A Novel Meshing Approach for Large Eddy Simulation

This work focuses on the development of efficient computational tools for the simulation of turbulent multiphase polydispersed flows. In terms of methodologies we focus here on the use of Large Eddy Simulation (LES) and Quadrature-Based Methods of Moments (QBMM). In terms of applications the work is finalised, in order to be applied in the future, to particle production processes (precipitation and crystallisation in particular). An important part of the work concerns the study of the flow field in a Confined Impinging Jets Reactor (CIJR), frequently used in particle production processes. The first part is limited to the comparison and analysis of micro Particle Image Velocimetry (μPIV) experiments, carried out in a previous work, and Direct Numerical Simulation (DNS), carried out in this thesis. In particular the effects of boundary and operating conditions are studied and the numerical simulations are used to understand the experimental predictions and demonstrate the importance of unavoidable fluctuations in the experimental inlets. This represents a preparatory work for the LES modelling of the CIJR. Before investigating the accuracy of LES predictions for this particular application, the model and the implementation are studied in a more general context, represented by a well-known test case such as the periodic turbulent channel flow: the LES model implementation in TransAT, the code used in this work, is compared with DNS data and with predictions of other codes. LES simulations for the CIJR, provided with the proper boundary conditions obtained by the previous DNS/μPIV study, are then performed and compared with experiments, validating the model in a more realistic test case. Since particle precipitation and crystallization often result in complex interactions between particles and the continuous phase, in the second part of the work particular attention has been paid in the modelling of the momentum transfer and the resulting velocity of the particles (relative to the fluid). In particular the possibility of describing poly-disperse fluid-solid systems with QBMM together with LES and Equilibrium Eulerian Model (EEM) is assessed. The study is performed by comparing our predictions with DNS Lagrangian data in the turbulent channel flow previously described, seeded with particles corresponding to a realistic Particle Size Distribution (PSD). The last part of the work deals with particle collisions, extending QBMM to the investigation of non-equilibrium flows governed by the Boltzmann Equation with a hard-sphere collision kernel. The evolution of the particle velocity distribution is predicted and compared with other methods for kinetic equations such as Lattice Boltzmann Method (LBM), Discrete Velocity Method (DVM) and Grad's Moment Method (GM). The overall results of this thesis can be extended to a broad range of other applications of single-phase, dispersed multiphase and non-equilibrium flows

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

In this paper, advanced wall-modeled large eddy simulation (LES) techniques are used to predict conjugate heat transfer processes in turbulent channel flow. Thereby, the thermal energy transfer process involves an interaction of conduction within a solid body and convection from the solid surface by fluid motion. The approaches comprise a two-layer RANS–LES approach (zonal LES), a hybrid RANS–LES representative, the so-called improved delayed detached eddy simulation method (IDDES) and a non-equilibrium wall function model (WFLES), respectively. The results obtained are evaluated in comparison with direct numerical simulation (DNS) data and wall-resolved LES including thermal cases of large Reynolds numbers where DNS data are not available in the literature. It turns out that zonal LES, IDDES and WFLES are able to predict heat and fluid flow statistics along with wall shear stresses and Nusselt numbers accurately and that are physically consistent. Furthermore, it is found that IDDES, WFLES and zonal LES exhibit significantly lower computational costs than wall-resolved LES. Since IDDES and especially zonal LES require considerable extra work to generate numerical grids, this study indicates in particular that WFLES offers a promising near-wall modeling strategy for LES of conjugated heat transfer problems. Finally, an entropy generation analysis using the various models showed that the viscous entropy production is zero inside the solid region, peaks at the solid–fluid interface and decreases rapidly with increasing wall distance within the fluid region. Except inside the solid region, where steep temperature gradients lead to high (thermal) entropy generation rates, a similar behavior is monitored for the entropy generation by heat transfer process.

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

DNS and LES of turbulent flow in a closed channel featuring a pattern of hemispherical roughness elements

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.

<p><span>Large-eddy simulation (LES) is an often used technique in the geosciences to simulate turbulent oceanic and atmospheric flows. In LES, the effects of the unresolved turbulence scales on the resolved scales (via the Reynolds stress tensor) have to be parameterized with subgrid models. These subgrid models usually require strong assumptions about the relationship between the resolved flow fields and the Reynolds stress tensor, which are often violated in reality and potentially hamper their accuracy.</span></p><p><span>In this study, using the finite-difference computational fluid dynamics code MicroHH (v2.0) and turbulent channel flow as a test case (friction Reynolds number Re<sub>τ</sub> 590), we incorporated and tested a newly emerging subgrid modelling approach that does not require those assumptions. Instead, it relies on neural networks that are highly non-linear and flexible. Similar to currently used subgrid models, we designed our neural networks such that they can be applied locally in the grid domain: at each grid point the neural networks receive as an input the locally resolved flow fields (u,v,w), rather than the full flow fields. As an output, the neural networks give the Reynolds stress tensor at the considered grid point. This local application integrates well with our simulation code, and is necessary to run our code in parallel within distributed memory systems.</span></p><p><span>To allow our neural networks to learn the relationship between the specified input and output, we created a training dataset that contains ~10.000.000 samples of corresponding inputs and outputs. We derived those samples directly from high-resolution 3D direct numerical simulation (DNS) snapshots of turbulent flow fields. Since the DNS explicitly resolves all the relevant turbulence scales, by downsampling the DNS we were able to derive both the Reynolds stress tensor and the corresponding lower-resolution flow fields typical for LES. In this calculation, we took into account both the discretization and interpolation errors introduced by the finite staggered LES grid. Subsequently, using these samples we optimized the parameters of the neural networks to minimize the difference between the predicted and the ‘true’ output derived from DNS.</span></p><p><span>After that, we tested the performance of our neural networks in two different ways:</span></p><ol><li><span>A priori or offline testing, where we used a withheld part of the training dataset (10%) to test the capability of the neural networks to correctly predict the Reynolds stress tensor for data not used to optimize its parameters. We found that the neural networks were, in general, well able to predict the correct values. </span></li> <li><span>A posteriori or online testing, where we incorporated our neural networks directly into our LES. To keep the total involved computational effort feasible, we strongly enhanced the prediction speed of the neural network by relying on highly optimized matrix-vector libraries. The full successful integration of the neural networks within LES remains challenging though, mainly because the neural networks tend to introduce numerical instability into the LES. We are currently investigating ways to minimize this instability, while maintaining the high accuracy in the a priori test and the high prediction speed.</span></li> </ol>

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.

The concept of an integrated rocket ramjet was initially introduced in the 1960s, leading to decades of research into dump combustor design [1]- [3] . The incoming air jets generate four corner vortices, while the dump section creates suction, collectively shaping the reactors. Therefore, the design of dump section is critical for a successful propulsion systems development. Parameters such as pressure drop, pressure fluctuations, and combustion efficiency must be evaluated across various flight regimes. Some of the known factors that affect overall ramjet engine performance include the size and efficiency of the reactors, dump effects, the dimensions of air intakes, angle, intake curvature, the flow separators in the intake flow stream, Reynolds number, and combustor dimensions [4]- [7] . The inherent inability to scale ramjet engine combustion chambers [8] poses a challenge when evaluating various geometrical configurations and operating points through experimentation. As a result, Computational Fluid Dynamics (CFD) becomes a crucial tool for advancing the development of ramjet propulsion engines. In this study, Large Eddy Simulation (LES) and Delayed Detached Eddy Simulation (DDES) techniques, coupled with the Steady Laminar Flamelet combustion model, are used to model a generic ramjet combustor which is introduced by Ristori et al. [9] . The experimental data used in context of the work is studied by many researchers to have more insight of combustion phenomenon in ramjet engine combustor [10], [11] . Grid convergence was ensured through the application of the Richardson extrapolation method [12] , and the grid quality was evaluated using the M-index defined by Pope [13] . A close agreement between both LES and DDES approaches, and experimental data was observed, confirming their accuracy in simulating the complex flow behaviour of the combustor. The findings reveal that both approaches provide good agreement with the experimental data regarding velocity profiles with only some minor discrepancies. However, a noteworthy distinction between DDES and LES is the behaviour of Turbulent Kinetic Energy and its distribution. The LES with WALE subgrid scale model tends to predict higher levels of Turbulent Kinetic Energy in the near-wall region compared to DDES, resulting in improved mixing and the formation of an early heated zone. This early combustion phase leads to a higher flow expansion and hence an increase in axial velocity, causing LES WALE to overestimate axial velocity at x=270 mm, whereas DDES predictions align slightly better with the experimental data. Both DDES and LES WALE simulations tend to overestimate combustion efficiency compared with measurements. However, the total pressure loss is well predicted by both approaches with only a discrepancy of lower than 0.3% compared to measured data that is well within the measurement error range. It's important to note that the overprediction of combustion efficiency remains an open issue, as discussed by other researchers also [11] . Future simulations could be extended to calculate heat loss to the walls what could be an explanation for the overprediction of combustion efficiency. The present research demonstrates that the Steady Laminar Flamelet model is capable of predicting flow structures in a ramjet combustor under reacting conditions. Within LES simulations, the prediction of turbulent kinetic energy within the near-wall region was enhanced, resulting in faster mixing and an overestimation of combustion efficiency. Even closer agreement with experimental data was achieved in DDES predictions, highlighting the effectiveness of employing eddy simulation with near-wall modeling when wall resolution is unfeasible. This approach not only demonstrates better CSP 118-2 agreement between DDES predictions and experimental data but also showcases its efficiency in reducing the need for excessively refined meshes in the study of dump-type low subsonic combustors.

Introduction. The reduction in beach width due to erosion is a significant issue that can either be mitigated or exacerbated by coastal protection structures. Modelling breaking waves near the coast and around coastal structures can be used to determine their impact on the dynamics of the coastal zone. The objective of this study is to model and analyze the dynamics of turbulent structures around a single breakwater, obtained using two turbulence modelling schemes: RANS and LES.Materials and Methods. Turbulence induced by breaking waves was investigated. The modelling was based on bathymetric measurements conducted along the Azov Sea coast and a three-dimensional wave hydrodynamics model supplemented with various turbulence calculation configurations.Results. Modelling results of wave processes generating turbulent flows in the presence of coastal protection structures using different turbulence models were obtained. Results obtained based on Reynolds-averaged Navier-Stokes (RANS) equations are compared with the results of Large Eddy Simulation (LES) approach with Smagorinsky dynamic subgrid-scale model (DSM).Discussion and Conclusions. The results showed that wave heights simulated by LES were higher than those simulated by RANS in the front and leeward regions of the coastal protection structure and were lower in its upper part. Thus, according to LES, a greater amount of wave energy was preserved after passing over the breakwater. Velocity vectors of the water medium showed the formation of a vortex when LES was used, whereas no evidence of such turbulent vortices was detected in the case of RANS, confirming the better performance of LES for turbulence modelling in the coastal zone. According to the presented results, LES is the preferred tool for generating turbulence under incoming wave conditions in engineering practices.

With the development of computational power, large eddy simulation (LES) method is increasingly used in simulating complex flow. However, there still exist many factors affecting the LES quality and appropriate mesh resolution is among one of them. This work aims to develop an automatic procedure to refine the LES mesh by combining adaptive mesh refinement (AMR) and LES quality criteria. An LES refinement criterion is developed by estimating the proper grid length scale which meets the accuracy requirement of LES method. With this criterion, the baseline mesh is automatically refined with the AMR method. In this work, an efficient one-shot refinement strategy is also proposed to reduce the overall simulation time. Current AMR-based LES method is verified with the typical LES test case about the flow past circular cylinder at ReD = 3900. Results show that the automatically refined mesh provides systematically better agreement with experimental results and with current method the balance between accuracy and computational expense for LES can be obtained.

The log-layer mismatch arises when a Reynolds-averaged Navier-Stokes (RANS) model is blended with a large-eddy simulation (LES) model in a hybrid fashion. Numerous researchers have tackled this problem by simulating a turbulent channel flow. We show that the log-layer mismatch in hybrid RANS-LES can be reduced substantially by splitting the mean pressure gradient term in the wall-normal direction in a manner that keeps the mass flow rate constant. Additionally, an analysis of the wall-normal variation of the friction velocity shows a constant value is recovered in the resolved LES region different than the value at the wall. Second-order turbulence statistics agree very well with direct numerical simulation (DNS) benchmarks when scaled with the friction velocity extracted from the resolved LES region. In light of our findings, we suggest that the current convention to drive a turbulent periodic channel flow with a uniform mean pressure gradient be revisited in testing eddy-viscosity-based hybrid RANS-LES models as it appears to be the culprit behind the log-layer mismatch.

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