European Journal of Mechanics B-fluids最新文献

This paper explores local absolute instability in the boundary layer flow over two distinct families of rotating spheroids (prolate and oblate). While convective instability was established in earlier work by Samad and Garrett [1], this study delves into the potential occurrence of local absolute instability. Some results of local convective instability under the assumption of stationary vortices are reproduced for a more comprehensive investigation. The analysis considers viscous and streamline curvature effects, demonstrating that the localized mean flow within the boundary layer over either family of the rotating spheroid is absolutely unstable for each fixed value of the eccentricity parameter $e\in [0,0.8]$. For certain combinations of Reynolds number $Re$ and azimuthal wave number $\beta$, a third branch (Branch 3) of the dispersion relation intersects Branch 1 at a pinch point, indicating absolute instability. Neutral curves depict regions that are absolutely unstable, while below critical Reynolds numbers, the region is either convectively unstable or stable. The paper also illustrates the effect of increasing eccentricity on spatial branches within both convectively and absolutely unstable regions. From lower to moderate latitudes, the stabilizing effect of $e$ on the onset of absolute instability is robust for the prolate family and almost negligible for the oblate family. At high latitudes of the prolate spheroid, the stabilizing effect of $e$ is fainter but persists until close to the equator. Conversely, at high latitudes of the oblate spheroid, the stabilizing effect of $e$ is more pronounced. The paper discusses the implications of the parallel flow assumption employed in the analyses.

Inhomogeneities in the wave field due to wave groups, currents, and shoaling among other ocean processes can affect the mean water level. In this work, the classical and unsolved problem of continuously computing the set-down and the following set-up induced by wave breaking on a shoal of constant finite slope is tackled. This is possible by using available theoretical knowledge on how to approximate the distribution of wave random phases in finite depth. Then, the non-homogeneous spectral analysis of the wave field allows the computation of the ensemble average by means of the phase distribution and the inversion of the integral of the second moment for the special case of a shoaling process with uniform phase distribution. In doing so, I am able to obtain a direct effect of the slope magnitude on the phases distribution. Therefore, an analytical and slope-dependent mean water level with continuity over the entire range of water depth is provided.

It is challenging to apply numerical simulations to accurately predict the stall behavior of aircraft equipped with high-lift devices. Simulations with Reynolds-Averaged NavierStokes (RANS) models suffer from lack of the reliability at high angles of attack with separated and reattached boundary layers, whereas wall-resolved Large Eddy Simulations (LES) of wall-bounded flows at high Reynolds numbers currently costs too much computational resources. A new unified hybrid turbulence modeling approach, denoted the Self-Adaptive Turbulence Eddy Simulation (SATES), is proposed and applied for complex turbulent flows combining with high-order numerical scheme of the Weighted Compact Nonlinear Scheme (WCNS) in the present study. It enables a seamless evolution from unsteady RANS to LES and finally approaches Direct Numerical Simulation (DNS) depending on the turbulent scales. In the framework of SATES, a new SATES-σ model with an adaptive model coefficient is developed by extending the underlying LES mode based on an enhanced sub-grid-scale model of the σ-model. The new SATES-σ is first examined in two benchmark cases of channel flow and flow past a square cylinder. Then, it is validated in supercritical flow past a circular cylinder to assess the performance of turbulent models. The results show significant improvements over the previous SATES and IDDES in the predictions of boundary layer flow. Finally, successful application is achieved in the accurate prediction of the stall of the MD-30P30N airfoil at a Reynolds number of 9×10⁶ with wide angles of attack. The simulation results show good agreement with experimental results for surface pressure even for the challenging cases of 21 and 23 deg angles of attack. Again, the SATES-σ shows better results than the previous SATES and IDDES. The presented method has considerable potential for the challenging stall predictions.

In the numerical simulations of multi-phase flow using Volume-of-Fluid (VOF) method, the calculation of the interface normal is a crucial point. In this paper, a machine learning method is used to develop an artificial neural network (ANN) model to make more accurate prediction of the local normal vector from neighboring volume fractions. Spherical surfaces with different radii are intersected with a structural background grid to generate 84328 groups of data: 3×3×3 neighboring volume fractions are used as input, and normal vector as output. Using 90% data as training dataset, the ANN model is well trained by optimizing the number of hidden layers and the number of neurons on each layer. Using the remaining 10% data, normal predictions are made using ANN-VOF and the most used YOUNG and HEIGHT-FUNCTION methods. The RMSE of the ANN-VOF/YOUNG/ HEIGHT-FUNCTION methods are 0.008/0.022/0.045 respectively. In the reconstruction of a sinusoidal surface, the MSE of the ANN-VOF/YOUNG/ HEIGHT-FUNCTION methods are 0.008/0.018/0.041. It is demonstrated that the ANN-VOF method has better performance for interface normal prediction. The proposed method has a simple computational logic and does not need to deal with complex geometric topology, which lays the foundation for application in other more complex grids.

The quantification of global turbulence statistical moments generated by grid turbulators is crucial for the enhancement of conjugate heat transfer in industrial thermo-fluid systems. As such, there is a need for precise, low-cost alternatives to numerically model three-dimensional flow dynamics of fractal-generated turbulence (FGT) behind multilength-scale square fractal grids (SFGs), in contrast to previously-reported direct numerical simulations. In this study, a numerical framework consisting of multiple applications of the Reynolds stress model (RSM), each employing its own distinct set of optimized coefficient values, is developed by segregating an FGT flow domain into its production and decay regions with Nelder-Mead optimization on key coefficients then performed independently for each region. The flow fields predicted by such RSM framework achieved overall disparities below 3% and 13% w.r.t. reported experimental measurements of mean velocity and turbulence intensity, respectively, considering the evolution in the flow domain along the streamwise, vertical, and spanwise directions. This is therefore the first documentation of any RANS-turbulence model being validated for mean velocity and turbulence intensity predictions of FGT in all three-dimensions. Thereafter, this proposed RSM framework is generalized to predict industry-relevant turbulence statistical moments of four additional FGT flows. The predicted centerline-statistics are verified against reported experiments, and the findings potentially enable realizations of FGT induced by arbitrary SFGs without relying on a posteriori validation while eliminating further reliance on the Nelder-Mead optimization algorithm on a case-by-case basis. The findings indicate a potential to apply the model coefficients as continuous functions of space to simulate the entire FGT domain. Overall, the accurate and numerically sustainable realizations of FGT in 3D provide valuable insights to engineer potent fluid-solid heat transfer via passive turbulence management within HVAC systems.

Research has demonstrated the significant influence of surface roughness on electrical conductivity and streaming potential. This article presents a model for the flow potential in a porous medium with rough fractures, based on fractal theory and representative elementary volume theory. Expressions for the model’s permeability, conductivity, and coupling coefficient between flow and potential are derived. The results indicate that both the relative roughness and structural parameters of the model have certain effects on the conductivity and coupling coefficient. By comparing experimental data from previous literature with the predicted values from the model, the correctness and effectiveness of the model are validated.

The problem of determining a mean flow induced by longitudinal libration of a rapidly rotating fluid-filled container bounded by the surfaces of two oppositely oriented right circular cones is considered. It is shown that the problem is reduced, through introducing a cosine of the angle between the normal to the conical surfaces and the axis of rotation, to the problem of determining a mean flow induced by libration of a fluid-filled rotating cylindrical container of infinite radius. A theoretical scenario is proposed of how the solved problem can be applied to the approximate determination of the differential mean rotation in a significant part of a rotating spherical and/or oblate spheroidal cavity under the action of longitudinal libration forcing.

With the limitation of the high sensitivity of nonlinear models to initial conditions, the accurate estimation of wave spatial evolution is difficult to perform at a long distance. At this stage, a helpful approach is to improve the accuracy and robustness of the model through data assimilation technique. A robust data assimilation framework is developed by coupling ensemble Kalman filtering (EnKF) with the nonlinear wave model. The spatial evolution is obtained by numerically integrating the viscous modified Nonlinear Schrödinger (MNLS) equation. The performance of the EnKF-MNLS coupled framework is tested using synthetic data and laboratory measurements. The synthetic data is generated by the MNLS simulation superposing the Gaussian noise. In the synthetic cases, the estimated wave envelopes agree well with the clean solution. The results of laboratory experiments indicate that the EnKF-MNLS framework can improve the accuracy of wave forecasts compared to noised MNLS simulations. This study aims to enhance the noise resistance of the nonlinear wave model in spatial evolution and improve the accuracy of the model forecast.

The extensive use of lightweight materials in aerial vehicle wings involves structural flexibility phenomena that generate non-negligible deformation effects. This influence is not restricted to big aircraft but also plays a role in smaller aeroplanes and Unmanned Aerial Vehicles (UAVs). Here, we conduct wind tunnel experiments to analyze the effect of passive deformation on the wing model lift slopes. To isolate the deformation effect, we compare rigid wings with a NACA0012 airfoil imposing a prescribed spanwise deformation. We study three levels of deformation: non-deformed, around 2% and 4.5% of tip deflection. Also, we consider the effect of the wing length by using three different semi-aspect ratios (1, 2, and 4), so a total of nine rigid wing models have been analyzed for a range of Reynolds number from $80\times 10^3$ to $160\times 10^3$. Deformed wing models show an increase in lift coefficient compared to non-deformed wing cases. Both deformation levels exhibit a qualitatively similar lift increment. A correlation to predict lift coefficient slope in a flat plate is adapted for a NACA0012 airfoil and validated using our experimental results and literature data. The adjusted correlation can quantify the deformation effect on the lift slope, which is comparable to using a slightly longer wing model.

In order to improve the propulsive performance of the existing pure heaving motion hydrofoil, the effect of varying stiffness ratio K*, damping ratio C* and inertia ratio J* on the propulsive efficiency of the semi-active NACA 0012 hydrofoil is systematically investigated by using the combination of CFD, Taguchi method and neural network. The results show that the passive pitching motion can significantly affect the propulsive performance of the hydrofoil. Compared to the pure heaving hydrofoil, the propulsive efficiency of the optimized semi-active hydrofoil can be improved by up to 20.97%. Further analysis reveals that the passive pitching motion can weaken the strength of the vortex around the hydrofoil, thus reducing the thrust and lift force on the hydrofoil, which results less power consumed by the active heaving motion of the hydrofoil. Although the thrust coefficient is reduced, the energy consumed by the passive pitching hydrofoil is reduced more, which leads a higher propulsive efficiency of the semi-active hydrofoil.