zn-M alloys as model systems (M = Mn and other transition metals). An in-situ optical visualization coupled with finite element analysis is utilized to mimic actual electrochemical environments analogous to the actual aqueous batteries and analyze the complex electrochemical behaviors. The Zn-Mn alloy anodes achieved stability over thousands of cycles even under harsh electrochemical conditions, including testing in seawater-based aqueous electrolytes and using a high current density of 80 mA cm –2 . The proposed design strategy and the in-situ visualization protocol for the observation of dendrite growth set up a new milestone in developing durable electrodes for aqueous batteries and beyond.

25 ENERGY STORAGE↗

Chapman–Jouguet deflagration criteria and compressibility dynamics of turbulent fast flames for turbulence-induced deflagration-to-detonation transition

This work characterizes the compressibility dynamics in turbulent fast flames for a range of turbulent flame speeds. These turbulent fast flames experience increased effects of compressibility through the formation of strong shocks and may develop a runaway acceleration combined with a pressure buildup that leads to turbulence induced deflagration-to-detonation transition (tDDT). Simultaneous high-speed particle image velocimetry, OH* chemiluminescence, schlieren, and pressure measurements are used to examine the reacting flow field and flame dynamics. We examine flames with turbulent flame speeds ranging from 100 to 600 m/s. At lower turbulent flame speeds, the flame is not able to produce favorable background conditions for deflagration-to-detonation transition (DDT) onset, and thus flame compressibility and turbulence amplification are less dominant, resulting in a weaker acoustic coupling between the flame and compressed region. As the turbulent burning velocities exceed the Chapman–Jouguet deflagration speed, favorable background conditions are produced, as we observe flame-generated shocks and flame-generated turbulence with higher turbulent velocities and larger turbulent scales. At this regime, the flame is categorized to be at the runaway transition regime that leads to tDDT.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NOVA AQUILAE 1918 (V603 Aql) FADED BY 0.44 MAG PER CENTURY FROM 1938 TO 2013

We present the light curve of the old nova V603 Aql (Nova Aql 1918) from 1898-1918 and 1934-2013 using 22,721 archival magnitudes. All of our magnitudes are either in, or accurately transformed into, the Johnson B and V magnitude systems. This is vital because offsets in old sequences and the visual-to-V transformation can cause errors of 0.1-1.0 mag if not corrected. Our V603 Aql light curve is the first time that this has been done for any nova. Our goal was to see the evolution of the mass accretion rate on a century timescale, and to test the long-standing prediction of the Hibernation model that old novae should be fading significantly in the century after their eruption is over. The 1918 nova eruption was completely finished by 1938 when the nova decline stopped, and when the star had faded to fainter than its pre-nova brightness of B = 11.43 ± 0.03 mag. We find that the nova light from 1938 to 2013 was significantly fading, with this being seen consistently in three independent data sets (the Sonneberg plates in B, the American Association of Variable Star Observers (AAVSO) V light curve, and the non-AAVSO V light curve). We find that V603 Aql has been declining in brightness at an average rate of 0.44 ± 0.04 mag per century since 1938. This work provides remarkable confirmation of an important prediction of the Hibernation model.

79 ASTRONOMY AND ASTROPHYSICS↗

pnnl/GeoCLUSTER

GeoCLUSTER is a Python-based web application that provides a collection of interactive methods for streamlining the visualization of the technical and economic modeling of closed-loop geothermal systems.

Buchko, Alex [Pacific Northwest National Laborator↗

Visual Sample Plan Version 7.0 User's Guide

User's guide for VSP 7.0 This user's guide describes Visual Sample Plan (VSP) Version 7.0 and provides instructions for using the software. VSP selects the appropriate number and location of environmental samples to ensure that the results of statistical tests performed to provide input to risk decisions have the required confidence and performance. VSP Version 7.0 provides sample-size equations or algorithms needed by specific statistical tests appropriate for specific environmental sampling objectives. It also provides data quality assessment and statistical analysis functions to support evaluation of the data and determine whether the data support decisions regarding sites suspected of contamination. The easy-to-use program is highly visual and graphic. VSP runs on personal computers with Microsoft Windows operating systems (XP, Vista, Windows 7, and Windows 8). Designed primarily for project managers and users without expertise in statistics, VSP is applicable to two- and three-dimensional populations to be sampled (e.g., rooms and buildings, surface soil, a defined layer of subsurface soil, water bodies, and other similar applications) for studies of environmental quality. VSP is also applicable for designing sampling plans for assessing chem/rad/bio threat and hazard identification within rooms and buildings, and for designing geophysical surveys for unexploded ordnance (UXO) identification.

97 MATHEMATICS AND COMPUTING↗

Liquid Fluoride Salt Experimentation Using a Small Natural Circulation Cell

A small molten fluoride salt experiment has been constructed and tested to develop experimental techniques for application in liquid fluoride salt systems. There were five major objectives in developing this test apparatus: Allow visual observation of the salt during testing (how can lighting be introduced, how can pictures be taken, what can be seen) Determine if IR photography can be used to examine components submerged in the salt Determine if the experimental configuration provides salt velocity sufficient for collection of corrosion data for future experimentation Determine if a laser Doppler velocimeter can be used to quantify salt velocities. Acquire natural circulation heat transfer data in fluoride salt at temperatures up to 700oC All of these objectives were successfully achieved during testing with the exception of the fourth: acquiring velocity data using the laser Doppler velocimeter. This paper describes the experiment and experimental techniques used, and presents data taken during natural circulation testing.

circulation cell↗

Unified Language Frontend for Physic-Informed AI/ML

Artificial intelligence and machine learning (AI/ML) are becoming important tools for scientific modeling and simulation as in several other fields such as image analysis and natural language processing. ML techniques can leverage the computing power available in modern systems and reduce the human effort needed to configure experiments, interpret and visualize results, draw conclusions from huge quantities of raw data, and build surrogates for physics based models. Domain scientists in fields like fluid dynamics, microelectronics and chemistry can automate many of their most difficult and repetitive tasks or improve the design times by use of the faster ML-surrogates. However, modern ML and traditional scientific highperformance computing (HPC) tend to use completely different software ecosystems. While ML frameworks like PyTorch and TensorFlow provide Python APIs, most HPC applications and libraries are written in C++. Direct interoperability between the two languages is possible but is tedious and error-prone. In this work, we show that a compiler-based approach can bridge the gap between ML frameworks and scientific software with less developer effort and better efficiency. We use the MLIR (multi-level intermediate representation) ecosystem to compile a pre-trained convolutional neural network (CNN) in PyTorch to freestanding C++ source code in the Kokkos programming model. Kokkos is a programming model widely used in HPC to write portable, shared-memory parallel code that can natively target a variety of CPU and GPU architectures. Our compiler-generated source code can be directly integrated into any Kokkosbased application with no dependencies on Python or cross-language interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

FY2022 Q4: Demonstrate multi-turbine simulation with hybrid-structured/unstructured-moving-grid software stack running primarily on GPUs and propose improvements for successful KPP-2 [Poster]

Milestone accomplishments staged the ExaWind team for successful completion of KPP-2 challenge problem in FY23, which requires the simulation on Frontier of at least four MW-scale turbines in an atmospheric boundary layer with at least 20B gridpoints. The ExaWind project and software stack is many faceted, with team members working on multiple areas, including linear-system solvers (Trilinos, hypre, AMReX), overset meshes, turbulence modeling, and in situ visualization, all with an aim for high fidelity predictions and performance portability. This milestone marks significant improvements on many fronts and provides the team with a pathway to exascale wind farm simulations in FY23.

17 WIND ENERGY↗

When Spectral Modeling Meets Convolutional Networks: A Method for Discovering Reionization-era Lensed Quasars in Multiband Imaging Data

Over the last two decades, around 300 quasars have been discovered at z ≳ 6, yet only one has been identified as being strongly gravitationally lensed. We explore a new approach—enlarging the permitted spectral parameter space, while introducing a new spatial geometry veto criterion—which is implemented via image-based deep learning. We first apply this approach to a systematic search for reionization-era lensed quasars, using data from the Dark Energy Survey, the Visible and Infrared Survey Telescope for Astronomy Hemisphere Survey, and the Wide-field Infrared Survey Explorer. Our search method consists of two main parts: (i) the preselection of the candidates, based on their spectral energy distributions (SEDs), using catalog-level photometry; and (ii) relative probability calculations of the candidates being a lens or some contaminant, utilizing a convolutional neural network (CNN) classification. The training data sets are constructed by painting deflected point-source lights over actual galaxy images, to generate realistic galaxy–quasar lens models, optimized to find systems with small image separations, i.e., Einstein radii of θ E ≤ 1''. Visual inspection is then performed for sources with CNN scores of P lens > 0.1, which leads us to obtain 36 newly selected lens candidates, which are awaiting spectroscopic confirmation. These findings show that automated SED modeling and deep learning pipelines, supported by modest human input, are a promising route for detecting strong lenses from large catalogs, which can overcome the veto limitations of primarily dropout-based SED selection approaches.

High-redshift galaxies↗

Results of Robotic Evaluation of Uranium-235 in Gaseous Diffusion Piping Holdup Deposits - 18303

Measurement of U-235 in pipes within old uranium enrichment facilities is time-consuming and very costly. Radiometric assay from outside the pipes suffers from manual deployment challenges, attenuation of detection through pipe walls, long counting times, approximate modeling, and shortfalls associated with transcription and human interpretation. The D and D process of cutting into these pipes creates a unique possibility of robotic in-pipe assay to address these problems. This paper presents the results of testing a first-of-kind radiometric non-destructive assay (NDA) robot for high-cadence, accurate, certain, paperless assay of U-235 in holdup deposits within process piping. The robot's enabling capability is an innovative radiometric collimation method that views only a one-foot moving annulus of pipe wall. This exploits the internal axisymmetry of pipes to provide a direct measurement of industry-standard grams per foot U-235. The initial proof-of-application robot was successfully hot tested by operators at the Gaseous Diffusion Enrichment Facility in Piketon, Ohio, in late 2017. This testing achieved all goals of traversing pipe, measuring U-235, deployment by facility personnel, and displaying analyzed radiation, visual, and geometric information. The success was a Kitty Hawk moment. The system demonstrated robotic in-pipe measurement of holdup deposit to a resolution, accuracy, and speed unachievable by alternate methods. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗