Modeling the pressure strain correlation in turbulent flows using deep neural networks

The pressure strain correlation plays a critical role in the Reynolds stress transport modeling. Accurate modeling of the pressure strain correlation leads to the proper prediction of turbulence stresses and subsequently the other terms of engineering interest. However, classical pressure strain correlation models are often unreliable for complex turbulent flows. Machine learning–based models have shown promise in turbulence modeling, but their application has been largely restricted to eddy viscosity–based models. In this article, we outline a rationale for the preferential application of machine learning and turbulence data to develop models at the level of Reynolds stress modeling. As an illustration, we develop data-driven models for the pressure strain correlation for turbulent channel flow using neural networks. The input features of the neural networks are chosen using physics-based rationale. The networks are trained with the high-resolution DNS data of turbulent channel flow at different friction Reynolds numbers (Reλ). The testing of the models is performed for unknown flow statistics at other Reλ and also for turbulent plane Couette flows. Based on the results presented in this article, the proposed machine learning framework exhibits considerable promise and may be utilized for the development of accurate Reynolds stress models for flow prediction.

A New Cross-Platform Instrument for Microstructure Turbulence Measurements

This study developed a new cross-platform instrument for microstructure turbulence measurement (CPMTM) and evaluated its performance. The CPMTM is designed as an “all-in-one” payload that can be easily integrated with a variety of marine instrumentation platforms. The sensors in the CPMTM include two shear probes, a fast-response temperature probe, and an accelerometer for monitoring vibrations. In addition, a custom-designed flexible connection vibration-damping device is used to isolate platform vibrations. To validate the CPMTM performance, a direct comparison was carried out with a reference acoustic Doppler velocimeter in a controlled flume for four background turbulence levels. The results of the comparison show that the velocity spectra measured by the CPMTM and ADV w components are in agreement, which demonstrates the ability of the CPMTM to acquire accurate turbulence data. Furthermore, the CPMTM was integrated into the long-range Sea-Whale 2000 AUV and tested in the northern South China Sea in September 2020. The data collected by the CPMTM show that the measured shear spectrum of the noise reduction agrees well with the empirical Nasmyth spectrum. Turbulent kinetic energy dissipation rates as low as 7 × 10−10 W kg−1 can be resolved. Laboratory and field experiments illustrate that the CPMTM has an extraordinarily low noise level and is validated for turbulence measurements.

Multi-scale analysis of turbulence data from AIRTEC-CM urban field campaigns in Madrid

<p>Several urban field campaigns have been carried out in the city of Madrid (Spain) during the years 2020 and 2021 in the frame of the AIRTEC-CM <sup>(*)</sup> research project (Urban Air Quality and Climate Change Integral Assessment). The analysis of the relation between the turbulence measured close to the surface and pollution concentration (e.g., particle matter of different sizes, NO<sub>x</sub>, etc.) is a key aspect to achieve the different objectives of the project. In this context, we present some preliminary analyses of the turbulence data measured from sonic anemometers located at different emplacements. We focus on the turbulence differences among two instruments nearby located but at different heights above the street level: 1) at the top of a 22 m-height building, and 2) at the top of a shorter building of 2.5 m of height. Typical turbulent parameters (turbulent kinetic energy (TKE), friction velocity (u*) and sensible heat flux (SH)) are analysed for both sonic anemometers and their differences are statistically compared. An investigation of the main temporal scales involved in the atmospheric diffusion is also performed using the Multi-Resolution Flux Decomposition technique (MRFD), applied over a relatively long period that includes different atmospheric conditions in February 2020. The information obtained from this analysis will be related to the pollution concentration measured in the city, trying to determine the importance of the near-surface turbulence (and the corresponding scales of the main eddies found) in the pollutant’s levels.</p><p> </p><p>(*) AIRTEC-CM research project (S2018/EMT-4329) is funded by The Regional Government of Madrid (Spain).</p>

A Two-Day Case Study: Comparison of Turbulence Data from an Unmanned Aircraft System with a Model Chain for Complex Terrain

The airborne measurement platform MASC-3 (Multi-Purpose Airborne Sensor Carrier) is used for measurements over a forested escarpment in the Swabian Alps to evaluate the wind field. Data from flight legs between 20 and 200 m above the ground on two consecutive days with uphill (westerly) flow in September 2018 are analyzed. In the lowest 140 m above the ground a speed-up is found with increased turbulence and changes in wind direction directly over the escarpment, whereas in the lowest 20 to 50 m above the ground a deceleration of the flow is measured. Additionally, simulation results from a numerical model chain based on the Weather Research and Forecasting (WRF) model and an OpenFOAM (Open Source Field Operation and Manipulation) model, developed for complex terrain, are compared to the data captured by MASC-3. The models and measurements compare well for the mean wind speed and inclination angle.

H∞ controller design for the mitigation of atmospheric effects on the laser beam pointing

In this paper, the control of a fast steering mirror, which is the core element of an adaptive optics system, is investigated to suppress the beam jitter. The main source of the jitter is taken as the atmospheric turbulence. The effect of the atmospheric turbulence on the beam jitter is experimentally determined with respect to the two different refractive index structure parameters. The mathematical model of the fast steering mirror based on the atmoshperic turbulence data is obtained using the system identification. In order to overcome implementation problems, the low order proportional-integral-derivative (PID) type controllers, which minimize the [Formula: see text] norm of the closed loop system, are designed in the centralized and the decentralized settings. In addition to this, the fixed order weighted [Formula: see text] controller is based on the frequency characteristics of the atmospheric turbulence that is determined experimentally. Then, in order to show the effectiveness of the proposed low order PID type controller, the designed controllers are compared on the experimental setup. Finally, the simulation and the experimental results are presented. Comparison of advantageous and disadvantageous of centralized and decentralized controller architectures are discussed.

Surface cooling caused by rare but intense near-inertial wave induced mixing in the tropical Atlantic

<p>The direct response of the tropical mixed layer to near-inertial waves (NIWs) has only rarely been observed. Here, we present upper-ocean turbulence data that provide evidence for a strongly elevated vertical diffusive heat flux across the base of the mixed layer in the presence of a NIW, thereby cooling the mixed layer at a rate of 244 Wm<sup>−2</sup> over the 20 h of continuous measurements. We investigate the seasonal cycle of strong NIW events and find that despite their local intermittent nature, they occur preferentially during boreal summer, presumably associated with the passage of atmospheric African Easterly Waves. We illustrate the impact of these rare but intense NIW induced mixing events on the mixed layer heat balance, highlight their contribution to the seasonal evolution of sea surface temperature, and discuss their potential impact on biological productivity in the tropical North Atlantic.</p>

Multiscale Sample Entropy of Two-Dimensional Decaying Turbulence

Multiscale sample entropy analysis has been developed to quantify the complexity and the predictability of a time series, originally developed for physiological time series. In this study, the analysis was applied to the turbulence data. We measured time series data for the velocity fluctuation, in either the longitudinal or transverse direction, of turbulent soap film flows at various locations. The research was to assess the feasibility of using the entropy analysis to qualitatively characterize turbulence, without using any conventional energetic analysis of turbulence. The study showed that the application of the entropy analysis to the turbulence data is promising. From the analysis, we successfully captured two important features of the turbulent soap films. It is indicated that the turbulence is anisotropic from the directional disparity. In addition, we observed that the most unpredictable time scale increases with the downstream distance, which is an indication of the decaying turbulence.

Observations of Sweep-Ejection Dynamics for Heat and Momentum Fluxes during Wildland Fires in Forested and Grassland Environments

The vertical turbulent transfer of heat and momentum in the lower atmospheric boundary layer is accomplished through intermittent sweep, ejection, outward interaction, and inward interaction events associated with turbulent updrafts and downdrafts. These events, collectively referred to as sweep-ejection dynamics, have been studied extensively in forested and non-forested environments and reported in the literature. However, little is known about the sweep-ejection dynamics that occur in response to turbulence regimes induced by wildland fires in forested and non-forested environments. This study attempts to fill some of that knowledge gap through analyses of turbulence data previously collected during three wildland (prescribed) fires that occurred in grassland and forested environments in Texas and New Jersey. Tower-based high-frequency (10 or 20 Hz) three-dimensional wind velocity and temperature measurements are used to examine frequencies of occurrence of sweep, ejection, outward interaction, and inward interaction events and their actual contributions to the mean vertical turbulent fluxes of heat and momentum before, during, and after the passage of fire fronts. The observational results suggest that wildland fires in these environments can substantially change the sweep-ejection dynamics for turbulent heat and momentum fluxes that typically occur when no fires are present, especially the relative contributions of sweeps compared to ejections in determining overall heat and momentum fluxes.

Stochastic Models of Particle Trajectories in Turbulent Atmosphere Flows by Using the LANGEVIN Equations

The stochastic behavior of wind speed is a particular characteristic of wind energy production, which affects the degradation mechanism of the turbine, resulting in stochastic charging on the wind turbine. A model stochastic is used in this study to evaluate the efficiency of wind turbine power of whatever degree given fluctuating wind turbulence data. This model is based on the Langevin equations, which characterize, by two coefficients, drift and diffusion functions. These coefficients describe the behavior of the transformation process from the input wind speed to the output data that need to be determined. For this present work, the computation of drift and diffusion functions has been carried out by using the stochastic model to assess the output variables in terms of the torque and power curves as a function of time, and it is compared by the classical method. The results show that the model stochastic can define the efficiency of wind turbine generation more precisely.