Reynolds-averaged Navier-Stokes Simulations Research Articles

Net escape velocity, transfer probability, and travel time distributions within a cross-ventilated room model sheltered by urban-like block array

Natural ventilation offers significant advantages, especially in terms of energy conservation. However, most published articles have focused on the ventilation flow rate to determine the average contaminant concentration, while few have examined local ventilation distributions. Therefore, isothermal steady-state Reynolds-averaged Navier–Stokes simulations were conducted to analyze the airflow and scalar concentration fields of a cross-ventilation model sheltered by buildings. Based on these fields, we generated the spatial distributions of ventilation indices, namely, the net escape velocity (NEV), point-to-point indices transfer probability (TP), and travel time (TT), to discuss the dispersion of scalars emitted from local points in a room with natural ventilation. The NEV, which indicates the direction of the scalar discharge from each cell, exhibited a distribution distinct from the advection velocity because of concentration gradient effect. Higher TPs were observed when evaluated from a contaminant source to a target point following the NEV streamlines. Meanwhile, lower TTs were observed when evaluated in a point near the source and also from a contaminant source to a target point following the NEV streamlines. Although TP and TT are independent ventilation indices, a negative correlation between them was observed. Instead of the ventilation flow rate, the detailed structure of scalar dispersion can now be described by simultaneously analyzing the ventilation efficiency indices, which provide information on the general contaminant transport direction, and the probability and duration of transfer from a source to a target point. This potentially helps in the design of ventilation system especially in room lay-out to avoid cross-contamination.

Design, Multi-Point Optimization, and Analysis of Diffusive Stator Vanes to Enable Turbine Integration Into Rotating Detonation Engines

Abstract Pressure gain combustion is considered a possible path toward improved thermal cycle efficiency and reduced carbon emissions. However, ad hoc turbine designs are required to maximize the thermodynamic potential; the new turbomachinery should be suited for the oscillations in flow conditions generated by the detonation combustor, which are very different from conventional gas turbines. This paper investigates the design, optimization, and analysis of diffusive stator vanes operating under large inlet flow angles in the high-subsonic regime. First, the design methodology is outlined, focusing on the geometric requirements to ingest high Mach number flow and the parametric modeling of the endwall and the 3D vane pressure and suction sides. Then, the impact of the inlet flow angle on the flow field and vane design is studied through a multi-point, multi-objective optimization with three different inlet angles, performed using steady Reynolds-averaged Navier–Stokes simulations. Remarkable reductions in pressure loss and stator-induced rotor forcing are attained while maintaining an extensive operating envelope and high flow turning. Moreover, several design guidelines are provided based on the analysis of the optimized geometries. Finally, the effectiveness of the proposed methodology is verified with an unsteady assessment of the baseline and optimized vane designs.

The Impact of Upstream Static Deformation on Flow Past a Cylinder/Flare

Reynolds-averaged Navier–Stokes simulations are performed for supersonic turbulent flow over a cylinder/flare with upstream surface distortion representative of structural deformation induced via fluid–structural and fluid–thermal–structural behavior. Broad parametric analysis is carried out through the generation of Kriging-response surfaces from a database of general simulations. A posteriori simulations are then carried out at parametric combinations that correspond to extrema in the Kriging response surfaces to gain deeper insights into the interaction between the surface distortion and flow responses. Upstream distortions tend to decrease, rather than increase, the peak pressure and heat flux loads on the flare compared to an undeformed cylinder. Furthermore, decreases in these quantities reach up to O(10%) compared to up to O(1%) for increases. Integrated quantities over the flare are relatively insensitive to upstream distortion. The corner separation length is the most sensitive quantity to upstream distortion, with protrusions tending to increase the separation length and recessions reducing the separation length. Modifications in the separation length of up to 40% are observed. Reductions in peak loads tend to correspond to increases in the corner separation length. The movement of the surface distortion relative to the corner indicates a negligible impact beyond 1.5 distortion lengths from the corner, and the largest impact on the corner separation length occurs when distortion is directly adjacent. These results are an important step toward understanding and quantifying the impact of surface deformations on downstream components.

A Full-Scale Tidal Blade Fatigue Test using the FastBlade Facility

Fatigue testing of tidal turbine blades requires the application of cyclic loads without the ability to match the natural frequency of the blade due to their high stiffness and the associated thermal issues of testing composite materials at those frequencies (i.e., 18–20 Hz). To solve this, loading the blades with an auxiliary system is necessary; in most cases, a conventional hydraulic system tends to be highly energy-demanding and inefficient. A regenerative digital displacement hydraulic pump system was employed in the FastBlade fatigue testing facility, which saved up to 75 % compared to a standard hydraulic system. A series of equivalent target loads were defined using Reynolds-Averaged Navier Stokes (RANS) simulations (based on on-site collected water velocity data) and utilised in FastBlade to demonstrate an efficient way to perform fatigue testing. During the test, a series of measurements were performed on the blade response and the Fastblade test structure itself, providing novel insights into the mechanical behaviour of a blade, and enabling improved testing practice for FastBlade. Without catastrophic failure, the blade withstood the principal tidal loading for 20 years (equivalent). This test data will enable FastBlade to identify improvements to the testing procedures, i.e., control strategies, load introduction, instrumentation layout, instrument calibration, and test design.

Extraction of flow features around a bridge pier with an evolving scour hole using Lagrangian coherent structures

Local scouring around a bridge pier poses a severe threat to the safety of the bridge. A better understanding of flow features around the bridge piers is necessary for accurate prediction of the scour depth. The ridges of the finite-time Lyapunov exponent, called Lagrangian coherent structures (LCSs), were used to extract the flow features around a circular bridge pier with an evolving scour hole. The velocity field required for the LCSs computation was obtained using a three-dimensional Reynolds-averaged Navier–Stokes simulation. The simulation results were validated with the published experimental and numerical findings. The computed LCS stretching field extracted all the flow features around the bridge pier that were previously reported in the literature. In addition, the LCSs extracted the region of flow acceleration on both sides of the pier. The forward LCSs upstream of the pier extracted a particle trapping region, providing insight into the volume of fluid converting into the downflow. They extracted anchor-like structures inside the scour hole upstream of the pier. The analysis of velocity variations along the width and depth of the flow domain revealed that a change in the velocity profile is triggering the formation of LCS. The behavior of non-inertial particles released and integrated into the flow field revealed the significance of LCSs in particle transport. Using the LCS method, the study extracted the flow features that were difficult to extract with traditional flow visualization methods.

Flows past airfoils for the low-Reynolds number conditions of flying in Martian atmosphere

Fixed-wing aircraft with potential for long-duration flight and efficient manoeuvrability is expected to be the next frontier of Mars surface exploration. However, the feasibility of such an aircraft demands for wing airfoil suitable for low Reynolds flight conditions. In this framework, the paper deals with the computational study of two wing sections specifically designed for Mars exploration aircraft. Two-dimensional steady Reynolds-averaged Navier–Stokes simulations, using the computational fluid dynamics tool SU2 with the γ−Reθ transition model and the XFoil panel flow solver, are performed to address airfoils’ aerodynamics. Computational tools are validated by simulating flow past the Eppler 387 airfoil at Re∞=60×103, and comparing the results with experimental data collected in wind tunnel experiments. Aerodynamic performances of optimal wing sections are investigated at Re∞=3.4×104 by considering pressure coefficients and skin friction coefficients. The application of a literature-based correlation, specifically tailored to identify transition and reattachment locations, is extended to separation point detection. Computational Fluid Dynamics analysis conducted on the studied airfoils revealed that separation occurs within the laminar regime. Additionally, examination of turbulent shear stresses highlighted the role of airfoil curvature in counterbalancing the suction defect produced by the laminar separation bubble. This curvature-induced effect was found to play a crucial role in optimizing airfoil efficiency.

A New Axial Compressor Test Facility for the Investigation of Aerodynamic Damping Featuring an Electromagnetic Excitation System

Abstract Aerodynamic damping simulations involving detailed computational fluid dynamics (CFD) models are nowadays an integral part of turbomachinery design processes, thanks to advancements made in simulation tools and in computer hardware over the last decades. However, the test cases available in the open literature suitable for the validation and continued development of simulation tools is rather limited. On this background, a new test facility is introduced that allows acquiring relevant and high-quality aerodynamic damping test data on axial compressor rotor test objects in a controlled manner. The test facility is built as a closed loop and thus enables operation at variable pressure levels ranging from near-vacuum to overpressure and with different operating media. Overall damping test data are acquired at controlled synchronous and nonsynchronous vibration conditions. While vibrations of the blades at controlled nonsynchronous vibration conditions can be introduced in the test facility by means of a proprietary electromagnetic excitation system that is acting below the hub line, vibrations at controlled synchronous conditions can be introduced from a set of magnets integrated into the casing. Great care has been spent to create a clean test case without any intruding parts or openings in the test section. In addition, an axial compressor blisk is presented, which acts as test object to show the capabilities of the test facility as well as to allow for detailed investigations of aerodynamic damping. While the first part of the article discusses the setup and the instrumentation of the test facility to excite and measure blade vibration in a nonintrusive way, flow-field measurements and the validation accompanying steady-state Reynolds-averaged Navier-Stokes (RANS) simulations are shown in the second part. The third part of the article focuses on aerodynamic damping measurements for seven different modes at three different pressure levels in total. It can be shown that aerodynamic damping is by far the largest contributor to the overall damping.

Turbulent Particle Flow in Spent Nuclear Fuel Storage Systems

Deposition models are being developed with the commercial computational fluid dynamics software STAR-CCM+ to evaluate particulate deposition on spent nuclear fuel (SNF) canisters. The primary particulate of concern is chloride salts, which are dispersed in the atmosphere and then deposited onto the canisters. During dry storage, the primary degradation process is likely to be chloride-induced stress corrosion cracking (CISCC) at the heat-affected zones of the canister welds. It is known that stainless steel canisters are susceptible to CISCC; however, the rate of chloride deposition onto the canisters is poorly known, based on sparse field data from a small number of sites. This paper describes work looking at various approaches to modeling turbulence, such as Reynolds-averaged Navier Stokes (RANS) and large eddy simulation (LES), and its impact on particle flow and deposition within a ventilated SNF storage system. The deposition rate is determined for a vertical canister system and a horizontal canister system. LES has the potential to simulate turbulent flows more accurately versus RANS, but is much more computationally expensive. A k-omega version of the RANS turbulence model was used for this study. The computational efficient RANS steady-state model predicted a similar canister deposition result as the LES simulation for a vertical canister storage system. For a horizontal storage system, the RANS steady-state model predicted more particles depositing on the canister than the LES simulation, providing a conservative estimation for particle deposition. A wall correction factor was added to the RANS model to dampen the turbulence fluctuation normal to a surface that left undamped, leads to the RANS model overpredicting deposition along a surface for smaller particles. This work was done to further development of deposition models that could be used to plan and inform SNF canister aging management programs with predictive models for the timing and occurrence of canister CISCC. This work is part of a larger effort tasked with understanding the likelihood of canister degradation due to CISCC. These models are still under development, and testing is needed for validation. However, these models are being presented now to demonstrate to canister vendors, utilities, regulators, and stakeholders the value of this type of modeling.

Sparse learning model with embedded RIP conditions for turbulence super-resolution reconstruction

In practical engineering scenarios, constraints arising from sensor placement, quantity, and the limitations of current testing technologies often lead to turbulence data characterized by low resolution and irregular structures. Turbulence super-resolution reconstruction is crucial for extracting finer details from irregularly structured, low-resolution measurement data, thereby facilitating comprehensive flow field analyses. This article introduces a sparse learning model (Embedding Restricted Isometry Property Autoencoder (RIP-AE)) for achieving super-resolution reconstruction of flow fields by obtaining compressed representations and sparse transform domain information. In this model, we embed the Restricted Isometry Property (RIP) condition to ensure the effectiveness of compressed representations and sparse transform domains, thereby enhancing the super-resolution reconstruction accuracy of the model. To assess the performance of the RIP-AE model, we utilized data sets of flow around a cylinder at different Reynolds numbers generated by unsteady Reynolds-Averaged Navier–Stokes simulations. We sequentially validate the effectiveness of the RIP condition at different Reynolds numbers (ranging from 1,000 to 500,000) and compare the reconstruction results of the RIP-AE model with those of the downsampled skip-connection/multi-scale (DSC/MS) and MS-AE models under different sampling ratios. The results indicate that the RIP-AE model excels in terms of L2 relative error and demonstrates the capability to achieve high-precision flow field reconstruction even under high sampling ratios.

MÔ PHỎNG XOÁY TÁCH RỜI TRONG NGHIÊN CỨU CÁC ĐẶC TRƯNG KHÍ ĐỘNG CỦA DÒNG CHẢY RỐI TRÊN VÙNG TƯƠNG TÁC

The turbulent mixing layer is a phenomenon that occurs and has many applications in aeronautical engineering. The study of mixing layer turbulence by the numerical method is suitable under domestic conditions. Two numerical simulation methods are used in most studies including, direct numerical simulation DNS and large eddy simulation LES, while there are very few studies using detached eddy simulation DES. In this article, the authors use numerical simulation methods evolving Reynolds average Navier-Stokes simulation RANS and detached eddy simulation DES to propose a numerical simulation model that allows to study of the aerodynamic characteristics of the turbulent flow interaction. RANS is used to evaluate grid independence. With the selected mesh, two models counting the DES-2D model and the DES-3D model are conducted. Processing velocity field data with Matlab code, the results show that the average flow behavior has closely followed the experimental results, while the turbulent kinetic energy still has a large error. POD and Q-criterion analysis has shown some large coherent structures in the interaction region.

Aerodynamic Prediction of the High-Lift Common Research Model with Modified Turbulence Model

Aerodynamic simulations were carried out in the study presented in this paper focusing on the stall performance of the High-Lift Common Research Model obtained from the fourth AIAA High-Lift Prediction Workshop. Various turbulence models of Reynolds-averaged Navier–Stokes simulations are analyzed. A modified version of the transitional k−v2¯−ω model was developed to enhance stall prediction accuracy for high-lift configurations with a nacelle chine. The vortex generator, three-element airfoil, and high-lift model are numerically simulated. The results reveal that implementing a k−v2¯−ω model with the separation shear layer fixed notably enhances the stall prediction behavior for both the three-element airfoil and high-lift configuration without affecting the prediction of the vortex strength of a vortex generator. Moreover, incorporating rotation correction into the SPF k−v2¯−ω model improves the prediction of vortex strength and further enhances stall prediction for the high-lift configuration. The relative error in predicting the maximum lift coefficient is less than 5% of the experimental data. The study also investigated the impact of the nacelle chine on the stall behavior of the high-lift configuration. The results demonstrate that the chine vortex can mitigate the adverse effects of the nacelle/pylon vortex system and increase the maximum lift coefficient.

Data-driven RANS closures for improving mean field calculation of separated flows

Reynolds-averaged Navier-Stokes (RANS) simulations have found widespread use in engineering applications, yet their accuracy is compromised, especially in complex flows, due to imprecise closure term estimations. Machine learning advancements have opened new avenues for turbulence modeling by extracting features from high-fidelity data to correct RANS closure terms. This method entails establishing a mapping relationship between the mean flow field and the closure term through a designated algorithm. In this study, the k-ω SST model serves as the correction template. Leveraging a neural network algorithm, we enhance the predictive precision in separated flows by forecasting the desired learning target. We formulate linear terms by approximating the high-fidelity closure (from Direct Numerical Simulation) based on the Boussinesq assumption, while residual errors (referred to as nonlinear terms) are introduced into the momentum equation via an appropriate scaling factor. Utilizing data from periodic hills flows encompassing diverse geometries, we train two neural networks, each possessing comparable structures, to predict the linear and nonlinear terms. These networks incorporate features from the minimal integrity basis and mean flow. Through generalization performance tests, the proposed data-driven model demonstrates effective closure term predictions, mitigating significant overfitting concerns. Furthermore, the propagation of the predicted closure term to the mean velocity field exhibits remarkable alignment with the high-fidelity data, thus affirming the validity of the current framework. In contrast to prior studies, we notably trim down the total count of input features to 12, thereby simplifying the task for neural networks and broadening its applications to more intricate scenarios involving separated flows.

A data‐driven turbulence modeling for the Reynolds stress tensor transport equation

AbstractThe long lasting demand for better turbulence models and the still prohibitively computational cost of high‐fidelity fluid dynamics simulations, like direct numerical simulations and large eddy simulations, have led to a rising interest in coupling available high‐fidelity datasets and popular, yet limited, Reynolds averaged Navier–Stokes simulations through machine learning (ML) techniques. Many of the recent advances used the Reynolds stress tensor or, less frequently, the Reynolds force vector as the target for these corrections. In the present work, we considered an unexplored strategy, namely to use the modeled terms of the Reynolds stress transport equation as the target for the ML predictions, employing a neural network approach. After that, we solve the coupled set of governing equations to obtain the mean velocity field. We apply this strategy to solve the flow through a square duct. The obtained results consistently recover the secondary flow, which is not present in the baseline simulations that used the model. The results were compared with other approaches of the literature, showing a path that can be useful in the seek of more universal models in turbulence.

Urban-canopy airflow dynamics: A numerical investigation of drag forces and distribution for generic neighborhoods, and their relationships with breathability

Thorough investigations of urban-canopy drag primarily stemming from pressure drag on building surfaces are necessary given the turbulent flows within complex urban areas. Moreover, a gap persists regarding the relationships between canopy drag and breathability. Therefore, this work delves into the canopy-layer airflow dynamics for generic urban neighborhoods by performing three-dimensional Reynolds-Averaged Navier-Stokes simulations. A total of 32 subcases are examined, encompassing uniform- and varying-height and diverse plan area densities (λp, categorized into groups of sparse: 0.0625/0.067, medium: 0.23/0.25, and dense: 0.53/0.56). Results for the drag distribution highlight the windward-row shelter effect for the medium and the dense, local shelter by taller buildings, and distinct shapes of sectional drag forces (F⁎Z). Local velocity and mean age of air are found strongly positively and negatively correlated to F⁎Z, respectively, with distinct slopes in relation to λp. For the uniform-height, the normalized bulk drag (F⁎bulk, referred to as drag coefficient in literature) peaks for the medium with wake-interference regime; F⁎bulk demonstrates a maximum increase of over two times with height variation; moreover, F⁎bulk for varying-height groups exhibits a marked increase from the sparse to the medium, while remaining comparable values for the dense. The frontal area averaged drag (FAf,ave) exhibits a decreasing trend against λp across all cases. Further, FAf,ave exhibits strong correlations with λp and porosity, and with bulk ventilation indices such as spatially averaged velocity, air change rate, and normalized net escape velocity. Throughout the ‘suburban-urban-suburban’ canopy, medium neighborhoods exerting larger drag cause greater streamwise outdoor pressure drops and flow reductions compared to the sparse. However, dense neighborhoods with lower drag exhibit even larger pressure losses, which should be carefully scrutinized. The findings can inform urban planners in designing more aerodynamically efficient neighborhoods and guide strategies for improving air quality within urban environments.

Adaptive Turbulence Model for Leading Edge Vortex Flows Preconditioned by a Hybrid Neural Network

Eddy-viscosity-based turbulence models provide the most commonly used modeling approach for computational fluid dynamics simulations in the aerospace industry. These models are very accurate at a relatively low cost for many cases but lack accuracy in the case of highly rotational leading edge vortex flows for mid to low aspect-ratio wings. An enhanced adaptive turbulence model based on the one-equation Spalart–Allmaras turbulence model is fundamental to this work. This model employs several additional coefficients and source terms, specifically targeting vortex-dominated flow regions, where these coefficients can be calibrated by an optimization procedure based on experimental or high-fidelity numerical data. To extend the usability of the model from single or cluster-wise calibrated cases, this work presents a preconditioning approach of the turbulence model via a neural network. The neural network provides a case-unspecific calibration approach, enabling the use of the model for many known or unknown cases. This extension enables aircraft design teams to perform low-cost Reynolds-averaged Navier–Stokes simulations with increased accuracy instead of complex and costly high-fidelity simulations.

Numerical simulation of windsurfing sail aerodynamics: Insights into forces and flow characteristics

In windsurfing, the sail is the primary source of propulsive force. Due to the unique shape and structure, the aerodynamic performance of a windsurfing sail is not well understood. This study aims to investigate the aerodynamic performance of a windsurfing sail under various angles of attack and sail heights using steady Reynolds-averaged Navier–Stokes simulations. The simulations were validated with wind tunnel measurements. The study finds that the local maximum lift coefficient and stall angle are different at different sections along the sail height. Further investigations on the pressure distributions and sectional flow fields indicate that the different sectional lift coefficients and stall are significantly influenced by the geometric profiles and orientations of the luff pocket. The sectional geometric profile consists of a reduced camber near the sail tip, which is prone to flow separation. Thus, flow separation first occurred at the sail tip with increasing angle of attack, then extended towards the sail foot. During flow separation, a recirculation region was found on the suction side of the sail, leading to a reduction in lift and increase in drag. The findings of this study provide insights into the aerodynamic forces and flow characteristics of windsurfing sails, which can be applied to improve sail design and performance.

Experimental and numerical investigation of porous bleed control for supersonic/subsonic flows, and shock-wave/boundary-layer interactions

This paper presents a comprehensive experimental and numerical investigation into the control of boundary layers using porous bleed systems. The study focuses on both supersonic and subsonic flow regimes, as well as on the control of shock-wave/boundary-layer interactions. By simplifying this complex problem into two separate scenarios, the research establishes the necessity of individually characterizing bleed systems for both supersonic and subsonic flow regimes due to variations in the flow topology within the bleed holes. In supersonic conditions, a strong agreement between experimental and numerical results validates the effectiveness of porous bleed in controlling boundary layers. Notably, three-dimensional effects are experimentally demonstrated, and variations of the boundary-layer profiles along the span are the first time experimentally proven. The study extends its scope to subsonic flows, revealing that while boundary-layer bleeding enhances flow momentum near the wall, mass removal induces a decrease in momentum in the outer boundary layer and external flow. The research also explores shock-wave/boundary-layer interaction control, achieving a remarkable alignment between simulations and experiments. The findings endorse the use of Reynolds-Averaged Navier-Stokes simulations for studying porous bleed systems in various flow conditions, providing valuable insights to enhance bleed models, especially in the context of shock-wave/boundary-layer interaction control.

Modelling of the Flame Surface Density Transport During Flame-Wall Interaction of Premixed Flames within Turbulent Boundary Layers

ABSTRACT A priori Direct Numerical Simulation (DNS) analysis of the modelling of the generalised flame surface density (FSD) transport equation in the framework of Reynolds Averaged Navier-Stokes (RANS) simulations has been conducted with a focus on flame-wall interaction (FWI) within turbulent boundary layers. The analysis was performed using two different scenarios: one involving the unsteady head-on interaction of a statistically planar premixed flame as it propagates through a turbulent boundary layer, and the other addressing statistically stationary oblique-wall interaction of a V-shaped premixed flame within a turbulent channel flow. Flame-wall interaction has been observed to exert a significant influence on the statistical behavior of the terms in the FSD transport equation. Throughout all phases of flame-wall interaction in both configurations, the primary source and sink terms in the FSD transport equation are consistently associated with the tangential strain rate and curvature terms. The relative importance of the contributions of the propagation and turbulent transport terms in the FSD transport equation have been found to be influenced by the flame-wall interaction configuration. Existing models for the tangential strain rate term in the FSD transport equation have been identified as inadequate based on a priori DNS assessment. Hence, adjustments to these models have been proposed to address the impact of flame orientation and near-wall effects specifically in the context of flame-wall interaction within turbulent boundary layers. The alignment between the flame normal vector and the wall normal vector has been identified as a crucial factor in modelling the contributions of unresolved dilatation rate and unresolved normal strain rate to the FSD transport equation. New models for these terms have been demonstrated to exhibit satisfactory agreement with the corresponding terms extracted from DNS data.

Effect of Leading-Edge Bluntness on Shockwave–Boundary-Layer Interaction in a Scramjet Intake

An experimental and numerical study was carried out to investigate the effect of leading edge bluntness on the flowfield characteristics of a Mach 6 scramjet inlet. The numerical study was performed using Ansys Fluent 18.0 software. A steady two-dimensional Reynolds-Averaged Navier–Stokes simulation was carried out using k-ε-Re-Normalisation Group model for a sharp edge and leading edge with bluntness of 0.5 and 1 mm (ramp and cowl tip). Significant changes in the flowfield characteristics and parameters were observed for a blunt leading edge compared to the sharp leading edge case. The experimental campaign was carried out in the Mach 6 S1 Hypersonic Ludwieg Tunnel to validate the numerical results, and a good match was observed up to the separation bubble, and deviation in the reattachment is observed. Furthermore, the unsteadiness associated with the shockwave–boundary-layer interaction region inside the isolator was studied for the sharp and blunt leading edge cases. It was observed that changing the leading edge bluntness modifies the flowfield oscillations, separation bubbles, shear layer oscillations, etc.

Detached-eddy simulation of the vortex system on the high-lift common research model

A complex vortex system exists on the high-lift transport aircraft with components of the nacelle, pylon, high-lift devices, strakes, and brackets, and the investigation of the vortex system is helpful in profoundly understanding the aerodynamic characteristics of actual high-lift aircraft. To investigate the vortex system on the high-lift transport aircraft and evaluate the simulation capacity of detached-eddy simulation (DES) for the vortex system on the high-lift aircraft configuration, a high-resolution DES numerical investigation is carried out on a standard high-lift transport aircraft configuration, the National Aeronautics and Space Administration (NASA) high-lift common research model (CRM-HL). Reynolds-averaged Navier–Stokes simulation (RANS) is also performed to investigate the differences between DES and RANS in predicting time-averaged aerodynamic data on the CRM-HL. After experimental validation of time-averaged surface load and flow patterns, three vortex identification methods are adopted to extract the vortex structures of the flow field. It is found that the Rortex-based vortex identification method can more distinctly extract the fine vortex structures. The DES method can reliably predict the time-averaged surface load while capturing the complex vortex system on the CRM-HL under the concerned case of this work with high resolution.