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Jennings, Christopher Ashley↗
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Quantitative Voltammetry Measurements of High-Concentration Actinides in Molten Chloride Fuel Salts
Molten chloride mixtures containing high concentrations of UCl 3 (i.e., >70 wt%) are candidates for next-generation molten salt reactor (MSR) fuel salts that enable new plant optimization and fuel cycle strategies. MSR licensing, however, is contingent on the development of effective material control and accounting (MC&A) practices for these salts. To close this gap, we have developed an electroanalytical approach that enables accurate in situ measurements of uranium concentrations in these highly loaded fuel salts. This methodology uses a multielectrode array voltammetry sensor combined with digital simulations that account for non-idealities such as uncompensated resistance effects. The theory-based numerical simulations of voltammetry responses yielded correction factors that are agnostic of electrochemical cell geometry and produced consistent voltammetry peak current results when correcting for varying amounts of ohmic resistance. In doing so, we have demonstrated accurate concentration measurements for UCl 3 in LiCl-KCl-UCl 3 across a range of mass fractions between 55 and 72.3 wt% at 550 °C.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Flow Enhanced Electrochemical Sensor Performance in Complex Salt Systems
To advance MSR MC&A practices, Argonne National Laboratory developed and optimized robust flow enhanced electrochemical sensors (FEES) and multielectrode array voltammetry sensors (MAVS) which provide accurate near-real time measurements of actinides in molten salts. Flow-enhanced electrochemical sensors are installed directly into MSR flow conduits for inline salt chemistry measurement, while MAVS are deployed in quiescent salt conditions enabling online species concentration determination in stationary salt vessels. This report summarizes efforts to improve electrochemical sensor technological readiness through (1) sensor testing in complex, high concentration molten salt systems to demonstrate low uncertainty actinide measurements in MSR-representative solutions and (2) demonstrations of sensor performance in challenging real-world conditions in collaboration with partner MSR institutions.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Smart Readout of Nondestructive Image Sensors with Single Photon-Electron Sensitivity
Image sensors with nondestructive charge readout provide single-photon or single-electron sensitivity, but at the cost of long readout times. We present a smart readout technique to allow the use of these sensors in visible light and other applications that require faster readout times. The method optimizes the readout noise and time by changing the number of times pixels are read out either statically, by defining an arbitrary number of regions of interest in the array, or dynamically, depending on the charge or energy of interest in the pixel. This technique is tested in a Skipper CCD showing that it is possible to obtain deep subelectron noise, and therefore, high resolution of quantized charge, while dynamically changing the readout noise of the sensor. These faster, low noise readout techniques show that the skipper CCD is a competitive technology even where other technologies such as electron multiplier charge coupled devices, silicon photo multipliers, etc. are currently used. This technique could allow skipper CCDs to benefit new astronomical instruments, quantum imaging, exoplanet search and study, and quantum metrology.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Integration of Rucio in Belle II
The Belle II experiment, which started taking physics data in April 2019, will multiply the volume of data currently stored on its nearly 30 storage elements worldwide by one order of magnitude to reach about 340 PB of data (raw and Monte Carlo simulation data) by the end of operations. To tackle this massive increase and to manage the data even after the end of the data taking, it was decided to move the Distributed Data Management software from a homegrown piece of software to a widely used Data Management solution in HEP and beyond : Rucio. This contribution describes the work done to integrate Rucio with Belle II distributed computing infrastructure as well as the migration strategy that was successfully performed to ensure a smooth transition.
97 MATHEMATICS AND COMPUTING↗
pyTDGL: Time-dependent Ginzburg-Landau in Python
Time-dependent Ginzburg-Landau (TDGL) theory is a phenomenological model for the dynamics of superconducting systems. Due to its simplicity in comparison to microscopic theories and its effectiveness in describing the observed properties of the superconducting state, TDGL is widely used to interpret or explain measurements of superconducting devices. Here, we introduce pyTDGL, a Python package that solves a generalized TDGL model for superconducting thin films of arbitrary geometry, enabling simulations of vortex and phase dynamics in mesoscopic superconducting devices. pyTDGL can model the nonlinear magnetic response and dynamics of multiply connected films, films with multiple current bias terminals, and films with a spatially inhomogeneous critical temperature. We demonstrate these capabilities by modeling quasi-equilibrium vortex distributions in irregularly shaped films, and the dynamics and current-voltage-field characteristics of nanoscale superconducting quantum interference devices (nanoSQUIDs).
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Prominent radiative contributions from multiply-excited states in laser-produced tin plasma for nanolithography
Extreme ultraviolet (EUV) lithography is currently entering high-volume manufacturing to enable the continued miniaturization of semiconductor devices. The required EUV light, at 13.5 nm wavelength, is produced in a hot and dense laser-driven tin plasma. The atomic origins of this light are demonstrably poorly understood. Here we calculate detailed tin opacity spectra using the Los Alamos atomic physics suite ATOMIC and validate these calculations with experimental comparisons. Our key finding is that EUV light largely originates from transitions between multiply-excited states, and not from the singly-excited states decaying to the ground state as is the current paradigm. Moreover, we find that transitions between these multiply-excited states also contribute in the same narrow window around 13.5 nm as those originating from singly-excited states, and this striking property holds over a wide range of charge states. We thus reveal the doubly magic behavior of tin and the origins of the EUV light.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Analysis of Lobe Power Calculator and Indication System with Physics and Cycle Based Models
The Advanced Test Reactor (ATR) at INL measures reactor power through two methods, thermal and Nitrogen-16 (N-16) activity. Water power calculator (WPC) is a thermal power system that measures flow and temperature to determine the thermal quadrant powers. The N-16 system utilizes a beta chamber detector that outputs reactivity levels to calculate lobe power through an algorithm called lobe power calculation and indication system (LPCIS). The LPCIS utilizes the N-16 system and the WPC system to determine reactor core power levels. The WPC provides accurate calculations of quadrant and total reactor thermal power. With the use of WPC measurements, thermal-to-N-16 (T2N) power ratios are produced to determine if the two indication systems agree on core power. Relative magnitude equations are used to utilize N-16 coefficients and multipliers to improve the indications of the LPCIS. This is crucial for maintaining safety limits. Currently, the LPCIS system uses linear equations and matrices to calculate lobe power through multipliers and coefficients. Advancements in technology and system upgrades have assisted system engineers at INL with the objective to reach a more dynamic system. In return the system demonstrates an increase in the accuracy of power reading while maintaining safety margins. The new proposed coefficient and multiple method implements a cycle specific, and a physics-based model intended for changing coefficients during operation. This calibration experiment focuses on power splitting, outer shim and neck shim, as well as fuel burning into the RDAS weighting factors. Results show that the Physics learning method yields a smaller error margin inside of the desired power range for the data set 166-A. This proved true for both constrained and unconstrained testing. This is most likely due to the physics data fitting approach that resulted in favorable coefficients and multipliers for 166-A. Continuing to improve the physics-based model will help improve the power accuracy of the LPCIS system.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
From physics to fixtures to food: current and potential LED efficacy
Light-emitting diodes (LEDs) have enabled a historic increase in the conversion of electric energy to photons, but this is approaching a physical limit. The theoretical maximum efficiency occurs when all input energy is converted to energy in photosynthetic photons. Blue LEDs can be 93% efficient, phosphor-converted “whites” 76% efficient, and red LEDs 81% efficient. These improvements open new opportunities for horticultural lighting. Here we review (1) fundamental physics and efficiency of LEDs, (2) the current efficacy of LEDs, (3) the effect of spectral quality on crop yield, and (4) the potential efficacy of horticultural fixtures. Advances in the conversion of photons to yield can be achieved by optimization of spectral effects on plant morphology, which vary among species. Conversely, spectral effects on photosynthesis are remarkably similar across species, but the conventional definition of photosynthetic photons (400–700 nm) may need to be modified. The upper limit of LED fixture efficacy is determined by the LED package efficacy multiplied by four factors inherent to all fixtures: current droop, thermal droop, driver (power supply) inefficiencies, and optical losses. With current LED technology, the calculations indicate efficacy limits of 3.4 µmol J- 1 for white + red fixtures, and 4.1 µmol J -1 for blue + red fixtures. Adding optical protection from water and high humidity reduces these values by ~10%. We describe tradeoffs between peak efficacy and cost.
Agriculture↗
Next-Generation, High-temperature, High-frequency, High-efficiency, High-power-density Traction System
To meet performance and reliability requirements necessary for broader adoption of electric drive vehicles, the Electrical and Electronics Technical Team of the U.S. Drive partnership has established aggressive design goals for next-generation electric vehicle drivetrains. Specifically, the 2025 roadmap stipulates a 100 kW/L power density target and a $\$$2.7/kW cost target for power electronics, in addition to high-voltage operation (i.e., greater than 800 VDC). The additional targets for traction motor and the overall system performance impose further challenges on the power electronics design. For example, many high specific power machines have reduced iron content, and therefore reduced intrinsic filtering, thus requiring the inverter to supply a low-distortion drive current. These machines also typically have a high pole count, thus requiring drive current at a higher electrical frequency. Other motors, such as brush-less dc and switch reluctance machines, require a carefully-shaped, non-sinusoidal drive current (Yang, Shang, Brown, & Krishnamurthy, 2015), (Zhang, Bowman, O'Connel, & Haran, 2018), (Anderson, et al., 2018). Two- and three-level inverter topologies are the conventional framework for the power electronics design of the drivetrain, and some demonstrations have shown recent progress towards addressing cost, power density and efficiency goals (Gurpinar & Ozpineci, 2018), (Zhu, Kim, Chen, Erickson, & Maksimović, 2018), (Deshpande, Chen, Narayanasamy, Sathyanarayanan, & Luo, 2018), (Alizadeh, et al., 2019). However, an unconventional approach may be necessary to take the dramatic leap in power density necessitated by the roadmap—while simultaneously addressing the other system needs. Therefore, this project leverages the flying capacitor multilevel (FCML) topology, together with a scalable, modular approach, to address these needs. This type of hybrid converter has several advantages: lower voltage (i.e., less than 300 V) transistors can be used, energy-dense capacitors process most of the power, and the output current waveform is multilevel and exhibits a frequency multiplying effect—in other words, the output has reduced dv/dt and filtering requirements for the same high voltage dc bus. For example, in an electric vehicle with an 800 V bus, a 10-level FCML could leverage 100 V, commercially available GaN devices switching at 115 kHz to produce a ~1 MHz switching waveform (modulated according to the motor drive requirements) with one ninth of the dv/dt of a two-level converter. Prior work has already demonstrated promising performance and gravimetric power density figures for more electric aircraft applications (Pallo, Foulkes, Modeer, Coday, & Pilawa-Podgurski, 2018). This project leverages lessons learned to achieve the volumetric power density of 100 kW/L by employing advanced liquid cooling, address the 300,000 mile reliability challenge with redundant design, topology failure studies and online health monitoring, and reduce costs to $\$$2.7/kW through the use of low-cost GaN devices, modular converter assemblies, and modest modifications to traditional manufacturing methods. The project involved several hardware designs, each achieving increasing performance. At the conclusion of the project, a volumetric power density of 380 kW/L was achieved, in a 800V dc-ac converter, greatly surpassing even the aggressive target goal.
33 ADVANCED PROPULSION SYSTEMS↗
Analysis of Lobe Power Calculator and Indication System with Physics and Cycle Based Models
The Advanced Test Reactor (ATR) at INL measures reactor power through various methods, two of them being thermal and Nitrogen-16 (N-16) activity. Water power calculator (WPC) is a thermal power system that measures flow and temperature to determine thermal quadrant powers. The N-16 system utilizes a beta detector that outputs Nitrogen activation levels to calculate lobe power through an algorithm called Lobe Power Calculation and Indication system (LPCIS). The LPCIS utilizes the N-16 system and the WPC system to determine reactor core power levels. The WPC provides accurate calculations of quadrant and total reactor thermal power. With the use of WPC measurements, thermal-to-N-16 (T2N) power ratios are produced to determine if the two indication systems agree on core power. Relative magnitude equations are used to utilize N-16 coefficients and multipliers to improve the indications of the LPCIS. These correct indications are crucial for maintaining safety limits because operators rely on this information for decision making. Currently, the LPCIS system uses linear equations and matrices to calculate lobe power through multipliers and coefficients. Advancements in technology and system upgrades have increased the accuracy of power readings by making the system more dynamic. The new proposed coefficient and multiplier method implements a cycle specific and physics-based model intended for changing coefficients during operation. This calibration experiment focused on power splitting, outer shim and neck shim, as well as fuel burning into the reactor digital acquisition system (RDAS) weighting factors. Results demonstrated that the physics learning method yields a smaller error margin inside of the desired power range for the data set 166-A. Continuing to improve the physics-based model will help improve the power accuracy of the LPCIS system.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
E-Area Low Level Waste Generator Inventory Uncertainty Estimation
This report describes the method used to estimate the uncertainty and bias in the low-level waste inventory, as reported by Waste Generators, for waste disposed in the E-Area Low-Level Waste Facility at SRS. The waste cut uncertainty and bias is summed to calculate the current total uncertainty and bias in each disposal unit in the E-Area Low-Level Waste Facility. This information is used to estimate the future uncertainty and bias when all disposal units are closed. For most waste cuts, there are two areas of inventory uncertainty and bias: in the isotopic characterization of the waste stream and in the measurement of total waste cut activity. Waste stream characterization is accomplished through a combination of process knowledge and analytical measurements. This characterization is documented by a technical baseline that describes the relative quantity of each isotope present in the waste stream. The total activity of each individual waste cut is usually measured directly or is calculated through a ratio of activity per weight or activity per volume. The waste cut total activity is multiplied by the waste stream isotopic fraction to calculate the total isotopic activity present in the waste cut. The waste cut uncertainty and bias is calculated by analyzing the uncertainties and biases in the waste stream characterization and waste cut measurements and adding the uncertainties in quadrature and multiplying the reported isotopic activities by the bias factors. The current isotopic inventory, uncertainty, and bias of a disposal unit is the sum of the currently disposed individual waste cut isotopic activities, uncertainties, and biases. The future uncertainty and bias is estimated based on the average “worst-case” (largest) uncertainties and biases of currently closed and operational disposal units. This report details the method, data sources, and calculation techniques used to calculate these values. It also presents some of the difficulties in working with the reported data and gives examples of the calculations and analysis. The software used to carryout the analysis is included and the location of the complete individual analyses is given. After discussion with waste generators, examination of multiple waste characterization documents, and a review of SRS Manual 1S, the reported ELLWF radionuclide activities are clearly conservative and likely represent reasonable upper bounds for the true activities. However, quantifying the bias and uncertainty in each waste cut requires detailed analysis of the documentation for each waste cut measurement and waste stream characterization.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
A Reinforcement Learning Approach to Parameter Selection for Distributed Optimal Power Flow
With the increasing penetration of distributed energy resources, distributed optimization algorithms have attracted significant attention for power systems applications due to their potential for superior scalability, privacy, and robustness to a single point-of-failure. The Alternating Direction Method of Multipliers (ADMM) is a popular distributed optimization algorithm; however, its convergence performance is highly dependent on the selection of penalty parameters, which are usually chosen heuristically. In this work, we use reinforcement learning (RL) to develop an adaptive penalty parameter selection policy for alternating current optimal power flow (ACOPF) problem solved via ADMM with the goal of minimizing the number of iterations until convergence. We train our RL policy using deep Q-learning and show that this policy can result in significantly accelerated convergence (up to a 59% reduction in the number of iterations compared to existing, curvatureinformed penalty parameter selection methods). Furthermore, we show that our RL policy demonstrates promise for generalizability, performing well under unseen loading schemes as well as under unseen losses of lines and generators (up to a 50% reduction in iterations). This work thus provides a proof-of-concept for using RL for parameter selection in ADMM for power systems applications.
alternating current optimal power flow↗
PMT calibration for the JSNS^2-II far detector with an embedded LED system
The JSNS^2-II (the second phase of JSNS^2, J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) is an experiment aimed at searching for sterile neutrinos. Here, this experiment has entered its second phase, employing two liquid scintillator detectors located at near and far positions from the neutrino source. Recently, the far detector of the experiment has been completed and is currently in the calibration phase. The following properties of all functioning Photo-Multiplier-Tubes (PMTs) to detect the neutrino events in the far detector have been calibrated: PMT gain, its dependence of supplied High Voltage (HV), Peak-to-Valley (PV), and signal timing. This paper presents a detailed description of the calibration process utilizing the LED system. The LED system of the far detector uses two Ultra-Violet (UV) LEDs, which are effective in calibrating all of the PMTs at once. The UV light is converted into the visible light wavelengths inside liquid scintillator via the wavelength shifters, providing pseudo-isotropic light. To achieve a good energy resolution for physics events, a relative gain adjustment of up to 10% is required for all functioning PMTs. This will be achieved using the HV curves measured and the results of the LED calibration. The Peak-to-Valley (PV) ratio values, which distinguish the single photo-electron signal from the pedestal, are similar to those from the production company. Additionally, the precision of the PMT signal timing is measured to be 2.1 ns. This meets the event reconstruction requirement of 10 ns.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Digitization modeling of a CGEM detector based on Garfield++ simulation
Abstract Background The Cylindrical Gas Electron Multiplier Inner Tracker (CGEM-IT) is one of the candidates for the replacement of the current BESIII inner drift chamber, which has developed serious aging effects due to beam-related backgrounds. Purpose To build a full digitization model, it is necessary to understand the electron drift behavior and signal induction. Methods A simulation study based on Garfield++ and ANSYS software has been performed. Results Parameters describing the Lorentz angle, diffusion effect, drift time, multiplication, and induction are obtained from the Garfield++ simulation. Based on these results, a preliminary digitization model is implemented in the BESIII offline software system.
Zhao, Jing-Yi (ORCID:0000000220287286)↗
Effect of self-generated magnetic fields on x-ray emission in Kr-filled targets at the National Ignition Facility
We examine the effects of self-generated magnetic fields in a Kr gas pipe x-ray source platform. X-ray emission from Kr plasma is dependent on the plasma conditions, as the ionization state is largely a function of temperature. Magnetic fields are known to limit heat conduction, which increases temperature. We show that the emission in simulations of the gas pipe x-ray source is dependent on how self-generated magnetic fields are modeled. The inclusion of self-generated magnetic fields in simulations more accurately captures the emission of lower energy x-ray emission (L-shell), bringing results closer to experiments. The modeled x-ray emission and self-generated magnetic fields are shown to be particularly sensitive to the inclusion of the Nernst effect in simulations. Severely limiting the Nernst effect leads to a hotter Kr plasma, which can account for the discrepancy seen in earlier studies. By modifying the Nernst effect multiplier, we can achieve better experimental agreement in x-ray emission from gas pipes; the value of the multiplier that leads to the best agreement is dependent on the laser power of the drive. Currently, the suppression factor of the Nernst effect needed for high power drives (PL>200 TW) is more restrictive than what is currently put forward by non-local models.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Accuracy and precision of ESI-Orbitrap-IRMS observations of hours to tens of hours via reservoir injection
Here, orbitrap isotope ratio mass spectrometry (Orbitrap-IRMS) has recently been applied to high-precision, natural-abundance isotope ratio measurements of a diverse range of compounds, including amino acids, oxyanions, fatty acids, and metals. These measurements can characterize many isotope ratios simultaneously at high (≈1.0‰) precision. In a successful experiment, observed precision will track the shot-noise limit and be limited by experimental time. Some isotope ratios, for example those involving 17 O in organic compounds or multiply-substituted (‘clumped’) isotopologues, require experimental times of hours to tens of hours to achieve desired precision, while current sample introduction techniques focus on observations on the order of seconds to tens of minutes. In this study, we characterize Orbitrap-IRMS performance for three long duration measurements (individual acquisitions ≥1 h and as long as 24 h) using an automated reservoir injection system coupled to a Q Exactive HF Orbitrap with an electrospray ionization (ESI) source. First, we characterize long-term intra-measurement stability through a 24-h long measurement of acetone. We report the following isotope ratios and precisions (as acquisition errors, errors on the observed ratio within this measurement (σ AE )): 13 C/ 12 C (σ AE = 0.07‰), 17 O/ 16 O (σ AE = 1.1‰), 18 O/ 16 O (σ AE = 0.3‰), and 13 C 13 C/ 12 C (σ AE = 0.65‰). The σ AE of each tracks the shot noise limit throughout and is limited by the challenging conditions (high resolution and low numbers of ions per scan) required for 17 O/ 16 O measurement in the presence of 13 C via Orbitrap. Second, we characterize inter-measurement stability via a sequence of seven 75-min analyses of perchlorate. We observe the following ratios and acquisition errors: 37 Cl/ 35 Cl (σ AE = 0.09‰); 17 O/ 16 O (σ AE = 1.6‰); 18 O/ 16 O (σ AE = 0.7‰), 37 Cl 17 O/ 35 Cl 16 O (σ AE = 2.7‰), and 37 Cl 18 O/ 35 Cl 16 O (σ AE = 1.2‰). However, we find that inter-measurement drift between acquisitions limits our accuracy and precision for standardized measurements (i.e., error on reported δ values) to ≈1‰ for the 37 Cl/ 35 Cl measurement. Hence, the benefits of low σ AE may not be fully realized. Third, we demonstrate accuracy via sample/standard comparisons of a methionine sample with 13 C enrichment of ≈20‰ relative to a known standard. Using a sequence of seven 60-min analyses, we recover the following isotope ratios and standardized precisions (i.e., error on reported δ values, denoted propagated acquisition errors, σ PAE ): 33 S/ 32 S (σ PAE = 1.0‰), 34 S/ 32 S (σ PAE = 0.7‰), 15 N/ 14 N (σ PAE = 2.1‰), 2 H/ 1 H (σ PAE = 3.2‰), 13 C/ 12 C (σ PAE = 0.4‰), 18 O/ 16 O (σ PAE = 1.6‰), & 13 C 13 C/ 12 C (σ PAE = 2.8‰) with confirmation of accurate results for the known 13 C/ 12 C and 13 C 13 C/ 12 C enrichments. Together, our results demonstrate the viability of Orbitrap-IRMS for long duration measurements of diverse sample types via an automated reservoir injection system. Inter-measurement stability remains a challenge; we expect our methods to be most applicable to extended measurements of hard-to-observe properties, such as 17 O in organics and clumped isotopologues.
58 GEOSCIENCES↗
FLASH: FPGA-Accelerated Smart Switches with GCN Case Study
Some communication switches, e.g., the Mellanox SHArP and those in the IBM BlueGene clusters, are augmented to process packets at the application level with fixed-function collectives. This approach, however, lacks flexibility, which limits their applicability in diverse and dynamic workloads. Recently, a new type of programmable packet processor, which uses high-level languages, e.g., P4, has emerged as possible candidates. P4-based switches, however, fall short in certain applications, including machine learning, where capabilities not currently supported by P4 are needed. These include more complex calculation, such as sparse computation and fused multiply-accumulate, data-intensive floating point operations, data reuse, and significant memory. The problem addressed here is that such a switch augmentation needs to support: a large amount of state, significant flexible compute capability, and ease of programming, all while maintaining full functionality, including ensuring high throughput, and demonstrating utility. In this work, we propose a programmable look-aside-type accelerator that can be embedded into, or attached to, existing communication switch pipelines and that is capable of processing packets at line-rate. The proposed in-switch accelerator is based on mixing an ISA (subset of RISC-V instructions) with dataflow graphs (found in CGRAs). To augment performance, vector instructions are also supported. To facilitate usability, we have developed a complete toolchain to compile user-provided C/C++ codes to appropriate back-end instructions for configuring the accelerator. While this approach is flexible enough to support various workloads, in this paper, we consider Graph Convolutional Networks (GCNs) as a case study. Experimental results show that this approach considerably improves the performance of distributed GCN applications.
Haghi, Pouya↗