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At least 397 records · Page 22

Characterization of the ITER CS conductor and projection to the ITER CS performance

The ITER Central Solenoid (CS) is one of the critical elements of the machine. The CS conductor went through an intense optimization and qualification program, which included characterization of the strands, a conductor straight short sample testing in the SULTAN facility at the Swiss Plasma Center (SPC), Villigen, Switzerland, and a single-layer CS Insert coil recently tested in the Central Solenoid Model Coil (CSMC) facility in QST-Naka, Japan. In this paper, we obtained valuable data in a wide range of the parameters (current, magnetic field, temperature, and strain), which allowed a credible characterization of the CS conductor in different conditions. Finally, using this characterization, we will make a projection to the performance of the CS in the ITER reference scenario.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Dataset of theoretical multinary perovskite oxides

Perovskite oxides (ternary chemical formula ABO 3 ) are a diverse class of materials with applications including heterogeneous catalysis, solid-oxide fuel cells, thermochemical conversion, and oxygen transport membranes. However, their multicomponent (chemical formula $A_xA^{'}_{1-x}B_yB^{'}_{1-y}O_3$) chemical space is underexplored due to the immense number of possible compositions. To expand the number of computed $A_xA^{'}_{1-x}B_yB^{'}_{1-y}O_3$ compounds we report a dataset of 66,516 theoretical multinary oxides, 59,708 of which are perovskites. First, 69,407 $A_{0.5}A^{'}_{0.5}B_{0.5}B^{'}_{0.5}O_3$ compositions were generated in the a - b + a - Glazer tilting mode using the computationally-inexpensive Structure Prediction and Diagnostic Software (SPuDS) program. Next, we optimized these structures with density functional theory (DFT) using parameters compatible with the Materials Project (MP) database. Our dataset contains these optimized structures and their formation (ΔH f ) and decomposition enthalpies (ΔH d ) computed relative to MP tabulated elemental references and competing phases, respectively. This dataset can be mined, used to train machine learning models, and rapidly and systematically expanded by optimizing more SPuDS-generated $A_{0.5}A^{'}_{0.5}B_{0.5}B^{'}_{0.5}O_3$ perovskite structures using MP-compatible DFT calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Generalized and efficient algorithm for computing multipole energies and gradients based on Cartesian tensors

Accurate representation of intermolecular forces has been the central task of classical atomic simulations, known as molecular mechanics. Recent advancements in molecular mechanics models have put forward the explicit representation of permanent and/or induced electric multipole (EMP) moments. The formulas developed so far to calculate EMP interactions tend to have complicated expressions, especially in Cartesian coordinates, which can only be applied to a specific kernel potential function. For example, one needs to develop a new formula each time a new kernel function is encountered. The complication of these formalisms arises from an intriguing and yet obscured mathematical relation between the kernel functions and the gradient operators. Here, I uncover this relation via rigorous derivation and find that the formula to calculate EMP interactions is basically invariant to the potential kernel functions as long as they are of the form f(r), i.e., any Green’s function that depends on inter-particle distance. I provide an algorithm for efficient evaluation of EMP interaction energies, forces, and torques for any kernel f(r) up to any arbitrary rank of EMP moments in Cartesian coordinates. The working equations of this algorithm are essentially the same for any kernel f(r). Recently, a few recursive algorithms were proposed to calculate EMP interactions. Depending on the kernel functions, the algorithm here is about 4–16 times faster than these algorithms in terms of the required number of floating point operations and is much more memory efficient. I show that it is even faster than a theoretically ideal recursion scheme, i.e., one that requires 1 floating point multiplication and 1 addition per recursion step. This algorithm has a compact vector-based expression that is optimal for computer programming. The Cartesian nature of this algorithm makes it fit easily into modern molecular simulation packages as compared with spherical coordinate-based algorithms. A software library based on this algorithm has been implemented in C++11 and has been released.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impurity transport studies at the HSX stellarator using active and passive CVI spectroscopy

The transport of carbon impurities has been studied in the helically symmetric stellarator experiment (HSX) using active and passive charge exchange recombination spectroscopy (CHERS). For the analysis of the CHERS signals, the STRAHL impurity transport code has been re-written in the python programming language and optimized for the application in stellarators. In addition, neutral hydrogen densities both along the NBI line of sight as well as for the background plasma have been calculated using the FIDASIM code. By using the basinhopping algorithm to minimize the difference between experimental and predicted active and passive signals, significant levels of impurity diffusion are observed. In this work, comparisons with neoclassical calculations from DKES/PENTA show that the inferred levels exceed the neoclassical transport by about a factor of four in the core and more than 100 times towards the plasma edge, thus indicating a high level of anomalous transport. This observation is in agreement with experimental heat diffusivites determined from a power balance analysis which exhibits strong anomalous transport as well.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Constraint of pionless EFT using two-nucleon spectra from lattice QCD

Finite-volume pionless effective field theory (FVEFT π/ ) at next-to-leading order (NLO) is used to analyze the two-nucleon lattice QCD spectrum of Ref. [1], performed at quark masses corresponding to a pion mass of approximately 800 MeV. Specifically, the effective theory is formulated in finite volume, and variational sets of wave functions are optimized using differential programming. Using these wave functions projected to the appropriate finite-volume symmetry group, variational bounds from FVEFT π/ are obtained for the ground state, as well as excited states. By comparison with the lattice QCD GEVP spectrum, different low energy constants (LECs) are constrained. Furthermore, relativistic corrections are incorporated, allowing for the s-d-wave mixing term in the deuteron channel.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ancilla-Free Quantum Error Correction Codes for Quantum Metrology

Quantum error correction has recently emerged as a tool to enhance quantum sensing under Markovian noise. It works by correcting errors in a sensor while letting a signal imprint on the logical state. This approach typically requires a specialized error-correcting code, as most existing codes correct away both the dominant errors and the signal. To date, however, few such specialized codes are known, among which most require noiseless, controllable ancillas. We show here that such ancillas are not needed when the signal Hamiltonian and the error operators commute, a common limiting type of decoherence in quantum sensors. We give a semidefinite program for finding optimal ancilla-free sensing codes in general, as well as closed-form codes for two common sensing scenarios: qubits undergoing dephasing, and a lossy bosonic mode. Lastly, we analyze the sensitivity enhancement offered by the qubit code under arbitrary spatial noise correlations, beyond the ideal limit of orthogonal signal and noise operators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Trilevel Model for Segmentation of the Power Transmission Grid Cyber Network

Network segmentation of a power grid's communication system can make the grid more resilient to cyberattacks. Here we develop a novel trilevel programming model to optimally segment a grid communication system, taking into account the actions of an information technology (IT) administrator, attacker, and grid operator. The IT administrator is allowed to segment existing networks, and the attacker is given a budget to inflict damage on the grid by attacking the segmented communication system. Finally, the grid operator can redispatch the grid after the attack to minimize damage. The resulting problem is a trilevel interdiction problem that we solve using a branch and bound algorithm for bilevel problems. We demonstrate the benefits of optimal network segmentation through case studies on the 9-bus Western System Coordinating Council (WSCC) system and the 30-bus IEEE system. These examples illustrate that network segmentation can significantly reduce the threat posed by a cyberattacker.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Impacts of Integrating Topology Reconfiguration and Vehicle-to-Grid Technologies on Distribution System Operation

Autonomous electric vehicles (AEVs) provide unique opportunities to cope with the uncertainties of distributed energy generation in distribution networks. But the effects are limited by both inherent radial topology and the behaviors of decentralized AEVs. As such, we investigate the potential benefits of dynamic distribution network reconfiguration (DDNR), taking into account AEVs' spatial-temporal availability and their charging demand. We propose a mixed integer programming model to optimally coordinate the charging/discharging of AEVs with DDNR, while satisfying AEVs' original travel plan. Numerical studies based on a test system overlaying the IEEE 33-node test feeder and Sioux Falls transportation network show that DDNR and AEV complement each other, which improves the operation of the distribution system. We also conduct sensitivity analyses on inputs including renewable fluctuation and AEVs penetration level.

33 ADVANCED PROPULSION SYSTEMS↗

WE-A-19A-01: SRT I: Comparison of SRT Techniques

Within the past several years, the field of radiosurgery has seen numerous technological enhancements, including new dedicated devices for stereotactic delivery, the use of re-locatable frames to facilitate fractionated delivery and the image guided frameless approaches. The goal of this symposium is to compare and contrast competing technologies for cranial SRS/SRT. The symposium will open with a review of the general concept of cranial SRS/SRT procedures as well as describe the key differences from conventional radiotherapy. The speakers will then review each of the delivery technique (Gamma Knife, CyberKnife and Conventional linear accelerator) in turn. The focus of each speaker will be to describe the general workflow of each SRS modality, indications and counterindications for treatment. To compare and contrast different technologies, 2–3 cases examples demonstrating interesting treatment situations and expected outcomes, a sample treatment plan (either live or pre-recorded with live commentary) demonstrating the treatment planning technique, and machine and patient-specific QA required for treatment (if applicable). Additionally, workflows and data describing the use of immobilization devices or tracking/monitoring during SRS/SRT delivery will also be discussed. The session will close with a roundtable discussion of methods to evaluate plan quality, and achievable technical and clinical goals for intracranial SRS. Learning Objectives: Understand the key differences between cranial SRS/SRT and conventional treatments. Review Gamma Knife, CyberKnife and Conventional Linac-based radiosurgery delivery techniques and quality assurance Compare and contrast treatment plans, treatment planning strategy and and quality assurance procedures for each technology. Be able to establish cranial SRS/SRT procedure with optimized quality assurance program for each technology.

60 APPLIED LIFE SCIENCES↗

Spectral Peak Enhancement by Combining Trusted Response Elements via Machine Learning (SPECTRE-ML) v0.8.0

SPECTRE-ML (Spectral Peak Enhancement by Combining Trusted Response Elements via Machine Learning) is a machine learning based program for finding optimal clusters of radiation detector segments (i.e., pixels or voxels) in order to improve spectral performance. It provides facilities for pre-processing and analyzing training datasets, running ML algorithms, and evaluating and visualizing outputs. SPECTRE-ML outperforms simpler ad-hoc segmentation methods such as uniform depth clusters, learning detector performance trends such as dead layers, edge effects, and gain shifts. Although extensible to arbitrary highly-segmented spectroscopic radiation detectors, SPECTRE-ML currently focuses on improving spectral performance in highly-segmented CdZnTe (CZT) detectors for International Atomic Energy Agency (IAEA) non-destructive assay (NDA) safeguards tasks.

Vavrek, Jayson↗

Green Design of a Cellulosic Butanol Supply Chain Network: A Case Study of Sorghum Stem Bio-butanol in Missouri

Cellulosic butanol is a very promising renewable fuel to consider for the future transportation market. However, the seasonal availability of the raw materials, high maintenance cost, and high logistical cost of the biomass energy supply chain are the main factors impeding the commercialization and large-scale-production of this energy source. Furthermore, research focusing on an environmental or green supply chain network design of cellulosic butanol has been insufficient. Here, this study focused on designing a green supply chain network for cellulosic butanol. A life cycle analysis was integrated into a multi-objective linear programming model to optimize the cellulosic butanol supply chain network. With the objectives of maximizing the economic profits and minimizing the greenhouse gas emissions, the proposed model can optimize the location and size of a bio-butanol production plant. The mathematical model was applied to a case study in the state of Missouri, and solved the tradeoff between the feedstock and market availabilities of sorghum stem bio-butanol.

09 BIOMASS FUELS↗

Theoretical Multinary Perovskite Oxides Dataset

Perovskite oxides (ternary chemical formula ABO3) are a diverse class of materials with applications including heterogeneous catalysis, solid-oxide fuel cells, thermochemical conversion, and oxygen transport membranes. However, their multicomponent chemical space is underexplored due to the immense number of possible compositions. To expand the number of computed compounds we report a dataset of 66,516 theoretical multinary oxides, 59,708 of which are perovskites. First, the AA'BB'O6 compositions were generated in the a-b+a- Glazer tilting mode using the computationally-inexpensive Structure Prediction and Diagnostic Software (SPuDS) program. Next, we optimized these structures with DFT using parameters compatible with the Materials Project (MP) database. Our dataset contains these optimized structures and their formation (ΔHf) and decomposition enthalpies (ΔHd) computed relative to MP tabulated elemental references and competing phases, respectively. This dataset can be mined, used to train machine learning models, and rapidly and systematically expanded by optimizing more SPuDS-generated AA'BB'O6 perovskite structures using MP-compatible DFT calculations

Bare, Zachary↗

GCAM–GLORY v1.0: representing global reservoir water storage in a multi-sector human–Earth system model

Abstract. Reservoirs play a significant role in modifying the spatiotemporal availability of surface water to meet multi-sector human demands, despite representing a relatively small fraction of the global water budget. Yet the integrated modeling frameworks that explore the interactions among climate, land, energy, water, and socioeconomic systems at a global scale often contain limited representations of water storage dynamics that incorporate feedbacks from other systems. In this study, we implement a representation of water storage in the Global Change Analysis Model (GCAM) to enable the exploration of the future role (e.g., expansion) of reservoir water storage globally in meeting demands for, and evolving in response to interactions with, the climate, land, and energy systems. GCAM represents 235 global water basins, operates at 5-year time steps, and uses supply curves to capture economic competition among renewable water (now including reservoirs), non-renewable groundwater, and desalination. Our approach consists of developing the GLObal Reservoir Yield (GLORY) model, which uses a linear programming (LP)-based optimization algorithm and dynamically linking GLORY with GCAM. The new coupled GCAM–GLORY approach improves the representation of reservoir water storage in GCAM in several ways. First, the GLORY model identifies the cost of supplying increasing levels of water supply from reservoir storage by considering regional physical and economic factors, such as evolving monthly reservoir inflows and demands, and the leveled cost of constructing additional reservoir storage capacity. Second, by passing those costs to GCAM, GLORY enables the exploration of future regional reservoir expansion pathways and their response to climate and socioeconomic drivers. To guide the model toward reasonable reservoir expansion pathways, GLORY applies a diverse array of feasibility constraints related to protected land, population, water sources, and cropland. Finally, the GLORY–GCAM feedback loop allows evolving water demands from GCAM to inform GLORY, resulting in an updated supply curve at each time step, thus enabling GCAM to establish a more meaningful economic value of water. This study improves our understanding of the sensitivity of reservoir water supply to multiple physical and economic dimensions, such as sub-annual variations in climate conditions and human water demands, especially for basins experiencing socioeconomic droughts.

54 ENVIRONMENTAL SCIENCES↗

Physical Activity Types and Programs Recommended by Primary Care Providers Treating Adults With Arthritis, DocStyles 2018

Primary care providers (PCPs) can offer counseling to adults with arthritis on physical activity, which can reduce pain and improve physical function, mental health, and numerous other health outcomes. We analyzed cross-sectional 2018 DocStyles data for 1,366 PCPs who reported they always or sometimes recommend physical activity to adults with arthritis. Most PCPs sampled (88.2%) recommended walking, swimming, or cycling; 65.5% did not recommend any evidence-based, arthritis-appropriate physical activity programs recognized by the Centers for Disease Control and Prevention. Opportunities exist for public health awareness campaigns to educate PCPs about evidence-based physical activity programs proven to optimize health for adults with arthritis when more than counseling is needed.

60 APPLIED LIFE SCIENCES↗

Sisal

Sisal (Streams and Iterations in a Single Assignment Language) was a general-purpose applicative language developed for shared-memory and vector supercomputer systems. It provided an hierarchical intermediate form, parallel runtime system, optimizing compiler, and programming environment. The language was strongly typed. It supported both array and stream data structures, and had both iterative and parallel loop constructs.

Feo, John T↗

Marrying Quality Assurance with Design Engineering - A Winning Partnership! But, a Cultural Divide?: Preprint

Investors would like to be confident that a PV plant will work as promised before investing large sums of money. Data showing that PV modules can withstand thousands of hours of accelerated testing are a comfort, but are not sufficient. An inability to be confident of every aspect of the system can motivate higher interest rates; high degradation or failure rates can substantially decrease the return on investment and the value of the plant for resale later on. In the end, a winning partnership is obtained when a carefully engineered, durable design is married with a robust quality management system and the marriage is extended across all parts of the value chain. However, this marriage is challenging because of the conventional cultural divide between design engineers and quality management specialists. This paper discusses the motivation for increased emphasis on quality assurance and describes three new standards that detail requirements for a higher level of quality assurance for 1) PV module manufacturing, 2) inverter and other balance-of-systems (BOS) manufacturing, and 3) control of the system installation and operation. The paper concludes with a discussion of the challenges and benefits of marrying the quality assurance program with further optimization of the PV system design.

14 SOLAR ENERGY↗

Condensation in horizontal heat exchanger tubes

Many innovative reactor concepts for Generation III nuclear power plants use passive safety equipment for residual heat removal. These systems use two phase natural circulation. Heat transfer to the coolant results in a density difference providing the driving head for the required mass flow. By balancing the pressure drop the system finds its operational mode. Therefore the systems depend on a strong link between heat transfer and pressure drop determining the mass flow through the system. In order to be able to analyze these kind of systems with the help of state of the art computer codes the implemented numerical models for heat transfer, pressure drop or two phase flow structure must be able to predict the system performance in a wide parameter range. Goal of the program is to optimize the numerical models and therefore the performance of computer codes analyzing passive systems. Within the project the heat transfer capacity of a heat exchanger tube will be investigated. Therefore the tube will be equipped with detectors, both temperature and pressure, in several directions perpendicular to the tube axis to be able to resolve the angular heat transfer. In parallel the flow structure of a two phase flow inside and along the tube will be detected with the help of x-ray tomography. The water cooling outside of the tube will be realized by forced convection. It will be possible to combine the flow structure measurement with an angular resolved heat transfer for a wide parameter range. The test rig is set up at the TOPLFOW facility at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR), so that it will be possible to vary the pressure between 5 and 70 bar. The steam mass content will be varied between 0 and 100 percent. The results will be compared to the large scaled Emergency Condenser Tests performed at the INKA test facility in Karlstein (Germany). The paper will explain the test setup and the status of the project will be presented. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗