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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Scaling dynamics in low-salt-rejection reverse osmosis for high-salinity produced water desalination: Mechanistic modeling and membrane autopsy

Membrane scaling remains a critical barrier to the reliable operation of desalination systems, particularly for hypersaline produced water (PW) treatment. This study fills the knowledge gap of autopsy-based model validation for PW desalination by elucidating scaling mechanisms in a Low-Salt-Rejection Reverse Osmosis (LSRRO) system through the integration of pilot-scale experimentation and complementary modeling approaches. A semi-empirical modeling framework was developed and applied to a multistage pilot LSRRO system equipped with nanofiltration and RO membranes treating high-salinity PW from the Permian Basin. Water quality analysis showed that total dissolved solids decreased from ~130,000 mg/L to ~1900 mg/L in the permeate, then further reduced to ~300 mg/L by a second-pass RO. Two different thermodynamic modeling approaches were evaluated: the first extends the LSRRO framework by incorporating system complexity and scaling phenomena, whereas the second method explicitly captures concentration polarization in localized supersaturation. Both methods illustrate the tendency for carbonate and sulfate scaling throughout the stages. Membrane autopsies revealed a silica-dominated deposit matrix, localized CaSO 4 at Stage 2, and minor barite/celestite despite their prominence in model predictions. Quantum-chemical calculations indicated silica scaling can be rationalized by favorable adsorption of H 4 SiO 4 on Fe-oxide surfaces (ΔG ≈ −44 kJ/mol), providing a kinetic pathway for interfacial inorganic polymerization even when bulk equilibrium predictions are conservative. Overall, the thermodynamic scaling modeling and membrane autopsy revealed heterogeneous, localized deposits with limited impact on LSRRO performance, while quantum analysis rationalized the thermodynamically unfavorable precipitation formation under bulk equilibrium, reconciling model–autopsy discrepancies. These insights support targeted pretreatment and silica-specific antiscalants to extend membrane lifetime and increase recovery, providing a transferable framework for hypersaline water desalination systems. The combined experimental–computational approach provides new mechanistic insight into scaling in hypersaline membrane systems and establishes a transferable framework for predicting and mitigating scaling in next-generation desalination technologies.

Low-salt-rejection reverse osmosis↗
DOE OSTI2022

Scaling CFB risers: Maintaining microstructure dynamics

Over the years there have been numerous approaches to develop a scaleup methodology for circulating fluidized beds. Many of these past approaches have relied on macroscopic definitions of similitude to define dimensionless groups such as Reynolds number, Froude number, density ratios, and dimensional ratios involving different length scales. These approaches have demonstrated various levels of success, but often fail when used outside the bounds of experimental datasets. The issue with these methods is that they rely on macroscopic similitude with the hopes that those conditions would provide microscopic similitude as it does in single phase systems where the Buckingham Pi techniques have given reasonable success. Two of the main reasons for failure are 1) changing fluidization regimes and 2) changing material properties that result in the material falling into a different Geldart group. Both are certain to change the microstructure (local instantaneous volume solids fraction) and changes to the microstructure affect the interphase transport properties of the reactor system, namely the mass transfer and heat transfer. Here, this work presents a new approach towards scaling based upon maintaining similitude at the microscale. It reviews a novel dimensionless flow regime map developed from analysis of the deterministic chaos parameters and higher order moments to ensure microstructure similitude. The work then examines four cases from the literature to assess the scaling approach used: (1) same particle-different scale risers for Geldart Group B particles, (2) Glicksman scaling of atmospheric circulating fluidized bed combustor, (3) same particle-different scale risers for Geldart Group A particles and (4) Glicksman scaling for pressurized gasification. General findings are that none of the scaling approaches produced directly applicable microstructure similar behavior based upon the chaotic and higher moment analysis. The positive take away is that the approach can define scale conditions that will provide similar microstructure that can be us to predict transport behavior.

42 ENGINEERING↗
DOE OSTI2026

Cost estimation of balance of plant equipment scale up for proton exchange membrane water electrolyzer systems

Water electrolyzers that use electricity to split water into hydrogen and oxygen could be a key technology for increasing hydrogen supply to meet expanded and emerging market applications, although currently the capital costs of these electrolyzers are high. Here we examine cost reductions that might be achieved by scaling up proton exchange membrane (PEM) electrolyzer systems and leveraging economies of scale through balance of plant (BOP) components for system sizes between 1 MW and 1 GW. We estimate BOP equipment capital costs of about $\$$848/kW at 1 MW, potentially decreasing to $\$$87/kW at 1 GW (2022-dollar year basis) with most of the cost reduction happening as systems scale from 1 MW to 100 MW. We find that BOP subsystems hydrogen drying and water knockout benefited the most from economies-of-scale cost reductions, and piping, instrumentation, and housing and power electronics were less impacted. These cost reductions from economies of scale could be more significant than estimated cost reductions from manufacturing scale-up reported in literature. These results add to the knowledge base that could guide optimal system designs that balance process scale-up with plant modularization and numbering-up. We also estimate that scaling up BOP could potentially lower the levelized cost of hydrogen (LCOH) by $\$$1.7-$\$$4.6/kg, depending on the scale-up magnitude and the plant capacity factor.

08 HYDROGEN↗
DOE OSTI2021

Scale dependence in functional equivalence and difference in the soil microbiome

Climatic history can shape the functioning of soil microbial communities and thus rates of ecosystem processes such as organic matter decomposition. For example, broad spatial scale differences in climatic history, such as contrasting precipitation regimes, have been shown to generate unique microbial functional responses to contemporary moisture conditions. Yet it is an open question as to whether local differences in soil microclimate similarly influence the functional potential of decomposer communities. Here, we use a multi-scale approach within and among two temperate forest field sites to investigate this question. Soils from fifty-four microsites, that vary in their soil moisture climate-regimes, were used as inocula for a common leaf litter (Quercus rubra L.) in a controlled, laboratory microcosm study. Microcosms were placed under dry, mesic and wet lab-moisture conditions and the rate of carbon (C) mineralization of the litter was measured over 202 days. Our results reveal differences in decomposition rates under controlled conditions that highlight broad-scale functional differences between the soil communities at each site. Specifically, we found that C mineralization differed by as much as two-fold for soil communities when compared between the sites. Our results also show that functional differences of soil communities are observable within one site but not the other. In the site where local-scale functional legacies were apparent, the historical soil moisture microclimate-regimes generated as much as an 89% change in C mineralization rates of the leaf litter under the same contemporary, lab-imposed moisture conditions. Here, a similar pattern was not observable in the other site; instead, laboratory moisture conditions explained almost all variation in C mineralization. Notably, for the site with pronounced local-scale functional legacies, there was much greater within-site variation in field-soil microsite moisture than at the site which did not exhibit functional legacies, suggesting that the extent of local-scale variation in microclimate may act as control on whether local-scale functional legacies are observed. Regardless of whether this mechanism does explain our findings, our observations do confirm those from prior studies where regional-scale moisture-regime differences shape microbial function, and extend this prior work by providing evidence that pronounced local-scale differences in soil moisture microclimate-regimes are associated with microbial functional legacies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

GLUE Code: A framework handling communication and interfaces between scales

Many scientific applications are inherently multiscale in nature. Such complex physical phenomena often require simultaneous execution and coordination of simulations spanning multiple time and length scales. This is possible by combining expensive small-scale simulations (such as molecular dynamics simulations) with larger scale simulations (such continuum limit/hydro solvers) to allow for considerably larger systems using task and data parallelism. However, the granularity of the tasks can be very large and often leads to load imbalance. Traditionally, we use approximations to streamline the computation of the more costly interactions and this introduces trade-offs between simulation cost and accuracy. In recent years, the available computational power and the advances in machine learning have made computing these scale-bridging interactions and multiscale simulations more feasible. One driving application has been plasma modeling in inertial confinement fusion (ICF), which is fundamentally multiscale in nature. This requires deep understanding of how to extrapolate microscopic information into macroscopically relevant scales. For example, in ICF one needs an accurate understanding of the connection between experimental observables and the underlying microphysics. The properties of the larger scales are often affected by the microscale behavior incorporated usually into the equations of state and ionic and electronic transport coefficients (Liboff, 1959; Rinderknecht et al., 2014; Rosenberg et al., 2015; Ross et al., 2017). Instead of incorporating this information using reliable molecular dynamics (MD) simulations, one often needs to use theoretical models, due to the inability of MD to reach engineering scales (Glosli et al., 2007; Marinak et al., 1998). One approach to resolve this issue is by coupling two MD simulations of different scales via force interpolation, e.g., the AdResS method (Krekeler et al., 2018; Nagarajan et al., 2013). Another approach, which we will pursue in the scope of this work, is by enabling scale bridging between MD simulations and meso/macro-scale models through the development and support of application programming interfaces that these different applications can interact through.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Scaled CMOS Technology Reliability Users Guide

The desire to assess the reliability of emerging scaled microelectronics technologies through faster reliability trials and more accurate acceleration models is the precursor for further research and experimentation in this relevant field. The effect of semiconductor scaling on microelectronics product reliability is an important aspect to the high reliability application user. From the perspective of a customer or user, who in many cases must deal with very limited, if any, manufacturer's reliability data to assess the product for a highly-reliable application, product-level testing is critical in the characterization and reliability assessment of advanced nanometer semiconductor scaling effects on microelectronics reliability. A methodology on how to accomplish this and techniques for deriving the expected product-level reliability on commercial memory products are provided.Competing mechanism theory and the multiple failure mechanism model are applied to the experimental results of scaled SDRAM products. Accelerated stress testing at multiple conditions is applied at the product level of several scaled memory products to assess the performance degradation and product reliability. Acceleration models are derived for each case. For several scaled SDRAM products, retention time degradation is studied and two distinct soft error populations are observed with each technology generation: early breakdown, characterized by randomly distributed weak bits with Weibull slope (beta)=1, and a main population breakdown with an increasing failure rate. Retention time soft error rates are calculated and a multiple failure mechanism acceleration model with parameters is derived for each technology. Defect densities are calculated and reflect a decreasing trend in the percentage of random defective bits for each successive product generation. A normalized soft error failure rate of the memory data retention time in FIT/Gb and FIT/cm2 for several scaled SDRAM generations is presented revealing a power relationship. General models describing the soft error rates across scaled product generations are presented. The analysis methodology may be applied to other scaled microelectronic products and their key parameters.

Microelectronics Reliability↗
NASA NTRSDate not supplied

Wind-Tunnel to Full-Scale Mapping of Winds and Loads for Launch-Vehicle Ground Wind Loads

A launch vehicle ground-wind-loads program was conducted at the NASA Langley Transonic Dynamics Tunnel. The objectives were to quantify key aerodynamic and structural characteristics that impact the occurrence of large wind-induced oscillations of a launch vehicle when exposed to ground winds prior to launch. Of particular interest is the dynamic response of a launch vehicle when a von Kármán vortex street forms in the wake of the vehicle resulting in quasiperiodic lift and drag forces. Vehicle response to these quasiperiodic forces can become quite large when the frequency of vortex shedding nears that of a lowly-damped structural mode thereby exciting a resonant response. The study of ground-wind-loads presents unique challenges to quantify significant characteristics of the approaching wind and to relate the wind-tunnel acquired static, dynamic, and gravitational loads to full-scale vehicles. This paper will explain the correlation process between model-scale and full-scale wind characteristics and resulting structural loads. Characterization of the wind at a launch site requires knowledge of the vehicle dynamics and the anemometer performance. Vehicle dynamics dictate the frequency range of interest in characterization of the atmospheric turbulence, and in defining the required data window-length to model dynamic oscillation build-up during wind-gust analysis. Knowledge of the anemometer performance is required to infer peak wind magnitudes since most anemometers cannot directly measure instantaneous peak values. Following proper wind-speed correlation, static and dynamic wind-tunnel loads must be converted to full-scale equivalent values to derive design and operational guidance. In addition to the direct computation of full-scale equivalent loads using relevant scaling parameters, the corrections applied to dynamic loads accounting for differences in structural damping will also be discussed. Furthermore, a phenomenon that manifests in many slender and flexible launch vehicles is a load magnification due to gravity resulting from mass offset under deflection. A method for scaling this contribution from model-scale to full-scale is presented. Finally, a comparison of wind-tunnel derived loads using the described methodologies to launch vehicle measured loads is presented.

Ground wind loads↗
NASA NTRS2023

Control and Scaling Approach for the Emulation of Dynamic Subscale Torque Loads

Research and development of electrified aircraft propulsion powertrains are relying on the use of electromechanical systems to emulate turbomachinery/rotor loads. Replacing a physical turbomachinery/rotor with a model driving a subscale electromechanical system capable of emulating subscale torque loads and responses is a lower risk, lower cost alternative to using the full-scale turbomachinery/rotor for initial control system verification. This paper outlines a novel control and scaling approach for emulating dynamic subscale torque loads using electric machine (EM) hardware for electrified aircraft propulsion research and development purposes. The approach, known as the Sliding Mode Impedance Controller with Scaling (SMICS), drives a mechanically coupled, two-EM system to behave like a subscale hardware representation of a hybrid-electric turbomachinery shaft. One EM reflects the inertial dynamics and torque load of the subscale turbomachinery under steady-state and transient operation while the second EM represents a motor/generator connected to the shaft, which is intended to hybridize the turbomachinery. This closed loop control and scaling algorithm applies impedance and sliding mode control schemes, along with parameter scaling, to match subscale, desired dynamics in real-time and to allow this system to be driven by a full-scale hybrid-electric turbomachinery model and control. The paper elaborates on the concept of the closed loop control and scaling approach and explains the significance of using impedance and sliding mode control. It shows a derivation of the closed loop control and scaling algorithm, its implementation, and presents a comparison of theoretical and actual simulation results acquired during hardware-in-the-loop testing of a partial turboelectric propulsion concept aircraft at the NASA Electric Aircraft Testbed (NEAT).The results show that the intended dynamic responses of the hardware and the aircraft model are achieved in both the time and frequency domain. Full scale propulsion control systems can be tested using this hardware and software approach.

Emulation↗
DOE OSTI2021

Quantifying the hierarchy of structural and mechanical length scales in granular systems

Continuum modeling of granular media is made possible by the existence of a length scale at and above which grain-resolved properties can be meaningfully homogenized. Progress has been made in identifying such length scales relevant to local structural properties such as porosity. However, a systematic analysis of scales above which different mechanical properties can be homogenized has yet to emerge. Here, X-ray tomography and 3D X-ray diffraction data are examined to identify such length scales. The data was obtained in-situ in compressed granular materials with rigid and flexible confinement. The experimental data are supplemented with validated discrete element simulations which examine different system sizes and different boundary conditions. Overall, our study reveals a hierarchy in the length scales of granular solids, with lengths governing structural variables being the shortest, lengths of stress variables being intermediate, and lengths of energy dissipation being the longest. All structural and mechanical length scales obey a power law based on the theory of Geostatistics, implying that the length scales can be found by analyzing samples significantly smaller than the length scales themselves. The length scales are also found to be sensitive to boundary conditions, implying that they are extrinsic features of granular media.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Morphological and chemical characteristics of oxide scales formed on δ-Phase plutonium metal alloys I: 3.5 at% ga

Focused ion-beam scanning electron microscopy (FIB-SEM) and three-dimensional (3D) microscopy were applied to characterize the subsurface morphological features of oxide scales formed on an ~3.5 at.% Ga plutonium (Pu) metal alloy. Using the FIB-SEM technique, a number of morphological features formed in the interior of the oxide scale from Pu metal's environmental exposure were observed and identified. Here, Auger electron spectroscopy (AES) was utilized to characterize the cross-sectional composition and chemistry of the oxide scale. The oxide scale formed during inert storage and operational environments has a characteristic internal scale structure that includes a relatively dense oxide layer with some lateral and transverse cracking. Generally, after subsequent exposure to dry air environment, the oxide scale retained most of the original structural and chemical characteristics. However, after aging in a moist air environment, while the oxide scale was found to maintain the chemical characteristics of the source oxide, the scale was found to be on average thinner and without the previously observed internal microcracking, likely the result of spallation of the source scale during exposure to the new environment.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Probabilistic evolution of stochastic dynamical systems: A meso-scale perspective

Stochastic dynamical systems arise naturally across nearly all areas of science and engineering. Typically, a dynamical system model is based on some prior knowledge about the underlying dynamics of interest in which probabilistic features are used to quantify and propagate uncertainties associated with the initial conditions, external excitations, etc. From a probabilistic modeling standing point, two broad classes of methods exist, i.e. macro-scale methods and micro-scale methods. Classically, macro-scale methods such as statistical moments-based strategies are usually too coarse to capture the multi-mode shape or tails of a non-Gaussian distribution. Micro-scale methods such as random samples-based approaches, on the other hand, become computationally very challenging in dealing with high-dimensional stochastic systems. In view of these potential limitations, a meso-scale scheme is proposed here that utilizes a meso-scale statistical structure to describe the dynamical evolution from a probabilistic perspective. The significance of this statistical structure is twofold. First, it can be tailored to any arbitrary random space. Second, it not only maintains the probability evolution around sample trajectories but also requires fewer meso-scale components than the micro-scale samples. To demonstrate the efficacy of the proposed meso-scale scheme, a set of examples of increasing complexity are provided. Connections to the benchmark stochastic models as conservative and Markov models along with practical implementation guidelines are presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Temporal dynamics of large-scale structures for turbulent Rayleigh–Bénard convection in a moderate aspect-ratio cylinder

We investigate the spatial organization and temporal dynamics of large-scale, coherent structures in turbulent Rayleigh–Bénard convection via direct numerical simulation of a 6.3 aspect-ratio cylinder with Rayleigh and Prandtl numbers of 9.6×10 7 and 6.7, respectively. Fourier modal decomposition is performed to investigate the structural organization of the coherent turbulent motions by analysing the length scales, time scales and the underlying dynamical processes that are ultimately responsible for the large-scale structure formation and evolution. We observe a high level of rotational symmetry in the large-scale structure in this study and that the structure is well described by the first four azimuthal Fourier modes. Two different large-scale organizations are observed during the duration of the simulation and these patterns are dominated spatially and energetically by azimuthal Fourier modes with frequencies of 2 and 3. Studies of the transition between these two large-scale patterns, radial and vertical variations in the azimuthal energy spectra, as well as the spatial and modal variations in the system's correlation time are conducted. Rotational dynamics are observed for individual Fourier modes and the global structure with strong similarities to the dynamics that have been reported for unit aspect-ratio domains in prior works. It is shown that the large-scale structures have very long correlation time scales, on the order of hundreds to thousands of free-fall time units, and that they are the primary source for a horizontal inhomogeneity within the system that can be observed during a finite, but a very long-time simulation or experiment.

42 ENGINEERING↗
DOE OSTI2025

Small-scale properties from exascale computations of turbulence on a $\mathbf{32\,768^3}$ periodic cube

To study the physics of small-scale properties of homogeneous isotropic turbulence at increasingly high Reynolds numbers, direct numerical simulation results have been obtained for forced isotropic turbulence at Taylor-scale Reynolds number R λ = 2500 on a 32 768 3 three-dimensional periodic domain using a GPU pseudo-spectral code on a 1.1 exaflop GPU supercomputer (Frontier). These simulations employ the multi-resolution independent simulation (MRIS) technique (Yeung & Ravikumar 2020, Phys. Rev. Fluids, vol. 5, 110517) where ensemble averaging is performed over multiple short segments initiated from velocity fields at modest resolution, and subsequently taken to higher resolution in both space and time. Reynolds numbers are increased by reducing the viscosity with the large-scale forcing parameters unchanged. Although MRIS segments at the highest resolution for each Reynolds number last for only a few Kolmogorov time scales, small-scale physics in the dissipation range is well captured – for instance, in the probability density functions and higher moments of the dissipation rate and enstrophy density, which appear to show monotonic trends persisting well beyond the Reynolds number range in prior works in the literature. Attainment of range of length and time scales consistent with classical scaling also reinforces the potential utility of the present high-resolution data for studies of short-time-scale turbulence physics at high Reynolds numbers where full-length simulations spanning many large-eddy time scales are still not accessible. A single snapshot of the 32 768 3 data is publicly available for further analyses via the Johns Hopkins Turbulence Database.

intermittency↗
DOE OSTI2025

Impact of Electromagnetic Fields on Gypsum and Silica Scaling in Reverse Osmosis

Electromagnetic field (EMF) is a cost-effective, simple, and energy-efficient method for scale control in reverse osmosis (RO) systems. However, its effects on gypsum and silica scaling, as well as the underlying mechanisms, remain poorly understood. This study systematically investigates the effects of EMF treatment on gypsum and silica scaling in RO systems, utilizing synthetic brackish water and natural RO concentrate (ROC) from a desalination facility. For gypsum, EMF changes the crystal morphology, resulting in the formation of a porous, less compact scaling layer. It is more readily removed through hydraulic flushing (HF), enhancing scaling reversibility and water recovery. In the case of silica scaling, EMF promotes homogeneous polymerization in the bulk solution, producing larger silica particles that inhibit the formation of a dense, cross-linked gel layer on the membrane surface, mitigating flux decline. This study thus demonstrates EMF’s effectiveness in controlling gypsum scaling in undersaturated feedwaters when combined with HF and in mitigating silica scaling under both HF and non-HF conditions for supersaturated feedwaters. These findings underscore EMF’s versatility as a nonchemical approach for scale control in RO desalination and show its substantial potential to enhance membrane performance and operational efficiency in real-world water treatment applications.

Du, Xuewei [New Mexico State University, Las Cruce↗
DOE OSTI2025

Assessment of dynamic-screw-pinch-driven, current-scaled MagLIF target implosion performance using 3D magnetohydrodynamic simulations

Analytic studies and two-dimensional “clean” radiation-magnetohydrodynamic (rad-MHD) simulations employing dynamical similarity driver-target scaling prescriptions [Ruiz et al., Phys. Plasmas 30, 032708 (2023)] suggest that Magnetized Liner Inertial Fusion (MagLIF) target implosions can scale to > 10 MJ DT fusion yields when peak drive current is increased beyond 60 MA. We present results from three-dimensional (3D) rad-MHD simulations of similarity-scaled MagLIF target implosions at peak drive currents ranging from 15 to 40 MA. Simulations in this study suggest that magneto-Rayleigh–Taylor instability (MRTI) growth and feedthrough to the fuel region are more severe at higher drive current scales, which reduces the fusion yield compared to prior analytic and 2D clean simulation predictions. In contrast to standard MagLIF, simulations of current-scaled MagLIF target implosions driven by a dynamic screw pinch (DSP) demonstrate reduced MRTI feedthrough and greater fuel magnetization, resulting in improved thermonuclear performance and enhanced performance scaling with peak drive current. DSP drive enables additional scaling of the liner mass to increase liner radius but maintain implosion time, resulting in higher implosion velocities at the expense of increased susceptibility to MRTI. We present a current- and mass-scaled simulated DSP-MagLIF target implosion at the ∼ 40 MA peak current level that produces ignition scale performance, demonstrating a burn-averaged Lawson ignition parameter above unity and DT fusion yield above 1 MJ.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

The role of ion-scale micro-turbulence in pedestal width of the DIII-D wide-pedestal QH mode

The low-edge rotation, intrinsically ELM-free, and improved confinement wide-pedestal quiescent H-mode (QH-mode), discovered in DIII-D tokamak, has pedestal widths exceeding the EPED-kinetic-ballooning mode (KBM) model scaling typically by at least 25%. Ion-scale ($k_yp_s$ < 1) microturbulence and its role in setting the pedestal structure is investigated using the radially local δ$f$ gyrokinetic code CGYRO. The electromagnetic trapped electron mode (TEM) is unstable at the pedestal top, while plasma beta (β$_e$) is ∼60% below the KBM onset threshold and the electron temperature gradient mode is found to be unstable in the peak gradient region. Nonlinear simulation reveals that the ion-scale turbulence could produce electron energy flux consistent with the flux inferred from power balance at the pedestal top, with a reasonable variation of the local shearing rate; and the local neoclassical transport from NEO is dominant over the simulated turbulent transport in the ion energy flux channel. The simulated ion-scale turbulence produces much lower electron energy flux than inferred from experiment in the pedestal peak gradient region. A correction to the EPED-KBM pedestal width scaling is obtained based on the two-dimensional scan of pedestal top plasma beta (β$_e$) and normalized electron density and temperature scale lengths,${a}$/${L_n}_e$, ${a}$/${L_T}_n$using CGYRO linear simulations. Mode transitions among TEM, micro-tearing mode, ion-temperature gradient mode and KBM, are observed in the 2D scan at the pedestal top. A fixed normalized growth rate for these drift-type modes is taken to determine the pedestal width scaling, which shows good consistency with the QH experimental database on pedestal heights and widths. The onset of KBM instabilities and the local E × B shear suppression criterion set the lower and upper limit for the pedestal width of standard QH-mode, wide-pedestal QH-mode and type-I ELMy H mode. A potentially higher and wider pedestal is expected from the new scaling of pedestal width. This work presents an improved understanding of the ion-scale micro-turbulence of wide-pedestal QH-mode and sheds light on a promising scenario for future reactors, including ITER and beyond.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Magnetorotational dynamo can generate large-scale vertical magnetic fields in 3D GRMHD simulations of accreting black holes

ABSTRACT Jetted astrophysical phenomena with black hole engines, including binary mergers, jetted tidal disruption events, and X-ray binaries, require a large-scale vertical magnetic field for efficient jet formation. However, a dynamo mechanism that could generate these crucial large-scale magnetic fields has not been identified and characterized. We have employed three-dimensional global general relativistic magnetohydrodynamical simulations of accretion discs to quantify, for the first time, a dynamo mechanism that generates large-scale magnetic fields. This dynamo mechanism primarily arises from the non-linear evolution of the magnetorotational instability (MRI). In this mechanism, large non-axisymmetric MRI-amplified shearing wave modes, mediated by the axisymmetric azimuthal magnetic field, generate and sustain the large-scale vertical magnetic field through their non-linear interactions. We identify the advection of magnetic loops as a crucial feature, transporting the large-scale vertical magnetic field from the outer regions to the inner regions of the accretion disc. This leads to a larger characteristic size of the, now advected, magnetic field when compared to the local disc height. We characterize the complete dynamo mechanism with two time-scales: one for the local magnetic field generation, $t_{\rm gen}$, and one for the large-scale scale advection, $t_{\rm adv}$. Whereas the dynamo we describe is non-linear, we explore the potential of linear mean field models to replicate its core features. Our findings indicate that traditional $\alpha$-dynamo models, often computed in stratified shearing box simulations, are inadequate and that the effective large-scale dynamics is better described by the shear current effects or stochastic $\alpha$-dynamos.

Astronomy & Astrophysics↗
DOE OSTI2022

Non-Boussinesq subgrid-scale model with dynamic tensorial coefficients

A major drawback of Boussinesq-type subgrid-scale stress models used in large-eddy simulations is the inherent assumption of alignment between large-scale strain rates and filtered subgrid-stresses. A priori analyses using direct numerical simulation (DNS) data have shown that this assumption is invalid locally as subgrid-scale stresses are poorly correlated with the large-scale strain rates [J. Bardina, J. Ferziger, and W. Reynolds, Improved subgrid-scale models for large-eddy simulation, in Proceedings of the 13th Fluid and Plasmadynamics Conference, AIAA (1980); C. Meneveau and K. Katz, Scale-invariance and turbulence models for large-eddy simulation, Ann. Rev. Fluid Mech. 32, 1 (2000)]. In the present work, a new, non-Boussinesq subgrid-scale model is presented where the model coefficients are computed dynamically. Some previous non-Boussinesq models have observed issues in providing adequate dissipation of turbulent kinetic energy [e.g., Bardina et al., Proceedings of the 13th Fluid and Plasmadynamics Conference (1980); R. A. Clark, J. Ferziger, and W.C. Reynolds. Evaluation of subgrid-scale models using an accurately simulated turbulent flow, J. Fluid Mech. 91, 1 (1979); S. Stolz and N. A. Adams, An approximate deconvolution procedure for large-eddy simulation, Phys. Fluids 11, 1699 (1999)]; however, the present model is shown to provide sufficient dissipation using dynamic coefficients. Modeled subgrid-scale Reynolds stresses satisfy the consistency requirements of the governing equations for large-eddy simulation (LES), vanish in laminar flow and at solid boundaries, and have the correct asymptotic behavior in the near-wall region of a turbulent boundary layer. The new model, referred to as the dynamic tensor-coefficient Smagorinsky model (DTCSM), has been tested in simulations of canonical flows: decaying and forced homogeneous isotropic turbulence, and wall-modeled turbulent channel flow at high Reynolds numbers. The results show favorable agreement with DNS data. It has been shown that DTCSM offers similar predictive capabilities as the dynamic Smagorinsky model for canonical flows. In order to assess the performance of DTCSM in more complex flows, wall-modeled simulations of high Reynolds number flow over a Gaussian bump (Boeing speed bump) exhibiting smooth-body flow separation are performed. Predictions of surface pressure and skin friction, compared against DNS and experimental data, show improved accuracy from DTCSM in comparison to existing static coefficient (Vreman) and dynamic Smagorinsky model. The computational cost of performing LES with this model is up to 15% higher than the dynamic Smagorinsky model.

42 ENGINEERING↗