Reynolds-averaged Navier-Stokes Research Articles

Numerical analysis of a parallel triple-jet of liquid-sodium in a turbulent forced convection regime

In the present study, we have applied a combined wall-resolving dynamic Large-Eddy Simulation (LES) (for the velocity field) and Direct Numerical Simulation (DNS) (for the temperature field) approach for mixing of parallel triple-jets with different temperatures of liquid sodium in a turbulent forced convection regime. Because of the high thermal conductivity of sodium (a low-Prandtl fluid), we adopted the dynamic Smagorinsky subgrid closure for the unresolved velocity scales, while the thermal scales are fully resolved. Furthermore, the Time-dependent Reynolds-Averaged Navier-Stokes (T-RANS) approach with the high-Reynolds number variant (i.e. with the wall functions as boundary conditions along solid boundaries) of the four-equation eddy viscosity model (k−ε−kθ−εθ) was applied. The fine-mesh LES/DNS provided a close agreement with the experimental data for both velocity and temperature fields (for both first- and second-moments). In contrast, the coarse-mesh LES/DNS overestimated the turbulent kinetic energy profiles at different distances from the inlet plane. The T-RANS results confirmed a good agreement with the mean streamwise velocity and turbulent kinetic energy, as well as the mean temperature profiles. Finally, the analysis of power spectral density distributions of the temperature signal revealed that all simulation techniques captured a dominant flow frequency originating from the induced Kelvin-Helmholtz instabilities between the side and central jets. The presented combined dynamic LES/DNS approach is recommended for future simulations of the turbulent forced convection flows of low Prandtl fluids, especially if thermal fatigue effects need to be predicted correctly.

A face-centred finite volume method for laminar and turbulent incompressible flows

This work develops, for the first time, a face-centred finite volume (FCFV) solver for the simulation of laminar and turbulent viscous incompressible flows. The formulation relies on the Reynolds-averaged Navier–Stokes (RANS) equations coupled with the negative Spalart–Allmaras (SA) model and three novel convective stabilisations, inspired by Riemann solvers, are derived and compared numerically. The resulting method achieves first-order convergence of the velocity, the velocity-gradient tensor and the pressure. FCFV accurately predicts engineering quantities of interest, such as drag and lift, on unstructured meshes and, by avoiding gradient reconstruction, the method is less sensitive to mesh quality than other FV methods, even in the presence of highly distorted and stretched cells. A monolithic and a staggered solution strategies for the RANS-SA system are derived and compared numerically. Numerical benchmarks, involving laminar and turbulent, steady and transient cases are used to assess the performance, accuracy and robustness of the proposed FCFV method.

Chaotic Vortex-Induced Vibrations of Rigid Cylinders with Nonlinear Snapping Support

Vortex-Induced Vibration (VIV) is a complex fluid–structure interaction in offshore structures. Traditionally, this phenomenon is considered periodic; however, many of its signals show chaotic behavior. The basic model already employed by other researchers is a rigid circular cylinder with linear springs and dampers. In this work, nonlinear snapping support is used to model nonlinearity in the system. To numerically simulate the flow, Reynolds-Averaged Navier–Stokes (RANS) equations for two-dimensional incompressible unsteady flows are applied. The degree of nonlinearity of the system can be changed by manipulating [Formula: see text], which is one of the geometric properties of the spring and takes values between 0 and 1. The 0–1 test, Poincaré section, and Fast Fourier Transform are used to analyze the cylinder and lift force behavior. Also, the Hilbert transform is applied to the signals, and the phase shift between displacement and lift force is obtained. The results show that the system behavior consists of branches: branch I and branch II. The large amplitudes occur in branch II. It is found that chaos emerges at the beginning of branch II, regardless of the value of [Formula: see text]. By raising the [Formula: see text] value, the span of branch II becomes more expansive, and its first point is placed at lower reduced velocities. Also, the wake dynamics becomes more regular at the end of branch I and more irregular at the beginning of branch II with the increase in [Formula: see text]. When the cylinder displacement signal is chaotic, the lift force behavior is also chaotic, but not vice versa.

Numerical study on effects of geometric parameters influence on two-dimensional cycloidal propellers

Aiming to investigate different geometric parameters on cycloidal propellers' hydrodynamic characteristics, an efficient two-dimensional (2D) cycloidal propeller model was established. The Reynolds-averaged-Navier-Stokes (RANS) solver was used to simulated the open water maneuverability of the cycloidal propellers' in fully azimuth angle. Hydrodynamic characteristics under different geometric parameters were analyzed in detail. The geometric parameters are blade number, chord length, thickness and camber, respectively. The research shows that with the increase of the blade number, the side thrust increases, and main thrust decreases. The longer of the blade chord length, the greater the thrust. As the blade camber increases, the effective thrust increases. Additionally, the blade thickness has little effect on side thrust, but it can improve the utilization of torque and significantly increase the efficiency of the propeller. The revealed findings in present paper should contribute to cycloidal propellers' preliminary design.

A two-stage CFD-GNN approach for efficient steady-state prediction of urban airflow and airborne contaminant dispersion

Urban design requires accurate prediction of wind, gusts, and contaminant dispersion to create sustainable cities. While computational fluid dynamics (CFD) models like large-eddy simulation (LES) provide accurate predictions, they are computationally expensive. Steady Reynolds-averaged Navier-Stokes (SRANS) is fast but inaccurate due to inherent limitations. This study proposes a two-stage CFD-graph neural network (GNN) framework for efficient steady-state prediction. A CFD solver provides the initial state, and then a GNN directly corrects the CFD outputs towards a high-fidelity target in a single inference step, bypassing SRANS flaws. LES results for parametrically generated urban cases provided training data. The proposed framework is thus distinguished from previous GNN applications, which were unsteady RANS surrogates that are still constrained by RANS inaccuracy. SRANS with the k-ε model provided an informative initial state for GNN (termed KE-GNN). Less detailed initializations increased prediction difficulty. Uneven sampling of building density and heights introduced dataset bias, improving specialization but reducing generalizability. For an actual urban case, KE-GNN employing a coarse mesh achieved considerable agreement with the fine LES result and was thousands of times faster. On the same coarse mesh, KE-GNN was seven times faster than a tightly converged SRANS and 280 times faster than an under-resolved LES.

A framework of a data-driven model for ship performance

An accurate assessment of a ship's required power is increasingly relevant for ship operations. We used a simplified framework of a data-driven model to predict ship's fuel consumption. Our approach was based on the learning capabilities of a generalized AutoML (Automated Machine Learning) process, trained with a variety of databases obtained from Computational-Fluid-Dynamics (CFD) simulations or from simplified numerical methods. These CFD simulations were conducted by solving the Reynolds Averaged Navier-Stokes (RANS) equations, using the STARCCM + commercial CFD software to calculate the ship resistance at speed under different operating conditions. Initially, we conducted a statistical analysis to select the independent variables before fitting the regression models and identifying potentially wrong assumptions. The AutoML process allowed optimizing the model's hyperparameters and designing the topology of the neural networks. For a set of unknown scenarios, comparative predictions obtained from the data-driven model and from numerical simulations showed that the data-driven model, trained with results obtained from CFD simulations, accurately and efficiently predicted ship operational parameters under realistic operating conditions, thereby dispensing with the need to perform elaborate CFD computations. Specifically, this low-cost and efficient operational data-driven technique forecasted the ship's operational fuel consumption although only a limited amount of recorded operational data was available.

Enhancing the SST turbulence model for predicting heat flux in hypersonic flows through symbolic regression

In the context of hypersonic flows, shock-wave/turbulent boundary-layer interactions (SWTBLIs) can lead to substantial aerodynamic heating. The commonly used Reynolds-averaged Navier–Stokes (RANS) method in engineering applications faces challenges in accurately predicting heat transfer in these conditions, as the assumptions made by Morkovin’s assumption in the RANS method are not applicable in hypersonic SWTBLI flows. This article addresses these challenges by introducing a variable turbulent Prandtl number (Prt) model for non-adiabatic walls, established through field inversion and symbolic regression (SR) techniques. The methodology begins with field inversion for an oblique SWTBLI case at Mach 5. The corrected field, denoted as β(x), obtained from this inversion, is integrated with selected local flow characteristics to derive a corrected expression using SR. Following the necessary adjustments, this expression is incorporated into the RANS solver. Various cases with different wall cooling ratios, Mach numbers, and Reynolds numbers are chosen to assess the generalization ability of the variable Prt model. The outcomes demonstrate a substantial improvement in the model’s ability to predict heat transfer in hypersonic SWTBLI flows without compromising the baseline model’s performance in predicting the undisturbed boundary layer. The correction effect remains notably enhanced even in complex three-dimensional cases.

Numerical and experimental analysis of the formation of nitrogen oxides in a non-premixed industrial gas burner

Nitrogen oxides (NOx) formation in a non-premixed industrial gas burner is analyzed with Reynolds-averaged Navier-Stokes (RANS) computational fluid dynamics, using the Flamelet Generated Manifold (FGM) approach for chemistry and the Reynolds stress model for turbulence closure. Analysis and validation of the numerical methodology use both the RANS and the Large Eddy Simulation methods to study the Sandia flame D experiment. Four regimes of the gas burner, differing by thermal power, are studied experimentally and numerically, comparing measured and computed flue gas temperature and emissions. The flow features leading to NOx formation are analyzed. At low power, most NOx formation occurs in the flame core, where temperatures are highest. At high power, a significant amount of NOx forms where a secondary stream of oxidizer meets the high-temperature burnt gas stream. The NOx formation rate is modeled either by summing the contributions of the main paths relevant to the studied problem or via two variants of the FGM scalar transport approach. One of these variants features a correction to the transported scalar approach that enables accounting for the effects of non-adiabatic phenomena, e.g. heat radiation, on NOx formation without increasing the look-up table dimensionality and the required memory usage. The correction is shown to improve emission predictions over the baseline model, although quantitative differences between predicted and measured emission levels remain significant. The approach computing the NOx formation rate as by summing contributions yields the best agreement with measurements when the thermal path predominates, and the formation of nitrogen dioxide is negligible.

Turbo-RANS: straightforward and efficient Bayesian optimization of turbulence model coefficients

PurposeIndustrial simulations of turbulent flows often rely on Reynolds-averaged Navier-Stokes (RANS) turbulence models, which contain numerous closure coefficients that need to be calibrated. This paper aims to address this issue by proposing a semi-automated calibration of these coefficients using a new framework (referred to as turbo-RANS) based on Bayesian optimization.Design/methodology/approachThe authors introduce the generalized error and default coefficient preference (GEDCP) objective function, which can be used with integral, sparse or dense reference data for the purpose of calibrating RANS turbulence closure model coefficients. Then, the authors describe a Bayesian optimization-based algorithm for conducting the calibration of these model coefficients. An in-depth hyperparameter tuning study is conducted to recommend efficient settings for the turbo-RANS optimization procedure.FindingsThe authors demonstrate that the performance of the k-ω shear stress transport (SST) and generalized k-ω (GEKO) turbulence models can be efficiently improved via turbo-RANS, for three example cases: predicting the lift coefficient of an airfoil; predicting the velocity and turbulent kinetic energy fields for a separated flow; and, predicting the wall pressure coefficient distribution for flow through a converging-diverging channel.Originality/valueTo the best of the authors’ knowledge, this work is the first to propose and provide an open-source black-box calibration procedure for turbulence model coefficients based on Bayesian optimization. The authors propose a data-flexible objective function for the calibration target. The open-source implementation of the turbo-RANS framework includes OpenFOAM, Ansys Fluent, STAR-CCM+ and solver-agnostic templates for user application.

Improvements for the DDES model with consideration of grid aspect ratio and coherent vortex structures

The delayed detached eddy simulation (DDES) model has achieved great success in simulations of massive separations, but has been found to significantly delay the Kelvin-Helmholtz (K-H) instability in weak separations due to the “grey area” problem. A new DDES model was proposed by considering the grid aspect ratio and local coherent vortex structures, named the DDES with an adaptive grid-scale and adaptive coefficient (DDES-AGAC). The DDES-AGAC model was examined in detail by computing four typical types of turbulent flows: fully attached turbulent boundary layer, massive separation, weakly unstable flow with a fixed separation point, and weak separation over a smooth surface due to pressure gradient. The results confirm the advantages of the new DDES-AGAC model over the standard DDES. It exhibits high efficiency and insensitivity to spanwise or circumferential grid spacing in flow simulations of quasi-three-dimensional flows. For the weakly unsteady separation, it helps to accelerate the rapid switch from Reynolds-averaged Navier-Stokes equations to large eddy simulation, unlock the K-H instability in the shear layer, and hence accurately resolve the turbulent structures, profiles of velocity and turbulent kinetic energy, and spectra in the separation regions. Furthermore, it does not result in a noticeable drag or skin friction reduction in the fully attached flow simulations. The DDES-AGAC model is expected to be widely used in simulations of engineering flows with separations.

The impact of wedge and wavy-wall combustor side walls on shock-induced mixing and combustion in a hydrogen-fuelled model scramjet combustor

The mixing and combustion processes are linked and challenging for a supersonic combustion engine. Supersonic air doesn't spend much time in the combustor, making it challenging to blend fuel with supersonic air. The expansion of shear-mixing layer with shock waves and their interactions are the primary characteristics of mixing augmentation. This paper investigates the same methodology for a model scramjet combustion chamber with wedge and wavy sides. The novel scramjet combustion models include wedge and way-wall sidewalls based on the basic scramjet model. By combining the finite volume approach with a second-order upwind discretization method, the Reynolds-averaged Navier-Stokes equations are numerically analyzed. The interplay between wedge and wavy-wall effects and free stream flows is taken into consideration by using the shear stress transport (SST) k−ω turbulence model. The effect of the wedge and wavy wall combustor has been evaluated by analysing the shock production and their interactions with the mixing layer and internal flow structure. The turbulence characteristics are also examined to analyse the degree of flow disturbance for wedge and wavy-wall combustion. The wavy wall combustor model results in a 14.5% increase in turbulence intensity, which raises air-fuel mixing and there by improves mixing and combustion efficiency by 12.59% and 11.23%, compared to the base wedge type combustor.

Effects of Leading Edge Radius on Stall Characteristics of Rotor Airfoil

The effects of leading edge radius on the static and dynamic stall characteristics of rotor airfoils are investigated. Initially, a parametric airfoil (PARFOIL) method is employed to generate four morphed airfoils with different leading edge radii based on a NACA 0012 airfoil. Subsequently, the Reynolds-averaged Navier–Stokes (RANS) method is employed to simulate the aerodynamic characteristics of static airfoils, while the improved delayed detached-eddy simulation (IDDES) method is employed for pitching airfoils. The effectiveness and accuracy of the computational fluid dynamics (CFD) methods are demonstrated through favorable agreement between the numerical and experimental results. Finally, both the static and dynamic aerodynamic characteristics are simulated and analyzed for the airfoils with varying leading edge radii. Comparative analyses indicate that at low Mach numbers, the high adverse pressure gradient near the leading edge is the primary cause of leading edge separation and stall. A larger leading edge radius helps to reduce the suction pressure peak and adverse pressure gradients, thus delaying the leading edge separation and stall of airfoil. At high Mach numbers, the leading edge separation and stall are mainly induced by the shock wave. Variations in leading edge radius have minimal impacts on the high adverse pressure gradient induced by the shock wave, thus making the stall characteristics of airfoils almost unaffected at high Mach numbers.

Numerical and Experimental Analysis of Lifting Forces of Fin Stabilizers with Fin–Hull Interaction

A fin stabilizer is one of the most effective and frequently used anti-roll devices for maintaining a ship’s operational safety and passengers’ comfort. However, the discrepancy between theoretical hydrofoil-based predictions and the actual dynamic lift force of fin stabilizers due to fin–hull interactions requires more research attention. This study investigates the effect of fin stabilizers on mitigating roll motion through the performance of extensive computational fluid dynamic (CFD) simulations over a range of fin angles and ship speeds. Model tests were carried out to validate the drag and motion results obtained from numerical analyses. The results show that fin stabilizers significantly reduce the roll motion, with the lift coefficient values influenced by the Reynolds number, leading to differences between the theoretical and Reynolds-averaged Navier–Stokes (RANS) calculations. At a high Froude number (Fr), the actual fin lift is about half of the theoretical value. These findings highlight the requirement of selecting an adequate fin area at the predominant ship speeds and ensuring an effective anti-roll effect with fin–hull interaction. This study provides a significant reference for ship design, as well as stabilization system control and optimization.

The impact of the Impeller's hub design on the performance and blood damage in a microaxial mechanical circulatory support device – A numerical study

This study uses CFD methods to investigate the effects of the impeller's geometry on the hemodynamic characteristics, pump performance, and blood damage parameters, in a percutaneous microaxial Mechanical Circulatory Support (MCS) device. The numerical simulations employ the steady state Reynolds-Averaged Navier-Stokes approximation using the SST k−ω turbulent model. Three different impeller models are examined with different hub conversion angles (α = 0○, 3○ and 5○). The analysis includes 23 cases for different pressure heads (Δp = 60–80 mmHg) and angular velocities (ω = 30–52 kRPM). The obtained flow rate is compared between the cases to assess the effect of the impeller's design and working conditions on the pump performance. The comparative risk of shear-induced platelet activation is estimated using the statistical median of the stress-accumulation values calculated along streamlines. The risk of hemolysis is estimated using the average exposure time to shear stress above a threshold (τ > 425 Pa). The results reveal that the shape of the impeller's hub has a great impact on the flow patterns, performance, and risk of blood damage, as well as the angular velocity. The highest flow rate (Q = 3.7 L/min) and efficiency (η = 11.3 %) were achieved using a straight hub (α = 0○). Similarly, for the same condition of flow and pressure, the straight hub impeller has the lowest blood damage risk parameters. This study shed light on the effect of pump design on the performance and risk of blood damage, indicating the roles of the hub shape and angular velocity as dominant parameters.

Influence of Incident Shock on Fuel Mixing in Scramjet

During the operation of hypersonic vehicles, a reciprocal coupling effect is manifested between the inlet and the combustion chamber. This results in an unavoidable non-uniformity of conditions at the combustion chamber’s entrance, which, in turn, influences the fuel mixing within the chamber. The present study employed the Reynolds-averaged Navier–Stokes (RANS) equations to perform a numerical simulation of an X-51-like vehicle, with a focus on examining the impact of isolation section length and multi-injection strategies on the fuel mixing characteristics within the combustion chamber under conditions of non-uniform inflow. The findings indicated that a supersonic non-uniform inlet triggers incident shock waves, leading to a non-uniform pressure distribution across the flow section. Moreover, the position of injection was found to be pivotal in regulating penetration depth and mixing efficiency. The incident shock wave, bow shock, and boundary layer separation shock interacted with each other to increase local pressure. The coupling of high and low pressures generated an adverse pressure gradient that led to boundary layer separation, which further enhanced fuel penetration depth.

Fluid-to-fluid similarity and CFD predictions of surrogate fluid as a replacement for R11 refrigerant used in a subcooled flow boiling analysis: Validation against reference experimental data

In this study, we present the possibility of substituting the primary fluid Freon 11 (CCl3F, R11) used in the experimental thermohydraulic test facility which offers the advantage to obtain phase change at relatively low heat fluxes and pressure if compared to water working fluid. Nevertheless, R11 is a CFC (Chlorofluorocarbures) part of the gases that contribute to the degradation of the ozone layer.For this purpose, four working fluids (non-CFC) are judiciously selected to replace the R11, namely the R123, R134a, R143a and CO2, and this through multidimensional Computational Fluid Dynamics (CFD) modeling of steady state flow boiling phenomenon. The calculation model covers a wide range of mass fluxes (435 – 1443 kg/m2s) and heat fluxes (1.2– 36 W/cm2); it predicts the heat transfer rates and transitions points for each flow regime. In this research, the experiment's data were compared to the outcomes of Ansys-CFX computations, using a steady Reynolds-Averaged Navier-Stokes (Steady-RANS) model, to investigate the best replacement refrigerant for R11. The turbulence effects on the mean flow and near wall are taken into consideration using the Shear Stress Transport (SST k-ω) turbulence model. The results from the four fluids were transposed to their water equivalent and compared to those deduced from the experimentation and correlations available in the literature to select the appropriate substitution fluid. The results qualitative and quantitative for vertical and horizontal subcooled boiling flow at the CHF location show that, the most effective surrogate fluid is R123 (HCFC), is still widely used in the refrigeration and air-conditioning industry, then R134a (HFC), then R143a (HFC).

Comparative study of nonlinear wave-induced global loads on a container ship in regular head waves predicted with numerical methods based on weakly nonlinear potential theory and Reynolds-averaged Navier-Stokes equations

ABSTRACT Wave-induced loads on the ship hull are of significant interest for many reasons. These loads, however, are highly nonlinear in realistic wave conditions and consequently difficult to predict. In this paper, we analysed and compared wave-induced loads acting on a container vessel in regular head waves computed with a newly developed weakly nonlinear potential theory-based code and a flow solver based on the Reynolds-averaged Navier-Stokes Equations. We investigated both long and short waves with moderate steepness. Initially, the vessel was completely fixed and the ship motions were suppressed, then the vessel was free to heave and pitch motion. We compared time-histories of the computed wave-induced longitudinal and vertical global forces as well as the pitch moment and we deeply analysed nonlinear effects by applying a Fourier transformation and comparing the corresponding harmonic amplitude up to the fourth order. Our results demonstrated satisfactory agreement between the two numerical methods, especially when the ship was free to heave and pitch. Additionally, the results provided detailed information about the capabilities and limitations of the weakly nonlinear potential theory-based approach.

Usage of high-fidelity large eddy simulation to improve the turbulence modeling of Reynolds averaged navier stokes simulation in film cooling applications via a neural network

In this study, high-Fidelity Large eddy simulation (LES) data was used to create a surrogate turbulence model to enhance the estimation of turbulent heat flux in a Reynolds averaged Navier Stokes (RANS) solver for film cooling applications. The LES simulation (A flat plate film cooling application with a Reynolds number of 17,382, a blowing ratio of 1 and a density ratio of 2) was validated by comparison with experimental data. A correlation analysis was performed to identify the most influential parameters, and temperature gradient, velocity gradient, turbulent dissipation rate, shear strain rate, and turbulent viscosity ratio were selected as the most effective parameters. A second model was developed to create a Galilean-invariant model that remains unaffected by changes in the coordinate system. Neural network was applied to the LES training data to propose a modified surrogate dynamic turbulent Prandtl number to be applied to the k − ε realizable RANS simulation. The first surrogate model was implemented to two different geometries, one geometry was a flat plate film cooling similar to the training data but with different flow conditions, and another one was a more complex geometry with pressure gradient. The second model was only implemented on the second geometry and produced similar results. The surrogate models predicted a more accurate thermal field near the cooling wall (up-to 58 % error reduction) with a computational time complexity similar to the base RANS solver.

Computational Fluid Dynamics Analysis on the Road Bike Using Different Flow Models under Extreme Inlet Velocity

At high velocities, the aerodynamic forces acting on the road bike and rider become more pronounced, potentially affecting stability and control. Riders might experience increased resistance, requiring more effort to maintain balance and direction. This research employs Computational Fluid Dynamics (CFD) to thoroughly examine the external aerodynamics of road bikes, focusing on pre-processing techniques and their impact on overall aerodynamic performance. The research applies CFD methods for geometry preparation, meshing, and material property definition within a structured workflow using a road bike model representative of the cycling industry via SimFlow software. Through systematic variations in extreme inlet velocities (40, 70, and 100 m/s) and the utilization of diverse turbulent models, k-ω Shear-Stress Transport (SST) and Reynolds-Averaged Navier-Stokes (RANS) with k-ε and k-ω, the study reveals intricate airflow patterns around the road bike. The results explain the complicated connection between turbulent models and inlet velocities and provide new information on critical aerodynamic parameters, such as pressure and maximum velocity of the road bike model.

Experimental and numerical investigation of the effects of porous bleed systems on a model scramjet inlet under high backpressure conditions

In this study, we conducted experimental and numerical investigations to assess the effects of backpressure and configurations of porous bleeds on a scramjet inlet's performance at Mach 5. Experiments in a high-enthalpy wind tunnel, using a backpressure controller and a porous bleed with 1 mm holes and 10 mm lateral spacing, were paired with Reynolds-averaged Navier-Stokes simulations to explore the mitigation of flow separation and the prevention of inlet unstart under various backpressure conditions. The simulations provided insights into how backpressure levels and porous bleed geometries impact internal flow structures, as well as the critical backpressure ratio at which inlet unstart occurs. Additional simulations varied the bleed system's hole diameter and spacing, identifying configurations that optimize aerodynamic performance by enhancing total pressure recovery and Mach number at the isolator exit, while reducing bleed mass flow rates. The study also quantified the impact of these configurations on engine thrust, determining that certain bleed system designs significantly improve thrust by efficiently suppressing the interaction between the core flow and corner recirculation zones. This study examined the internal three-dimensional flow structure characteristics under high back pressure and provided insights into porous bleed configuration capable of efficiently suppressing inlet unstart.