Real Turbulence Research Articles

Blind Restoration of a Single Real Turbulence-Degraded Image Based on Self-Supervised Learning

Turbulence-degraded image frames are distorted by both turbulent deformations and space–time varying blurs. Restoration of the atmospheric turbulence-degraded image is of great importance in the state of affairs, such as remoting sensing, surveillance, traffic control, and astronomy. While traditional supervised learning uses lots of simulated distorted images for training, it has poor generalization ability for real degraded images. To address this problem, a novel blind restoration network that only inputs a single turbulence-degraded image is presented, which is mainly used to reconstruct the real atmospheric turbulence distorted images. In addition, the proposed method does not require pre-training, and only needs to input a single real turbulent degradation image to output a high-quality result. Meanwhile, to improve the self-supervised restoration effect, Regularization by Denoising (RED) is introduced to the network, and the final output is obtained by averaging the prediction of multiple iterations in the trained model. Experiments are carried out with real-world turbulence-degraded data by implementing the proposed method and four reported methods, and we use four non-reference indicators for evaluation, among which Average Gradient, NIQE, and BRISQUE have achieved state-of-the-art effects compared with other methods. As a result, our method is effective in alleviating distortions and blur, restoring image details, and enhancing visual quality. Furthermore, the proposed approach has a certain degree of generalization, and has an excellent restoration effect for motion-blurred images.

Transition to Equilibrium and Coherent Structure in Ideal MHD Turbulence, Part 2

We continue our study of the transition of ideal, homogeneous, incompressible, magnetohydrodynamic (MHD) turbulence from non-equilibrium initial conditions to equilibrium using long-time numerical simulations on a 1283 periodic grid. A Fourier spectral transform method is used to numerically integrate the dynamical equations forward in time. The six runs that previously went to near equilibrium are here extended into equilibrium. As before, we neglect dissipation as we are primarily concerned with behavior at the largest scale where this behavior has been shown to be essentially the same for ideal and real (forced and dissipative) MHD turbulence. These six runs have various combinations of imposed rotation and mean magnetic field and represent the five cases of ideal, homogeneous, incompressible, and MHD turbulence: Case I (Run 1), with no rotation or mean field; Case II (Runs 2a and 2b), where only rotation is imposed; Case III (Run 3), which has only a mean magnetic field; Case IV (Run 4), where rotation vector and mean magnetic field direction are aligned; and Case V (Run 5), which has non-aligned rotation vector and mean field directions. Statistical mechanics predicts that dynamic Fourier coefficients are zero-mean random variables, but largest-scale coherent magnetic structures emerge and manifest themselves as Fourier coefficients with very large, quasi-steady, mean values compared to their standard deviations, i.e., there is ‘broken ergodicity.’ These magnetic coherent structures appeared in all cases during transition to near equilibrium. Here, we report that, as the runs were continued, these coherent structures remained quasi-steady and energetic only in Cases I and II, while Case IV maintained its coherent structure but at comparatively low energy. The coherent structures that appeared in transition in Cases III and V were seen to collapse as their associated runs extended into equilibrium. The creation of largest-scale, coherent magnetic structure appears to be a dynamo process inherent in ideal MHD turbulence, particularly in Cases I and II, i.e., those cases most pertinent to planets and stars. Furthermore, the statistical theory of ideal MHD turbulence has proven to apply at the largest scale, even when dissipation and forcing are included. This, along with the discovery and explanation of dynamically broken ergodicity, is essentially a solution to the ‘dynamo problem’.

An improved method for estimating the dissipation rate of turbulent kinetic energy using structure functions evaluated from the motion of finite-sized neutrally buoyant particles

Statistical relations used for estimating the dissipation rate of turbulent kinetic energy (TKE) in isotropic turbulence from the inertial subrange of Lagrangian temporal and spatial structure functions are extended here to the case of more realistic turbulence spectra that include low-frequency and low-wavenumber ranges. It is shown that using the traditional relations based only on the inertial subrange substantially underestimates the dissipation. The improved relations are better constrained by experimental data from which the dissipation is evaluated, enabling more accurate dissipation estimates. The concept is illustrated using laboratory data from water tank experiments of turbulence generated by an oscillating cylinder, where the dissipation is evaluated in three independent ways: from Lagrangian spectra and from Lagrangian temporal and spatial structure functions calculated from the motion of neutrally buoyant finite-sized particles. An additional correction to the relations for estimating the dissipation from the spatial structure functions is applied to take into account the filtering effect of the particles due to their finite size. It is found that, for these particular experiments, the TKE dissipation rate scales well with dimensionally consistent quantities built using the amplitude of the oscillation of the cylinder and the period of its motion, and the constant of proportionality in this scaling relation is determined using the method proposed here. Although the turbulence under consideration is quite anisotropic, the adopted theoretical framework, which assumes isotropic turbulence, seems to be applicable to the experimental data as long as the turbulence statistics are averaged over the three main flow directions.

Wind turbulence modeling for real-time simulation

This paper proposes a method to design a real-time wind turbulence simulator. The objective of such a simulator is to make dynamical models more accurate in order to develop more robust controls, especially in the case of mechanical systems operating outdoors such as tracking antennas. The models used to generate a random wind speed are based on the wind spectral characteristics rather than time domain ones. Indeed, turbulence is a stochastic and non-stationary process corresponding to the short-term component of wind and therefore is difficult to model in time domain. Wind spectral characteristics are described by the power spectral density whose approximation is used in the real-time simulator to reproduce wind behavior. The von Kármán model is the most commonly used model to approximate the power spectral density of wind turbulence. However, this model was originally designed for aircraft, and therefore for high altitudes and moving systems. In our case, tracking antennas are used under different conditions: low altitude and slow moving systems. This makes the von Kármán model less precise in middle and high range frequency. Consequently, there is a need in more accurately modeling wind turbulence under these specific conditions. As von Karman’s model expression uses fractional calculus, other models with the same range of parameter number are proposed to better approximate the wind power spectral density by using Cole-Cole and Davidson-Cole fractional models. The idea is to use shaping filters issued from these more precise fractional models to generate realistic random wind speed turbulence from a random white noise input. These filters are approximated by rational functions and their parameters are tuned in the same way as those of the von Kármán model with the same inputs (mean speed, standard deviation and length scale). If a rational model is sought, a very high number of parameters (more than six times) is needed to have the same precision as our proposed fractional Cole-Cole model which has only four parameters. Finally, an accurate turbulence wind speed generator is proposed.

Impact of the turbulence wavenumber spectrum and probing beam geometry on Doppler reflectometry perpendicular velocity measurements

The perpendicular propagation velocity of turbulent density fluctuations is an important parameter in fusion plasmas, since sheared plasma flows are crucial for reducing turbulence, and thus an essential input parameter for turbulent transport simulations. In the recent past various fusion devices have observed poloidal asymmetry in this velocity using Doppler reflectometry (DR) and correlation reflectometry. In this work, the phase screen model is used to analytically explain and quantify the combined effect of finite wavenumber resolution due to plasma curvature and probing beam geometry in a realistic turbulence wavenumber spectrum, leading to a reduced dominantly back-scattered wavenumber and a further underestimation of the perpendicular propagation velocity determined by DR. The full-wave code IPF-FD3D, which simulates microwave propagation and scattering, is used as a synthetic DR to study the effects of this diagnostic effect in a circular geometry using various isotropic synthetic turbulence wavenumber spectra. Angular scans from the midplane and variations in the position of the probing antenna are shown to estimate the impact of the diagnostic effect on the poloidal asymmetries.

Atmospheric effects on the laser-driven avalanche-based remote detection of radiation

The effect of realistic atmospheric conditions on mid-IR (λ = 3.9 µm) and long-wave-IR (λ = 10 µm) laser-induced avalanche breakdown for the remote detection of radioactive material is examined experimentally and with propagation simulations. Our short-range in-lab mid-IR laser experiments show a correlation between increasing turbulence level and a reduced number of breakdown sites associated with a reduction in the portion of the focal volume above the breakdown threshold. Simulations of propagation through turbulence are in excellent agreement with these measurements and provide code validation. We then simulate propagation through realistic atmospheric turbulence over a long range (0.1-1 km) in the long-wave-IR regime (λ = 10 µm). The avalanche threshold focal volume is found to be robust even in the presence of strong turbulence, only dropping by ∼50% over a propagation length of ∼0.6 km. We also experimentally assess the impact of aerosols on avalanche-based detection, finding that, while background counts increase, a useful signal is extractable even at aerosol concentrations 105 times greater than what is typically observed in atmospheric conditions. Our results show promise for the long-range detection of radioactive sources under realistic atmospheric conditions.

Helical model based on artificial neural network for large eddy simulation of compressible wall-bounded turbulent flows

Similar to the kinetic energy cascade, a helicity cascade is also a basic and key process in the generation and evolution of the turbulent flows. Furthermore, the helicity flux (HF) plays a crucial role between two scales in the helicity cascade. In this study, we will supply a new helical model constrained by the helicity flux for the large eddy simulation of the compressible turbulent flows. Then, in order to obtain a more precise HF, the local coefficient of the modeled HF is determined by the artificial neural network (ANN) method. The new model combines merits of the high robustness and the correlation with the real turbulence. In the test case of the compressible turbulent channel flow, the new model can supply a more accurate mean velocity profile, turbulence intensities, Reynolds stress, etc. Then, for the test in the compressible flat-plate boundary layer, the new model can also precisely predict the onset and peak of the transition process, the skin-friction coefficient, the mean velocity in the turbulent region, etc. Moreover, the ANN here is a semi-implicit method, and the new model would be easier to be generalized to simulate other types of the compressible wall-bounded turbulent flows.

Transition to Equilibrium and Coherent Structure in Ideal MHD Turbulence

Transition of ideal, homogeneous, incompressible, magnetohydrodynamic (MHD) turbulence to near-equilibrium from non-equilibrium initial conditions is examined through new long-time numerical simulations on a 1283 periodic grid. Here, we neglect dissipation because we are primarily concerned with behavior at the largest scale which has been shown to be essentially the same for ideal and real (forced and dissipative) MHD turbulence. A Fourier spectral transform method is used to numerically integrate the dynamical equations forward in time and results from six computer runs are presented with various combinations of imposed rotation and mean magnetic field. There are five separate cases of ideal, homogeneous, incompressible, MHD turbulence: Case I, with no rotation or mean field; Case II, where only rotation is imposed; Case III, which has only a mean magnetic field; Case IV, where rotation vector and mean magnetic field direction are aligned; and Case V, which has nonaligned rotation vector and mean field directions. Dynamic coefficients are predicted by statistical mechanics to be zero-mean random variables, but largest-scale coherent magnetic structures emerge in all cases during transition; this implies dynamo action is inherent in ideal MHD turbulence. These coherent structures are expected to occur in Cases I, II and IV, but not in Cases III and V; future studies will determine whether they persist.

String Stable Heterogeneous Aircraft in a Windy Environment

This research develops and analyzes an approach to solve the continuous monitoring problem. The analysis focuses on the string stability of a system of airspeed heterogeneous nonlinear aircraft that are controlled to overfly an endpoint at specified time intervals. The system is modeled as a cascaded set of subsystems where the position of each subsystem, an individual aircraft, is based off the estimated overfly time of the preceding vehicle. The model also includes the effects of steady-state wind and turbulence. The system is made to be string stable by nondimensionalizing a portion of the dynamics, selecting variable command limits, and solving for exponentially stable controller gains. The simulation results confirm the stability guarantees of the theoretical analysis and show that a randomized group of 20 airspeed heterogeneous aircraft experiencing realistic wind and turbulence results in an estimated arrival time error that converges toward a relatively small steady-state range.

Wavelet applications for turbulence characterisation of real tidal flows measured with an ADCP

Understanding turbulence is crucial to the design of tidal energy converters as it influences loads, fatigue life and power production. Acoustic Doppler Current Profilers (ADCPs) are normally employed in measurement campaigns to analyse turbulence at a particular location. Coherent turbulent structures are known to lead to the highest turbulence-induced stresses and are typically analysed by Fourier transform. However, this method can only yield parameters which are averaged over the signal length or the analysing window, and hence may not fully represent real flow turbulence, which is often non-stationary. This study applies wavelet time–frequency analysis to ADCP data from an active tidal test site to examine the turbulence spectrum and coherence characteristics of the flow, comparing these to Fourier methods. Results show that the average quantities from wavelet analysis agree favourably with Fourier analysis. Moreover, wavelet analysis yields instantaneous spectra and coherence, which show that at this site, high energy bursts occur at frequencies known to be significant for TEC loading and have turbulence intensities up to 80% higher than the average. We show that these intermittent, coherent bursts are obscured by the averages associated with Fourier analysis, highlighting the need for methods such as wavelets to understand interactions between fluid flow and TEC.

Analysis of atmospheric optical turbulence model— methods and progress

Stratification is a significant characteristic of atmospheric turbulence, especially high-altitude turbulence. At a fixed height, the real optical turbulence value fluctuates by 1–2 orders of magnitude or even greater on the average value. The turbulence profile model based on the observed data is a statistical average result. It can neither represent the stratification characteristics of an actual atmospheric turbulence profile nor have the prediction function, and can not fully meet the demand of optical engineering. Owing to the limitation of the capacity and speed of the computer, it is impossible to solve the Navier Stokes equation through direct numerical simulation (DNS) and large eddy simulation (LES) to predict the optical turbulence. The solution is to predict the conventional gas parameters through the mesoscale weather numerical prediction model MM5/ WRF, and then calculate the turbulence parameters through the turbulence parameterization scheme. In this paper, the prediction methods and research results of <inline-formula><tex-math id="M6">\begin{document}$ C_n^2 $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="4-20221986_M6.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="4-20221986_M6.png"/></alternatives></inline-formula> in surface layer,boundary layer and free atmosphere layer are introduced. Tatarski formula is derived in detail from the turbulence kinetic energy prediction equation and the temperature fluctuation variance prediction equation, and the physical meaning and applicable conditions of the formula are summarized. The latest research progress of neural network prediction and Antarctic astronomical site selection is mainly introduced. The characteristics and differences among different models, such as the empirical model fitted with experimental data, the parameter model with conventional meteorological parameters based on Kolmogorov turbulence theory, the prediction model related to mesoscale meteorological model, and the neural network method based on data driving and so on, are analyzed. It is emphasized that Kolmogorov turbulence theory is the theoretical basis of the existing atmospheric optical turbulence parameter models.

Semi-analytic simulation of optical wave propagation through turbulence.

Split-step wave-optical simulations are useful for studying optical propagation through random media like atmospheric turbulence. The standard method involves alternating steps of paraxial vacuum propagation and turbulent phase accumulation. We present a semianalytic approach to evaluating the Fresnel diffraction integral with onephase screen between the source and observation planes and another screen in the observation plane. Specifically, we express the first phase screen's transmittance as a Fourier series, which allows us to bring phase screen effects outside of the Fresnel diffraction integral, thereby reducing the numerical computations. This particular setup is useful for simulating astronomical imaging geometries and two-screen laboratory experiments that emulate real turbulence with phase wheels, spatial light modulators, etc. Further, this is a key building block in more general semianalytic split-step simulations that have an arbitrary number of screens. Compared with the standard angular-spectrum approach using the fast Fourier transform, the semianalytic method provides relaxed sampling constraints and an arbitrary computational grid. Also, when a limited number of observation-plane points is evaluated or when many time steps or random draws are used, the semianalytic method can compute faster than the angular-spectrum method.

Effect of convective schemes in wall-resolved and wall-modeled LES of compressible wall turbulence

The current study discusses how numerical schemes and discretization approaches affect wall-resolved and wall-modeled LES outcomes. A turbulent boundary layer setup over a flat plate in both super- and hypersonic conditions is used to illustrate the effect of different numerical discretization strategies. In particular, six convective methods are examined, as well as various degrees of hybridization between shock-capturing and centered approaches: The former introducing non-negligible numerical viscosity, the latter being virtually dissipation-free. The analysis reveals that injected numerical viscosity due to upwinding procedures considerably alters wall dynamics for both wall-resolved and especially wall-modeled arrangements. In particular, if low-order or pure shock-capturing schemes are used, wall modeling fails in heading the system dynamics due to a strong modulation of main turbulent features. Conversely, realistic turbulence patterns are recovered if hybrid and/or high-order shock-capturing methods are employed. Thus, the paper establishes criteria for selecting a suitable numerical setup in wall-modeled LES, providing suggestions for grid resolution levels and convective scheme selection/hybridization. An overview perspective concerning numerical diffusion coupling with turbulent stresses in wall-resolved and wall-modeled LES is also provided.

Adaptive optics compensation of orbital angular momentum beams using a hybrid input-output algorithm with complementary binary masks.

For orbital angular momentum (OAM) beams, we show that the twin-image problem in the single-intensity-measurement hybrid input-output algorithm (HIOA) severely impairs the phase retrieval performance and propose a very simple method to overcome this problem. First, we introduce the principle of the single-intensity-measurement HIOA together with the underlying reason for the twin-image problem and propose a new scheme of the HIOA using a pair of complementary binary masks (CBMs) to overcome the twin-image problem. To verify the usefulness of the proposed CBM-HIOA in the OAM free-space optical system, a wave-optics simulation is used to produce relatively realistic atmospheric turbulence, and the turbulence-induced distorted phase of the probe Gaussian beam is retrieved to compensate for the phase distortion of OAM beams. The suppression of the bidirectional and stagnant convergence caused by the twin-image problem, the compensation of the turbulence-induced distorted phase of the OAM beams, and the influence of different CBM shapes are studied in detail by numerical simulations. The corresponding numerical results show the feasibility and efficacy of the CBM-HIOA used for the adaptive optics compensation of OAM beams.

Improvement of the Ocean Mixed Layer Model via Large-Eddy Simulation and Inverse Estimation

Abstract The ocean mixed layer model (OMLM) is improved using the large-eddy simulation (LES) and the inverse estimation method. A comparison of OMLM (Noh model) and LES results reveals that underestimation of the turbulent kinetic energy (TKE) flux in the OMLM causes a negative bias of the mixed layer depth (MLD) during convection, when the wind stress is weak or the latitude is high. It is further found that the entrainment layer thickness is underestimated. The effects of alternative approaches of parameterizations in the OMLM, such as nonlocal mixing, length scales, Prandtl number, and TKE flux, are examined with an aim to reduce the bias. Simultaneous optimizations of empirical constants in the various versions of Noh model with different parameterization options are then carried out via an iterative Green’s function approach with LES data as constraining data. An improved OMLM is obtained, which reflects various new features, including the enhanced TKE flux, and the new model is found to improve the performance in all cases, namely, wind-mixing, surface heating, and surface cooling cases. The effect of the OMLM grid resolution on the optimal empirical constants is also investigated. Significance Statement This work illustrates a novel approach to improve the parameterization of vertical mixing in the upper ocean, which plays an important role in climate and ocean models. The approach utilizes the data from realistic turbulence simulation, called large-eddy simulation, as proxy observation data for upper ocean turbulence to analyze the parameterization, and the statistical method, called inverse estimation, to obtain the optimized empirical constants used in the parameterization. The same approach can be applied to improve other turbulence parameterization, and the new vertical mixing parameterization can be applied to improve climate and ocean models.

Consistency improved random flow generation method for large eddy simulation of atmospheric boundary layer

Realistic turbulence is the key component to obtain accurate simulations for large eddy simulation of atmospheric boundary layer (ABL). At present, synthetic turbulence methods have been widely applied, but there are still some defects such that spatial correlations and cross-correlations between different velocity components cannot be strictly reproduced. Thus, we propose a new inflow turbulence generation (ITG) method, the consistency improved random flow generation (CIRFG) method. The proposed method is derived to model the spatial correlations and cross-correlations between different velocity components by explicitly embedding turbulence characteristics, thus it can be used widely in arbitrary situations without any empirical parameters. Meanwhile, the CIRFG method is maintained to satisfy arbitrary mean velocity, turbulence intensity, frequency spectra, temporal correlation, etc. Further, according to the simulation of ABL flows, it is verified that the new method has good self-sustainability of wind profiles. Finally, compared with the simulations of flow around high-rise building model with wind tunnel tests, it is demonstrated that the proposed method has high accuracy and feasibility.

Blind Restoration of Images Distorted by Atmospheric Turbulence Based on Deep Transfer Learning

Removing space-time varying blur and geometric distortions simultaneously from an image is a challenging task. Recent methods (including physical-based methods or learning-based methods) commonly default the turbulence-degraded operator as a fixed convolution operator. Obviously, the assumption does not hold in practice. According to the situation that the real turbulence distorted operator has double uncertainty in space and time dimensions, this paper reports a novel deep transfer learning (DTL) network framework to address this problem. Concretely, the training process of the proposed approach contains two stages. In the first stage, the GoPro Dataset was used to pre-train the Network D1 and freeze the bottom weight parameters of the model; in the second stage, a small amount of the Hot-Air Dataset was employed for finetuning the last two layers of the network. Furthermore, residual fast Fourier transform with convolution block (Res FFT-Conv Block) was introduced to integrate both low-frequency and high-frequency residual information. Subsequently, extensive experiments were carried out with multiple real-world degraded datasets by implementing the proposed method and four existing state-of-the-art methods. In contrast, the proposed method demonstrates a significant improvement over the four reported methods in terms of alleviating the blur and distortions, as well as improving the visual quality.

Hybrid RANS/LES study of tip leakage vortex instability and turbulence characteristics of a transonic turbine cascade

To conduct detailed investigations about vortex instability and turbulence characteristics near a transonic turbine tip region, a highly accuracy hybrid Reynolds averaged Navier Stokes (RANS) / large eddy simulation (LES) method, namely detached eddy simulation (DES)-type method, is adopted at the exit isentropic Mach number of 0.95. Validation results show that this hybrid method can provide an accurate prediction against experiments. In contrast with the RANS method, this method can exhibit superiority in capturing detailed small-scale flow structures and more realistic turbulence distribution. Based on various identification methods, two predominant instability patterns of tip leakage vortex (TLV), namely, vortex wandering and breakdown have been recognized successfully in its downstream progression. Due to the supplement of tip leakage flow (TLF), the TLV maintains a concentrated vortex morphology with a monotonically increasing transverse wandering magnitude inside the blade passage. Subsequently, the TLV breakdown phenomenon, which is mainly due to the high adverse pressure gradient aggravated by shock waves, can be observed downstream the trailing edge. Meanwhile, a “spiral-type” vortex breakdown is distinguished firstly in a transonic turbine environment, which cannot be found in the previous RANS literature. To investigate the nature of the vortex instability, we perform an analysis based on the vorticity transport equation, it's found that the convection term due to the velocity gradient dominated the leakage vorticity damping. Combined the triple decomposition with the proper orthogonal decomposition (POD) method, the mechanisms of vortex wandering have been further revealed, which exhibits non-zero perturbations in transverse modes and a helical mode in the streamwise direction. Furthermore, detailed analysis of the turbulence characteristics has been also conducted, which contains distributions of Reynolds stress terms and the turbulent kinetic energy (k) along the TLV core trajectory. It can be recognized that the high adverse pressure gradient by shock waves can result in a sharp increase of Reynolds normal stresses (τii), which can stretch the TLV in different directions and exerts detrimental effects on the vortex breakdown. As a complementary, the turbulent anisotropy is also evaluated by the Lumley triangle method, which exhibits a variation from the one-component anisotropy to a two-component morphology as the TLV migrating downstream, while a isotropic turbulence field may be formed downstream the trailing edge due to the intense mixing. Predicted turbulence characteristics, vortical instabilities, and their flow mechanism can provide guide towards lower loss design and flow control of the turbine blade.

Applications Of Thermographic Particle Image Velocimetry To Film Cooling Flow Experiments In A Closed Loop Wind Tunnel

A laser-imaging method based on thermographic phosphor tracer particles (thermographic particle image velocimetry) is used to simultaneously measure temperature and velocity fields in film cooling flows in wind tunnels, in order to compare novel film cooling configurations under conditions of realistic mainstream turbulence. Several important experimental factors that affect the measurement precision, accuracy, and ultimately the success of the technique in its application in these practical environments are identified: (1) the choice of phosphor particles, which affects the inherent temperature sensitivity and flow tracing accuracy; (2) the particle seeding and management of particle deposition, which affects control of the overall particle number density and seeding uniformity and temporal stability; (3) the setup of the excitation laser/detection cameras and the wind tunnel geometry, which influences background interference from deposited particles and potential influence of multiple scattering. This paper discusses these three factors, gathering and adding to information in prior journal publications, to provide guidance and future research directions for experimental researchers wishing to use these optical diagnostics in film cooling studies and similar enclosed geometries.

Investigating the Influence of Mainstream Turbulence and Large Vortices on Gas Turbine Trenched Film Cooling Flows Using Planar Temperature-Velocity Imaging

Abstract Film cooling is a critical gas turbine technology to reduce heat loads on the combustion chamber and the turbine vanes and blades. To improve film cooling performance, trenched cooling configurations where the holes are connected by a cross-stream slot in the surface have been developed. In this study, for the first time, we experimentally examine the influence of mainstream turbulence and large vortices on trenched film cooling flows. We apply an imaging technique based on thermographic phosphor particles seeded into the flow to measure 2D time-resolved gas temperature and velocity distributions in film cooling flows established in a closed-loop heated wind tunnel. Two trenched configurations (straight and an optimized zigzag design) are compared with ordinary effusion holes at momentum ratios (I=3.5,5.7, and 8.3) relevant to gas turbine combustors. Furthermore, two turbulence generation methods were used to create realistic mainstream turbulence levels (Tu=16.4% and 22.7%) and large vortices, so film cooling flows at typical wind tunnel turbulence (Tu=5.3%) can be compared with combustor-relevant conditions. By comparing the film position derived from the time-average temperature fields, the optimized trench performs best at low momentum ratios and turbulence levels but the performance rapidly drops when the momentum ratio rises or the turbulence level is increased. The straight trench performs best across all conditions studied and this configuration is therefore recommended for combustor liner cooling where main flow turbulence levels are high. In general, increased turbulence intensity reduces the effective length of the cooling film for all geometries. The straight trench, however, produces a more stable cooling film than typical effusion holes or the optimized trench configuration. Both phase-locked and time-resolved data indicate that, in the presence of a dominating frequency in the turbulent main flow field produced using a vortex generator, there are instances where the cooling films are strongly disturbed in the streamwise direction and hot gas is locally in contact with the surface.