Tip vortex prediction for contra-rotating propeller using large eddy simulation

The flow field developing inside the stator-rotor disc cavities of gas turbines is characterized by highly complex and unsteady behavior driven by strong vortical structures and transient interactions. These features pose significant challenges for accurate prediction using standard Computational Fluid Dynamics models. In particular, the inherent unsteadiness of the flow field has a considerable impact on the sealing performance of the rim, especially when predicted by steady Reynolds-Averaged Navier-Stokes (RANS) methods, which tend to overestimate the sealing effectiveness by more than an order of magnitude. In this study, a series of numerical simulations were conducted using RANS, unsteady RANS (URANS), and large Eddy Simulation (LES) approaches to gain insight into the behaviour of the rim seal flow. The main objective was to compare the numerical results with experimental data obtained from the test rig at the University of Florence, in order to validate the accuracy of different numerical approaches. The RANS, URANS and LES simulations all demonstrated satisfactory agreement in terms of steady-state measurements of pressure coefficients and velocity fields, offering valuable insight into the time-averaged behavior of the flow. However, the Reynolds-averaged models failed to effectively capture the turbulent fluctuations between the main flow and the secondary flow. In contrast, LES simulations accurately captured the development of vortices and replicated more realistic flow conditions, resulting in a closer match with experimental data. Therefore, the resolution of these fluctuations, which are nowadays considered to be one of the fundamental factors driving the ingestion of mainstream flow into the cavity, appeared to be crucial to accurately understand the unsteady interaction between mainstream and secondary flows. Although the high computational cost and long transient phases required to reach periodic convergence make LES a resource-intensive approach, it demonstrates great potential for accurately predicting this interaction and providing valuable insights into the complex flow dynamics of rim seal flows.

Modeling of flow field and separation efficiency of a deoiling hydrocyclone using large eddy simulation

The present paper focuses on the recent development of an implicit pressure-based finite volume algorithm for numerical solution of Navier Stokes equation in an inertial frame of reference for prediction of unsteady incompressible flow problems. The algorithm uses boundary-conforming, multiblock structured grid with moving boundaries, collocated variable arrangement with momentum equations resolved along cartesian directions, second order accurate spatial and temporal discretisation schemes for the convective fluxes and a pressurevelocity solution strategy. Effect of turbulence is simulated using one of the two different approaches. In the Unsteady Reynolds Averaged (URANS) approach coupled to appropriate eddy viscosity based turbulence models, the Navier Stokes (NS) equations, averaged over the whole range of turbulent length scales of the flow, are solved numerically. On the other hand, in the Large Eddy Simulation (LES) approach, the model filtered 3D NS equations are directly solved for the flow variables to resolve the large scale turbulent motions whereas the transport processes at the fine subgrid scale level only are simulated using simple algebraic turbulence model. The capabilities and limitations of both the cost-effective URANS approach and the relatively expensive but rich in physics LES approach have been demonstrated for few application problems of engineering interest.

In the present paper, the analysis of concentration and flow fields around a model building was performed using two different approaches in turbulence modeling. In the first approach, the non-linear model of Ehrhard and Moussiopoulos was employed as one of the best cubic non-linear eddy viscosity models, and large eddy simulation was utilized in the second approach. The obtained results suggest that although the non-linear model has the ability to predict the anisotropic normal components of Reynolds stress tensor, due to time-averaged nature of its governing equations, it is incapable of estimating the correct values of Reynolds stress components and turbulent characteristics in the wake region of the model building. So the predicted turbulence kinetic energy values by the non-linear model are 45% smaller than those of large eddy simulation approach in the wake region behind the model building. Also different predictions of the wake region structure by the non-linear model and large eddy simulation approach revealed that elongation of iso-surface for \(\left\langle K \right\rangle\) = 1.5 in non-linear model is 56% more than that of large eddy simulation approach. The large eddy simulation approach shows much consistent behavior to the physics governing the flow compared to the non-linear model. Also good agreement observed between the results obtained through this approach and the experimental data. However, the disadvantage of large eddy simulation approach is the high computational costs.

In large eddy simulation (LES), the filtering grid scale (FGS) of LES equations is calculated generally by local mesh size. Therefore, proper LES Meshing is very decisive for better results and more economical cost. An effort was made to provide an available approach for LES meshing by turbulence theory and CFD methods. The expression for proper filtering grid scale (PFGS) was proposed on the basis of −5/3 law of inertial sub-range. A new parameter named grid ratio coefficient was put forward for the mesh adjustment. The proper mesh of LES could be built directly from the adjustment of RANS mesh. Two test cases both backward facing step flow and turbulent channel flow were provided to verify the approach. There were three kinds of mesh size, including coarse mesh for RANS (RCM), adjusted mesh for LES with the novel approach (NAM) and fine mesh for LES (LFM), employed here. The grid numbers of NAM were less than those of LFM evidently, and the results of NAM were in a good agreement with those of DNS and experiments. It was also revealed that results of NAM were very close to those of LFM. The conclusions provided positive evidences in the application of the approach.

Aero-thermal characteristics of transitional flow through a highly loaded transonic linear turbine are studied at the design incidence using computational methods. The three-dimensional compressible turbulent flow through a turbine inlet guide vane is simulated using finite-volume method-based fluid flow solutions using both Reynolds-averaged Navier Stokes (RANS) equations-based turbulence models, and a dynamic large eddy simulation (LES) approach which is based on a Smagorinsky-Lilly subgrid scale (SGS) model. The calculations are made for exit isentropic Mach numbers ranging from 0.7 to 1.1, and for Reynolds numbers ranging from 5 × 105 to 2 × 106. The numerical results obtained from different turbulence model simulations are compared with each other, and with the experimental data available in the open literature in terms of integrated flow parameters, such as pressure and heat transfer coefficients for varying exit Mach and Reynolds numbers. The present numerical approach indicates a guide line that the present LES approach can be a reliable choice for turbomachinery flows.

Dynamic procedures, typically motivated by scale-similarity concepts, have proven highly successful and are widely used in Large Eddy Simulation (LES) for determining model coefficients. However, in hybrid Reynolds-Averaged Navier–Stokes (RANS)/LES approaches, excessively coarse grids can undermine scale-similarity-based dynamic procedures: the turbulence mode implied by the test filter scale may be inconsistent with that of the grid filter. In this study, we derive a consistent dynamic model (CDM) by minimizing dependence of stress on the turbulence-resolution length scale, thereby ensuring consistency between RANS and LES modes. The CDM is capable of recovering the standard dynamic model (SDM) in regions far from the wall, while smoothly transitioning to the RANS mode near the wall. A priori tests in homogeneous isotropic turbulence show that, as filter width increases, the SDM coefficient quickly decays toward zero, whereas the CDM remains consistent with Direct Numerical Simulation (DNS)-calibrated values, demonstrating broader applicability. A posteriori tests in turbulent channel flow confirm that the CDM avoids underprediction of CDES near the wall and accurately distinguishes between RANS and LES regions without additional wall treatments. Consequently, mean and fluctuating quantities predicted on coarse grids agree better with experimental data and scaling laws than those from LES and the SDM. In periodic hill simulations, the CDM also predicts separation and reattachment points closer to high-resolution LES, further validating its ability to capture separated flows on coarse grids.

The goal of this study is to develop advanced numerical models and algorithms to improve the accuracy of engine spray combustion simulation. This study developed a large eddy simulation (LES) turbulence model and adaptive mesh refinement (AMR) algorithms to enhance the accuracy and computational efficiency of engine simulation. The LES approach for turbulence modeling is advantageous over the traditional Reynolds Averaged Navier Stokes (RANS) approach due to its capability to obtain more detailed flow information by resolving large-scale structures which are strongly geometry dependent. The current LES approach used a one-equation, non-viscosity, dynamic structure model for the sub-grid stress tensor and also used a gradient method for the sub-grid scalar fluxes. The LES implementation was validated by comparing the predicted spray penetrations and structures in a non-evaporating diesel spray. The present LES model, when coupled with spray breakup and detailed chemistry models, were able to predict the overall cylinder pressure history, heat release rate data, and the trends of NOx and soot emissions with respect to different injection timings and EGR levels in a heavy-duty diesel engine. Results also indicated that the LES model could predict the unsteadiness of in-cylinder flows and have the potential to provide more detailed flow structures compared to the RANS model. AMR algorithms were also developed to improve transient engine spray simulation. It is known that inadequate spatial resolution can cause inaccuracy in spray simulation using the stochastic Lagrangian particle approach due to the over-estimated diffusion and inappropriate

With a view to ensure that proper interaction between resolvable or grid scale and subgrid scale (SGS) motions are mimicked, it is vital to determine the necessary physics that must be built into the SGS models. In ordinary large eddy simulation (LES) approaches, models are introduced for closure in the low-pass filtered Navier-Stokes equations (NSEs), which are the ones solved numerically. A promising LES approach is monotonically integrated LES (MILES), which involves solving the unfiltered NSE using high-resolution monotone algorithms; in this approach, implicit SGS models, provided by intrinsic nonlinear high-frequency filters built into the convection discretization, are coupled naturally to the resolvable scales of the flow. Formal properties of the effectual SGS modeling using MILES are documented using databases of simulated homogeneous turbulence and transitional freejets; mathematical and physical aspects of (implicit) SGS modeling through the use of nonlinear flux limiters are addressed in this context

Bayesian source term estimation of atmospheric releases in urban areas using LES approach

With the rapid development of artificial intelligence, machine learning algorithms are becoming more widely applied in the modification of turbulence models. In this paper, with the aim of improving the prediction accuracy of the Reynolds-averaged Navier–Stokes (RANS) model, a semi-implicit treatment of Reynolds stress anisotropy discrepancy model is developed using a higher-order tensor basis. A deep neural network is constructed and trained based on this discrepancy model. The trained model parameters are embedded in a computational fluid dynamics solver to modify the original RANS model. Modification computations are performed for two cases: one interpolation and one extrapolation of different Reynolds numbers. For these two cases, the ability of the modified model to capture anisotropic features has been improved. Moreover, when compared with the mean velocity of large eddy simulations (LES), the root mean square error of the modified model is significantly lower than the original RANS model. Meanwhile, the modified model can better simulate flow field separation and fluctuation in the shear layer and has better prediction accuracy for the reattachment point and the mean velocity profile compared with the original RANS model. In addition, the modified model also improves the prediction accuracy for the mean pressure coefficient and mean friction coefficient of the underlying wall surface. The previously trained model is also directly performed for the modification computation of the two massive separation periodic hill flows. It is shown that the results simulated by the modified model and LES approach are more consistent in both trend and magnitude than the original RANS model and LES approach.

The wake produced by a model wind turbine is investigated using proper orthogonal decomposition (POD) of numerical data obtained by large eddy simulations at a diameter‐based Reynolds number . The blades are modeled employing the actuator line method and an immersed boundary method is used to simulate tower and nacelle. Two simulations are performed: one accounts only for the blades effect; the other includes also tower and nacelle. The two simulations are analyzed and compared in terms of mean flow fields and POD modes that mainly characterize the wake dynamics. In the rotor‐only case, the most energetic modes in the near wake are composed of high‐frequency tip and root vortices, whereas in the far wake, low‐frequency modes accounting for mutual inductance instability of tip vortices are found. When tower and nacelle are included, low‐frequency POD modes are present already in the near wake, linked to the von Karman vortices shed by the tower. These modes interact nonlinearly with the tip vortices in the far wake, generating new low‐frequency POD modes, some of them lying in the frequency range of wake meandering. An analysis of the mean kinetic energy (MKE) entrainment of each POD mode shows that tip vortices sustain the wake mean shear, whereas low‐frequency modes contribute to wake recovery. This explains why tower and nacelle induce a faster wake recovery.

Joint RANS/LES approach to premixed flames modelling in the context of the TFC combustion model

The basic philosophy of large eddy simulation (LES) is to explicitly compute only those large-scale motions that are directly affected by the boundary conditions and to model the small scales. LES has always been described as attractive for engineering computations because it is significantly less computer-intensive than direct numerical simulation (DNS), yet promises to be more accurate and robust than single point closures.

Accurate prediction of nitrogen oxides (NOX) emissions is of great importance in combustion simulations. This work proposes an improved model to predict NO distributions in turbulent flames, based on the large eddy simulation approach and flamelet-progress-variable turbulence combustion model. A separate table for NO reaction rate is constructed to account for both unsteady and nonadiabatic effects on NO production. Different from the existing models, the nonadiabatic effect is considered by specifying different enthalpy defects by a scaling factor in the flamelet calculations. Additionally, it is observed that the transient variation of NO reaction rate with NO concentration exhibits two linear stages. As a result, only three flamelet databases are included to describe the NO reaction rate in a transient process, thereby simplifying the flamelet table while maintaining model accuracy. The proposed NO prediction model is validated in large eddy simulations of turbulent combustion, including the classic Sandia D and the Sydney swirling SM1 flames. The calculated NO variations show good agreement with experimental data, demonstrating the applicability and accuracy of the proposed model.