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Cost decomposition of linear systems with application to model reduction

A means is provided to assess the value or 'cst' of each component of a large scale system, when the total cost is a quadratic function. Such a 'cost decomposition' of the system has several important uses. When the components represent physical subsystems which can fail, the 'component cost' is useful in failure mode analysis. When the components represent mathematical equations which may be truncated, the 'component cost' becomes a criterion for model truncation. In this latter event component costs provide a mechanism by which the specific control objectives dictate which components should be retained in the model reduction process. This information can be valuable in model reduction and decentralized control problems.

Skelton, R. E.↗

Small-Scale Interstellar Structure Toward the Open Cluster CHI Persei-Fuse II

The purpose of this study was to measure the physical conditions of gas along sight lines toward 6 stars in the core Chi Persei open cluster. These sight lines traverse gas in both the Orion and Perseus spiral arms of the Galaxy, at distances of 500 and 2000 pc, respectively. The stars have angular separations ranging from 45 to 280 arcsec; 60 arcsec corresponds to linear distances of 0.15 and 0.6 pc in the two arms. Thus, abundance variations in these observations would constitute evidence for small-scale variations in the properties of the interstellar medium. Ground-based Na I observations at high resolution (approx. 15 km/sec) toward 172 stars (including the 6 in this study) in the double open cluster h and Chi Persei have revealed complex spatial variation. These variations are especially evident in the gas at velocities of -40 and -55 km/sec, corresponding to the Perseus spiral arm. 21 cm observations of HI emission using the Low Resolution DRAO Survey, with a 12-arcmin beam, also show variations. Averaging the Na I apparent optical depth profiles of neighboring sight lines in order to mimic such a beam size reduces the variation, as compared to the individual Na I measurements, but still show variations larger than seen in the 21 cm profiles. Na I is not the dominant ionization state of Na in the interstellar medium. Thus, it is possible that the variations seen really trace physical structures in the interstellar medium, or they may simply result from variations in the radiation field seen by the gas, or be due to some other environmental circumstance. To distinguish among these possibilities in the present study we obtained FUSE spectra toward the 6 targets in order to measure the molecular hydrogen absorption profiles along these sight lines. The higher J states of H2 are populated by the ambient W radiation field, and thus can provide insight into the environment affecting the gas. If both the high and low J states reveal absorption line profiles with variations similar to that observed in Na I, this would indicate that the variations are due to real structures in the interstellar medium. On the other hand, if the only the high J profiles mimicked the Na I profiles, then the variations may be attributable to environmental effects. We found that the H2 profiles showed considerable variation over the 6 sight lines, and that the profiles, despite having somewhat lower velocity resolution, resemble the Na I profiles. Thus, it appears that the gas really does exhibit variations in physical structures along these sight lines. Useful follow-up work would be to obtain higher signal-to-noise FUSE observations of H2, since the present data are of only moderate quality, and to obtain data on additional targets in this double cluster, in order to map out in more detail the extent and magnitude of the small-scale variations.

Sonneborn, George↗

Quantum-enhanced distributed phase sensing with a truncated SU(1,1) interferometer

In recent years, distributed quantum sensing has gained interest for a range of applications requiring networks of sensors, from global-scale clock synchronization to high energy physics. In particular, a network of entangled sensors can improve not only the sensitivity beyond the shot noise limit, but also enable a Heisenberg scaling with the number of sensors. Here, using bright entangled twin beams, we theoretically and experimentally demonstrate the detection of a linear combination of two distributed phases beyond the shot noise limit with a truncated SU(1,1) interferometer. Specifically, we show a quantum noise reduction of 1.7 ± 0.3 dB below what is possible with the corresponding classical configuration. Additionally, we theoretically extend the use of a truncated SU(1,1) interferometer to a multi-phase-distributed sensing scheme that leverages entanglement as a resource to achieve a quantum improvement in the scaling with the number of sensors in the network. Our results pave the way for developing quantum-enhanced sensor networks that can achieve an entanglement-enhanced sensitivity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High-Temperature Linear Receiver Enabled by Multicomponent Aerogels

Concentrating solar thermal (CST) technology has significant potential mainly due to its dispatchability and low cost of storage. However, to compete with other sources, including utility-scale solar PV, its final cost (cents/kWh) still needs to be lowered. Cost reduction can be achieved by improving the system level efficiency of the CST plants through the deployment of advanced power cycles, which operate at high temperatures of ~700°C. However, optical, and thermal losses pose a major challenge to the efficiency of such CST systems. The overall aim of this project is to investigate and de-risk a linear solar receiver concept called an Aerogel Insulated Receiver (AIR) that generates high temperatures (up to 700°C) at a low solar concentration ratio (<100) and with a high collection efficiency (optical × receiver). Our prior work has demonstrated the thermal stability1 and optical and heat-insulating properties2,3 of transparent aerogel insulation at a one-inch scale. The focus of this work is on (1) co-optimization of the geometry of the aerogel tile and receiver enclosure to fit a standard parabolic collector (PTC), (2) scale-up of aerogels into 4-inch tiles while preserving key properties, (3) experimental measurement of receiver heat loss (W/m) in a >70-cm test stand and validation of anticipated receiver performance at high temperatures. Regarding (1), appropriate optical and thermal models for a parabolic trough receiver (PTR) are developed and validated. The geometry of the aerogels and the receiver enclosure are co-optimized to maximize the collection efficiency. The model predicts a 54% collection efficiency at 700°C for an AIR design based on flat aerogels. By combining the collection efficiency with the power block efficiency of supercritical CO 2 cycles, we predict >10% improvements in peak plant efficiency relative to existing line-focusing CST systems. The application of curved plasmonic aerogels is predicted to further increase the collection efficiency to 64%. Regarding (2), we demonstrate the successful development of 6-inch-long refractory aerogel tiles with optical, thermal, and stability characteristics consistent with our prior work. This scale-up requires a transition to a larger ALD station and modifying the ALD process variables such as exposure time and the number of precursor doses. Regarding (3), we design and develop an AIR test stand measuring 3 feet in length. Heat loss performance analysis is carried out using the test stand. The results indicate that aerogel insulation can significantly reduce receiver thermal losses at the high operating temperatures required for next-generation PTRs. The experimental results agree with the heat loss performance predicted by our receiver model. Lastly, we conducted preliminary failure mode and effects (FMEA) and techno-economic (TEA) analyses to identify failure mitigation strategies and commercial opportunities, respectively. Overall, this project identifies key opportunities and challenges in deploying aerogel insulating receivers in next-generation line-focusing CST technologies.

14 SOLAR ENERGY↗

Improving deep learning performance for predicting large-scale geological ${{CO}_{2}}$ sequestration modeling through feature coarsening

Physics-based reservoir simulation for fluid flow in porous media is a numerical simulation method to predict the temporal-spatial patterns of state variables (e.g. pressure p) in porous media, and usually requires prohibitively high computational expense due to its non-linearity and the large number of degrees of freedom (DoF). This work describes a deep learning (DL) workflow to predict the pressure evolution as fluid flows in large-scale 3-dimensional(3D) heterogeneous porous media. In particular, we develop an efficient feature coarsening technique to extract the most representative information and perform the training and prediction of DL at the coarse scale, and further recover the resolution at the fine scale by spatial interpolation. We validate the DL approach to predict pressure field against physics-based simulation data for a field-scale 3D geologic CO 2 sequestration reservoir model. We evaluate the impact of feature coarsening on DL performance, and observe that the feature coarsening not only decreases the training time by >74% and reduces the memory consumption by >75%, but also maintains temporal error 0.63% on average. Besides, the DL workflow provides predictive efficiency with 1406 times speedup compared to physics-based numerical simulation. The key findings from this research significantly improve the training and prediction efficiency of deep learning model to deal with large-scale heterogeneous reservoir models, and thus it can also be further applied to accelerate workflows of history matching and reservoir optimization for close-loop reservoir management.

58 GEOSCIENCES↗

Spatial and Temporal Scaling of Thermal Infrared Remote Sensing Data

Although remote sensing has a central role to play in the acquisition of synoptic data obtained at multiple spatial and temporal scales to facilitate our understanding of local and regional processes as they influence the global climate, the use of thermal infrared (TIR) remote sensing data in this capacity has received only minimal attention. This results from some fundamental challenges that are associated with employing TIR data collected at different space and time scales, either with the same or different sensing systems, and also from other problems that arise in applying a multiple scaled approach to the measurement of surface temperatures. In this paper, we describe some of the more important problems associated with using TIR remote sensing data obtained at different spatial and temporal scales, examine why these problems appear as impediments to using multiple scaled TIR data, and provide some suggestions for future research activities that may address these problems. We elucidate the fundamental concept of scale as it relates to remote sensing and explore how space and time relationships affect TIR data from a problem-dependency perspective. We also describe how linearity and non-linearity observation versus parameter relationships affect the quantitative analysis of TIR data. Some insight is given on how the atmosphere between target and sensor influences the accurate measurement of surface temperatures and how these effects will be compounded in analyzing multiple scaled TIR data. Last, we describe some of the challenges in modeling TIR data obtained at different space and time scales and discuss how multiple scaled TIR data can be used to provide new and important information for measuring and modeling land-atmosphere energy balance processes.

Quattrochi, Dale A.↗

Kinetic Scale Structure of Low-Frequency Waves and Fluctuations

The dissipation of solar wind turbulence at kinetic scales is believed to be important for the heating of the corona and for accelerating the wind. The linear Vlasov kinetic theory is a useful tool for identifying various wave modes, including kinetic Alfven, fast magnetosonic/whistler, and ion-acoustic (or kinetic slow), and their possible roles in the dissipation. However, the kinetic mode structure in the vicinity of ion-cyclotron modes is not clearly understood. The present paper aims to further elucidate the structure of these low-frequency waves by introducing discrete particle effects through hybrid simulations and Klimontovich formalism of spontaneous emission theory. The theory and simulation of spontaneously emitted low-frequency fluctuations are employed to identify and distinguish the detailed mode structures associated with ion-Bernstein modes versus quasi-modes. The spontaneous emission theory and simulation also confirm the findings of the Vlasov theory in that the kinetic Alfven waves can be defined over a wide range of frequencies, including the proton cyclotron frequency and its harmonics, especially for high-beta plasmas. This implies that these low-frequency modes may play predominant roles even in the fully kinetic description of kinetic scale turbulence and dissipation despite the fact that cyclotron harmonic and Bernstein modes may also play important roles in wave-particle interactions.

waves↗

Compare linear-system solver and preconditioner stacks with emphasis on GPU performance and propose phase-2 NGP solver development pathway

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. In this report we evaluated GPU-performance baselines for the linear solvers in the Trilinos and hypre solver stacks using two representative Nalu-Wind simulations: an atmospheric boundary layer precursor simulation on a structured mesh, and a fixed-wing simulation using unstructured overset meshes. Both strong-scaling and weak-scaling experiments were conducted on the OLCF supercomputer Summit and similar proxy clusters. We focused on the performance of multi-threaded Gauss-Seidel and two-stage Gauss-Seidel that are extensions of classical Gauss-Seidel; of one-reduce GMRES, a communication-reducing variant of the Krylov GMRES; and algebraic multigrid methods that incorporate the afore-mentioned methods. The team has established that AMG methods are capable of solving linear systems arising from the fixed-wing overset meshes on CPU, a critical intermediate result for ExaWind FY20 Q3 and Q4 milestones. For the fixed-wing strong-scaling study (model with 3M grid-points), the team identified that Nalu-Wind simulations with the new Trilinos and hypre solvers scale to modest GPU counts, maintaining above 70% efficiency up to 6 GPUs. However, there still remain significant bottlenecks to performance: matrix assembly (hypre), AMG setup (hypre and Trilinos) In the weak-scaling experiments (going from 0.4M to 211M gridpoints), it's shown that the solver apply phases are faster on GPUs, but that Nalu-Wind simulation times grow, primarily due to the multigrid-setup process. Finally, based on the report outcomes, we propose a linear solver path-forward for the remainder of the ExaWind project. Near term, the NREL team will continue their work on GPU-based linear-system assembly. They will also investigate how the use of alternatives to the NVIDIA UVM (unified virtual memory) paradigm affects performance. Longer term, the NREL team will evaluate algorithmic performance on other types of accelerators and merge their improvements back to the main hypre repository branch. Near term, the Trilinos team will address performance bottlenecks identified in this milestone, such as implementing a GPU-based segregated momentum solve and reusing matrix graphs across linear-system assembly phases. Longer term, the Trilinos team will do detailed analysis and optimization of multigrid setup.

17 WIND ENERGY↗

Kinetic Measurements in Heterogeneous Catalysis

This contribution is about the experimental determination of the rate of a heterogeneous catalytic reaction and the analysis of kinetic data. In this case, the reaction rate can be defined as the frequency at which the closed sequence of elementary steps transforming reactants into products is occurring. However, the rate of chemical reaction is not directly observed; rather, one records the rate of substance change. The rate of chemical reaction is calculated based on the rate of substance change and assumed stoichiometry of the reaction. In order to make this an intensive quantity (i.e., independent of the volume in which the reaction is performed, this frequency is divided by the latter or by a quantity proportional to the latter). As the focus of what follows is on heterogeneously catalyzed reactions this can be the catalyst mass, the catalyst surface area or the total number of active sites present in the reaction volume confined by the walls of a chemical reactor. For example, the rate may be reported as one of the following: Net rate of consumption/production of component i mol m-3 s-1 Net specific rate of consumption/production of component i mol kg-1 s-1 Rate of substance change (per unit volume of catalyst) mol m-3 s-1 Specific reaction rate (per unit mass of catalyst) mol kg-1 s-1 Net rate of consumption/production of component i mol m-2 s-1 The turnover frequency (TOF) is a characteristic originally introduced by Boudart [1] is expressed as TOF=R/G_tot , where R is the steady-state rate of reactant consumption or product generation and G_totis the total areal density of active sites [mol m-2]. The latter is typically taken from experimental chemisorption data obtained at low temperature. The advancement of a chemical reaction leads to changes in the amounts of reactants and products which, for a stoichiometric single reaction, are connected by the stoichiometric coefficients. In many cases, for the sake of simplicity, we will assume that the investigated reaction proceeds according to a single reaction pathway, so that the net production rate of a reaction component is directly proportional to the reaction rate and that the latter equals the net production rate of any of the involved components when divided by the appropriate stoichiometric coefficient. For complex stoichiometric reactions the net production rates of the involved components are linear combinations of the reaction rates. Different goals for kinetic measurements can be formulated: Catalyst testing, i.e., obtaining the kinetic dependences for the development and discrimination of efficient catalytic materials. Precise kinetic characterization of active materials via high-throughput screening is a part of such activity. Detailed kinetics, i.e., revealing the detailed mechanism of complex catalytic reaction via systematic kinetic studies, both steady-state and non-steady-state Industrial kinetics, i.e., obtaining data and relationships for describing and predicting the behaviour of catalytic reactors and processes at industrial scale Finally, mathematical modeling and analysis where kinetic measurements provide data for understanding complex kinetic phenomena, e.g., oscillations, non-linear self-organization, etc.

36 MATERIALS SCIENCE↗

Spectral and spatial energetics of the GISS model atmosphere

A calculation of the spectral and spatial energetics of the Goddard Institute for Space Studies (GISS) 9-level model of the global atmosphere is given. Results are presented from a model simulation of January 1973 and compared with previous model studies and an observational analysis for the Northern Hemisphere. The spectral analysis permits detailed study of those physical processes of scale larger than the grid spacing and allows indirect conclusions concerning unresolved subgrid-scale processes. Major conclusions for larger-than-grid-scale processes are that (1) the GISS model with a relatively coarse resolution of 4 deg latitude by 5 deg longitude produces significant nonlinear energy transfers; and (2) baroclinic conversion is large near planetary wave-number 6, but both the GISS model and another orographic model show a less peaked structure than nonorographic models and observations. A linear fit to the kinetic energy spectrum yields a power law of -2.6 in the wavenumber region 8 to 15. For subgrid-scale processes, the turbulence theory result of very small energy flux cascade is obtained.

Tenenbaum, J.↗

Mock gravity and the cosmic structure

The process of generating large-scale cosmic structure from the radiation-pressure or 'mock gravity' instability is studied with particular emphasis on the implications of the Berkeley-Nagoya rocket data for the submillimeter background. The linear theory of perturbations in an absorbing medium embedded in an expanding universe of radiation sources is presented. The instability sets up collapse velocities in linear perturbation theory which far exceed those from gravitational instability, so growth continues even after the instability switches off. Perturbation due to this effect is analyzed and related to the growth of large-scale cosmic structures at recent times; large-scale structure is shown to evolve very little from 1 + z about 5 to the present. Nonlinear small-scale effects of the instability are analyzed; it is shown that radiation pressure would compress gas into small, dense pressure-confined clouds with tau much greater than one.

Hogan, Craig J.↗

Phase-space entropy cascade and irreversibility of stochastic heating in nearly collisionless plasma turbulence

We consider a nearly collisionless plasma consisting of a species of “test particles” in one spatial and one velocity dimension, stirred by an externally imposed stochastic electric field—a kinetic analog of the Kraichnan model of passive advection. The mean effect on the particle distribution function is turbulent diffusion in velocity space—known as stochastic heating. Accompanying this heating is the generation of fine-scale structure in the distribution function, which we characterize with the collisionless (Casimir) invariant C 2 ∝ ∫ ∫ d x d v 〈 f 2 〉 —a quantity that here plays the role of (negative) entropy of the distribution function. We find that C 2 is transferred from large scales to small scales in both position and velocity space via a phase-space cascade enabled by both particle streaming and nonlinear interactions between particles and the stochastic electric field. We compute the steady-state fluxes and spectrum of C 2 in Fourier space, with k and s denoting spatial and velocity wave numbers, respectively. In our model, the nonlinearity in the evolution equation for the spectrum turns into a fractional Laplacian operator in k space, leading to anomalous diffusion. Whereas even the linear phase mixing alone would lead to a constant flux of C 2 to high s (towards the collisional dissipation range) at every k , the nonlinearity accelerates this cascade by intertwining velocity and position space so that the flux of C 2 is to both high k and high s simultaneously. Integrating over velocity (spatial) wave numbers, the k -space ( s -space) flux of C 2 is constant down to a dissipation length (velocity) scale that tends to zero as the collision frequency does, even though the rate of collisional dissipation remains finite. The resulting spectrum in the inertial range is a self-similar function in the ( k , s ) plane, with power-law asymptotics at large k and s . Our model is fully analytically solvable, but the asymptotic scalings of the spectrum can also be found via a simple phenomenological theory whose key assumption is that the cascade is governed by a “critical balance” in phase space between the linear and nonlinear timescales. We argue that stochastic heating is made irreversible by this entropy cascade and that, while collisional dissipation accessed via phase mixing occurs only at small spatial scales rather than at every scale as it would in a linear system, the cascade makes phase mixing even more effective overall in the nonlinear regime than in the linear one. Published by the American Physical Society 2024

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Ultrafast Surface Phosphor Thermometry for Pulsed-power and Hostile Environments

Modern concepts for next generation pulsed power (NGPP) are slated to deliver up to ten times the energy of Z today. An increase of this magnitude is concerning insofar that Z currently exhibits sizable amounts of inner magnetically insulated transmission line (MITL) loss current on the order of 5-10%. Loss phenomenon in these systems are complex and electrode heating and subsequent thermal desorption are a leading cause. Rapid heat-driven thermal desorption of contaminants scales as the square of the current. Therefore, even a modest doubling of drive current would yield an ~ 4X in non-linear surface electrode heating, quickening thermal desorption-based current loss. Exacerbating these physics is a current inability to measure ultra fast heating rates (>20°C/ns), which are paramount to benchmarking and code validation critical to NGPP design – as an empirical approach is not viable. Therefore, Ultrafast Photoluminescent Surface Heating Optical Thermometry (UP-SHOT) was developed as a new diagnostic for measurement of GHz-scale electrode heating. The discovery of UP-SHOT leveraged expertise in Engineering Science, Material Science, Pulsed-Power, and the Center for Integrated Nanotechnologies. This report includes information on: 1) The preparation of zinc oxide (ZnO) films, characterization, post-deposition treatments 2) Time-resolved photoluminescence at elevated temperatures and thermographic sensitivity

36 MATERIALS SCIENCE↗

Manufacturing Challenges and Benefits when Scaling the HIAD Stacked-Torus Aeroshell to a 15m Class System

Over a decade of work has been conducted in the development of NASA's Hypersonic Inflatable Aerodynamic Decelerator (HIAD) deployable aeroshell technology. This effort has included multiple ground test campaigns and flight tests culminating in the HIAD project's second generation (Gen-2) aeroshell system. The HIAD project team has developed, fabricated, and tested stacked-torus inflatable structures (IS) with flexible thermal protection systems (F-TPS) ranging in diameters from 3-6m, with cone angles of 60 and 70 deg. To meet NASA and commercial near term objectives, the HIAD team must scale the current technology up to 12-15m in diameter. The HIAD project's experience in scaling the technology has reached a critical juncture. Growing from a 6m to a 15m class system will introduce many new structural and logistical challenges to an already complicated manufacturing process. Although the general architecture and key aspects of the HIAD design scale well to larger vehicles, details of the technology will need to be reevaluated and possibly redesigned for use in a 15m-class HIAD system. These include: layout and size of the structural webbing that transfers load throughout the IS, inflatable gas barrier design, torus diameter and braid construction, internal pressure and inflation line routing, adhesives used for coating and bonding, and F-TPS gore design and seam fabrication. The logistics of fabricating and testing the IS and the F-TPS also become more challenging with increased scale. Compared to the 6m aeroshell (the largest HIAD built to date), a 12m aeroshell has four times the cross-sectional area, and a 15m one has over six times the area. This means that fabrication and test procedures will need to be reexamined to account for the sheer size and weight of the aeroshell components. This will affect a variety of steps in the manufacturing process, such as: stacking the tori during assembly, stitching the structural webbing, initial inflation of tori, and stitching of F-TPS gores. Additionally, new approaches and hardware will be required for handling and ground testing of both individual tori and the fully assembled HIADs. There are also noteworthy benefits of scaling up the HIAD aeroshell to 15m-class system. Two complications in working with handmade textiles structures are the non-linearity of the materials and the role of human accuracy during fabrication. Larger, more capable, HIAD structures should see much larger operational loads, potentially bringing the structural response of the materials out of the non-linear regime and into the preferred linear response range. Also, making the reasonable assumption that the magnitude of fabrication accuracy remains constant as the structures grow, the relative effect of fabrication errors should decrease as a percentage of the textile component size. Combined, these two effects improve the predictive capability and the uniformity of the structural response for a 12-15m class HIAD. In this paper, the challenges and associated mitigation plans related to scaling up the HIAD stacked-torus aeroshell to a 15m class system will be discussed. In addition, the benefits of enlarging the structure will be further explored.

Decellerators↗

The temporal behavior of upper stratospheric ozone at low latitudes - Evidence from Nimbus 4 BUV data for short-term responses to solar ultraviolet variability

Ozone mixing ratios at pressure levels near 2 mbar are analyzed for the purpose of estimating the average response of the upper stratospheric ozone to solar UV variability on the time scale of the solar rotation period. The data were obtained from observations made with the Nimbus 4 backscattering UV radiometer in 13 latitude zones between 65 degrees N and 65 degrees S. The anaysis showed that temporal variations are negatively correlated with changes in zonally averaged equivalent temperature measured simultaneously by Nimbus 4 radiometer. A linear regression analysis is performed in order to obtain estimates of the average percent change of ozone at low latitudes, on the considered time scale for given changes in 10.7-cm flux, and in the UV flux model developed by Lean et al. (1982). Reproductions of the ozone profiles are provided.

Hood, L. L.↗

Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures

The use of active wake mixing (AWM) to mitigate downstream turbine wakes has created new opportunities for reducing power losses in wind farms. However, many current analytical or semi-empirical wake models do not capture the flow instabilities that are excited through the blade pitch actuation. In this work, we develop a framework, which accounts for the impacts of the large-scale coherent structures and turbulence on the mean flow, for modeling AWM. The framework uses a triple-decomposition approach for the unsteady flow field and models the mean flow and fine-scale turbulence with a parabolized Reynolds-averaged Navier–Stokes (RANS) system. The wave components are modeled using a simplified spatial linear stability formulation that captures the growth and evolution of the coherent structures. Comparisons with high-fidelity large eddy simulations (LESs) of the turbine wakes showed that this framework was able to capture the additional wake mixing and faster wake recovery in the far-wake regions for both the pulse and helix AWM strategies with minimal computational expense. In the near-wake region, some differences are observed in both the RANS velocity profiles and initial growth of the large-scale structures, which may be due to some simplifying assumptions used in the model.

17 WIND ENERGY↗

The Compelling Need for a Mid-Scale Stellarator Facility

In the pursuit of the goal of commercial fusion as an abundant and safe source of energy, the stellarator is a leading concept with compelling attractiveness and demonstrated performance. A new mid-size stellarator is needed to retire risks and innovate towards a high performance, economically attractive, stellarator Fusion Pilot Plant. In this presentation we, as a community of US researchers from Universities, National Laboratories, and Private Industry, involved in studying the stellarator concept, lay out the programmatic and technical motivation for a new and modern mid-size stellarator research facility. A new mid-scale stellarator is needed to realize the potential predicted by a solid body of theory and simulation along with advances in computational tools for optimization and non-linear turbulence modeling. Notably, it is possible to combine the advantages of the stellarator (steady state, no current drive, no disruptions) with the good confinement regularly achieved in tokamaks. The top priorities for experimental work, and the motivation for a mid-scale stellarator experiment are: turbulence control, non-resonant divertor, MHD stability at large beta, confinement of fast particles, and coil simplification. A new mid-size quasi-symmetric stellarator, built as a user facility, would complement existing research at Wendelstein 7-X and LHD and strongly augment private industry. It would provide a program of innovative research, concept validation, theoretical advancement, and workforce development. Growing support and interest for stellarators by the fusion community and private industry affirms this rationale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Feedforward-feedback ammonia control at a water resource recovery facility based on a digital twin with hybrid model

Ammonia-based aeration control (ABAC) at full-scale Water Resource Recovery Facilities (WRRFs) can be challenged by diurnal loading and transport delays. This work addressed these challenges using a hybrid feedforward–feedback controller built on Activated Sludge Model 1 (ASM1), marking the first full-scale deployment to pair a mechanistic feedforward core with data-driven corrections. The objectives were to improve ammonia setpoint tracking, assess performance of the mechanistic model when enhanced with data-driven corrections, and document full-scale operation. The hybrid model incorporates two data-driven components: (1) a Mechanistic Error Forecasting Engine (MEFE), consisting of a multivariate linear regressor and a long short-term memory (LSTM) ensemble. Defying expectations, low-parameter models outperformed more complex alternatives, reducing the mechanistic error by 71%. (2) A Residual Oscillation Forecasting Engine (ROFE), based on Fast Fourier Transform, reduced the remaining error by another 35%. Two proportional–integral (PI) feedback loops further (i) trim the feedforward output and (ii) eliminate residual controller error in the final aerobic zone. In full-scale operation, the controller reduced mean-squared error (MSE) by 94% over the baseline and produced more stable dissolved oxygen (DO) setpoints. Overall, it was proven that layering multi-timescale data-driven models on a mechanistic core can yield reliable ABAC performance at WRRFs.

54 ENVIRONMENTAL SCIENCES↗