Simulation Of Boundary Layer Research Articles

Estimation of wind energy potential through experimental investigation of boundary layer in small wind tunnel

In Brazil, the persistent increase in electricity consumption, primarily propelled by economic and technological advancements, can exceed the capacity of generation and distribution, underscoring the imperative for alternative energy sources. Given the compromised state of hydroelectric power and the environmental ramifications of thermoelectric plants, wind energy emerges as a promising and sustainable solution. Research in this domain encompasses turbine efficiency and analysis of local wind potential. Precise determination of this potential is pivotal to ensure project viability and efficacy, directly impacting decisions of electrical generation companies. Tests for assessing wind potential can be conducted in situ or employing techniques such as Fluid Dynamics, crucial for large-scale projects. Experimental investigations, particularly those conducted in wind tunnels, assume a foundational role in research and development in this field. The distribution of wind velocity across the test section stands as a critical parameter, with accurate simulation of the atmospheric boundary layer being indispensable for dependable outcomes. The boundary layer, an area adjacent to the surface influenced by friction between solid and fluid, holds a crucial role in drag and heat transfer. Various techniques have been devised to simulate and control the boundary layer in wind tunnels, representing a burgeoning area of inquiry. The present study advocates for the utilization of the 'boundary layer plate with flap device' to examine how different flap angles and Reynolds numbers impact boundary layer height, employing experimental design with factorial planning for result analysis. Subsequently, the obtained results indicate that flap angle significantly alters the boundary layer height within a given range of Reynolds numbers, thereby enabling the simulation of diverse boundary layer heights within a small wind tunnel, facilitating experiments related to wind flow and atmospheric boundary layer. Consequently, this research contributes to the estimation of wind potential and propels the efficient utilization of wind energy as a clean and renewable source.

Generating synthetic turbulence with vector autoregression of proper orthogonal decomposition time coefficients

This study introduces vector autoregression (VAR) as a linear procedure that can be used for synthesizing turbulence time series over an entire plane, allowing them to be imposed as an efficient turbulent inflow condition in simulations requiring stationary and cross-correlated turbulence time series. VAR is a statistical tool for modelling and prediction of multivariate time series through capturing linear correlations between multiple time series. A Fourier-based proper orthogonal decomposition (POD) is performed on the two-dimensional (2-D) velocity slices from a precursor simulation of a turbulent boundary layer at a momentum thickness-based Reynolds number, $Re_{\theta }=790$ . A subset of the most energetic structures in space are then extracted, followed by applying a VAR model to their complex time coefficients. It is observed that VAR models constructed using time coefficients of 5 and 30 most energetic POD modes per wavenumber (corresponding to $66\,\%$ and $97\,\%$ of turbulent kinetic energy, respectively) are able to make accurate predictions of the evolution of the velocity field at $Re_{\theta }=790$ for infinite time. Moreover, the 2-D velocity fields from the POD–VAR when used as a turbulent inflow condition, gave a short development distance when compared with other common inflow methods. Since the VAR model can produce an infinite number of velocity planes in time, this enables reaching statistical stationarity without having to run an extremely long precursor simulation or applying ad hoc methods such as periodic time series.

Assessing the Effect of Coriolis Acceleration on the Coherent Structures in the Wake of a Wind Turbine using DMD

Abstract The present work aims to study the effect of veer, namely, the height-dependent lateral deflection of wind velocity due to Coriolis acceleration, on the coherent structures in the wake of the NREL 5-MW reference wind turbine using the sparsity-promoting dynamic mode decomposition (SP-DMD) method for the detection of dynamically-relevant flow structures. Large eddy simulation of the flow impacting the wind turbine is carried out by solving the filtered Navier-Stokes equations for incompressible flows. The effects of both tower and nacelle are included in the simulation using the immersed boundary method. Simulations are performed at Re ≈ 108, generating the inlet velocity profile by a precursor simulation of the atmospheric boundary layer subjected to Coriolis acceleration. The analysis of the DMD results allows to study the effects of the Coriolis acceleration on the most relevant dynamic modes in the turbine wake and to understand the basic mechanisms by which the wind veer significantly affects the wake recovery rate. Moreover, as a result of the SP-DMD methodology, the most relevant modes are extracted from the wake and a limited subset of relevant flow features that optimally approximates the original data sequence is identified. This small number of modes represent the kernel that can be employed for developing an accurate reduced order model of the wake.

Direct numerical simulations of turbulent boundary layers developing over synthesised calcareous marine biofouling surfaces

ABSTRACT The topographical complexity and multi-scale nature of biofouling makes the use of current drag-topography correlations over regular topographical arrangements impractical. In order to address this problem, we synthesise biofouling-type surfaces of tubeworm-type populations in various percentage coverages and distributions. To acquire the resulting flow field we utilise topography-resolving direct numerical simulations. The surface synthesis is performed by an in-house surface generation/analysis package, AdRoS, in which individual biofouling organisms are used as building blocks to synthesise surfaces that resemble those found on ship hulls. Our synthesis algorithm allows for a parametric study to be performed with respect to selected parameters characterising the topography. In this work we focus on the frontal solidity, λ f , in order for its impact to the mean flow to be investigated. Results indicate that both the boundary layer growth-rate, as well as the roughness function, Δ U + , scale with the frontal solidity, λ f , in a proportional fashion, indicating the significance of the frontal solidity parameter. The organism-characteristic height, h , proves to also have a significant impact to the mean flow and even counter-act against the frontal solidity. Interestingly, typical flow separation patterns such as those found on isolated wall-mounted objects were detected, which were found to be mitigated or amplified depending on the planar, λ p , and frontal, λ f , solidity.

CFD simulation of the stratified atmospheric boundary layer: Consistency between Monin-Obukhov similarity theory and the standard k-ε model

Including thermal stratification in CFD simulations of the atmospheric boundary layer (ABL) flow is important for a wide range of applications, from pollutant dispersion over wind energy farm performance to urban thermal microclimate. One of the most important prerequisites for accurate CFD simulations of thermally stratified ABL flow is horizontal homogeneity. Horizontal homogeneity refers to the absence of unintended streamwise gradients in the approach-flow profiles of mean velocity, turbulence quantities and temperature when flowing from the inlet of the domain to the location of interest in the domain, over uniformly rough level terrain. This paper proposes a generic and consistent solution to maintain horizontal homogeneity in CFD simulations of Monin-Obukhov similarity theory (MOST) based stratified ABL flow. A new description is proposed for the coefficient Cε3, which appears in the buoyancy term in the transport equation of the turbulence dissipation rate. This proposed solution is successfully demonstrated by simulations in an empty domain for four stability conditions (1/L = 1/152.4 m−1, 1/1071.7 m−1, 0 m−1 and -1/296.3 m−1), where the standard k-ε turbulence model with the new Cε3 is shown to well maintain the profiles of U, ε and T with only minor deviations for the k profiles. The performance of the turbulence model with the new Cε3 is also illustrated by the flow around a rectangular building under thermal stratification.

Standardized Daily High‐Resolution Large‐Eddy Simulations of the Arctic Boundary Layer and Clouds During the Complete MOSAiC Drift

AbstractThis study utilizes the wealth of observational data collected during the recent Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) drift experiment to constrain and evaluate close to two‐hundred daily Large‐Eddy Simulations (LES) of Arctic boundary layers and clouds at high resolutions. A standardized approach is adopted to tightly integrate field measurements into the experimental configuration. Covering the full drift represents a step forward from single‐case LES studies, and allows for a robust assessment of model performance against independent data under a range of atmospheric conditions. A homogeneously forced domain is simulated in a Lagrangian frame of reference, initialized with radiosonde and value‐added cloud profiles. Prescribed boundary conditions include various measured surface characteristics. Time‐constant composite forcing is applied, primarily consisting of subsidence rates sampled from reanalysis data. The simulations run for 3 hours, allowing turbulence and clouds to spin up while still facilitating direct comparison to MOSAiC data. Key aspects such as the vertical thermodynamic structure, cloud properties, and surface energy fluxes are well reproduced and maintained. The model captures the bimodal distribution of atmospheric states that is typical of Arctic climate. Selected days are investigated more closely to assess the model's skill in maintaining the observed boundary layer structure. The sensitivity to various aspects of the experimental configuration and model physics is tested. The model input and output are available to the scientific community, supplementing the MOSAiC data archive. The close agreement with observed meteorology justifies the use of LES for gaining further insight into Arctic boundary layer processes and their role in Arctic climate change.

Direct numerical simulation of a supersonic turbulent boundary layer with hydrogen combustion

Direct numerical simulation of a supersonic turbulent boundary layer with hydrogen combustion

Three-dimensional spatiotemporal wind field reconstruction based on LiDAR and multi-scale PINN

In this numerical study, we use a multi-scale version of physics-informed neural network (PINN) for wind field reconstruction from LiDAR measurements. The reference velocity field is obtained from high-fidelity large-eddy simulation of neutral atmospheric boundary layer, and the LiDAR measurement strategy is restricted to that of a real LiDAR. The multi-scale PINN reconstructs the velocity field by minimizing a combination of the L2-error with respect to the LiDAR measurements and residuals of the governing equations. Our most significant finding is that adding a multi-scale layer to PINN enables us to: (i) capture wider range of scales, (ii) reconstruct the flow field outside the LiDAR scanning area, and (iii) reach faster convergence. We also find that for volumetric flow reconstruction and to deal with uncertainty in the wind direction, the reconstruction accuracy can be greatly improved by employing multiple LiDAR devices. Overall, our results show that the normalized errors in the reconstructed wind field are lower than 5% for all the experiments conducted in this study and that the errors do not increase even in the presence of measurement noise levels of typical LiDAR. These findings show the feasibility of three-dimensional dynamic wind field reconstruction across large wind farms using LiDAR devices.

Designing a Fully‐Tunable and Versatile TKE‐l Turbulence Parameterization for the Simulation of Stable Boundary Layers

AbstractThis study presents the development of a so‐called Turbulent Kinetic Energy (TKE)‐l, or TKE‐l, parameterization of the diffusion coefficients for the representation of turbulent diffusion in neutral and stable conditions in large‐scale atmospheric models. The parameterization has been carefully designed to be completely tunable in the sense that all adjustable parameters have been clearly identified and the number of parameters has been minimized as much as possible to help the calibration and to thoroughly assess the parametric sensitivity. We choose a mixing length formulation that depends on both static stability and wind shear to cover the different regimes of stable boundary layers. We follow a heuristic approach for expressing the stability functions and turbulent Prandlt number in order to guarantee the versatility of the scheme and its applicability for planetary atmospheres composed of an ideal and perfect gas such as that of Earth and Mars. Particular attention has been paid to the numerical stability and convergence of the TKE equation at large time steps, an essential prerequisite for capturing stable boundary layers in General Circulation Models (GCMs). Tests, parametric sensitivity assessments and preliminary tuning are performed on single‐column idealized simulations of the weakly stable boundary layer. The robustness and versatility of the scheme are assessed through its implementation in the Laboratoire de Météorologie Dynamique Zoom GCM and the Mars Planetary Climate Model and by running simulations of the Antarctic and Martian nocturnal boundary layers.

Parallel and scalable AI in HPC systems for CFD applications and beyond

This manuscript presents the library AI4HPC with its architecture and components. The library enables large-scale trainings of AI models on High-Performance Computing systems. It addresses challenges in handling non-uniform datasets through data manipulation routines, model complexity through specialized ML architectures, scalability through extensive code optimizations that augment performance, HyperParameter Optimization (HPO), and performance monitoring. The scalability of the library is demonstrated by strong scaling experiments on up to 3,664 Graphical Processing Units (GPUs) resulting in a scaling efficiency of 96%, using the performance on 1 node as baseline. Furthermore, code optimizations and communication/computation bottlenecks are discussed for training a neural network on an actuated Turbulent Boundary Layer (TBL) simulation dataset (8.3 TB) on the HPC system JURECA at the Jülich Supercomputing Centre. The distributed training approach significantly influences the accuracy, which can be drastically compromised by varying mini-batch sizes. Therefore, AI4HPC implements learning rate scaling and adaptive summation algorithms, which are tested and evaluated in this work. For the TBL use case, results scaled up to 64 workers are shown. A further increase in the number of workers causes an additional overhead due to too small dataset samples per worker. Finally, the library is applied for the reconstruction of TBL flows with a convolutional autoencoder-based architecture and a diffusion model. In case of the autoencoder, a modal decomposition shows that the network provides accurate reconstructions of the underlying field and achieves a mean drag prediction error of ≈5%. With the diffusion model, a reconstruction error of ≈4% is achieved when super-resolution is applied to 5-fold coarsened velocity fields. The AI4HPC library is agnostic to the underlying network and can be adapted across various scientific and technical disciplines.

Reynolds-Number-Dependence of Length Scales Governing Turbulent-Flow Separation in Wall-Modeled Large Eddy Simulation

This paper proposes a Reynolds number Re scaling for the number of grid points Ncv required in wall-modeled Large Eddy Simulation (WMLES) of turbulent boundary layers (TBL) to accurately capture the regions of flow separation. Based on the various time scales in a nonequilibrium TBL, a definition of the near-wall “underequilibrium” scales is proposed (in which “equilibrium” refers to a quasi balance between the viscous and the pressure gradient terms). This length scale is shown to vary with Reynolds number as lp∼Re−2/3. A-priori analysis demonstrates that the resolution (Δ) required to reasonably predict the wall stress in several nonequilibrium flows is at least O(10)lp, irrespective of the Reynolds number and Clauser parameter. Further, a-posteriori studies (on the Boeing speed bump, Song– Eaton diffuser, Notre-Dame Ramp, and the backward-facing step) show that scaling Δ such that Δ/lp is independent of Reynolds number results in accurate predictions of separation for the same “nominal” grid across different Reynolds numbers. Finally, we suggest that near separation and reattachment points, Ncv for WMLES scale as Re4/3, which is more restrictive than the previous estimates (∼Re1) by Choi and Moin (Choi, H., and Moin, P., “Grid-Point Requirements for Large Eddy Simulation: Chapman’s Estimates Revisited,” Physics of Fluids, Vol. 24, No. 1, 2012, Paper 011702) and Yang and Griffin (Yang, X. I. A., and Griffin, K. P., “Grid-Point and Time-Step Requirements for Direct Numerical Simulation and Large-Eddy Simulation,” Physics of Fluids, Vol. 33, No. 1, 2021, Paper 015108).

Roughness constant selection for atmospheric boundary layer simulations using a k-ω SST turbulence model within a commercial CFD solver

Transit of an atmospheric boundary layer (ABL) profile within computational fluid dynamics (CFD) simulations is often hindered through unintended streamwise gradients in the flow resulting in ABL inhomogeneity. Within Reynolds-Averaged Navier–Stokes (RANS) turbulence modeling in Ansys Fluent, user-defined wall functions are not available for the k–ω class of RANS models as a remedy to this problem. Instead, the practitioner is required to use the sand–grain roughness property for ground surface roughness calibration, and specify a roughness height and roughness constant, Cs, accordingly. To-date, no clear guidance on their selection is available that can accommodate both high and low roughness terrains. To overcome this, a straightforward and practical calculation is presented for the roughness constant based on the standard wall function implementation. When this calculation is synthesized with other best-practice guidelines, it is possible to reliably model transiting ABL profiles based on wind-tunnel data whilst minimizing effects due to ABL inhomogeneity.

Feasible suggestions of scale-adaptive simulation approach based on the high-fidelity large-eddy simulation of supersonic turbulent boundary layer

Feasible suggestions of scale-adaptive simulation approach based on the high-fidelity large-eddy simulation of supersonic turbulent boundary layer

Generation of inflow turbulence using an improved synthetic eddy method

The generation of turbulent inflow conditions is a key issue in large eddy simulation (LES) or direct numerical simulation (DNS). In this paper, an improved synthetic eddy method (SEM) is proposed to generate inflow turbulence for LES and DNS. The improvements about SEM focus on the eddy radius and eddy distributions. First, the eddy radius is improved to reduce the nonphysical vortex structure on the wall caused by overestimation of the radius. Second, a sampling method using Gaussian distribution is proposed to improve the distribution of eddies, which accurately captures the randomness of turbulent structure size and is close to the actual flow field. The improved method is applied to the direct numerical simulation of the supersonic turbulent boundary layer at Mach 2.7 and the 24° compression ramp. Results indicate that the predictions yielded by the improved method are in good agreement with both DNS and experimental data. Compared to the original method, the improved method exhibits a more rapid recovery of the friction coefficient and effectively shortens the development distances. The improved SEM has enhanced the efficiency and accuracy of generating inlet turbulence, which can provide inlet turbulence boundary conditions for LES and DNS.

Aerothermal Loads on a Representative Porous Mesostructure at Flight Conditions Using Direct Simulation Monte Carlo

Spacecraft require thermal protection systems (TPS) in order to survive the extreme conditions present during atmospheric entry missions. Porous ablators are a class of TPS materials that have been used successfully on several entry missions, although they can be difficult to model because of their complex nature at the micro- and mesoscales. Specifically, the processes that lead to mechanical erosion (spallation) of these materials are poorly understood. In order to gain insight into the spallation process, the current work computes aerothermal loads on a mesostructure representative of FiberForm (the substrate of phenolic impregnated carbon ablator) by leveraging a simulation framework involving loosely coupled Computational Fluid Dynamics-Direct Simulation Monte Carlo (CFD-DSMC) simulations of hypersonic boundary layers. CFD boundary layers are extracted from two altitudes, 68.9 and 81 km, along the Stardust entry trajectory and are imposed as boundary conditions on a DSMC simulation over an artificially generated mesostructure, which is representative of the charred layer of the TPS material. In order to produce high-quality results, the DSMC boundary conditions require careful consideration; specifically, Chapman–Enskog distributions are needed to account for large velocity and temperature gradients. Visualizations of the DSMC flowfield indicate excellent agreement with the original CFD data, and the aerothermal loads (heat flux and traction force) on the surface were examined using probability density functions. Additionally, the effects of pyrolysis blowing through the mesostructure on the surface properties are also determined.

The impact of mesh size, turbulence parameterization, and land‐surface‐exchange scheme on simulations of the mountain boundary layer in the hectometric range

AbstractThe horizontal grid spacing of numerical weather prediction models keeps decreasing towards the hectometric range. We perform limited‐area simulations with the Icosahedral Nonhydrostatic (ICON) model across horizontal grid spacings (1 km, 500 m, 250 m, 125 m) in the Inn Valley, Austria, and evaluate the model with observations from the Cross‐Valley Flow in the Inn Valley Investigated by Dual‐Doppler LIDAR Measurements (CROSSINN) measurement campaign. This allows us to investigate whether increasing the horizontal resolution automatically improves the representation of the flow structure, surface exchange, and common meteorological variables. Increasing the horizontal resolution results in an improved simulation of the thermally induced circulation. However, the model still faces challenges with scale interactions and the evening transition of the up‐valley flow. Differences between two turbulence schemes (1D turbulence kinetic energy (TKE) and 3D Smagorinsky) emerge due to their different surface transfer formulations, yielding a delayed evening transition in the 3D Smagorinsky scheme. Generally speaking, the correct simulation of the mountain boundary layer depends mostly on the representation of model topography and surface exchange, and the choice of turbulence parameterization is secondary.

A stably-stratified atmospheric inflow assimilated to measured mean profiles interacting with a wind park

In this paper, a simulation chain is presented. This method comprises the precursor large-eddy simulation (LES) of a stably-stratified atmospheric boundary layer (ABL), the assimilation of the simulated mean velocities to measured wind profiles, and finally a simulation of the generated turbulent ABL flow passing through two wind turbines in a row. The high-resolved precursor simulation with a horizontal grid spacing of 3 m accounts for the characteristic turbulence of the stably-stratified ABL. Using an assimilation technique, the horizontal velocities are adapted accurately to the measured mean wind profiles for the WiValdi wind farm site at Krummendeich. The wakes of two wind turbines in a row with the assimilated inflow is successfully computed. With the simulation chain presented, it is possible to generate realistic atmospheric inflows for wind-turbine simulations with manageable computational effort.

Towards LES-RANS/LES coupling for simulation of a wind turbine rotor in a nocturnal atmospheric condition

A segregated approach with either synthetically generated velocity fluctuations or a precursor Large-Eddy Simulation (LES) of the atmospheric boundary layer (ABL) and a subsequent hybrid RANS/LES (HRLS) of the resolved rotor is presented in this paper. At first the approach is validated with synthetically generated velocity fluctuations that resemble neutrally stratified conditions. Subsequently the same turbine is artificially exposed to a stably stratified atmospheric inflow (nocturnal boundary layer) with a comparable mean velocity but different shear and veer characteristics. The HRLS simulations with the neutrally stratified and stably stratified inflow are compared to LESs with an implemented actuator disc (AD) model. The presented work is a first important step towards a digital twin for research wind parks.

Assessment of synthetic turbulence of stably stratified atmospheric boundary layers for LES

This work studies the evolution of turbulence in a Stable Boundary Layer (SBL) in Large-Eddy Simulations (LES) when a synthetic turbulence field of velocity and temperature is used as initial condition and as well as precursor. Following common approaches found in the literature, initial fields of different characteristics are created and their evolution in the LES is evaluated in order to assess the ability of the synthetically generated turbulence to represent a snapshot of SBL turbulence. The study is carried out with two modelling cases, a forested site as well as the GABLS benchmark [4]. In both cases, the usage of a turbulent SBL as an initial condition proved advantageous to reach a faster convergence presenting an opportunity for computational savings. Yet, the very different turbulence conditions of the modelling setups produce varying results with regard to the type of velocity and temperature fluctuations. Likewise, the usage of a precursor was shown able to represent the flow in a successor LES although with varying reliability, dependent on the background turbulence and the stratification level, that suppresses velocity fluctuations and could lead to the misrepresentation of turbulence level.

A numerical analysis of multi-dimensional iron flame propagation using boundary-layer resolved simulations

Iron combustion is emerging as a topic of immediate interest, given the need for the decarbonization of heat and power generation. Opposite to other solid fuels, iron particles burn predominantly in a non-volatile, heterogeneous combustion mode. For iron dust flames, two modes of flame propagation have been observed i.e. the discrete mode, when the heat transfer time scale is larger than the particle burn-time, and the continuous mode, when the heat transfer timescale is smaller than the burn-time of a single particle. The flame speed of such a flame primarily depends on the heat and mass transfer which is characterized by the distance between the particles for a dispersed mixture. Depending on the variation in particle distance and local distribution, planar or curved flames can form and propagate. The characteristics of flame propagation motivate this study and for the first time, three-dimensional particle boundary layer resolved simulations are used to analyse the effect of curvature and variable particle distances on iron–air flame propagation. Simulations are carried out for (1) planar flame propagation with constant particle spacing in the direction of propagation, and (2) curved flame propagation with varying particle spacing in the direction of propagation. The analysis of the flame speed for the planar flame propagation later guides the analysis of curved flames propagating through 900 boundary-layer resolved particles distributed in a 30 by 30 grid. The curved flame propagates with a uniform but decreased flame speed compared to the planar flame propagation with equivalent particle spacing. It is shown that positive curvature decreases the heat transfer from the burnt to the unburnt side while a variable spatial arrangement of particles allows for a local re-distribution of oxygen which causes some regions to burn richer or leaner than the corresponding planar flames with similar particle spacing.