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At least 109 records · Page 6

Quantum Effect on the Ground State of the Triple-Perovskite Ba 3 MNb 2 O 9 (M = Co, Ni, and Mn) with Triangular-Lattice

As the simplest example of geometrical frustration, the two-dimensional triangular lattice antiferromagnet exhibits the mismatch between the lattice geometry and spin-exchange interaction, which has been the subject of intensive studies due to its exotic quantum phenomena. In this work, we performed detailed studies of the magnetic structures and spin wave excitations by neutron powder diffraction and inelastic neutron scattering measurements on the triple-perovskite oxides Ba 3 MNb 2 O 9 (M = Co, Ni, and Mn) with triangular-lattice geometry. The interplay between the frustrated interaction and easy-plane/axis anisotropy gives rise to two magnetic phase transition temperatures for Ba 3 CoNb 2 O 9 (Ba 3 MnNb 2 O 9 ) and only one for Ba 3 NiNb 2 O 9 . The linear spin-wave theory +1/S calculations indicate that both spatial dimensionality and the spin size have a significant impact on the strength of quantum fluctuations, which lead to their different magnetic ground states and exotic physical properties. Moreover, the effects of the thermal fluctuations are presented for Ba 3 NiNb 2 O 9 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Local Structural Disorder in Metavanadates MV 2 O 6 (M = Zn and Cu) Synthesized by the Deep Eutectic Solvent Route: Photoactive Oxides with Oxygen Vacancies

Metavanadates MV 2 O 6–δ (M = Zn and Cu) are synthesized by using a deep eutectic solvent (DES), a mixture of hydrogen bond donor and acceptor, as a reaction medium. Dissolution of stable binary metal oxides in a DES followed by a heat treatment yields phase-pure vanadates. According to in situ powder X-ray diffraction, ternary phases (α-Zn 2 V 2 O 7 and β-Cu 2–x V 2 O 7 , x ~ 0.27) are intermediates in the reaction pathway taken. Identifying a polymorphic phase transformation temperature for CuV 2 O 6 as well as the narrow temperature range between formation and decomposition for both metavanadates allows for tackling the challenge of the synthesis of these materials. The oxygen vacancy introduced by the DES route is accompanied by the formation of reduced V 4+ and Cu + in the oxide matrix, based on X-ray photoelectron spectroscopy. These oxygen vacancies modify the vibrational modes in the corresponding Raman spectra and are also responsible for broad optical absorptions in the 1.8–1.1 eV range. The optical band gaps of the materials are found at 1.8 eV (CuV 2 O 6 ) and 2.2 eV (ZnV 2 O 6 ), approximately 0.1–0.3 eV below the values reported in the literature. The reduced band gaps and sub-band gap photon absorption are key features of the oxygen-deficient metavanadates. Surface photovoltage spectroscopy reveals that all the synthesized vanadates are n-type materials with electrons as the majority charge carriers, and photoelectrochemical measurements confirm photoanodic currents for methanol oxidation. Furthermore, these results provide insight into the synthesis and structure–property relationship of the metavanadates for their potential use as photoanodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Demonstration and Evaluation of the Human-Technology Integration Function Allocation Methodology

There is an imminent need for the existing nuclear power plants to reduce their operating and maintenance (O&M) costs to remain economically viable. Digital technology, including automation, provides a significant opportunity for the existing nuclear power plant fleet to transform the way in which work is accomplished, reducing O&M costs, and allowing the fleet to remain economically competitive. One notable opportunity to significantly reduce O&M costs pertains to modifications to the plant equipment and main control room (MCR). Existing instrumentation and control (I&C) technologies in the MCR are highly analog, costly to operate and maintain, and demand a high cognitive and physical workload from plant staff (i.e., operators). Digitalizing the MCR has a range of broad economic benefits, including improved plant performance and reduced manual work. Further, digital I&C systems can fundamentally change the way in which plant staff operate the plant; this is the concept of operation. Human-technology integration is important to ensure that impacts to the concept of operation are done in a way that account for capabilities of people and technology. Human-technology integration employs human factors engineering (HFE) methods and principles to maximize the benefits of digital technology, reducing human error, improving overall decision-making and usability. The U.S. Department of Energy Light Water Reactor Sustainability Program is applying human-technology integration research to ensure digital technologies are safe, reliable, and efficient. This paper documents the demonstration of the human-technology guidance developed by the Light Water Reactor Sustainability Program from a first-of-a-kind digital I&C upgrade, specifically addressing function analysis and allocation for a new digital I&C system that included changes in automation levels. The program’s specific approach is included in this work, following lessons learned. This document serves as a resource for industry to follow in applying human-technology integration and HFE to digital modifications, specific to function analysis and allocation. The lessons learned should be considered in the planning and execution of HFE activities that support such digital modifications.

99 GENERAL AND MISCELLANEOUS↗

PMDT: AI-Enabled Predictive Maintenance Digital Twins for Advanced Nuclear Reactors

Our team made substantial technical progress on various fronts during the course of the program. Multiple milestones were geared towards demonstrating the feasibility of machine learning based predictive maintenance digital twins towards reducing O&M costs, whereas some other milestones actually focused on identifying technical gaps and developing technologies such as humble AI to provide necessary robustness to the ML-based models. We were able to demonstrate in many cases that Machine learning-based methods can be successfully adapted for Nuclear plant environments especially for remote monitoring applications. Detailed analyses were carried out with plant and full scope simulation data along with capabilities of enhanced analytics to assess and set realistic expectations on cost reductions in O&M. These assessments are paving the way for investments towards reactor design improvements as well project planning for SMR projects as they develop and mature in the next few years. Technology developed under this program got direct visibility to GE Hitachi and their utility customers and resulted in positive intents to deploy some of the elements from design phase. The project additionally resulted in several reports, publications, software and data generation that will be useful in deployment and O&M services for BWRX300 fleets.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

On the instability of hypersonic flow past a flat plate

The instability of hypersonic boundary-layer flows over flat plates is considered. The viscosity of the fluid is taken to be governed by Sutherland's law, which gives a much more accurate representation of the temperature dependence of fluid viscosity at hypersonic speeds than Chapman's approximate linear law; although at lower speeds the temperature variation of the mean state is less pronounced so that the Chapman law can be used with some confidence. Attention is focussed on the so-called (vorticity) mode of instability of the viscous hypersonic boundary layer. This is thought to be the fastest growing inviscid disturbance at hypersonic speeds; it is also believed to have an asymptotically larger growth rate than any viscous or centrifugal instability. As a starting point the instability of the hypersonic boundary layer which exists far downstream from the leading edge of the plate is investigated. In this regime the shock that is attached to the leading edge of the plate plays no role, so that the basic boundary layer is non-interactive. It is shown that the vorticity mode of instability of this flow operates on a significantly different lengthscale than that obtained if a Chapman viscosity law is assumed. In particular, it is found that the growth rate predicted by a linear viscosity law overestimates the size of the growth rate by O(M(exp 2). Next, the development of the vorticity mode as the wavenumber decreases is described, and it is shown that acoustic modes emerge when the wavenumber has decreased from it's O(1) initial value to O(M (exp -3/2). Finally, the inviscid instability of the boundary layer near the leading edge in the interaction zone is discussed and particular attention is focussed on the strong interaction region which occurs sufficiently close to the leading edge. It is found that the vorticity mode in this regime is again unstable, and that it is concentrated in the transition layer at the edge of the boundary layer where the temperature adjusts from its large, O(M(exp 2), value in the viscous boundary layer, to its O(1) free stream value. The existence of the shock indirectly, but significantly, influences the instability problem by modifying the basic flow structure in this layer.

Blackaby, Nicholas↗

DOE’s National Solar Thermal Test Facility Operations and Maintenance

This report details operations and maintenance (O&M) activities performed across Fiscal Years 2022 through 2024 in support of the continued capabilities of the National Solar Thermal Testing Facility (NSTTF) at Sandia National Laboratories. The NSTTF O&M project is funded by the U.S. Department of Energy Solar Energy Technologies Office (SETO) to support research activities and testing on behalf of external customers at the facility under award number CPS 38491. During the project period, the NSTTF made progress in the areas of site metrics, site maintenance and utilization tracking, and customer engagement. The O&M project also supported special initiatives including procurement of a heat exchanger for particle concentrating solar thermal processes and a scoping and cost study for refurbishment and repair of component in the NSTTF heliostat field.

14 SOLAR ENERGY↗

Demonstration and Evaluation of Explainable and Trustworthy Predictive Technology for Condition-based Maintenance

The domestic nuclear power plant (NPP) fleet has historically relied on labor-intensive and time-consuming predictive maintenance (PdM) programs, thus driving up operation and maintenance (O&M) costs to achieve high-capacity factors. Artificial intelligence (AI) and machine-learning (ML) can help simplify complex problems such as diagnosing equipment degradation to enable more effective decision-making efforts. The benefits of AI will be felt through more efficient plant O&M, improved work processes, and better integration of people and technology. Together, these benefits hold the promise to make nuclear power more sustainable by reducing O&M costs while improving employee engagement. While AI and ML technologies hold significant promise for the nuclear industry, there are challenges or barriers to their adoption. Explainability and trustworthiness of AI are two salient challenges that need to be addressed for wider deployment of these technologies in NPPs. This research focuses specifically on addressing the explainability and trustworthiness of AI technologies to advance the human, technical, and organization (HTO) readiness levels in adopting a risk-informed PdM strategy at commercial NPPs. In addition, this approach can be adapted to enhance the acceptability of AI in other nuclear applications with a few application-specific modifications. The technical approach ensuring wider adoption of AI technologies was developed by Idaho National Laboratory (INL)—in collaboration with Public Service Enterprise Group (PSEG), Nuclear, LLC—by utilizing the circulating water system (CWS) at two PSEG-owned plant sites for demonstration. Focused user studies were performed in collaboration with subject matter experts (SMEs) from PSEG and other nuclear domains to enhance human and organization readiness by building trust in AI-informed technologies. VIsualization for PrEdictive maintenance Recommendation (VIPER)—a Battelle Energy Alliance, LLC, copyrighted software—was developed and expanded to provide a user-centric visualization by incorporating inputs from the collaborating utility, human factors engineering guidelines, and data analysts. The VIPER software enables users, who may be unfamiliar with ML in general, to be interactively engaged by asking technical questions about PdM, work orders, diagnosis results and their confidence levels, the kind of data being used, and the types of ML algorithms employed. This interactive engagement enhances explainability and builds trust. One of the enabling accomplishments was the integration of large language models (LLMs), both text-based and vision-based, in the VIPER software.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Determining the Conformation of Supported Complexes Using an 17 O TEDOR-like NMR Experiment

Dynamic nuclear polarization surface-enhanced nuclear magnetic resonance (NMR) spectroscopy has enabled the determination of the three-dimensional configuration of surface sites, in particular supported metal complexes of relevance to single-site heterogeneous catalysis. These approaches have chiefly leveraged the application of NMR double-resonance experiments that either reveal the complex conformation via point-to-point intramolecular distances between spin-labeled atoms or the complex-surface orientation via distances between the spins and the surface plane. Either method typically requires expensive isotope labeling and each reports on different structural features. The application of an experiment that simultaneously reveals both types of distances with chemical resolution would be ideal. Here, in this article, we describe an 17 O{ 1 H} pseudo-3D correlation experiment that achieves this goal. Specifically, Si–O–Si and Si–O–M oxygens are well-resolved by 17 O NMR; therefore, distances can be simultaneously measured radially, between Si– 17 O–M and the 1 H’s of the ligands, and vertically to the Si– 17 O–Si linkages of the silica support. We demonstrate the experiment using supported yttrium and zirconium complexes. Good agreement is obtained when comparing the experimental results to theoretical predictions from density functional theory calculations, highlighting the reliability of this relatively simple experiment.

alkyls↗

Evaluation of Component Reliability in Photovoltaic Systems using Field Failure Statistics

Ongoing operations and maintenance (O&M) are needed to ensure photovoltaic (PV) systems continue to operate and meet production targets over the lifecycle of the system. Although average costs to operate and maintain PV systems have been decreasing over time, reported costs can vary significantly at the plant level. Estimating O&M costs accurately is important for informing financial planning and tracking activities, and subsequently lowering the levelized cost of electricity (LCOE) of PV systems. This report describes a methodology for improving O&M planning estimates by using empirically-derived failure statistics to capture component reliability in the field. The report also summarizes failure patterns observed for specific PV components and local environmental conditions observed in Sandia's PV Reliability, Operations & Maintenance (PVROM) database, a collection of field records across 800+ systems in the U.S. Where system-specific or fleet-specific data are lacking, PVROM-derived failure distribution values can be used to inform cost modeling and other reliability analyses to evaluate opportunities for performance improvements.

14 SOLAR ENERGY↗

Boson localization and universality in YBa2Cu(3-x)M(x)O(7-delta)

We consider a two component mixture of charged fermions on neutralizing background with all sign combinations and arbitrarily small mass ratios. In the two impurity limit for the heavier component we show that the pair forms a bound state for all charge combinations. In the lowest order approximation we derive a closed form expression Veff(r) for the binding potential which has short-range repulsion followed by attraction. In the classical limit, when the mass of embedded particles is large m2 much greater than m, we can calculate from Veff(r) also the cohesive energy E and the bond length R of a metallic crystal such as lithium. The lowest order result is R = 3.1 A, E = -0.9 eV, not entirely different from the experimental result for lithium metal. The same interaction for two holes on a parabolic band with m2 greater than m gives the quantum mechanical bound state which one may interpret as a boson or local pair in the case of high-Te and heavy fermion superconductors. We also show that for compounds of the type YBa2Cu(3 - x)M(x)O(7 - delta) one can understand most of the experimental results for the superconducting and normal states with a single temperature dependent boson breaking function f(T) for each impurity content x governing the decay of bosons into pairing fermions. In the normal state f(T) turns out to be a linear, universal function, independent of the impurity content I and the oxygen content delta. We predict with universality a depression in Tc(x) with slight down bending in agreement with experiment. As a natural consequence of the model the bosons become localized slightly above Tc due to the Wigner crystallization, enhanced with lattice local field minima. The holes remain delocalized with a linearly increasing concentration in the normal state, thus explaining the rising Hall density. The boson localization temperature T(sub BL) shows up as a minimum in the Hall density R(sub ab)(exp -1). We also give explanation for very recently observed scaling of temperature dependent Hall effect in La(2 - x)Sr(x)CuO4.

Kallio, A.↗

Regional Economic Impacts of the Los Angeles 100% Renewable Energy Transition

To help mitigate greenhouse gas (GHGs) generation from burning fossil fuels, many state and local governments are requiring utilities to dramatically increase the share of electricity generated from renewable sources. The City of Los Angeles has set a target of 100% renewable energy by 2045 and has formulated a plan that considers nine potential alternative scenarios that differ by technology, location, and timing. Each scenario has a unique set of local investments, operating and maintenance (O&M) costs, and concomitant rate structures. In this study we develop and apply a computable general equilibrium (CGE) model built specifically for LA to estimate and compare the economic impacts for each of the scenarios over time relative to a reference case. We find differences in economic impacts across scenarios, depending on the level and timing of investment and O&M expenditures, as well as differences in the relative rate changes across scenarios. Results show that employment and economic output are positively correlated with greater capital and O&M spending, while higher electricity rates can dampen economic activity. Several scenarios generate positive economic impacts relative to the reference case, showing that the transition need not have harmful economic impacts, and all scenarios generate a number of other positive co-benefits, such as reduced damage to health from the reduction of ordinary air pollutants. The net employment impacts from 2026 to 2045 across the scenarios range from a low of 3,600 job-year losses annually to 4,700 job-year gains, both around only 0.1% of the baseline average annual employment in the city over that period. The analysis also indicates that lower-income households are relatively more affected than others by the scenarios. Overall, even in the most negatively impactful case, the economic output and employment effects are quite small when taken in the context of the overall size of the regional economy and the large reduction in GHGs.

economic impact modeling↗

Vibrational signatures of HNO 3 acidity when complexed with microhydrated alkali metal ions, M + ∙(HNO 3 )(H 2 O) n =5 (M = Li, K, Na, Rb, Cs), at 20 K

The speciation of strong acids like HNO 3 under conditions of restricted hydration is an important factor in the rates of chemical reactions at the air-water interface. Here we explore the trade-offs in play when HNO 3 is attached to alkali ions (Li + -Cs + ) with four water molecules in their primary hydration shells. This is achieved by analyzing the vibrational spectra of the M + ∙(HNO 3 )(H 2 O) 5 clusters cooled to about 20 K in a cryogenic photofragmentation mass spectrometer. The local acidity of the acidic OH group is estimated by the extent of the red shift in its stretching frequency when attached to a single water molecule. Here, the persistence of this local structural motif (HNO 3 -H 2 O) in all of these alkali metal clusters enables us to determine the competition between the effect of the direct complexation of the acid with the cation, which acts to enhance acidity, and the role of the water network in the first hydration shell around the ions, which acts to counter (screen) the intrinsic effect of the ion. Analysis of the vibrational features associated with the acid molecule as well as those of the water network reveal how cooperative interactions in the micro hydration regime conspire to effectively offset the intrinsic enhancement of HNO 3 acidity afforded by attachment to the smaller cations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Support Effect and Surface Reconstruction in In 2 O 3 / m- ZrO 2 Catalyzed CO 2 Hydrogenation

Here, we investigate the chemical and structural dynamics at the interface of In 2 O 3 /m-ZrO 2 and their consequences on the CO 2 hydrogenation reaction (CO 2 HR) under reaction conditions. While acting to enrich CO 2 , monoclinic zirconia (m-ZrO 2 ) was also found to serve as a chemical and structural modifier of In 2 O 3 that directly governs the outcome of the CO 2 HR. These modifying effects include the following: (1) Under reaction conditions (above 623 K), partially reduced In 2 O 3 , i.e., InO x (0 < x < 1.5), was found to migrate in and out of the subsurface of m-ZrO 2 in a semireversible manner, where m-ZrO 2 accommodates and stabilizes InO x by serving as a reservoir. The decreased concentration of surface InO x under elevated temperatures coincides with significantly decreased selectivity toward methanol and a sharp increase of the reverse water–gas shift reaction. The reconstruction-induced variation of InO x concentration appears to be one of the most important factors contributing to the altered catalytic performance of CO 2 HR at different reaction conditions. (2) The strong interactions and reactions between m-ZrO 2 and In 2 O 3 result in the activation of a pool of In–O bonds at the In 2 O 3 /m-ZrO 2 interface to form oxygen vacancies. On the other hand, the high dispersity of In 2 O 3 nanostructures onto m-ZrO 2 prevents their over-reduction under catalytically relevant conditions (up to 673 K), when bare In 2 O 3 is unavoidably reduced into the metallic phase (In 0 ). The relationship between the extent of reduction of In 2 O 3 and catalytic performance (CO 2 conversion, CH 3 OH selectivity, or yield of CH 3 OH) suggests the presence of an optimum coverage of surface InO x and oxygen vacancies under reaction conditions. The conventional model that links catalytic performance solely to the coverage of oxygen vacancies appears invalid in the present case. In situ analysis also allows the observation of surface reaction intermediates and their interconversions, including the reduction of CO 3 * into formate, a precursor for the formation of methanol and CO. The combinative ex situ and in situ study sheds light on the reaction mechanism of the CO 2 HR on In 2 O 3 /m-ZrO 2 -based catalysts. Our findings on the large-scale surface reconstructions, support effect, and the reaction mechanism of In 2 O 3 /m-ZrO 2 for CO 2 HR may apply to other related metal oxide catalyzed CO 2 reduction reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling the PV System Level Economic Impact of PV Connector Failure Modes

Photovoltaic (PV) connectors must maintain mechanical integrity for over 25 years while operating under UV exposure, elevated temperature, and mechanical loading. Connector degradation increases with electrical resistance, leading to energy losses, unplanned downtime, and higher operation and maintenance (O&M) costs and in severe cases, safety risks from overhearing or arcing. Connector related failures remain among the most frequent causes of disruption in utility-scale PV (UPV) systems, yet their lifetime economic impacts are poorly quantified. This work presents a techno-economic analysis (TEA) framework that links identified connector failure modes to system level energy losses and lifetime cost impacts using identified resistance measurements and failure rates from 6,2761 PV connectors inspected. Connector failures increase system level O&M costs, raising LCOE by roughly 5%. Downtime driven availability losses dominate economic impact. Resistance-driven I2R and IV-curve losses are secondary, but remain non-negligible. Thermal damage, bend-radius violations, and loose connections drive the majority of LCOE uplift Improving connector reliability through better installation quality, inspection, and design can meaningfully reduce lost energy, O&M costs, and LCOE.

14 SOLAR ENERGY↗

NREL’s Wind Turbine Drivetrain Condition Monitoring and Wind Plant Operation and Maintenance Research During the 2010s: A US Land-Based Perspective

The wind industry has seen tremendous growth during the past two decades, with the global cumulative installation capacity reaching more than 650 gigawatts by the end of 2019. Despite performance and reliability improvements of utility-scale wind turbines over the years, the industry still experiences premature component failures, leading to increased operation and maintenance (O&M) costs. Among various turbine components, gearboxes—and, more broadly, drivetrains—have shown to be costly to maintain throughout the design life of a wind turbine. The problem of premature component failure is industry wide. As early as 2007, the US Department of Energy (DOE) started to address this challenge through the National Renewable Energy Laboratory’s (NREL’s) reliability initiative that first focused on gearboxes and more recently expanded to entire drivetrains. The wind turbine drivetrain condition monitoring and wind plant O&M research that is the subject of this paper is part of the NREL initiative and includes a few research and development (R&D) activities conducted during the 2010s. These activities included technology evaluation during the first few years; novel monitoring technique investigation (specifically, compact filter analysis) during the middle years; and data and physics domain modeling for fault detection and prediction in recent years. A high-level summary of these activities is provided in this paper along with some key observations from each activity. Most of the work discussed has been published and can be referred to for more information. They reflect the expected evolution of wind turbine condition monitoring and O&M in the US market—primarily, a land-based perspective. In addition, we have identified several R&D opportunities that can be picked up by the research community to help industry advance in related areas, making wind power more cost competitive in the future.

17 WIND ENERGY↗

On the Use of Aqueous Metal-Aqua p K a Values as a Descriptor of Lewis Acidity

The behavior of Lewis acidic metal ions in multimetallic systems has become a subject of intense interest in recent years. Parametrizing the behavior of these ions in non-aqueous conditions, commonly used in the field, is challenging due to the lack of direct measures of the Lewis acidity of metal ions in polar organic solvents. Here, we report the use of triphenylphosphine oxide (TPPO) as a 31 P nuclear magnetic resonance (NMR) probe to quantify the Lewis acidity of a library of metal triflate salts using the Gutmann-Beckett method. Plots of the pK a values of the corresponding metal-aqua species, [M(H 2 O) m ] n+ , measured in H 2 O vs. the 31 P NMR shifts of TPPO in the presence of these metals in deuterated acetonitrile (d3-MeCN) and deuterated dichloromethane (CD 2 Cl 2 ) display tightly co-linear relationships, suggesting similar behavior for these ions in water, d 3 -MeCN, and CD 2 Cl 2 . This collinearity reinforces the utility of the common approach of using the aqueous pK a values as a descriptor of Lewis acidity, regardless of the solvent used in the immediate experiments, and provides an insight into the usefulness of this descriptor in wide-ranging applications. Titration studies in d 3 -MeCN suggest 1:1 binding of TPPO with monovalent ions, greater than 1:1 binding with divalent ions, and formation of multiple species with the highly Lewis acidic trivalent ions. Altogether, these data suggest that both aqueous pK a values and other single-measurement descriptors, while useful, provide only a snapshot of the influence of Lewis acidity on multimetallic chemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time-dependent SOLPS-ITER simulations of the tokamak plasma boundary for model predictive control using SINDy *

Abstract Time-dependent SOLPS-ITER simulations have been used to identify reduced models with the sparse identification of nonlinear dynamics (SINDy) method and develop model-predictive control of the boundary plasma state using main ion gas puff actuation. A series of gas actuation sequences are input into SOLPS-ITER to produce a dynamic response in upstream and divertor plasma quantities. The SINDy method is applied to identify reduced linear and nonlinear models for the electron density at the outboard midplane n e , s e p O M P and the electron temperature at the outer divertor T e , s e p d i v . Note that T e , s e p d i v is not necessarily the peak value of T e along the divertor. The identified reduced models are interpretable by construction (i.e. not black box), and have the form of coupled ordinary differential equations. Despite significant noise in T e , s e p d i v , the reduced models can be used to predict the response over a range of actuation levels to a maximum deviation of 0.5% in n e , s e p O M P and 5%–10% in T e , s e p d i v for the cases considered. Model retraining using time history data triggered by a preset error threshold is also demonstrated. A model predictive control strategy for nonlinear models is developed and used to perform feedback control of a SOLPS-ITER simulation to produce a setpoint trajectory in n e , s e p O M P using the integrated plasma simulator framework. The developed techniques are general and can be applied to time-dependent data from other boundary simulations or experimental data. Ongoing work is extending the approach to model identification and control for divertor detachment, which will present transient nonlinear behavior from impurity seeding, including realistic latency and synthetic diagnostic signals derived from the full SOLPS-ITER output.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Bit-parallel arithmetic in a massively-parallel associative processor

A simple but powerful new architecture based on a classical associative processor model is presented. Algorithms for performing the four basic arithmetic operations both for integer and floating point operands are described. For m-bit operands, the proposed architecture makes it possible to execute complex operations in O(m) cycles as opposed to O(m exp 2) for bit-serial machines. A word-parallel, bit-parallel, massively-parallel computing system can be constructed using this architecture with VLSI technology. The operation of this system is demonstrated for the fast Fourier transform and matrix multiplication.

Scherson, Isaac D.↗