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DOE OSTI2025

Characterizing in-stream turbulent flow for tidal energy converter siting in Cook Inlet, Alaska

Cook Inlet in Alaska is the most promising location for tidal energy development in the U.S. due to its significant tidal range of approximately 10 meters and high volume flux. The inlet's unique geometry and flow characteristics make it the most energetic tidal stream in the nation, with GW-scale potential energy capacity. With the growing interest in tidal energy converter (TEC) deployment in this area, we implemented a regional-scale, 3D hydrodynamic modeling framework to predict tidal current and turbulence characteristics that can assist TEC designers and project managers. We validated the model results extensively using various datasets collected with bottom-mounted acoustic Doppler current profilers and velocimeters. The comparison between the model outputs and observational data highlighted the effectiveness of the 3D FVCOM model and the Mellor-Yamada Level 2.5 Turbulence Model in accurately assessing macro-scale kinetic energy, turbulence intensity, and the production and dissipation rates at a prospective TEC site. Using two months of model simulation data, we examined the channel cross-section for TEC deployment, focusing on undisturbed power density and macro-scale turbulent properties. Further, our findings indicate that understanding the turbulence characteristics and flow properties can enhance Stage I/II resource characterization by identifying optimal locations for TECs and their layouts within the channel. Furthermore, we demonstrated that TEC designers can utilize macro-scale turbulence data from 3D coastal models as boundary conditions for other turbulence models, allowing for a more detailed resolution of the turbulence structure at TEC siting locations. Ultimately, this work emphasizes the importance of estimating flow and turbulence conditions in energetic systems to understand turbulent sites better and improve resource characterization.

16 TIDAL AND WAVE POWER↗

DOE OSTI2025

A generative artificial intelligence framework for long-time plasma turbulence simulations

Generative deep learning techniques are employed in a novel framework for the construction of surrogate models capturing the spatiotemporal dynamics of 2D plasma turbulence. The proposed Generative Artificial Intelligence Turbulence (GAIT) framework enables the acceleration of turbulence simulations for long-time transport studies. GAIT leverages a convolutional variational auto-encoder and a recurrent neural network to generate new turbulence data from existing simulations, extending the time horizon of transport studies with minimal computational cost. The application of the GAIT framework to plasma turbulence using the Hasegawa–Wakatani (HW) model is presented, evaluating its performance via various analyses. Very good agreement is found between the GAIT and the HW models in the spatiotemporal Fourier and Proper Orthogonal Decomposition spectra, the flow topology characterized by the Okubo–Weiss parameter, and the time autocorrelation function of turbulent fluctuations. Excellent agreement has also been obtained in the probability distribution function of particle displacements and the effective turbulent diffusivity. In-depth analyses of the latent space of turbulent states, choice of hyperparameters and alternative deep learning models for the time prediction are presented. Our results highlight the potential of Artificial Intelligence-based surrogate models to overcome the computational challenges in turbulence simulation, which can be extended to other situations such as geophysical fluid dynamics.

Artificial intelligence↗

DOE OSTI2026

Idealized simulations of wind farm interactions with intermittent turbulence in stable boundary layer conditions

Stable atmospheric boundary layer conditions typically correspond to weak turbulence levels, but intermittent periods of elevated turbulence can occur during otherwise quiescent conditions. The interaction between intermittent turbulence and wind turbines is not well understood because of sparse observations, as well as the difficulty in realistically resolving small-scale turbulence during strongly stable conditions with numerical simulations. In this study, an explicit filtering and reconstruction approach for large-eddy simulation (LES) is used to simulate weakly and strongly stable conditions, with surface cooling rates of −0.2 and −2.0 K h −1 , respectively. This approach can sustain resolved background turbulence at relatively coarse grid spacing and stronger stratification compared to conventional closures, permitting more realistic intermittent stable boundary layer (SBL) turbulence. The idealized LES capability of the Weather Research and Forecasting model is employed with turbine rotors parameterized using generalized actuator disks to examine (1) how the presence of turbine wakes affects SBL evolution and (2) the effect of intermittent turbulence on power production and wake recovery. Wakes increase mixing and deepen the SBL, with a stronger effect under strongly stable conditions, primarily because the SBL is shallower and closer to the top of the wind turbine rotor layer. Intermittent turbulence does not have a significant impact on mean power generation and wake recovery because the relevant intermittent turbulent structures in this study only affect the bottom half of the rotor disk. Power production is, however, more variable during periods of elevated turbulence, demonstrating the impact of SBL intermittency. This study uses an idealized configuration, focusing on LES model performance and physical understanding, with the goal of informing future simulations of the conditions observed during the American Wake Experiment.

Energy - Wind↗

DOE OSTI2025

Comparative studies of cross-phase dynamics in turbulent momentum flux and particle flux at the tokamak edge

Turbulent transport events, including turbulent transport flux of momentum (i.e., turbulent momentum flux or Reynolds stress) and turbulent transport flux of particle (i.e., turbulent particle flux), have important effects on the confinement performance of magnetic confinement fusion devices. Poloidal Reynolds stress is the ensemble average of the product of radial velocity fluctuations and poloidal velocity fluctuations, i.e., $\langle {\widetilde{v}}_{r}{\widetilde{v}}_{\theta }\rangle$. Turbulent particle flux is the ensemble average of the product of radial velocity fluctuations and density fluctuations, i.e., $\langle \widetilde{n}{\widetilde{v}}_{r}\rangle$. Changes in either amplitude of fluctuations or cross phase between fluctuations can cause changes in turbulent transport. In this paper, cross-phase dynamics in the Reynolds stress and turbulent particle flux at the tokamak edge are studied in detail. Reynolds stress and turbulent particle flux are, respectively, written as the product of fluctuation amplitudes and an average cross-phase factor. The mathematical expressions of the average cross-phase factors are derived. The average cross-phase factors and the power spectra of cross phase are obtained using experimental measurement data. It is found that the cross-phase dynamics in Reynolds stress and particle flux are very different. Reynolds stress is found to be more sensitive to cross phase than particle flux is. In the strong $E\times B$ shear layer, spatial slips of cross phase lead to the obvious radial gradient of Reynolds stress. In the no/weak $E\times B$ shear region, the cross phase in Reynolds stress tends to lock. Here, phase locking refers to that the power spectra of phase tend to distribute around a fixed phase which does not change with radial position, while phase slip means that the power spectra of cross phase tend to distribute around a phase that varies with radial position. Phase slip or locking mainly describes the central phase weighted by the power spectra, while the phase scattering mainly describes the dispersion of the power spectrum distribution of the phase. The increased scattering of cross phase, which indicates the power spectra distribution of the phase is more dispersed, contributes to the decreased Reynolds stress for higher collisionality. The cross phase in particle flux tends to lock in both strong and no/weak shear regions. The degree of scattering of cross phase in the particle flux does not change obviously as collisionality increases. For higher collisionality, it is the increased density fluctuation amplitude rather than cross-phase dynamics that leads to the increased particle flux. The underlying physical mechanism that causes Reynolds stress and particle flux to exhibit different phase dynamics is discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Sub-Alfvénic Turbulence: Magnetic-to-kinetic Energy Ratio, Modification of Weak Cascade, and Implications for Magnetic Field Strength Measurements

Abstract We study the properties of sub-Alfvénic magnetohydrodynamic (MHD) turbulence, i.e., turbulence with Alfvén mach number M A = V L / V A < 1, where V L is the velocity at the injection scale and V A is the Alfvén velocity. We demonstrate that MHD turbulence can have different properties, depending on whether it is driven by velocity or magnetic fluctuations. If the turbulence is driven by isotropic bulk forces acting upon the fluid, i.e., is velocity driven, in an incompressible conducting fluid we predict that the kinetic energy is M A − 2 times larger than the energy of magnetic fluctuations. This effect arises from the long parallel wavelength tail of the forcing, which excites modes with k ∥ / k ⊥ < M A . We also predict that as the MHD turbulent cascade reaches the strong regime, the energy of slow modes exceeds the energy of Alfvén modes by a factor M A − 1 . These effects are absent if the turbulence is driven through magnetic fluctuations at the injection scale. We confirm our predictions with numerical simulations. Since the assumption of magnetic and kinetic energy equipartition is at the core of the Davis–Chandrasekhar–Fermi (DCF) approach to measuring magnetic field strength in sub-Alfvénic turbulence, we conclude that the DCF technique is not universally applicable. In particular, we suggest that the dynamical excitation of long azimuthal wavelength modes in the galactic disk may compromise the use of the DCF technique. We discuss alternative expressions that can be used to obtain magnetic field strength from observations and consider ways of distinguishing the cases of velocity and magnetically driven turbulence using observational data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Collaborative Research: Unveiling the Interplay Between Magnetic Reconnection and Turbulence — Theory and Modeling

This is the final technical report for the project "Collaborative Research: Unveiling the Interplay Between Magnetic Reconnection and Turbulence — Theory and Modeling." This project investigated the interplay between two fundamental plasma processes — turbulence and magnetic reconnection — and the associated heating and particle acceleration. In particular, we focused on a new regime where the plasmoid instability mediates the turbulent energy cascade. In this new regime, reconnecting current sheets are disrupted by the growth of plasmoids/flux ropes on time scales shorter than the typical turnover times of eddies, speeding up the energy cascade and steepening the turbulence energy spectrum. This project addressed the following outstanding open questions: (1) What are the fundamental differences between plasmoid‐mediated turbulence cascade in three dimensions (3D) and two dimensions (2D)? (2) What are the essential features of plasmoid‐mediated turbulence in weakly collisional or collisionless regimes beyond resistive MHD? (3) How does the interplay of turbulence and reconnection regulate the energy release and dissipation in space and astrophysical plasmas? To address these questions, we have carried out three investigations: (1) Three-dimensional plasmoid-mediated turbulence energy cascade; (2) plasmoid-mediated reconnection and turbulence in three-dimensional Hall MHD; (3) reconnection and heating in coronal loops. This technical report summarizes the key findings of these investigations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Simulated meteorological impacts of offshore wind turbines and sensitivity to the amount of added turbulence kinetic energy

Offshore wind energy projects are currently in development off the east coast of the United States and may influence the local meteorology of the region. Wind power production and other commercial uses in this area are related to atmospheric conditions, and so it is important to understand how future wind plants may change the local meteorology. In the absence of measurements of potential wind plant impacts on meteorology, simulations offer the next-best possible insight into wake effects on boundary layer height, temperature, fluxes, and wind speeds. However, simulation tools that capture these effects offer multiple options for representing the amount of turbine-added turbulence that may impact assessments of micrometeorological effects. To explore this sensitivity, we compare 1 year of simulations from the Weather Research and Forecasting (WRF) model with and without wind plants incorporated, focusing on the lease area south of Massachusetts and Rhode Island. The simulations with wind plants are repeated to include both the maximum and minimum amounts of added turbulence to provide bounds on the potential impacts. We assess changes in wind speeds, 2 m temperature, surface heat flux, turbulence kinetic energy (TKE), and boundary layer height during different stability classifications and ambient wind speeds over the entire year and compare results for the degree of added turbulence in the wind plant simulations. Because the wake behavior may be a function of boundary layer stability, in this paper, we also present a machine learning algorithm to quantify the area and distance of the wake generated by the wind plant. This analysis enables us to identify the relationship between wake extent and boundary layer height. We find that hub-height wind speed is reduced within and downwind of the wind plant, with the strongest impacts occurring during stable conditions and faster wind speeds in region 3 of the turbine power curve, although impacts lessen as wind speeds increase past 15 m s−1. In contrast, wind speeds near the surface decrease when no turbine-added turbulence is included but can increase for stably stratified conditions when 100 % of possible TKE is included in the simulations. TKE increases at hub height in the simulations with added TKE for all stability classes, suggesting that atmospheric stability does not immediately modify the TKE generated by turbines. Negligible changes in hub-height TKE manifest in the simulations without the added TKE. At the surface, TKE increases in the simulations with maximum added turbulence only for unstable conditions. In the no-added-turbulence simulations, surface TKE decreases slightly in neutral and unstable simulations. Differences in 2 m temperatures and surface heat fluxes are small but vary considerably with atmospheric stability and the amount of added TKE. Boundary layer heights increase within the wind plant when turbine-added turbulence is included and decrease slightly downwind during stable conditions. In contrast, with no added turbulence, the boundary layer height is in general reduced in stable conditions with wind speeds less than 15 m s −1 and slightly increased in neutral conditions. Finally, shallower upwind boundary layer heights tend to correlate with larger wake areas and distances, though other factors likely also play a role in determining the extent of the wind plant wake. These simulation-based results provide a bound for micrometeorological impacts of wind plant wakes: simulations that couple the atmosphere to the ocean may reduce these impacts, and we await observational verification.

17 WIND ENERGY↗

NASA NTRS1951

On the recording of turbulent longitudinal and transverse fluctuations

A thorough understanding of the turbulent flow movements cannot be arrived at from investigations of the temporal mean values of the flows alone. Study of the fluctuation phenomena themselves is indispensable. Thus turbulence research entered a new promising stage when investigators started performing fluctuation measurements and basing theories on those measurements. The investigations of fluctuations carried out so far refer almost exclusively to the so-called isotropic turbulence. It represents a damping phenomenon; it is the simplest type of turbulence where merely the longitudinal fluctuations need to be measured. However, it is precisely nonisotropic turbulence which involves the most essential problem of the turbulent exchange movement and the turbulent apparent friction. Investigation of nonisotropic turbulence requires measurement of longitudinal and transverse fluctuations.

TURBULENCE MEASURING APPARATUS, HOT-WIRE↗

DOE OSTI2025

Free-Space Optical Channel Turbulence Prediction: A Machine Learning Approach

Channel turbulence is a formidable obstacle for freespace optical (FSO) communication. Anticipation of turbulence levels is highly important for mitigating disruptions but has not been demonstrated without dedicated, auxiliary hardware. We show that machine learning (ML) can be applied to raw FSO data streams to rapidly predict channel turbulence levels with no additional sensing hardware. FSO was conducted through a controlled channel in the lab under six distinct turbulence levels, and the efficacy of using ML to classify turbulence levels was examined. ML-based turbulence level classification was found to be > 98% accurate with multiple ML training parameters. Classification effectiveness was found to depend on the timescale of changes between turbulence levels but converges when turbulence stabilizes over about a one minute timescale.

Zobaer Islam, Md [School of Electrical and Compute↗

DOE OSTI2026

Impact of atmospheric turbulence on performance and loads of wind turbines: knowledge gaps and research challenges

Wind energy harvesting from the atmosphere takes place in the atmospheric boundary layer. The boundary layer shear and buoyancy create three-dimensional turbulent eddies spanning a range of scales that form a continuous forward cascade of kinetic energy to the smallest scales of motion where energy is dissipated. Large-scale atmospheric circulations modulate the boundary layer turbulence, characterized by coherence and intermittency. As wind turbines grow in size and the integrated control of both turbines and wind farms spans greater distances, the relationship between the scales of atmospheric turbulence and the design and operation of wind energy facilities has entered new territory. The boundary layer turbulence impacts both wind turbine power production and turbine loads. Optimizing wind turbine and wind farm performance requires an understanding of how turbulence affects both wind turbine efficiency and reliability. While the characteristics of atmospheric boundary layer turbulence have been observed and studied in detail over the last few decades, there are still significant gaps in our understanding of the impact of turbulence on wind power resources and wind farm operations. This paper outlines the current state of turbulence research relevant to wind energy applications and points to gaps in our knowledge that need to be addressed to effectively utilize wind resources.

Kosović, Branko [Johns Hopkins Univ., Baltimore, M↗

NASA NTRS1958

The effect of free-stream turbulence on heat transfer from a flat plate

Turbulence was generated by using screens, and the turbulence percentage was measured by a hot-wire anemometer both in the boundary layer and the free stream. The local heat-transfer coefficient was measured at 12 locations along the plate for the cases of various turbulence levels. The transition Reynolds number from laminar to turbulent flow decreases as the main-stream turbulence level increases. In the range of laminar heat transfer the effect of turbulence in the main flow was not great, but in the range of turbulent heat transfer the heat-transfer coefficient increases according to the increase of turbulence.

HEAT TRANSFER, AERODYNAMIC↗

NASA NTRS1995

Turbulance Boundary Conditions for Shear Flow Analysis, Using the DTNS Flow Solver

The effects of different turbulence boundary conditions were examined for two classical flows: a turbulent plane free shear layer and a flat plate turbulent boundary layer with zero pressure gradient. The flow solver used was DTNS, an incompressible Reynolds averaged Navier-Stokes solver with k-epsilon turbulence modeling, developed at the U.S. Navy David Taylor Research Center. Six different combinations of turbulence boundary conditions at the inflow boundary were investigated: In case 1, 'exact' k and epsilon profiles were used; in case 2, the 'exact' k profile was used, and epsilon was extrapolated upstream; in case 3, both k and epsilon were extrapolated; in case 4, the turbulence intensity (I) was 1 percent, and the turbulent viscosity (mu(sub t)) was equal to the laminar viscosity; in case 5, the 'exact' k profile was used and mu(sub t) was equal to the laminar viscosity; in case 6, the I was 1 percent, and epsilon was extrapolated. Comparisons were made with experimental data, direct numerical simulation results, or theoretical predictions as applicable. Results obtained with DTNS showed that turbulence boundary conditions can have significant impacts on the solutions, especially for the free shear layer.

M Mizukami↗

NASA NTRS1960

Turbulence Studies of a Rectangular Slotted Noise-Suppressor Nozzle

The problem of noise suppression of turbojet engines has shown a need for turbulence data within the flow field of various types of nozzles used in ad hoc investigations of the sound power. The result of turbulence studies in a nozzle configuration of four parallel rectangular slots is presented in this report with special attention to the effect of the spacing of the nozzles on the intensity of turbulence, scale of turbulence, spectrum of turbulence, and the mean stream velocity. Taylor's hypothesis, which describes the convection of the turbulence eddies, was tested and found correct within experimental error and certain experimental and theoretical limitations. The convection of the pressure patterns was also investigated, and the value of the convection velocity was found to be about 0.43 times the central core velocity of the jets. The effect of the spacing-to-width ratio of the nozzles upon the turbulence intensity, the scale of turbulence, and the spectral distribution of the noise was found in general to produce a maximum change for spacing-to-width ratios of 1.5 to 2.0. These changes may be the cause of the reduction in sound power reported for similar full-scale nozzles and test conditions under actual (static) engine operation. A noise reduction parameter is defined from Lighthill's theory which gives qualitative agreement with experiments which show the noise reduction is greatest for spacing-to-width ratios of 1.5 to 2.0.

Laurence, James C.↗

DOE OSTI2025

Molecular fluctuations inhibit intermittency in compressible turbulence

In the standard picture of fully developed turbulence, highly intermittent hydrodynamic fields are nonlinearly coupled across scales, where local energy cascades from large scales into dissipative vortices and large density gradients. Microscopically, however, constituent fluid molecules are in constant thermal (Brownian) motion, but the role of molecular fluctuations in large-scale turbulence is largely unknown, and with rare exceptions, it has historically been considered irrelevant at scales larger than the molecular mean free path. Recent theoretical and computational investigations have shown that molecular fluctuations can impact energy cascade at Kolmogorov length scales. Here, we show that molecular fluctuations not only modify energy spectrum at wavelengths larger than the Kolmogorov length in compressible turbulence, but also significantly inhibit spatio-temporal intermittency across the entire dissipation range. Using large-scale direct numerical simulations of computational fluctuating hydrodynamics, we demonstrate that the extreme intermittency characteristic of turbulence models is replaced by nearly Gaussian statistics in the dissipation range. These results demonstrate that the compressible Navier–Stokes equations should be augmented with molecular fluctuations to accurately predict turbulence statistics across the dissipation range. Our findings have significant consequences for turbulence modelling in applications such as astrophysics, reactive flows and hypersonic aerodynamics, where dissipation-range turbulence is approximated by closure models.

compressible turbulence↗

DOE OSTI2026

Combined effects of horizontal and vertical resolution on reliable turbulence prediction at tidal energy sites: A systematic study in the Salish Sea, WA

Predicting turbulence characteristics with coastal ocean models is essential for tidal energy converter deployment. While large eddy simulation provides a detailed turbulence representation, computational limitations restrict its use to smaller domains. We systematically evaluate whether well-configured coastal models can provide reliable turbulence prediction through progressive refinement of 3D model representation. We implemented four model configurations (Levels 1–4) using terrain-following coordinates, isolating the impacts of horizontal resolution, vertical resolution, and layer distribution. We validated all configurations against field measurements from the Salish Sea, WA. Results show that tidal current velocity predictions remain unchanged regarding model configuration, but turbulence properties are sensitive to resolution refinement. Increasing vertical resolution alone proved insufficient; even with vertical sigma-levels rising from 11 to 41, significant underprediction persisted until finer horizontal resolution better captured bathymetric variations. The Level 4 configuration, incorporating geometric sigma-levels distribution, achieved turbulence prediction skill scores exceeding 0.90. Turbulence closure comparison revealed Mellor- Yamada 2.5 outperformed k-epsilon in TKE prediction (skill scores 0.84–0.94 versus 0.72–0.81) due to better boundary layer parameterization. This study shows that well-configured coastal models effectively bridge the gap between simplified tools and costly high-fidelity modeling, offering the tidal energy industry practical and cost-effective turbulence data at commercially relevant scales.

Marine Energy↗

DOE OSTI2025

Global gyrokinetic simulations of kinetic-ballooning-mode turbulence in Wendelstein 7-X

We apply the global gyrokinetic code GENE-3D to perform kinetic-ballooning-mode (KBM) turbulence simulations in the Wendelstein 7-X (W7-X) stellarator using experimentally relevant parameters. In contrast to the flux-tube approach, we observe saturation of the turbulent fluctuations at finite amplitude. Analyzing the turbulent characteristics, we identify the presence of weakly driven KBM turbulence hybridizing with ion-temperature-gradient and trapped-electron-mode turbulence in the scenario under consideration, showing that it is possible that KBM activity can be driven in W7-X, opening up the path for studying this type of turbulence, which is highly relevant for future fusion power plants.

Electrostatics↗

DOE OSTI2025

Non-propagating structures and propagating waves in solar wind turbulence revealed by simulations and observations

Structures and waves are common features of solar wind turbulence at various scales. The interplay between structures and waves is important for processes such as the turbulent energy cascade, plasma heating, and particle scattering. Our understanding of turbulence has been advanced by not only new space missions and numerical simulations, but also techniques that have been developed to interpret the rapidly growing turbulence data. We review basic models of turbulence with a specific focus on the analysis methods for understanding magnetic structures and waves. MHD and kinetic waves in single-spacecraft time series measurements can be identified through mode decomposition or their characteristic polarization signatures. The structures in this paper are considered as zero-frequency, non-propagating or convected modes embedded in the solar wind. The synergy between observations and simulations is most evident in the application of spatial-temporal analysis to multi-spacecraft observation and turbulence simulations. The spatial-temporal analysis has greatly improved our understanding of structures and waves in turbulence. We conclude by discussing prospects for future research.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Nature of transonic sub-Alfvénic turbulence and density fluctuations in the near-Sun solar wind

Context. Recent Parker Solar Probe (PSP) measurements have revealed that solar wind (SW) turbulence transits from a subsonic to a transonic regime near the Sun, while remaining sub-Alfvénic. These observations call for a revision of the existing SW models, where turbulence is considered to be both subsonic and sub-Alfvénic. Aims. In this work, we introduce a new magnetohydrodynamic (MHD) model of transonic sub-Alfvénic turbulence (TsAT). Methods. We used 3D MHD simulations initialized with parameters measured by PSP to investigate the properties of the new near-Sun SW transonic turbulent regime. We then derived a reduced set of MHD equations in the transonic sub-Alfvénic limit to interpret our numerical results. Results. Our TsAT model shows that turbulence is effectively nearly incompressible (NI) and has a 2D + slab (quasi-2D) geometry not only in the subsonic limit, but also in the transonic regime, as long as it remains sub-Alfvénic, a condition essentially enforced everywhere in the heliosphere by the strong local magnetic field. These predictions are consistent with 3D MHD simulations, showing that transonic turbulence is dominated by low-frequency quasi-2D incompressible structures, while compressible fluctuations are a minor component corresponding to low-frequency slow modes and high-frequency fast modes. Conclusions. Our new TsAT model extends existing NI theories of turbulence, and is potentially relevant for the theoretical and numerical modeling of space and astrophysical plasmas, including the near-Sun SW, the solar corona, and the interstellar medium.

79 ASTRONOMY AND ASTROPHYSICS↗