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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Hydrodynamics of simply spinning black holes & hydrodynamics for spinning quantum fluids

We find hydrodynamic behavior in large simply spinning five-dimensional Anti-de Sitter black holes. These are dual to spinning quantum fluids through the AdS/CFT correspondence constructed from string theory. Due to the spatial anisotropy introduced by the angular momentum, hydrodynamic transport coefficients are split into groups longitudinal or transverse to the angular momentum, and aligned or anti-aligned with it. Analytic expressions are provided for the two shear viscosities, the longitudinal momentum diffusion coefficient, two speeds of sound, and two sound attenuation coefficients. Known relations between these coefficients are generalized to include dependence on angular momentum. The shear viscosity to entropy density ratio varies between zero and 1/(4π) depending on the direction of the shear. These results can be applied to heavy ion collisions, in which the most vortical fluid was reported recently. In passing, we show that large simply spinning five-dimensional Myers-Perry black holes are perturbatively stable for all angular momenta below extremality.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Narain to Narnia

We generalize the holographic correspondence between topological gravity coupled to an abelian Chern–Simons theory in three dimensions and an ensemble average of Narain’s family of massless free bosons in two dimensions, discovered by Afkhami-Jeddi et al. and by Maloney and Witten. We find that the correspondence also works for toroidal orbifolds but not for K3 or Calabi–Yau sigma-models and not always for the minimal models. Here, we conjecture that the correspondence requires that the central charge is equal to the critical central charge defined by the asymptotic density of states of the chiral algebra. For toroidal orbifolds, we extend the holographic correspondence to correlation functions of twist operators by using topological properties of rational tangles in the three-dimensional ball, which represent configurations of vortices associated to a discrete gauge symmetry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Beyond Taylor’s hypothesis: a novel volumetric reconstruction of velocity and density fields for variable‑density and shear flows

Abstract This work presents a novel numerical procedure for reconstructing volumetric density and velocity fields from planar laser-induced fluorescence (PLIF) and stereoscopic particle image velocimetry (SPIV) data. This new method is theoretically and practically demonstrated to provide more accurate 3D vortical structures and density fields in high shear flows than reconstruction methods based on the mean convective velocity. While Taylor’s hypothesis of frozen turbulence is commonly applied by using the local mean streamwise velocity, the proposed algorithm uses the measured local instantaneous velocity for data convection. It consists of a step-by-step reconstruction based on a mixed Lagrangian–Eulerian solver that includes the 3D interpolation of scattered flow data and that relaxes the Taylor’s hypothesis by iterative enforcement of the incompressibility constraint on the velocity field. This methodology provides 3D fields with temporal resolution, spatial resolution, and accuracy comparable to that of real 3D snapshots, thus providing a practical alternative to tomographic measurements. The procedure is validated using numerical data of the constant-density channel flow available on the Johns Hopkins University Turbulence Database (JHTDB), showing the accurate reconstruction of the 3D velocity field. The algorithm is applied to an experimental dataset of PLIF and SPIV measurements of a variable-density jet flow, demonstrating its capability to provide 3D velocity and density fields that are more consistent with the Navier–Stokes equations compared to the mean flow convective method. Graphic abstract

42 ENGINEERING↗
DOE OSTI2024

Integrated positron emission particle tracking (PEPT) and X-ray computed tomography (CT) imaging of flow phenomena in twisted tape swirl flow

Abstract A combined positron emission particle tracking (PEPT) and X-ray computed tomography (CT) technique is presented, and its utility is demonstrated through investigation of flow in a pipe with twisted tape swirl insert with varying flow conditions (diameter-based Reynolds numbers 16,300–63,300). A description of this technique is given, as well as data handling practices used to relate geometric information captured by CT to fluid flow data gathered via PEPT. It is found that the CT component is readily capable of capturing the stainless steel insert geometry in this present system, but the use of combined plastic and metal materials leads to artifacts in imaging of the plastic surface. Nonetheless, CT data are related to PEPT flow measurements, and average velocity fields are calculated via a pseudo-framing and interpolation scheme and used to visualize and interrogate key flow phenomena within the system. Radial velocity profiles of the mean flow characteristics are seen to collapse to a nearly common form across all flow conditions considered. Helical vortices are seen propagating through the flow field, generated by bypass flow around the gap between the insert and pipe wall, with additional coherent secondary flow structures seen in the higher Reynolds number cases. These findings enhance the understanding of the mixing mechanisms in these swirl flows and encourage the continued development of PEPT-CT methodologies for 3D flow measurements in optically inaccessible systems.

42 ENGINEERING↗
DOE OSTI2023

Extreme windstorms in the Northeastern USA in the contemporary and future climate

Cold-season windstorms represent an important, and potentially changing, geophysical hazard in the Northeastern United States. Here we employ an integrated research methodology including both a storyline approach, where three intense windstorms from the current climate are subjected to pseudo-global warming (PGW) experiments, and a long-term transient simulation using the Weather Research and Forecasting (WRF) model. An ensemble of WRF simulations is built for each windstorm using different planetary boundary layer and microphysical parameterizations. The fidelity assessment suggests all ensemble members capture the windstorm evolution in contemporary climate. The configuration with highest fidelity is used in the PGW experiments performed with perturbed temperature fields, constant relative humidity, and deiced Great Lakes. These perturbation simulations indicate some evidence for a reduction of sea level pressure and increases in wind speed over and downwind of the Great Lakes and over the Atlantic Ocean plus an increase in precipitation accumulation but a reduction in snow coverage. These changes are spatially inhomogeneous in terms of magnitude and sign but are consistent with changes in potential vorticity. Alberta Clippers and Colorado Lows dominate the cyclones responsible for historical windstorms and thus are sampled in the PGW simulations. However, the transient simulation suggests an increasing role for tropical cyclones that undergo transition to extratropical cyclones. Furthermore, this reinforces the value of combining information from both PGW perturbation experiments within a storyline context and transient simulations when seeking to quantify the future risk associated with cold-season windstorms under changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Transition in ICF Capsule Implosions

Longstanding design and reproducibility challenges in inertial confinement fusion (ICF) capsule implosion experiments involve recognizing the need for appropriately characterized and modeled three-dimensional initial conditions and high-fidelity simulation capabilities to predict transitional flow approaching turbulence, material mixing characteristics, and late-time quantities of interest—e.g., fusion yield. We build on previous coarse graining simulations of the indirect-drive national ignition facility (NIF) cryogenic capsule N170601 experiment-a precursor of N221205 which resulted in net energy gain. We apply effectively combined initialization aspects and multiphysics coupling in conjunction with newly available hydrodynamics simulation methods, including directional unsplit algorithms and low Mach-number correction-key advances enabling high fidelity coarse grained simulations of radiation-hydrodynamics driven transition. Our presentation includes discussion of the capsule initialization and implosion dynamics, analysis of the vorticity production budget, transition signatures, quantities of interest—late-time ion temperature and fusion-neutron yield, numerical uncertainty quantification, and comparisons with NIF data.

42 ENGINEERING↗
DOE OSTI2026

Characterizing Turbulence at a Forest Edge: Comparing Sub-Filter Scale Turbulence Models in Simulations of Flow over a Canopy

In wildfires, atmospheric turbulence plays a major role in the transfer of turbulent kinetic energy. Understanding how turbulence feeds back into a dynamical system is important, down to the varying small scales of fuel structures (i.e. pine needles, grass). Large eddy simulations (LES) are a common way of numerically representing turbulence. The Smagorinsky model (1963) serves as one of the most studied sub-grid scale representations in LES. In this investigation, the Smagorinsky model was implemented in HIGRAD/FIRETEC, LANL’s coupled fire-atmosphere model. This study was motivated by the need to quantitatively investigate the vorticity budget equation in HIGRAD/FIRETEC. The Smagorinsky turbulent kinetic energy (TKE) was compared to FIRETEC’s 1.5-order TKE eddy-viscosity subgrid-scale model, known as the Linn turbulence model. This was done in simulations of flow over flat terrain with a homogeneous, cuboidal canopy in the center of the domain. Examinations of the modeled vertical TKE profile and turbulent statistics at the leading edge, and throughout the canopy, show that the Smagorinsky model provides comparable results to that of the original closure model posed in FIRETEC.

58 GEOSCIENCES↗
DOE OSTI2025

Randomized Preconditioned Solvers for Strong Constraint 4D-Var Data Assimilation

The Strong Constraint 4D Variational (SC-4DVAR) data assimilation method is widely used in climate and weather applications. SC-4DVAR involves solving a minimization problem to compute the maximum a posteriori estimate, which we tackle using the Gauss-Newton method. The computation of the descent direction is expensive since it involves the solution of a large-scale and potentially ill-conditioned linear system, solved using the preconditioned conjugate gradient (PCG) method. Here, to address this cost, we efficiently construct scalable preconditioners using three different randomization techniques, which all rely on a certain low-rank structure involving the Gauss-Newton Hessian. The proposed techniques come with theoretical guarantees on the condition number, and at the same time, are amenable to parallelization. We also develop an adaptive approach to estimate the sketch size and choose between the reuse or recomputation of the preconditioner. We demonstrate the performance and effectiveness of our methodology on two representative model problems—the Burgers and barotropic vorticity equation—showing a drastic reduction in both the number of PCG iterations and the number of Gauss-Newton Hessian products after including the preconditioner construction cost.

Gauss-Newton↗
DOE OSTI2022

Computing diffraction patterns of microstructures from phase-field simulations

The diffraction pattern of a material contains information not only on the crystal structures of its constituting phases, but also on its mesoscale spatial distributions of phases, grains, and ferroelastic, ferroelectric, and ferromagnetic domains. While diffraction patterns from experiments such as X-ray diffraction are presented in the reciprocal or Fourier space, mesoscale microstructure models such as the phase-field method naturally produce real-space images of spatial distribution of chemical composition, structural, and ferroic domains. Although one could rather readily compute the Fourier amplitudes of chemical and structural domain distributions generated by mesoscale simulations, they only contain information about the length scale and alignment of the real-space chemical and structure domains. Therefore, a direct comparison between diffraction experiments and mesoscale microstructure simulations is not possible. Here, we develop a theoretical approach to directly compute the crystal diffraction patterns of microstructures predicted by phase-field simulations. In particular, we consider five representative examples of microstructure patterns involving purely compositional domains, a single pair of tetragonal twin structures, multiple twin variants in a hexagonal system, ferroelectric polar vortices, and polycrystalline grains. The results are compared with previous experimental observations as well as X-ray diffraction experiments performed in the present study. Furthermore, the theoretical framework allows one to directly connect material microstructures and diffraction patterns predicted from phase-field simulations and the corresponding diffraction patterns from experiments, and thus providing guidance to experimental diffraction characterization and interpretation of microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Numerical simulation of involute-plate research reactor flow behavior using RANS, LES and DNS

This paper investigates the flow behavior of involute-plate research reactors by performing Reynolds-Averaged Navier Stokes simulation (RANS), Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) of the channel flow between fuel plates. By modeling turbulence with different numerical approaches, this study provides data with three levels of fidelity. For the RANS simulation, three widely used turbulence models, i.e., k-ε, k-ω, Reynolds Stress Turbulence model (RST) are applied by using the commercial CFD code STAR-CCM +. For LES and DNS, the open-source CFD code, Nek5000, is used given its outstanding scalability on High Performance Computer (HPC) and high-order technique. The results from RANS simulations are compared with that from LES and DNS for benchmarking. Both macroscale parameters and turbulence statistics, such as velocity magnitude, lateral velocity and turbulence kinetic energy, are presented and analyzed. The results from RANS simulation achieve good agreement with LES and DNS on velocity and turbulence kinetic energy prediction. The RST turbulence model predicts the most similar flow pattern of lateral velocity as compared to LES and DNS. The Lambda-2 (λ2) criterion with a reasonable threshold is used to demonstrate the instantaneous vortices distribution in the involute channel from both LES and DNS calculation. The DNS simulation captures more detailed turbulence especially near the corner, which explains the discrepancy between LES and DNS results near the corner. The normalized RMS error are defined and calculated to assess the performance of those turbulence models. The RST model captures the anisotropic feature of turbulence, which enable it to outperform other turbulence models for predicting the flow behavior in an involute channel. Although some discrepancies are found between LES and DNS results in the corner, the overall deviations between LES and DNS are found to be small. In conclusion, given that the computational cost of DNS calculation is an order of magnitude higher, using LES data for benchmarking RANS model is a cost-effective approach.

DNS↗
DOE OSTI2022

A comprehensive and fair comparison of two neural operators (with practical extensions) based on $\mathrm{FAIR}$ data

Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering. Herein, we investigate the performance of two neural operators, which have shown promising results so far, and we develop new practical extensions that will make them more accurate and robust and importantly more suitable for industrial-complexity applications. The first neural operator, DeepONet, was published in 2019 (Lu et al., 2019), and its original architecture was based on the universal approximation theorem of Chen & Chen (1995). The second one, named Fourier Neural Operator or FNO, was published in 2020, and it is based on parameterizing the integral kernel in the Fourier space. DeepONet is represented by a summation of products of neural networks (NNs), corresponding to the branch NN for the input function and the trunk NN for the output function; both NNs are general architectures, e.g., the branch NN can be replaced with a CNN or a ResNet. According to Kovachki et al. (2021), FNO in its continuous form can be viewed conceptually as a DeepONet with a specific architecture of the branch NN and a trunk NN represented by a trigonometric basis. In order to compare FNO with DeepONet computationally for realistic setups, we develop several extensions of FNO that can deal with complex geometric domains as well as mappings where the input and output function spaces are of different dimensions. We also develop an extended DeepONet with special features that provide inductive bias and accelerate training, and we present a faster implementation of DeepONet with cost comparable to the computational cost of FNO, which is based on the Fast Fourier Transform. Here we consider 16 different benchmarks to demonstrate the relative performance of the two neural operators, including instability wave analysis in hypersonic boundary layers, prediction of the vorticity field of a flapping airfoil, porous media simulations in complex-geometry domains, etc. We follow the guiding principles of FAIR (Findability, Accessibility, Interoperability, and Reusability) for scientific data management and stewardship. The performance of DeepONet and FNO is comparable for relatively simple settings, but for complex geometries the performance of FNO deteriorates greatly. We also compare theoretically the two neural operators and obtain similar error estimates for DeepONet and FNO under the same regularity assumptions.

42 ENGINEERING↗
DOE OSTI2024

NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements

Multiphysics problems that are characterized by complex interactions among fluid dynamics, heat transfer, structural mechanics, and electromagnetics, are inherently challenging due to their coupled nature. While experimental data on certain state variables may be available, integrating these data with numerical solvers remains a significant challenge. Physics-informed neural networks (PINNs) have shown promising results in various engineering disciplines, particularly in handling noisy data and solving inverse problems in partial differential equations (PDEs). However, their effectiveness in forecasting nonlinear phenomena in multiphysics regimes, particularly involving turbulence, is yet to be fully established. Here, this study introduces NeuroSEM, a hybrid framework integrating PINNs with the highfidelity Spectral Element Method (SEM) solver, Nektar++. NeuroSEM leverages the strengths of both PINNs and SEM, providing robust solutions for multiphysics problems. PINNs are trained to assimilate data and model physical phenomena in specific subdomains, which are then integrated into the Nektar++ solver. We demonstrate the efficiency and accuracy of NeuroSEM for thermal convection in cavity flow and flow past a cylinder. The framework effectively handles data assimilation by addressing those subdomains and state variables where the data is available. We applied NeuroSEM to the Rayleigh-B´enard convection system, including cases with missing thermal boundary conditions and noisy datasets. Finally, we applied the proposed NeuroSEM framework to real particle image velocimetry (PIV) data to capture flow patterns characterized by horseshoe vortical structures. Our results indicate that NeuroSEM accurately models the physical phenomena and assimilates the data within the specified subdomains. The framework’s plug-and-play nature facilitates its extension to other multiphysics or multiscale problems. Furthermore, NeuroSEM is optimized for efficient execution on emerging integrated GPU-CPU architectures. This hybrid approach enhances the accuracy and efficiency of simulations, making it a powerful tool for tackling complex engineering challenges in various scientific domains.

42 ENGINEERING↗
DOE OSTI2024

Direct numerical simulation of a high-pressure hydrogen micromix combustor: Flame structure and stabilisation mechanism

A high-pressure hydrogen micromix combustor has been investigated using direct numerical simulation with detailed chemistry to examine the flame structure and stabilisation mechanism. The configuration of the combustor was based on the design by Schefer et al., using numerical periodicity to mimic a large square array. A precursor simulation of an opposed jet-in-crossflow was first conducted to generate appropriate partially-premixed inflow boundary conditions for the subsequent reacting simulation. The resulting flame can be described as an predominantly-lean inhomogeneously-premixed lifted jet flame. Five main zones were identified: a jet mixing region, a core flame, a peripheral flame, a recirculation zone, and combustion products. The core flame, situated over the jet mixing region, was found to burn as a thin reaction front, responsible for over 85% of the total fuel consumption. The peripheral flame shrouded the core flame, had low mean flow with high turbulence, and burned at very lean conditions (in the distributed burning regime). It was shown that turbulent premixed flame propagation was an order-of-magnitude too slow to stabilise the flame at these conditions. Stabilisation was identified to be due to ignition events resulting from turbulent mixing of fuel from the jet into mean recirculation of very lean hot products. Ignition events were found to correlate with shear-driven Kelvin-Helmholtz vortices, and increased in likelihood with streamwise distance. At the flame base, isolated events were observed, which developed into rapidly burning flame kernels that were blown downstream. Further downstream, near-simultaneous spatially-distributed ignition events were observed, which appeared more like ignition sheets. The paper concludes with a broader discussion that considers generalising from the conditions considered here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction

Here, we put forth a long short-term memory (LSTM) nudging framework for the enhancement of reduced order models (ROMs) of fluid flows utilizing noisy measurements for air traffic improvements. Toward emerging applications of digital twins in aviation, the proposed approach allows for constructing a realtime predictive tool for wake-vortex transport and decay systems. We build on the fact that in realistic application, there are uncertainties in initial and boundary conditions, model parameters, as well as measurements. Moreover, conventional nonlinear ROMs based on Galerkin projection (GROMs) suffer from imperfection and solution instabilities, especially for advection-dominated flows with slow decay in the Kolmogorov n-width. In the presented LSTM nudging (LSTM-N) approach, we fuse forecasts from a combination of imperfect GROM and uncertain state estimates, with sparse Eulerian sensor measurements to provide more reliable predictions in a dynamical data assimilation framework. We illustrate our concept by solving the two-dimensional vorticity transport equation. We investigate the effects of measurements noise and state estimate uncertainty on the performance of the LSTM-N behavior. We also demonstrate that it can sufficiently handle different levels of temporal and spatial measurement sparsity, and offer a huge potential in developing next-generation digital twin technologies for aerospace applications.

42 ENGINEERING↗
DOE OSTI2024

Nanocrystal programmable assembly beyond hard spheres (or shapes) and other (simple) potentials

Ligands are the key to almost any strategy in the assembly of programmable nanocrystals (or nanoparticles) and must be accurately considered in any predictive model. Hard Spheres (or Shapes) provide the simplest and yet quite successful approach to assembly, with remarkable sophisticated predictions verified in experiments. There are, however, many situations where hard spheres/shapes predictions fail. This prompts three important questions: In what situations should hard spheres/shapes models be expected to work? and when they do not work, Is there a general model that successfully corrects hard sphere/shape predictions? and given other successful models where ligands are included explicitly, and of course, numerical simulations, can we unify hard sphere/shape models, explicit ligand models and all atom simulations? . Further, the Orbifold Topological Model (OTM) provides a positive answer to these three questions. In this paper, I give a detailed review of OTM, describing the concept of ligand vortices and how it leads to spontaneous valence and nanoparticle “eigenshapes” while providing a prediction of the lattice structure, without fitting parameters, which accounts for many body effects not captured by (two-body) potentials. I present a thorough survey of experiments and simulations and show that, to this date, they are in full agreement with the OTM predictions. I conclude with a discussion on whether NC superlattices are equilibrium structures and some significant challenges in structure prediction.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Prediction of PbLi fluid flow and temperature field in a thermal convection loop for qualification of fusion materials

Two modeling tools, a thermohydraulics code and a computational model in COMSOL Multiphysics, have been developed, tested and then applied to the analysis of fluid flow and heat transfer in a thermal convection loop (TCL). Such a device has recently been used to experimentally evaluate corrosion compatibility of APMT (Fe–21Cr–5Al–3Mo) steel with high-temperature molten eutectic lead-lithium (PbLi) alloy at Oak Ridge National Lab, TN, USA. Here, the 1-D thermohydraulics code allows for rapid calculations of the loop parameters as a function of the applied heat flux. The supplemental COMSOL finite-element computations provide detailed 3-D velocity and temperature field data but are much more time consuming. Both modelling tools demonstrate an excellent agreement in the computed circulation velocity as well as maximum and minimum temperatures. The performed TCL analysis focuses on flow development in the “hot” and “cold” legs, formation of Dean vortices in corner regions, blocking effect of the immersed samples, and radiative and convective cooling effects under the experiment-relevant conditions for Prandtl number Pr = 0.015, Grashof numbers Gr ~10 7 , and Reynolds numbers Re ~10 4 .

36 MATERIALS SCIENCE↗
DOE OSTI2023

A direct numerical simulation study for confined non-isothermal jet impingement at moderate nozzle-to-plate distances: Capturing jet-to-ambient density effects

A direct numerical simulation (DNS) campaign is deployed for a series of confined downward oriented, non-isothermal turbulent impinging jet configurations. A baseline Reynolds number of 9960 is obtained through a precursor DNS pipe flow simulation (Re τ = 505). Three jet temperature configurations (confinement height to nozzle diameter of three) enter a cylindrical domain that share ambient and impingement plate temperatures (298.15 K). The range of jet temperatures are crafted such that the ratio of inlet to ambient density varies from unity to 0.52, showcasing the effect of density disparity on flow characteristics such as core collapse, radial mixing of momentum and energy, near-wall stagnation behavior, wall-jet profiles, and large-scale vortical structures. Surface quantities provided include mean radial heat flux and wall-shear stress profiles, and heat flux histograms at select radial stations. Results showcase increased radial normal stresses for higher temperature jets that support increased mixing, resulting in large-scale recirculation structures that are smaller, while retaining similar normalized radial wall profiles for shear stress, heat flux and pressure. Furthermore, radial plots for wall shear stress and Nusselt number showcase strong radial decay as compared to previous configurations that share similar jet and ambient temperatures. For the 373.15 K case, a Gaussian-like histogram for heat fluxes at the impingement plate transitions to a log-normal profile as radial distances increase. In contrast, the 573.15 K configuration displays a bi-modal heat flux characteristic at the impingement plate, and in similar manner to the moderate temperature counterpart, transitions to a log-normal profile at larger radial distances.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Thermovelocimetric characterization of liquid metal convection in a rotating slender cylinder

Rotating turbulent convection occurs ubiquitously in natural convective systems encompassing planetary cores, oceans and atmospheres, as well as in many industrial applications. While the global heat and mass transfer of water-like rotating Rayleigh–Bénard convection is well-documented, the dynamics in low-Prandtl-number liquid metals remain less understood. In this study, we experimentally investigate rotating Rayleigh-Bénard convection in liquid gallium (Prandtl number Pr ≈ 0.027) within a slender cylinder (diameter-to-height aspect ratio Γ = D/H =1/2) using novel thermovelocimetric diagnostic techniques that integrate simultaneous multi-point thermometry and ultrasonic Doppler velocity measurements. Our results reveal the formation of a stable, global-scale azimuthal wavenumber m = 2 quadrupolar vortex at low supercriticality. We propose that enhanced wall modes facilitated by the slender cylinder geometry interact with the bulk flow to create these large-scale axialized vortices. Furthermore, our findings imply a distinct scaling behavior for the wall-mode precession frequency in liquid metals, extending previous results obtained for moderate-Pr fluids. In conclusion, this provides new insights into wall-bulk coupling mechanisms of low-Pr rotating convective turbulence.

Magnetohydrodynamics↗