Development of a Coupled Subplane Capability in MPACT
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In recent years, the nonlinear 3D magnetohydrodynamic codes JOREK, M3D-C1, and NIMROD developed the capability of modeling realistic 3D vertical displacement events (VDEs) including resistive walls. In this paper, a comprehensive 3D VDE benchmark is presented between these state-of-the-art codes. The simulated case is based on an experimental NSTX plasma but with a simplified rectangular wall. There are differences between the physics models and numerical methods, and the VDE evolution leads to sensitivities on the initial conditions that cannot be avoided as can be done in edge localized modes (ELM) and sawtooth simulations (due to the non-cyclical nature of VDEs). Nonetheless, the comparison serves to quantify the level of agreement in the relevant quantities used to characterize disruptions, such as the 3D wall forces and energy decay. The results bring confidence regarding the use of the mentioned codes for disruption studies, and they distinguish aspects that are specific to the models used (e.g., reduced vs full MHD models). Here, the simulations show important 3D fea- tures for a NSTX plasma, such as the self-consistent evolution of the halo current and the origin of the wall forces. In contrast to other reduced MHD models based on an ordering in the aspect ratio, the ansatz-based JOREK reduced MHD model allows capturing many aspects of the 3D dynamics even in the spherical tokamak limit considered here.
This article discusses the use of radio frequency (RF) current drive to stabilize large islands, focusing on nonlinear effects that appear when relatively high powers are used to stabilize large islands. We are interested in developing a capability to stabilize large islands via RF driven currents to avoid the need for mitigation to the extent possible. As tokamaks are designed and built with increasing levels of stored energy in the plasma, disruptions become increasingly dangerous. It has been reported that 95% of the disruptions in the Joint European Torus tokamak with the ITER-like wall are preceded by the growth of large locked islands. These large islands are mostly produced by off-normal events other than neoclassical tearing modes. This paper presents theory and modeling for a nonlinear “RF current condensation” effect that can concentrate the RF driven current near the center of a large island, thereby increasing the efficiency of the stabilization. A nonlinear shadowing effect can hinder the stabilization of islands if the aiming of the ray trajectories does not properly consider the nonlinear effects.
We report on the measurement of the electrical properties of individual pristine and doped BaTiO 3 nanocubes by using in situ transmission electron microscopy with a two-electrode configuration. The dimensions of the nanocubes tested are between 10 and 20 nm, which rendered their in situ electrical characterization challenging. We characterized 4%Cr and 5%La (atomic percentage) doped BaTiO 3 nanocubes and compared them with the properties of pristine BaTiO3 nanocubes synthesized by the same solvothermal method. We found that the resistance of all three types of nanocubes when displayed in log-scale shows a nearly linear dependence on the applied electric field (R2 ≥ 0.95) over a wide range of electric fields (50–900 kV/cm). Compared with pristine BaTiO 3 nanocubes, the resistance of both 4%Cr and 5%La doped nanocubes showed reduced variation rates with respect to the electric field, with 5%La doping, demonstrating a better reduction in the variation rate. By developing techniques capable of evaluating the properties of individual BaTiO 3 nanocubes, we expect that our work to open the door to the use of BaTiO 3 nanomaterials in the design of future multilayer ceramic capacitors with improved volumetric efficiency and ferroelectrics-enabled nanodevices with advanced functionality.
The core electron temperature drops rapidly during the sawtooth crash in tokamak plasmas, which causes heat loss and may lead to fast particle losses or even a disruption. Several models have been proposed for the periodic crash, including the Kadomtsev model with magnetic reconnection and the quasi-interchange model with the growth of higher-mode-number pressure-driven instabilities. 3D MHD simulations were performed for these two models with a goal to develop intuition and to predict qualitatively how different types of sawtooth will appear in various diagnostics. The structures of electron density ne and electron temperature Te show a dominant (1, 1) mode for the Kadomtsev case and a dominant (4, 4) mode for the quasi-interchange case. The oscillations of ne and Te have a positive correlation near the inversion layer for both cases, while their frequencies and amplitudes are different depending on the dominant modes. Particularly, for the Kadomtsev case, we find a relation between the amount of flux reconnected during a sawtooth event and ne or Te oscillations. Therefore, we connect recently developed measurement capabilities for ne and Te to the internal sawtooth behavior. We propose that this method of analysis can help in identifying the type of sawtooth in future experiments augmented by simulations.
Historical data collection on nuclear fuel cladding materials has focused on generating a statistically significant amount of data to assess the material and its failure behavior. Furthermore, data generated to support material model and failure criteria development were previously posttest evaluations, so a large number of tests was required to gain new understanding. A way to expedite this process is to develop techniques capable of generating large, high-fidelity data sets from a single test with lower uncertainty or quantified uncertainty. One such example of this approach is Oak Ridge National Laboratory’s use of modified burst tests (MBTs) to analyze the mechanical behavior and failure conditions of cladding during a simulated reactivity-initiated accident (RIA). Each test incorporates digital image correlation (DIC) analysis techniques that are used to assess the accumulated strain in situ, as well as eventual cladding failure. This work has been fruitful in defining strain-to-failure conditions for materials like silicon carbide (SiC) fiber–reinforced/SiC matrix composite tubes (SiC/SiC), iron-chromium-aluminum (FeCrAl) alloy tubes, and chromium-coated Zircaloy-4 tubes. However, there are numerous DIC software available, including open-source and proprietary software. The different DIC software use various algorithms to process images and calculate displacement values. Using these different software and algorithms can lead to varying results, and perhaps larger-than-expected uncertainties. In the present study, previously published MBT data encompassing a variety of test conditions were reanalyzed with two different DIC software to assess the variance in the calculated strain results. The data consisted of SiC/SiC, FeCrAl, and chromium-coated Zircaloy-4 tubes. Plots of the calculated strains during the transient revealed good agreement between the two DIC software. The average root-mean-square errors between the two software was 0.20% strain, which is slightly larger than a previously reported error value for these tests. In conclusion, this variance in results is low enough that this analysis method can be used for code validation.
Although the high-temperature superconducting (HTS) REBa 2 Cu 3 O x (REBCO, RE-rare earth elements) material has a strong potential to enable dipole magnetic fields above 20 T in future circular particle colliders, the magnet and conductor technology needs to be developed. As part of an ongoing development to address this need, here we report on our CORC® canted cosθ magnet called C2 with a target dipole field of 3 T in a 65 mm aperture. The magnet was wound with 70 m of 3.8 mm diameter CORC® wire on machined metal mandrels. The wire had 30 commercial REBCO tapes from SuperPower Inc. each 2 mm wide with a 30 µm thick substrate. The magnet generated a peak dipole field of 2.91 T at 6.290 kA, 4.2 K. The magnet could be consistently driven into the flux-flow regime with reproducible voltage rise at an engineering current density between 400-550 A mm -2 , allowing reliable quench detection and magnet protection. The C2 magnet represents another successful step towards the development of high-field accelerator magnet and CORC® conductor technologies. The test results highlighted two development needs: continue improving the performance and flexibility of CORC® wires and develop the capability to identify locations of first onset of flux-flow voltage.
High-spin structures of holmium (𝑍 = 67) and erbium (𝑍 = 68) isotopes are presented near mass 160, a region where collective and single-particle modes of excitation compete in the generation of angular momentum at the highest experimentally attainable spins in atomic nuclei. The level schemes of the 156,157,158 Ho isotopes have been significantly extended, reaching spins in the 40ℏ to 55ℏ range, through multiple experiments utilizing the Gammasphere spectrometer. In particular, several new noncollective band-terminating states are reported for these nuclei. The nature of these states, including both valence-space terminations and core-excited oblateconfigurations, is discussed in terms of proton particle-hole (p-h) excitations across the semimagic 𝑍 = 64 shell closure. Cranked-Nilsson–Strutinsky (CNS) calculations have been used to interpret the nature of these noncollective states. The corresponding terminating states in 154–159 Er are also included, providing a systematic description of band termination in this mass region. In addition, three weak rotational structures have been assigned to 157 Ho at the highest spins. These collective bands are proposed to be based on a triaxial strongly deformed nuclear shape, involving neutron p-h excitations across the 𝑁 = 82 shell gap.
High-spin states in 60 Cu are investigated on the basis of reaction-channel-selected 𝛾-ray spectroscopy. Data stem from three experiments that used the same fusion-evaporation reaction at similar beam energies. The Gammasphere 𝛾-ray spectrometer was combined with the Microball CsI(Tl) detector array and sets of liquid-scintillator neutron detectors which allowed us to identify and tag on evaporated light charged particles and neutrons, respectively. A level scheme is proposed which comprises more than 300 𝛾-ray transitions connecting more than 100 excited states. Predictions from cranked Nilsson-Strutinsky calculations describe the observed high-spin collective structures in 60 Cu. Predictions of shell-model calculations are probed with a suite of low- to medium-spin states of both parities. Taking into account isospin-symmetry-breaking terms in these calculations, a case study of the yrast line of the weakly bound mirror nucleus 60 Ga is presented.
Compelling evidence exists for electronic phase separation in cuprate high-𝑇𝑐 superconductors, emerging near 1/8 hole doping. At these dopings and low temperatures, intertwined charge and spin stripes coexist with more uniformly doped regions in the two-dimensional (2D) copper-oxide planes. Each region is capable of developing superconducting pairing, either as a pair density wave (PDW) within the stripes or as a uniform 𝑑-wave condensate (𝑑-SC) in the more homogeneous regions. Using neutron scattering on single crystals of La1.875−𝑦Nd𝑦Sr0.125CuO4, we demonstrate that the onset temperatures for spin stripe order (𝑇𝑁) and superconductivity (𝑇𝑐) merge as the average ordered moment vanishes in LSCO (𝑦=0), whereas Nd doping stabilizes static stripe order and suppresses 𝑇𝑐. Because the spin stripes possess the same in-plane periodicity (8𝑎) as the PDW and establish the framework within which the PDW resides, the stabilization of spin stripe order enhances PDW correlations. Thus, the competition between 𝑑-wave pairing in the uniform regions and PDW pairing in the stripe-ordered regions can be controlled by the Nd concentration in La1.875−𝑦Nd𝑦Sr0.125CuO4, allowing the superconducting 𝑇𝑐 to vary by nearly an order of magnitude at a fixed 1/8-hole doping.
Understanding of the failure mechanisms of submarine dynamic power cables (SDPC) is critical for innovative design to meet the 2035 cost reduction target of U.S. DOE Floating Offshore Wind Shot. This is important because the current design suffers a significant failure rate in the field. This project explored a multiphysics approach and conducted systematic electro-thermo-mechanical (ETM) experimental study on the power cores extracted from a 15 kV power cable. The power cable had three cores of copper conductor and ethylene propylene rubber (EPR) insulation. An ETM testing system with transverse compression capability was developed. Mechanical loading induced dielectric breakdown. Increasing temperature from room temperature (RT, 22 degrees Celsius) to 90 degrees Celsius resulted in the 67% decrease in the failure mechanical load as defined by the dielectric breakdown. With the same temperature rise, the creep mechanical load was reduced by 70% at a given dielectric breakdown time. The post-test measurement revealed an impressive recovery of electrical resistance, although the dielectric breakdown occurred in the ETM test that would not be captured without the use of ETM testing.
Part of creating a successful solar industry is developing a capable workforce. It has been repeatedly shown that organizations and companies are more productive when they have diverse and inclusive cultures. The solar industry in the U.S. performs well in some aspects (non-white workforce, positive work environment) but drastically under-performs in many others. We discuss these metrics and how this impacts the renewable energy industry and the solar research community. We highlight some initial actions which are necessary to begin to remediate these deficiencies, such as demographic tracking, recruiting strategies, and mentoring. We also present the historical and ongoing efforts to improve the diversity and inclusion of the Photovoltaic Specialists Conference, particularly through the work of this year’s Diversity and Inclusion (D&I) oversight committee. This year’s D&I committee is implementing diversity tracking, a women’s lunch, a diversity lunch, childcare resources, pronouns on badges, gender-neutral restrooms, addressing accessibility issues, and publishing a diversity statement and code of conduct to the PVSC website.
This paper summarizes the three-year technical activities of the IEEE Task Force (TF) on behind-the-meter (BTM) distributed energy resources (DERs): estimation, uncertainty quantification, and control. The potential grid services from BTM DERs are discussed in detail. The paper also reviews the state-of-the-art for BTM DERs visibility, uncertainty quantification, and, optimization and control. Furthermore, different aspects of the market structures associated with BTM DERs are covered, including emerging market and business models. Finally, needs and recommendations are provided for additional areas such as system protection, computing capabilities, algorithm development, market structure design, cyberinfrastructure and security, and hardware and software developments.
Predictive maintenance refers to the ability to predict when machinery or systems need to be maintained. Making an accurate prediction is quite challenging given the costs for both over-estimating (unnecessary maintenance and reduction in availability of assets) and under-estimating (untimely breakdowns and possible loss of equipment or lives). To address these challenges researchers were able to develop new approaches for analyzing oil samples taken extracting samples from oil-wetted machinery that may provide information critical to developing predictive capabilities. We consider the problem from both supervised (though data limited) and unsupervised approaches and provide a first look into a data driven approach for identification of condition indicators. Through this work we identify a collection of candidate features that can form the basis of condition indicators for both a high level discrimination of failure vs. normal operation as well as a set for potential failure mode identification. Finally, we present an anomaly detection framework for detecting failures which can be a viable solution for an onboard analysis tool in deployed systems.
The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.
Sandia National Laboratories (SNL) and Oak Ridge National Laboratory (ORNL) are collaborating to develop a capability to test the epithermal/intermediate cross sections of tantalum (Ta) at the SNL critical experiments facility using the Seven Percent Critical Experiment (7uPCX) fuel. The Sandia Critical Experiments (SCX) Program provides a specialized facility for performing water moderated and reflected critical experiments with UO 2 fuel rod arrays. A history of safe reactor operations and flexibility in reactor core configuration has resulted in the completion of several benchmark critical experiment evaluations that are published in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The critical experiments described here are scheduled to be performed at SCX in fiscal year 2023. Currently, fabrication details for the needed new equipment are being finalized for completion of the procurement process. The experiments will then be executed and documented for publication consideration by the ICSBEP.
Developments related to generative artificial intelligence (AI) have brought a major breakthrough in AI. These developments are rapidly accelerating developments in different science and engineering applications. Nearly Autonomous Management and Control (NAMAC) system provides recommendations to the operator for maintaining the safety and performance of the reactor. The discrepancy checker (DC) is an important component of the NAMAC) system, whose goal is to determine if the plant is moving towards the expected system state after the control actions are injected. In this work, we explore generative AI methods, particularly, a generative pretrained transformer (GPT) for implementing the DC function in NAMAC. The GPT-based DC aims to alert the operator in situations outside NAMAC’s scope and act as a chatbot the operator can use to retrieve relevant information. This study involves two versions of GPT developed by OpenAI: GPT-3.5 and GPT-4. These GPTs are trained on huge amounts of undisclosed general domain datasets. We explored two methods to adapt GPTs for DC implementation in NAMAC: fine-tuning and retrieval augmented generation. A small knowledge base (information file) that encompasses rules for DC implementation and some general information related to NAMAC has been created to support DC implementation using GPT. In this work, the GPT-based DC implementations have been tested for their reasoning abilities, comprehension, information retrieval, and extraction abilities. It should be noted that this paper only presents a preliminary study to test the feasibility of DC implementation using generative AI technology. Given the potential risks and severe consequences associated with nuclear reactor applications, combined with the black-box nature of AI, extensive offline and online testing and reliability analyses of GPT-based DCs are needed for further developing such capabilities.
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