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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Development of a Direct Neutral Density Diagnostic for Fusion Edge Plasmas

As magnetically confined plasmas progress towards ignition and long pulse experiments, measurement and control of the neutral density in the plasma edge has become a critical issue for stability, formation of transport barriers, and fueling. Recent experiments by our research group have demonstrated that is possible to use two-photon absorption laser induced fluorescence (TA-LIF) to directly measure the density of neutral hydrogen in helicon sources and in the HIT-SI3 spheromak. While those experiments validated key elements of a diagnostic system that would enable similar measurements in tokamak plasmas, they did not fully address the issue of performance optimization in the presence of intense background light at the fluorescence wavelength and they also identified a number of other issues that must be resolved before successful TALIF neutral density measurements in a tokamak are likely to be achieved. Additional specific concerns raised during design reviews with the leadership of the DIII-D tokamak facility included: the minimum detection threshold for this TALIF diagnostic (currently ~ 5 x 10 15 m -3 ) and the rate at which neutral density measurements could be obtained. Improving the system performance to reduce the minimum detection threshold and demonstrating a faster rate of density determination are required to advance this diagnostic to the level where it could be considered for implementation on a major tokamak facility in the USA. The key issues that will be addressed through additional technological development are: validation of a new, chromatic aberration-free, xenon calibration scheme; increasing the output power of the laser; and suppression of background emission at the fluorescence wavelength through optimization of the collection optics and gating of the photomultiplier detector with a goal of obtaining a minimum detection threshold of 5 x 10 14 m -3 . Another key technological development, so far only tested in helicon source experiments, is the validation of Doppler-free TALIF as a means of obtaining higher speed, calibrated, neutral density measurements in tokamak-like conditions at the full cadence of the pulsed TALIF laser. In this work, we propose to complete these technological advancements through installation and testing of our prototype TALIF system on the proto-MPEX experiment at Oak Ridge National Laboratory (ORNL). The proto-MPEX facility will provide plasma conditions similar to the edge plasma of a major tokamak experiment but with pulse lengths and pulse repetition rates ideally suited for extensive development of a TALIF neutral density diagnostic. Measurement of the absolute neutral density in the edge of a magnetically confined plasma is necessary for plasma density control; calculation of charge-exchange power losses; control of plasma-wall interactions; determination of the braking of plasma flow; determination of the fuel mixture in deuterium-tritium plasma; and understanding the dynamics of the divertor region in the plasma edge. In terms of potential impact on the worldwide fusion program, we note that in burning plasma experiments, such as ITER, a 100 mJ/pulse Doppler-free TALIF diagnostic should be capable of directly measuring the deuterium/tritium (D/T) isotope ratio in the outer 0.5 to 1.0 m of the plasma radius. The D/T ratio is a critically important parameter for the control and optimization of burning plasmas. Therefore, development of the diagnostic system proposed here is also relevant to long-term US participation in diagnostic development for large tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Aqueous Bromide Discharges from U.S. Coal-Fired Power Plants: Points of Origin, Concentration Ranges, and Effluent Treatment Costs

Bromide discharges from coal-fired power plants have received increased attention from regulatory bodies due to their contribution to the formation of disinfection byproducts (DBPs) in downstream drinking water treatment plants. Here, this paper characterizes the relative contributions of bromide from coal feedstocks and bromine-based mercury control processes, estimates the distribution of bromide concentrations at 85 active coal-fired power plants across the United States (U.S.) with wet flue gas desulfurization units, and estimates the cost of bromide removal from wastewater discharge using year 2020 data. Bromide discharges are estimated at the plant level using a combination of the reported coal rank and composition combusted, estimates of bromide addition in mercury control techniques under multiple halogen addition scenarios, and the estimated flue gas desulfurization (FGD) wastewater flow rate. The median, simulated plant-level estimation of total FGD wastewater flow is 18.3 gallons/min at a bromide concentration of 319 mg/L, equivalent to ~11.6 tonnes/year of bromide discharges to the environment. Next, we evaluated the expected cost of employing the best available technology (BAT) to control bromide discharges in FGD wastewater to prevent contributions to DBP formation. Treatment would need to remove more than 99.8% of bromide to reach the 0.2 mg/L voluntary incentive program (VIP) limit. The total cost of treatment depends on whether disposal is on- or off-site; the average costs for all plants combined come to an average of $110 million ($95.2/kgal) in 2021 U.S. dollars for on-site disposal, or $134 million ($115/kgal) for off-site disposal.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Plasma assisted NH 3 /H 2 /air ignition in nanosecond discharges with non-equilibrium energy transfer

Ammonia (NH 3 ), with its high energy density and easiness to store and transport as a hydrogen carrier, has become a promising alternative green fuel. However, its adoption in power generation is hindered by challenges such as low burning velocity, slow low-temperature oxidation, high NO x emissions, and ignition difficulty. Here, this work computationally investigates the effects of non-equilibrium energy transfer by nanosecond discharges on NH 3 ignition and flame propagation in an NH 3 /H 2 /air flow at 700 K and 1 atm. The simulation results demonstrate that NH 3 /air mixtures require a large ignition energy due to their large critical ignition radius. It is shown that adding 30 % hydrogen significantly reduces the critical ignition radius and minimum ignition energy. Two-dimensional modeling further shows a non-monotonic dependence of ignition kernel volume on the applied voltage and reduced electric field. The optimum ignition enhancement occurs at 200 Td where the generation of electronically excited species and radicals including N 2 (B), O( 1 D) and OH becomes most efficient. Higher voltages divert electron energy toward ionization, which makes it less effective for NH 3 ignition. The study also identifies an optimal electrode gap size for a given pulse energy. Smaller gap sizes increase deposited energy density, raising temperature and radical concentrations. However, excessive reduction of the gap distance reduces flame propagation speed due to the flame stretch effect in rich mixtures with the effective Lewis number greater than unity. A nonlinear relationship between pulse repetition frequency and ignition kernel volume is observed in a nanosecond pulsed high frequency discharge (NPHFD). An optimal frequency range of 200 kHz to 2 MHz is found when two pulses are used. In addition, an optimal number of pulses exists for each pulse repetition frequency, with higher frequencies requiring more pulses to maximize the overlap region. These findings provide critical insights on developing controlled plasma discharge techniques for efficient NH 3 ignition in reactive flows within internal combustion engines and gas turbines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

New principles of self‐organization created through the interplay of DNA condensates, microtubules, and motors

Bioinspired design—which holds great promise for a new generation of materials that are robust to defects, scalable under green manufacture, environmentally responsive, and programmably reconfigurable—requires mastery over molecular self-organization. Yet, from its specific mechanisms to most general architectures, the principles governing self-organization remain poorly understood and not even fully enumerated. For living systems, one obvious architectural principle is the modular reuse of a few simple molecular components in myriad combinations to achieve more complex phenomena. For example, the mechanical tasks of a cell are driven by the nonequilibrium dynamics of cytoskeletal filaments and molecular motors—the same filaments and motors, reprogrammed by a variety of modulators, perform tasks ranging from cell movement to division. Similarly, many compartmentalization tasks are performed by liquid-like condensates of simple components, which act as membraneless organelles to localize particular molecules in space and time (e.g. for gene regulation or RNA processing). In a few cases, condensates combine and interact with the cytoskeleton to create still more complex phenomena, e.g. the nucleation of microtubule asters from the centrosome (a protein condensate) to form the mitotic spindle during cell division. Very little is known about the fundamental mechanisms of such filament-plus-condensate phenomena. Despite few examples, the landscape of behaviors that can be achieved through the combination of condensates, filaments, and motors appears vast. However, exploration has been hindered by a lack of systems that have sufficiently programmable and dynamically tunable interactions between component condensates, filaments, and motors. We proposed to combine programmable DNA condensates, filamentous microtubules, and light-controlled motors into self-organizing systems whose principles go beyond those that have been observed in nature. In one limit, our systems will use microtubules and motors to create the molecular analog of a network of roads, which will organize droplets of DNA condensates capable of carrying molecular cargo. DNA condensates coupled to motors will flow from one microtubule aster hub to another, with their direction and timing controlled by DNA circuits. In another limit, microtubules will swim through bulk DNA condensates and exhibit strong interactions with boundaries between different types of condensates. Microtubule swimmers will reflect, get trapped, or refract at boundaries, under a mechanical analog of the classical optical index of refraction. DNA condensates having different mechanical indexes of refraction will be used to construct the analog of optical lenses, so that microtubule swimmers can be manipulated like light—collimated, diffracted, focused, and sorted based on properties analogous to wavelength. These two limits define two new architectures, within which multiple new mechanistic principles for self-organization will be discovered and explored. To explore these architectures, the motor-based coupling between DNA condensates and filaments will be controlled in time and space through the use of opto-proteins that create reversible links between DNA condensates and motors upon illumination. For each principle of interest, patterns of light will create virtual experiments by defining patterns of activity where DNA condensates walk along filaments, or filaments swim through condensates, and patterns of inactivity which will serve either as controls, or as boundary conditions vital to create the desired phenomena. This research serves the goals of Basic Energy Sciences Biomolecular Material Program by elucidating the principles by which the emergent, nonequilibrium behavior of collections of DNA condensates, motors, and microtubules can be programmed by environmental light patterns to create complex motion and materials transport. Because DNA condensates can be readily coupled to virtually any high performance nanomaterial, from carbon nanotubes, to metal nanoparticles, to light harvesting systems, this work provides a path to the construction, self-maintenance and reconfiguration of materials relevant to the Department of Energy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Machine Learning for Real-time Fusion Plasma Behavior Prediction and Manipulation (Final Report)

The goal of this project is to implement real-time analysis of 2D Beam Emission Spectroscopy (BES) data to predict and control transient and high-bandwidth events at DIII-D. In essence, we wish to bring high-bandwidth fluctuation diagnostics into the realm of real-time measurements and control. The BES ML models will necessarily be deep neural networks (DNN) with a “data flow” architecture for compatibility with high-throughput, low-latency evaluation on a field-programmable gate array (FPGA) or other emerging processor technologies. The real-time output will be fed to the plasma control system (PCS) for real-time control tasks, specifically for ELM control and avoidance and for QH-mode access and sustainment. We anticipate that the real-time analysis of fluctuation diagnostics will create new enabling technologies to predict and control transient events such as confinement mode transitions, edge-localized modes, Alfven eigenmode events, and disruptions. The proposed research is aligned with ITER research needs and DIII-D programmatic goals. For instance, the prediction and avoidance of ELM events is critical for ITER machine safety. Also, H-mode access with RMP ELM suppression in ITER is an active research area due to high separatrix density, narrow SOL width, and elevated LH transition power threshold.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

ExaWind: Open‐source CFD for hybrid‐RANS/LES geometry‐resolved wind turbine simulations in atmospheric flows

Abstract Predictive high‐fidelity modeling of wind turbines with computational fluid dynamics, wherein turbine geometry is resolved in an atmospheric boundary layer, is important to understanding complex flow accounting for design strategies and operational phenomena such as blade erosion, pitch‐control, stall/vortex‐induced vibrations, and aftermarket add‐ons. The biggest challenge with high‐fidelity modeling is the realization of numerical algorithms that can capture the relevant physics in detail through effective use of high‐performance computing. For modern supercomputers, that means relying on GPUs for acceleration. In this paper, we present ExaWind, a GPU‐enabled open‐source incompressible‐flow hybrid‐computational fluid dynamics framework, comprising the near‐body unstructured grid solver Nalu‐Wind, and the off‐body block‐structured‐grid solver AMR‐Wind, which are coupled using the Topology Independent Overset Grid Assembler. Turbine simulations employ either a pure Reynolds‐averaged Navier–Stokes turbulence model or hybrid turbulence modeling wherein Reynolds‐averaged Navier–Stokes is used for near‐body flow and large eddy simulation is used for off‐body flow. Being two‐way coupled through overset grids, the two solvers enable simulation of flows across a huge range of length scales, for example, 10 orders of magnitude going from O(μm) boundary layers along the blades to O(10 km) across a wind farm. In this paper, we describe the numerical algorithms for geometry‐resolved turbine simulations in atmospheric boundary layers using ExaWind. We present verification studies using canonical flow problems. Validation studies are presented using megawatt‐scale turbines established in literature. Additionally presented are demonstration simulations of a small wind farm under atmospheric inflow with different stability states.

17 WIND ENERGY↗
DOE OSTI2022

Model predictive control for matrix converter operating in current control mode with load current estimation

A matrix converter system operating in current control mode is provided. The matrix converter includes a switching matrix coupled between a low voltage side and a high voltage side, wherein the matrix converter is coupled at its low voltage side to a generator for receiving an input power including an input current and transforming the input power into an output power at its high voltage side, wherein a load is coupled to the high voltage side. The control system includes a load observer and a model predictive controller (MPC). The load observer is configured to estimate a load current that flows to the load from the high voltage side of the matrix converter as a function of a switching state of the switching matrix, an output voltage output at the high voltage side of the matrix converter, and the input current. The MPC is configured to select the switching state of the switching matrix to meet one or more control objectives defined by minimization of a multi-objective function that tracks the output voltage and the input current using the estimated load current.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Simulation of dislocation evolution in microparticle impacts over a wide range of impact velocities

We report the dynamic loading environment created by high velocity microparticle impacts is very difficult to model. The extremely high strain rates, large deformations, and high temperatures affect the flow stress of the material in ways that standard flow stress models cannot capture. Plastic deformation and strain hardening in metals is controlled by the motion of dislocations. Dislocations can be nucleated, stored as forest dislocations, or be annihilated as loading progresses. A comprehensive accounting of dislocation density change is needed to accurately describe rate and temperature dependent dislocation glide and evolution across the wide rage of loading conditions present in microparticle impact problems. Therefore, we implement and apply a newly proposed flow stress model (Hunter and Preston, 2015, 2022) that is then coupled with mobile and immobile dislocation density evolution equations. This model is implemented in Los Alamos National Laboratory’s hydrodynamics code, FLAG, to model copper-on-copper microparticle impacts. This new strength model allows for accurate simulation of particle rebound and flattening across a wide range of impact velocities.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The revised FLORIDyn model: implementation of heterogeneous flow and the Gaussian wake

In this paper, a new version of the FLOw Redirection and Induction Dynamics (FLORIDyn) model is presented. The new model uses the three-dimensional parametric Gaussian FLORIS model and can provide dynamic wind farm simulations at a low computational cost under heterogeneous and changing wind conditions. Both FLORIS and FLORIDyn are parametric models which can be used to simulate wind farms, evaluate controller performance and can serve as a control-oriented model. One central element in which they differ is in their representation of flow dynamics: FLORIS neglects these and provides a computationally very cheap approximation of the mean wind farm flow. FLORIDyn defines a framework which utilizes this low computational cost of FLORIS to simulate basic wake dynamics. This is achieved by creating so-called observation points (OPs) at each time step at the rotor plane which inherit the turbine state. In this work, we develop the initial FLORIDyn framework further considering multiple aspects. The underlying FLORIS wake model is replaced by a Gaussian wake model. The distribution and characteristics of the OPs are adapted to account for the new parametric model but also to take complex flow conditions into account. To achieve this, a mathematical approach is developed to combine the parametric model and the changing, heterogeneous world conditions and link them with each OP. We also present a computationally lightweight wind field model to allow for a simulation environment in which heterogeneous flow conditions are possible. FLORIDyn is compared to Simulator for Offshore Wind Farm Applications (SOWFA) simulations in three- and nine-turbine cases under static and changing environmental conditions. The results show a good agreement with the timing of the impact of upstream state changes on downstream turbines. They also show a good agreement in terms of how wakes are displaced by wind direction changes and when the resulting velocity deficit is experienced by downstream turbines. A good fit of the mean generated power is ensured by the underlying FLORIS model. In the three-turbine case, FLORIDyn simulates 4 s simulation time in 24.49 ms computational time. The resulting new FLORIDyn model proves to be a computationally attractive and capable tool for model-based dynamic wind farm control.

17 WIND ENERGY↗
DOE OSTI2022

Optimal control to handle variations in moisture content and reactor in-feed rate

The variations in feedstock characteristics, such as moisture and particle size distribution, lead to an inconsistent flow of feedstock from the biomass pre-processing system to the reactor in-feed system. These inconsistencies result in low on-stream times at the reactor in-feed equipment. This research develops an optimal process control method for a biomass pre-processing system comprised of milling and densification operations to provide the consistent flow of feedstock to a reactor's throat. This method uses a mixed-integer optimization model to identify optimal bale sequencing, equipment in-feed rate, and buffer location and size in the biomass pre-processing system. This method, referred to as the hybrid process control (HPC), aims to maximize throughput over time. We compare HPC with a baseline feed forward process control. Our case study based on switchgrass finds that HPC reduces the variation of a reactor's feeding rate by up to 100% without increasing the operating cost of the biomass pre-processing system for biomass with moisture ranging from 10 to 25%. Additionally, HPC reduces the cost of processing biomass by 0.36%–2.22%, and reduces processing time by 0.35%-2.24%. Furthermore, a biorefinery can adapt HPC to achieve its design capacity.

09 BIOMASS FUELS↗
DOE OSTI2022

Simulation process and data flow for a large system dynamics model

This paper documents the workflow and supporting technologies that a large system dynamics model, the biomass scenario model, employs to streamline the data preparation, simulation, quality control, and analysis process at the National Renewable Energy Laboratory. The workflow centers on automation of routine aspects of the flow of data between data stores, simulations, and visualizations. It enforces quality checks on data, reproducibility of computations, and traceability of results, while maintaining complete archives of modeling and analysis artifacts. The resulting frictionless simulation/analysis environment supports large-scale sensitivity analysis, interactive creation of ensembles of simulations, and rapid visualization-based exploration of simulation results.

09 BIOMASS FUELS↗
DOE OSTI2023

Automatic Time Step Control to Resolve Hydromechanically Driven Fault Reactivation, Spontaneous Nucleation, and Seismic Arrest

Abstract A physical understanding of the progression from flow‐driven (quasi‐static) poromechanical deformation to dynamic fault rupture is critical to the resilient operations of several engineering systems. These processes are bridged by a progression from fault reactivation to the spontaneous nucleation of unstable sliding. Toward addressing this challenge, novel automatic time step size control methods are developed to enable accurate and efficient simulation of these dynamics and transitions from the first principles. The controllers combine local models for discretization error and Coulomb failure conditions to automatically adjust the time step size across several orders of magnitude. The methods do not require additional empirical or theoretical input and can resolve the pre‐rupture, interseismic, and seismic periods to the allowed accuracy. The computational results reveal that the proposed methods automatically capture the onset of reactivation and nucleation for homogeneous and heterogeneous fields. Hydrodynamic and structural heterogeneity lead to disparate critical nucleation sizes compared to those predicted by theory. The results highlight its potential in predicting induced seismicity in realistic subsurface engineering systems and at practical scales.

Environmental Sciences & Ecology↗
DOE OSTI2021

4D Proxy Imaging of Fracture Dilation and Stress Shadowing Using Electrical Resistivity Tomography During High Pressure Injections into a Dense Rock Formation

Fluid flow through fractured rock systems is governed in large part by the distribution, interconnectivity, and size of fracture apertures. In-situ stress is one of the primary factors controlling fracture aperture, and one that is altered significantly during high-pressure fluid injections or extractions. Interactions between stress, pore pressure, aperture, and fluid flow can result in complex and evolving poroelastic behavior with significant implications regarding the predictability and risk of developing and managing deep subsurface reservoirs (geothermal, fossil energy, and geologic carbon sequestration). In saturated crystalline rocks, bulk electrical conductivity is highly sensitive to porosity, and therefore to fracture aperture size and distribution. We demonstrate the use of time-lapse 3D electrical resistivity tomography for remotely monitoring stress induced changes in aperture distribution during high pressure injections into a fractured rock system at a scale of tens of meters. Results reveal a complex and continuously evolving stress field involving aperture dilations in the natural fracture system and aperture contractions in adjacent zones of shadow stress. Results provide information about the spatiotemporal changes in the system behavior and point to the potential of electrical imaging for autonomously and remotely monitoring evolving stress conditions by proxy through changes in bulk electrical conductivity.

electrical resisitivity tomography, stress, 4D Tim↗
DOE OSTI2020

Experimental Investigation of Hydraulic Fracturing and Stress Sensitivity of Fracture Permeability Under Changing Polyaxial Stress Conditions

Understanding and predicting fracture propagation and subsequent fluid flow characteristics is critical to geoenergy technologies that engineer and/or utilize favorable geological conditions to store or extract fluids from the subsurface. Fracture permeability decreases nonlinearly with increasing normal stress, but the relationship between shear displacement and fracture permeability is less well understood. We utilize the new Geo–Reservoir Experimental Analogue Technology (GREAT cell), which can apply polyaxial stress states and realistic reservoir temperatures and pressures to cylindrical samples and has the unique capability to alter both the magnitude and orientation of the radial stress field by increments of 11.25° during an experiment. We load synthetic analogue materials and real rock samples to stress conditions representative of 500–1,000 m depth, investigate the hydraulic stimulation process, and then conduct flow experiments while changing the fluid pressure and the orientation of the intermediate and minimum principal stresses. High–resolution circumferential strain measurements combined with fluid pressure data indicate fracture propagation can be both stable (no fluid pressure drop) and unstable (fluid pressure drop). The induced fractures exhibit both opening and shear displacements during their creation and/or during fluid flow with changing radial stress states. Flow tests during radial stress field rotation reveal that fracture normal effective stress has first–order control on fracture permeability but increasing fracture offset can lead to elevated permeabilities at maximum shear stress. Here, the results have implications for our conceptual understanding of fracture propagation as well as fluid flow and deformation around fractures.

58 GEOSCIENCES↗
DOE OSTI2024

Quantifying concentration distributions in redox flow batteries with neutron radiography

Abstract The continued advancement of electrochemical technologies requires an increasingly detailed understanding of the microscopic processes that control their performance, inspiring the development of new multi-modal diagnostic techniques. Here, we introduce a neutron imaging approach to enable the quantification of spatial and temporal variations in species concentrations within an operating redox flow cell. Specifically, we leverage the high attenuation of redox-active organic materials (high hydrogen content) and supporting electrolytes (boron-containing) in solution and perform subtractive neutron imaging of active species and supporting electrolyte. To resolve the concentration profiles across the electrodes, we employ an in-plane imaging configuration and correlate the concentration profiles to cell performance with polarization experiments under different operating conditions. Finally, we use time-of-flight neutron imaging to deconvolute concentrations of active species and supporting electrolyte during operation. Using this approach, we evaluate the influence of cell polarity, voltage bias and flow rate on the concentration distribution within the flow cell and correlate these with the macroscopic performance, thus obtaining an unprecedented level of insight into reactive mass transport. Ultimately, this diagnostic technique can be applied to a range of (electro)chemical technologies and may accelerate the development of new materials and reactor designs.

Science & Technology - Other Topics↗
DOE OSTI2024

Ultra-compact and efficient heat exchanger for solar desalination with unprecedented scaling resistance

The objective is to design, prototype, and test a heat exchanger technology with an efficiency improvement of more than 150% compared to state-of-the-art heat exchanger technology (UA/volume), with significantly improved fouling/scaling resistance at elevated temperatures (>120°C) when compared to existing technology where scaling is a major performance-limiting issue, as well as at lower operating-temperatures (~63-110°C). We now report our overall progress on the project. An ultra-compact, efficient heat exchanger geometry has been developed that can maximize surface-area-to-volume ratio so that proposed target (UA/volume). Advanced manufacturing techniques, such additive manufacturing, have made it possible to create complex structures cost effectively. In addition to traditional manufacturing methods, additive manufacturing has been successfully used for the development of high-performance geometries. These methods allow the ability to create custom surface textures, which are deployed to dramatically control wettability and create energy-gradient surfaces. These techniques allow fouling/scaling nucleation to be spatially controlled, such that as the fouling layer grows it will be broken and removed by flow forces.

42 ENGINEERING↗
DOE OSTI2022

Implications of Shear and Thermal Stratification on Wind Turbine Tip-Vortex Stability

The interaction between wind turbines in a wind farm through their wakes is a phenomenon that has been studied for decades and is still relevant today. Turbines clustered together in arrays will often operate in the wake of other upstream turbines which may lead to significant power losses and fatigue loads. For modern large-scale wind turbines, the mean shear velocity profile and thermal stratification are major components of the atmospheric boundary layer so it is important to understand their impact on near-wake development. Additionally, veer is present due to the rotation of the Earth. The impact of shear, thermal stratification and veer on the stable wake length of turbines with a dynamic control strategy is studied numerically in this work using a suite of highly resolved large-eddy simulations. Instantaneous flow fields are extracted from the simulations and used to conduct proper orthogonal decomposition (POD) and compute the mean kinetic energy fluxes by different POD modes to better understand the tip-vortex instability mechanisms. Our findings show that the dynamic pitch control scheme is able to shorten the stable wake length to about 1.5R in uniform flow. Shear can significantly affect the break up of wind turbine tip-vortices as well as the shape and stable length of the wake, whereas thermal stratification seems to only have limited contribution to the spatial development of the near-wake field. Veer causes the wake boundary to skew but has a limited impact on the wake length.

length thermal stratification↗
DOE OSTI2020

Overview of lithium injection and flowing liquid lithium results from the US–China collaboration on EAST

A multi-institutional team consisting of national labs and universities has been conducting research to understand and control the plasma-material interface (PMI) to improve long pulse discharge control and performance in the EAST device in Hefei, China. One particular focus of the group has been to evaluate the performance of different plasma-facing component (PFC) technologies and materials, particularly lithium. Flowing liquid lithium PFC technologies are currently into their third generation of development and deployment in EAST, demonstrating recycling control and mitigation of edge-localized modes (ELMs). A lithium powder dropper has also been used to control ELMs while a lithium granule injector has demonstrated ELM triggering and pacing. To support this work, the facilities at the Center for Plasma Material Interactions such as HIDRA are being commissioned and utilized to develop/test the technologies before deployment on EAST. This paper will present a summary of the collaborative lithium PMI program on EAST.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗