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At least 1,297 records · Page 72

Study on divertor detachment and pedestal characteristics in the DIII-D upper closed divertor

Abstract Experiments performed in DIII-D demonstrate that higher plasma current and heating power combined with impurity seeding facilitate the achievement of divertor detachment with a higher pedestal pressure and higher plasma performance in H-mode plasmas with a baffled closed divertor compared with an open divertor. Dedicated experiments were carried out to study the impact of power, plasma current and impurity seeding on divertor detachment with ion B × ∇ B directed into the divertor favorable for the L–H transition. With a factor of three variation in heating power and with only D 2 puffing, no significant difference in the separatrix density at detachment onset was found. The higher heating power leads to higher impurity concentration and wider scrape-off layer (SOL) width, and reduces the detachment onset density to one similar to that in lower-power plasmas. Higher current requires higher pedestal and line-averaged densities to achieve divertor detachment; however, the increase in separatrix density at increasing plasma current is found to be less pronounced. Initial calculations found that both power scan and plasma current scan datasets are qualitatively consistent with theory after considering the change in impurity concentration and heat flux width. This also motivates the future extensive study of transport and divertor impurity behavior in order to have a quantitative comparison between experiment and theory. Compared with an open divertor, a closed divertor facilitates detachment onset at ∼40% lower line-averaged plasma density. Additional N 2 seeding facilitates the achievement of detachment at a lower separatrix density and thus a higher pedestal temperature, which is beneficial for advanced tokamak scenarios. Higher heating power requires a higher N 2 puffing rate to achieve the same degree of detachment, while a higher N 2 puffing rate leads to lower detachment onset line-averaged density, both of which agree with theory. In contrast to the narrower pedestal in an open divertor approaching detachment, the pedestal density width in a closed divertor increases with density. The density gradient increases with line-averaged density at higher plasma current, but remains nearly unchanged at lower plasma current. In particular, compared with discharges with low power, at high heating power the pedestal density gradient is much weaker, while the SOL density is significantly higher and wider. At the same plasma current, both pedestal pressure gradient and temperature gradient decrease linearly with the line-averaged density but remain similar across different heating powers. Even with different plasma current and heating power, the normalized pressure gradient remains identical. As a result, achievement of divertor detachment with a higher pedestal pressure and higher plasma performance is shown in a closed divertor, which is important for improving core–edge integration as one of the critical issues for future tokamak fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Enhanced Component Performance Study: Turbine Driven Pumps 1998–2022

This report presents an enhanced performance evaluation of turbine driven pumps (TDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2022 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The TDP failure modes considered for standby systems are fail to start (FTS), fail to run (FTR) for one hour of operation (FTR=1H), FTR after one hour of operation (FTR>1H), and for normally running systems FTS and FTR. An eight hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10 year period while yearly estimates for reliability are provided for the entire study period. No increasing trends were identified for TDPs for the most recent 10 year period: The following decreasing trends were identified for TDPs for the most recent 10 year period: • Standby TDP FTR>1H failure rate • Normally running TDP FTR failure rate • Standby TDP unavailability • Standby MDP total unreliability (8-hour mission) • Standby TDP frequency of start demands (demands per reactor year) • Standby TDP frequency of FTR=1H hours (hours per reactor year) • Standby TDP frequency of FTR>1H events (failures per reactor year) • Normally running TDP frequency of start demands • Normally running TDP frequency of run hours • Normally running TDP frequency of FTR events.

99 GENERAL AND MISCELLANEOUS↗

Characterization of Arsenic and Selenium in Coal Fly Ash to Improve Evaluations for Disposal and Reuse Potential (Final Technical Report)

Coal fly ash is a high volume waste material that is discarded in landfills and surface water impoundments across the U.S. and is also widely recycled for a variety of applications. The leaching of potential of contaminants of concern, such as arsenic (As) and selenium (Se), is often the driver of risk assessments for coal ash disposal and reuse. The extent of leachable As and Se depends on several factors related to environmental conditions and fly ash characteristics. Previous studies employed various methods to delineate the concentration, chemical form, and distribution of As and Se in fly ash materials. However, few studies have attempted to directly correlate these properties to mobilization parameters relevant to disposal and reuse. Instead, the coal residuals industries often rely upon standardized leaching protocols that can be laborious or involve hazardous chemicals. The goals of the project were to: 1) Develop and evaluate a characterization protocol that can be used to screen fly ash samples for leachability of As and Se; 2) Characterize As, Se, and associated constituents of fly ash particles at multiple length scales (nanometer to micrometer) to determine if elemental associations differ as a function of the resolution of characterization; and 3) Establish a predictive model for the chemical composition of coal ash produced annually at major U.S. coal fired power facilities on 50-year national coal supply records. For the first objective, we performed leaching experiments with 52 fly ash samples collected from 15 different U.S. power plants and representing coal feedstocks from the three major domestic coal regions. For this work, we assessed the mobilization potential of As and Se in fly ash based on standardized leaching protocols and performed multivariate and lasso regression analyses to explore correlations of leachable As and Se contents with characteristics such as major element contents, loss on ignition (LOI) and pH. The results of regression models indicated that major elements (Fe, Ca, Al) for a wide range of fly ashes can serve as predictor variables for the leaching potential of As, but not for Se. LOI and pH were not important predictive variables in the models. Both regression approaches resulted in relatively strong fits for leachable As (correlation coefficient R 2 = 0.78 for both models) compared to models for leachable Se (R 2 = 0.49). Overall, these results suggest that correlation models combined with on-site elemental analysis with portable analyzers may enable a screening method for leachable As in coal ash. For the second objective, we utilized nanoscale 2-D imaging (30-50 nm spot size) with the Hard X-ray Nanoprobe (HXN) in combination with microprobe X-ray capabilities (~5 µm resolution) to determine As and Se elemental associations in fly ash particles. Speciation of As and Se was also measured at the nano- to microscale with X-ray absorption spectroscopy. The enhanced resolution of HXN showed As and Se that were diffusely located around or comingled with Ca- and Fe-rich particles. The results also showed nanoparticles of Se attached to the surface of fly ash grains. Overall, a comparison of As and Se species across scales highlights the heterogeneity and complexity of chemical associations for these trace elements of concern in coal fly ash. For the final objective, we developed a predictive model for major element composition of coal ash in reserve at disposal sites of major U.S. coal fired power plants. This model was constructed from coal purchase records of 705 power stations from 1973-2022 and was trained on coal ash composition data showing that coal ash elemental composition is strongly associated with the source of feedstock coal. The model showed regional shifts in the major element contents of ash produced by power plants in the last 50 years, particularly for calcium and iron (expressed as %CaO and %Fe 2 O 3 ), as coal-fired power stations changed their source of coal over this time frame. Our approach enables an estimation of coal ash chemical composition that is stored in waste impoundments at individual power stations. Such information can help delineate the regional market potential for material applications that would utilize coal ash harvested from disposal sites across the U.S.

01 COAL, LIGNITE, AND PEAT↗

Nonlinear controller for nonlinear wave energy converters

The present invention is directed to a nonlinear controller for nonlinear wave energy converters (WECs). As an example of the invention, a nonlinear dynamic model is developed for a geometrically right-circular cylinder WEC design for the heave-only motion, or a single degree-of-freedom (DOF). The linear stiffness term is replaced by a nonlinear cubic hardening spring term to demonstrate the performance of a nonlinear WEC as compared to an optimized linear WEC. By exploiting the nonlinear physics in the nonlinear controller, equivalent power and energy capture, as well as simplified operational performance is observed for the nonlinear cubic hardening spring controller when compared to an optimized linear controller.

Wilson, David G.↗

GridOPTICS/GridPACK

GridPACK is a software framework consisting of a set of modules designed to simplify the development of programs that model the power grid and run on parallel, high performance computing platforms. It also contains several fully developed applications, including powerflow, dynamic simulation, state estimation, Kalman filter analysis (dynamic state estimation), contingency analysis and real time path rating. These applications can be used either standalone or as components in more complicated workflows that combine several different types of application together. The framework modules are available as a combination of libraries and software templates and consist of components for setting up and distributing power grid networks, support for modeling the behavior of individual buses and branches in the network, converting the network models to the corresponding algebraic equations, and parallel routines for manipulating and solving large algebraic systems. The framework also contains a module for distributing tasks evenly amongst computing resources, even if individual tasks vary widely in their execution times. Additional modules support input and output, basic statistical analysis of contingency based calculations, distributed data structures, as well as basic profiling and error management.

Palmer, Bruce↗

Modeling a High-Temperature Electrochemically Driven Water-Gas-Shift Process Using a Mixed-Conducting Membrane without External Electrical Power

This paper develops a model to predict and interpret the performance of an elevated-temperature, electrochemical, membrane-assisted, water-gas-shift process. The process uses separated feed streams of H 2 O and CO to produce separated streams of H 2 and CO 2 , without an external electrical power source. The dense ceramic membrane is mixed ionic-electronic-conducting (MIEC) gadolinium-doped ceria (GDC) and the porous composite electrodes are Ni-YSZ. At elevated temperature, GDC conducts both oxygen ions and small polarons. The present process uses chemical potential to drive the process. Electrochemical oxidation of CO proceeds within the composite anode and H 2 O reduction proceeds within the composite cathode. At high temperature (e.g., T > 700 °C), GDC has significant electronic leakage in the form of a reduced-cerium small polaron, which supports the charge-transfer reactions. In a typical electrolyzer or fuel cell, this leakage is significantly problematic. However, the present process depends on the leakage current to complete the electrochemical circuit. Model development and validation is based on measured material properties and reactor performance. Potential applications include using CO-rich blast-furnace off gases in steel processing, producing separated streams of H 2 and CO 2 .

Zhu, Huayang↗

Metamorphic Epitaxy Solutions for Thermophotovoltaic and Laser Power Conversion Applications

Metamorphic GaInAs enables photovoltaic devices optimized for a wide range of bandgaps between 0.35 and 1.41 eV. We have developed compositionally graded buffers made of GaInP and AlGaInAs to enable growth of these devices on GaAs substrates with low dislocation densities and high performance. We present results for devices grown on both graded buffer materials with device bandgaps in the range 0.58-1.41 eV and compare the benefits and drawbacks of each material system. These results enable high performance for applications such as thermophotovoltaics and optical power transmission using high power lasers.

III-V↗

Extending Power of Nature from Binary Problems to Real-Valued Graph Learning in Real World

Nature performs complex computations constantly at clearly lower cost and higher performance than digital computers. It is crucial to understand how to harness the unique computational power of nature in Machine Learning (ML). In the past decade, besides the development of Neural Networks (NNs), the community has also relentlessly explored nature-powered ML paradigms. Although most of them are still predominantly theoretical, a new practical paradigm enabled by the recent advent of CMOS-compatible room-temperature nature-based computers has emerged. By harnessing the nature's power of entropy increase, this paradigm can solve binary learning problems delivering immense speedup and energy savings compared with NNs, while maintaining comparable accuracy. Regrettably, its values to the real world are highly constrained by its binary nature. A clear pathway to its extension to real-valued problems remains elusive. This paper aims to unleash this pathway by proposing a novel end-to-end Nature-Powered Graph Learning (NP-GL) framework. Specifically, through a three-dimensional co-design, NP-GL can leverage the nature's power of entropy increase to efficiently solve real-valued graph learning problems. Experimental results across 4 real-world applications with 6 datasets demonstrate that NP-GL delivers, on average, 6970X speedup and 10^5x energy consumption reduction with comparable or even higher accuracy than Graph Neural Networks (GNNs).

artificial intelligence↗

A physics-based parametric regression approach for feedwater pump system diagnosis

Here in this paper, we assessed the performance of a model-based approach for fault diagnosis of a nuclear power plant feedwater pump system. Physics-based models were constructed to monitor the performance of the system components. Plant data were used for the calibration of the models and subsequently in the diagnosis of abnormal events. We considered two real-time events representing scenarios of a pump fault and component performance degradation. The two events were correctly diagnosed, and the results demonstrated the high detection sensitivity of the physics-based models. Various sensor fault scenarios were simulated to show the capability of the approach to detect and uniquely identify sensor faults. Results for a scenario in which the plant operated in flexible power mode also showed that the diagnostic approach is insensitive to changes of operating conditions, which is one of the advantages of the model-based approach using physics-based models over purely data-driven approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Carbon decorated Li 3 V 2 (PO 4 ) 3 for high-rate lithium-ion batteries: Electrochemical performance and charge compensation mechanism

Fast charging and high-power delivering batteries are highly demanded in mobile electronics, electric vehicles and grid energy storage, but there are full of challenges. The star-material Li 3 V 2 (PO 4 ) 3 is demonstrated as a promising high-rate cathode material meeting the above requirements. Herein, we report the carbon decorated Li 3 V 2 (PO 4 ) 3 (LVP/C) cathode prepared via a facile method, which displays a remarkable high-rate capability and long-term cycling performance. Briefly, the prepared LVP/C delivers a high discharge capacity of 122 mAh g -1 (~93% of the theoretical capacity) at a high rate up to 20 C and a superior capacity retention of 87.1% after 1000 cycles. Importantly, by applying a combination of X-ray absorption spectroscopy and full-range mapping of resonant inelastic X-ray scattering, we clearly elucidate the structural and chemical evolutions of LVP upon various potentials and cycle numbers. Furthermore, we show unambiguous spectroscopic evidences that the evolution of the hybridization strength between V and O in LVP/C as a consequence of lithiation/delithiation is highly reversible both in the bulk and on the surface during the discharge-charge processes even over extended cycles, which should be responsible for the remarkable electrochemical performance of LVP/C. Our present study provides not only an effective synthesis strategy but also deeper insights into the surface and bulk electrochemical reaction mechanism of LVP, which should be beneficial for the further design of high-performance LVP electrode materials.

25 ENERGY STORAGE↗

Boosting the Performance of Plug-and-Play Priors via Denoiser Scaling

Plug-and-play priors (PnP) is an image reconstruction framework that utilizes an image denoiser as an imaging prior. Unlike traditional regularized inversion, PnP does not require the prior to be expressible in the form of a regularization function. This flexibility enables PnP algorithms to exploit the most effective image denoisers, leading to their state-of-the-art performance in various imaging tasks. However, many powerful denoisers, such as the ones based on convolutional neural networks (CNNs), do not have tunable parameters that would allow controlling their influence within PnP. To address this issue, in this paper, we introduce a scaling parameter that adjusts the magnitude of the denoiser input and output. We theoretical justify the denoiser scaling from the perspectives of proximal optimization, statistical estimation, and consensus equilibrium. Finally, we provide numerical experiments demonstrating the ability of denoiser scaling to systematically improve the performance of PnP for denoising CNN priors that do not have explicitly tunable parameters.

Boosting↗

High-performance windows improve thermal survivability of occupants during cold snaps

Exposure to low indoor air temperature is a major contributor to temperature-related mortality during extreme cold events, especially when power outages disrupt operation of space heating systems. This study explores the impact of high-performance windows on the thermal resilience of residential buildings during extreme cold weather and grid power outages, as well as their long-term benefits through energy efficiency and reduced risk of property damage. Building performance simulations were conducted for reference residential buildings in three construction vintages and two major U.S. cities located in cold climate zones, considering two types of extreme cold events: short and severe, and long and milder. Our research found that even houses compliant with current energy codes struggle to maintain safe indoor temperatures for more than a few hours during power outages, necessitating rapid evacuations. High-performance windows can extend the thermal survivability time by up to 3.8 days within a 7-day cold snap and significantly reduce risk of bursting frozen water pipes, depending on the building’s insulation and infiltration level, cold event severity, and occupant vulnerability. This extended thermal safety time is crucial in scenarios where reduced mobility complicates emergency responses in senior housing. In addition to boosting thermal resilience, upgrading older homes with high-performance windows can reduce heating energy consumption by over 18% and cooling energy by 15%. Our findings highlight the need to incorporate thermal resilience assessments into new designs or major retrofits, including the use of typical and extreme weather scenarios and advanced technologies like high-performance windows.

Krelling, Amanda F↗

DIII-D research to provide solutions for ITER and fusion energy

The DIII-D tokamak has elucidated crucial physics and developed projectable solutions for ITER and fusion power plants in the key areas of core performance, boundary heat and particle transport, and integrated scenario operation, with closing the core-edge integration knowledge gap being the overarching mission. New experimental validation of high-fidelity, multi-channel, non-linear gyrokinetic turbulent transport models for ITER provides strong confidence it will achieve Q ≥ 10 operation. Experiments identify options for easing H-mode access in hydrogen, and give new insight into the isotopic dependence of transport and confinement. Analysis of 2,1 islands in unoptimized low-torque IBS demonstration discharges suggests their onset time occurs randomly in the constant β phase, most often triggered by non-linear 3-wave coupling, thus identifying an NTM seeding mechanism to avoid. Pure deuterium SPI for disruption mitigation is shown to provide favorable slow cooling, but poor core assimilation, suggesting paths for improved SPI on ITER. At the boundary, measured neutral density and ionization source fluxes are strongly poloidally asymmetric, implying a 2D treatment is needed to model pedestal fuelling. Detailed measurements of pedestal and SOL quantities and impurity charge state radiation in detached divertors has validated edge fluid modelling and new self-consistent 'pedestal-to-divertor' integrated modeling that can be used to optimize reactors. New feedback adaptive ELM control minimizes confinement reduction, and RMP ELM suppression with sustained high core performance was obtained for the first time with the outer strike point in a W-coated, compact and unpumped small-angle slot divertor. Advances have been made in integrated operational scenarios for ITER and power plants. Wide pedestal intrinsically ELM-free QH-modes are produced with more reactor-relevant conditions, Low torque IBS with W-equivalent radiators can exhibit predator-prey oscillations in Te and radiation which need control. High-β P scenarios with q min > 2, q 95 –7.9, β N > 4, β T –3.3% and H 98y2 > 1.5 are sustained with high density ($\overline{n}$ = 7E19 m -3 , f G –1) for 6 τ E , improving confidence in steady-state tokamak reactors. Diverted NT plasmas achieve high core performance with a non-ELMing edge, offering a possible highly attractive core-edge integration solution for reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Comparative assessment of neutron flux sensor technologies for advanced reactors

This report documents the comparative assessment of the rhodium-based self-powered neutron detectors (Rh-SPND), micro-pocket fission detectors (MPFD), and dosimetry wires in heated irradiations at the Neutron Radiography reactor facility at Idaho National Laboratory. The sensors performances are evaluated high-temperature environments (upwards of 850°C) during maximum reactor power to simulate use in advanced reactor applications. The performance of the Rh-SPNDs indicates the experiment cartridge heater power supply interferes with the SPND signals. This interference become increasingly significant at temperatures above 500°C with minimal interference observed for temperatures below 500°C. This work also demonstrated the fabrication process for the updated design of the MPFD, but issues related to the seal welds were identified and usable data was limited. Finally, the dosimetry measurements were within the expected range correlated with reactor power; thus, the dosimetry results were used to provide preliminary SPND calibration factors. The results from this experiment serves as a reference for developing and testing of flux sensors that are designed for high-temperature irradiations and advanced reactor deployments. This includes upcoming FY22 irradiations at the Massachusetts Institute of Technology Reactor and the Neutron Radiography (NRAD) reactor utilizing additional fission chambers from Photonis Technologies and fission chambers and SPNDs from The French Alternative Energies and Atomic Energy Commission.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An Uncertainty-Informed and High-Fidelity Performance Forecasting Framework for Heliostat Fields

Concentrating Solar Thermal (CST) tower systems employ heliostat fields to direct solar energy to a central receiver, which then transfers the heat either directly to a thermal process (e.g., steam production) or to a thermal energy storage system for future use. Heliostat fields compose a significant proportion of the project costs of a CST tower system and the performance of the heliostats determines a plant's productivity at a given location. While CST characterization tools such as SolarPILOT and System Advisor Model (SAM) include a large collection of inputs that influence the performance of a CST tower system, many are uncertain prior to the development of the project and may have a significant impact on the overall energy delivery and profitability of a project; moreover, the fidelity of these models under default conditions may be insufficient to determine the value of component improvements such as those under development in the Heliostat Consortium. This work introduces a Monte Carlo simulation framework that incorporates uncertainty in key performance parameters to generate confidence intervals and percentile estimates for a CST solar field's energy delivery.

14 SOLAR ENERGY↗

An Effective Current Balancing Method for Inverters With Paralleled Silicon Carbide Power Modules

Silicon carbide (SiC) MOSFET has many superior characteristics in high power applications. Paralleling the SiC devices is an effective approach to increase the current capacity of the system, which also leads to current sharing issues. In this article, both transient and steady-state current sharing issues are studied for the high-power grid-tied inverters with paralleled SiC modules with an effective current balancing strategy proposed to address both issues simultaneously. The steady-state imbalance current due to the parameter mismatch is suppressed by the self-inductance of power cables used for paralleling connection. With the elimination of steady-state imbalance current, the transient imbalance current sensing is much simplified and can be realized by using low-cost current sensors. With the sensed imbalance current, a closed-loop control approach is proposed to adjust the modulation reference signal for each module to mitigate the remaining transient imbalance current. Furthermore, the proposed method is straightforward to implement with enhanced compatibility and flexibility compared to existing methods. Experimental studies are performed using inverters with 2 and 4 power modules paralleled in each phase to demonstrate the effectiveness of the proposed method.

42 ENGINEERING↗

Integration of Superconducting Magnetic Energy Storage (SMES) Systems Optimized with Second-Generation, High-Temperature Superconducting (2G-HTS) Technology with a Major Fossil-Fueled Asset

Utility companies and fossil fueled generation assets are seeking combinations of “hybrid energy storage” to allow power to be provided in advance of, and to otherwise complement, peaking natural gas-fired generation. American Maglev Technology of Florida Inc. (AMT) learned during the Phase I program based on interactions with NRG Energy (NRG) that energy storage such as superconducting magnetic energy storage (SMES) can qualify as a Black Start unit in most markets, ensuring orderly re-start of grid operations and fossil fueled power plants and serving as an important asset of hybrid energy storage technology. In conjunction with the University of Houston (UH), AMT and NRG are working together to scale up low-cost, high- efficiency, second-generation high-temperature superconducting (2G-HTS) technology for deployment across several markets, with a primary focus on the commercial development of utility grid-scale SMES (g-SMES) systems. Ultimately the program confirmed that the novel g-SMES design can meet the performance and financial requirements of the fossil power plant industry, while exhibiting continuous grid-voltage regulation; cost-effective, peak-hour energy storage with almost infinite life; increased input/output efficiency; and the capability to undergo millions of charging cycles, without degradation, representing a significant improvement over lithium ion and other conventional storage technologies. We believe wide scale deployment of this technology is feasible and practical when compared to the higher life cycle cost and relatively short lifespan of chemical batteries. Based on these findings, the future for deployment of SMES at many fossil-fueled power plants exceeding 100MW capability is bright. Further de-risking g-SMES technology would pave the way for the construction of a subscale prototype. Eventually, scaled-down versions of SMES are expected to be competitive with the multi-billion-dollar lithium-ion market for a wide range of commercial, industrial, and transportation uses. There is long-term potential for commercialization and widespread deployment of this disruptive technology, which would spawn a new worldwide supply chain and create domestic, high-tech manufacturing jobs in the green industry.

20 FOSSIL-FUELED POWER PLANTS↗

Pathways to the Next-Generation Power System With Inverter-Based Resources: Challenges and recommendations

Managing the stability of today's electric power systems is based on decades of experience with the physical properties and control responses of large synchronous generators. Today's electric power systems are rapidly transitioning toward having an increasing proportion of generation from nontraditional sources, such as wind and solar (among others), as well as energy storage devices, such as batteries. In addition to the variable nature of many renewable generation sources (because of the weather-driven nature of their fuel supply), these newer sources vary in size - from residential-scale rooftop systems to utility-scale power plants - and they are interconnected throughout the electric grid, both from within the distribution system and directly to the high-voltage transmission system. Most important for our purposes, many of these new resources are connected to the power system through power electronic inverters. Collectively, we refer to these sources as inverter-based resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗