High-fidelity Large-eddy Simulation Research Articles

A numerical study on suspended sediment transport in a partially vegetated channel flow

Turbulent structures generated by vegetation patches play a dominant role in the dispersion of suspended sediment, which in turn is of great significance for ecosystem cycling and river geomorphology development. High fidelity Large Eddy Simulations (LES) coupled with the Discrete Phase Method (DPM) were used to explore the particle distribution and its variance (the non-uniformity in temporal and spatial space) in a partially vegetated straight channel. The novel findings and conclusions are outlined here. Firstly, the contour of the vertical vorticity component coincides well with particle preferential gatherings in the outer edge of the mixing layer in the near-bed region. Large-scale turbulent structures grow in mixing layer along the side of a vegetation patch (VP), which deplete particles away from the mixing layer into the neighbouring region. Also, higher vegetation densities (Dn) promote this depletion trend. Secondly, the Probability Density Function (PDF) and its variance were defined to quantify these phenomena, illustrating that the VP continuously interrupts the flow condition and promotes higher non-uniformity of particle distribution among the vegetated and non-vegetated regions. The variance of the PDF in the non-vegetated region is significantly higher than that in the neighbouring vegetated region located in the same streamwise location. The particle parcels are highly unevenly located along the periphery of the large eddies and are exchanged by the mixing flow between the non-vegetated and vegetated regions. Finally, the vertical entrainment of particles occurs in the vegetated region of the present cases. This is because the horseshoe structures provide an upwards velocity for the current Dn conditions (Dn < 0.1) and an increase of Dn (Dn < 0.1) accelerates the upward suspension. These findings complete our understanding of particles’ transportation in both spanwise and vertical directions.

Towards multiscale modeling of ocean surface turbulent mixing using coupled MPAS-Ocean v6.3 and PALM v5.0

Abstract. A multiscale modeling approach for studying the ocean surface turbulent mixing is explored by coupling an ocean general circulation model (GCM) MPAS-Ocean with the Parallelized Large Eddy Simulation Model (PALM). The coupling approach is similar to the superparameterization approach that has been used to represent the effects of deep convection in atmospheric GCMs. However, the focus of this multiscale modeling approach is on the small-scale turbulent mixing and their interactions with the larger-scale processes in the ocean, so that a more flexible coupling strategy is used. To reduce the computational cost, a customized version of PALM is ported on the general-purpose graphics processing unit (GPU) with OpenACC, achieving 10–16 times overall speedup as compared to running on a single CPU. Even with the GPU-acceleration technique, a superparameterization-like approach to represent the ocean surface turbulent mixing in GCMs using embedded high fidelity and three-dimensional large eddy simulations (LESs) over the global ocean is still computationally intensive and infeasible for long simulations. However, running PALM regionally on selected MPAS-Ocean grid cells is shown to be a promising approach moving forward. The flexible coupling between MPAS-Ocean and PALM allows further exploration of the interactions between the ocean surface turbulent mixing and larger-scale processes, as well as future development and improvement of ocean surface turbulent mixing parameterizations for GCMs.

Analysis and Interpretation of Data-Driven Closure Models for Large Eddy Simulation of Internal Combustion Engine

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;We present an automatic data-driven machine learning (ML) approach for the development, evaluation and interpretation of deep neural networks (DNNs) for turbulence closures and demonstrate their usage in the context of cold-flow large-eddy simulation (LES) of the four-stroke Darmstadt engine using an open-source compressible multi-dimensional CFD solver OFICE, in a hybrid PDE-ML framework. Rather than explicitly using canonical formulations of closure terms, these DNNs robustly discover the functional relationships between the large-scale features of the resolved flow (cell Re, strain and rotation rate tensors etc.) obtained by solving the Navier Stokes to the small-scale unresolved terms. Experimentally validated high-fidelity LES solutions of the engine at different crank angles are utilized as the ground truth to train the DNN based closure models. Since optimizing these DNNs can be a laborious process for scientific datasets, and often require specialized expertise, we propose a Bayesian optimization framework that automatically determines the best set of network parameters, including the architecture and training hyperparameters - batch size, regularization etc. for optimum performance. We compare and contrast various networks for their effectiveness in an &lt;i&gt;a-priori&lt;/i&gt; testing setting. Finally, the best ‘learnt’ network is integrated with the open-source CFD solver (OFICE), and solutions are obtained over several injection cycles. These experiments reveal that the DNN models temporally track resolved scalar variance with a good accuracy. Additionally, we interpret the artificial neural networks with sensitivity analysis to determine the relevant large-scale features for the learning process.&lt;/div&gt;&lt;/div&gt;

Universal Wind Profile for Conventionally Neutral Atmospheric Boundary Layers.

Conventionally neutral atmospheric boundary layers (CNBLs), which are characterized with zero surface potential temperature flux and capped by an inversion of potential temperature, are frequently encountered in nature. Therefore, predicting the wind speed profiles of CNBLs is relevant for weather forecasting, climate modeling, and wind energy applications. However, previous attempts to predict the velocity profiles in CNBLs have had limited success due to the complicated interplay between buoyancy, shear, and Coriolis effects. Here, we utilize ideas from the classical Monin-Obukhov similarity theory in combination with a local scaling hypothesis to derive an analytic expression for the stability correction function ψ=-c_{ψ}(z/L)^{1/2}, where c_{ψ}=4.2 is an empirical constant, z is the height above ground, and L is the local Obukhov length based on potential temperature flux at that height, for CNBLs. An analytic expression for this flux is also derived using dimensional analysis and a perturbation method approach. We find that the derived profile agrees excellently with the velocity profile in the entire boundary layer obtained from high-fidelity large eddy simulations of typical CNBLs.

Can Water Dilution Avoid Flashback on a Hydrogen-Enriched Micro-Gas Turbine Combustion?—A Large Eddy Simulations Study

Abstract Considering the growing interest in Power-to-Fuel, i.e., production of H2 using electrolysis to store excess renewable electricity, combustion-based technologies still have a role to play in the future of power generation. Especially in a decentralized production with small-scale cogeneration, micro-Gas Turbines (mGTs) offer great advantages related to their high adaptability and flexibility, in terms of operation and fuel. Hydrogen (or hydrogen enriched methane) combustion is well-known to lead to flame and combustion instabilities. The high temperatures and reaction rates reached in the combustor can potentially lead to flashback. In the past, combustion air humidification (i.e., water addition) has proven effective to reduce temperatures and reaction rates, leading to significant NOx emission reductions. Therefore, combustion air humidification can open a path to stabilize hydrogen combustion in a classical mGT combustor. However accurate data assessing the impact of humidification on the combustion is still missing for real mGT combustor geometries and operating conditions. In this framework, this paper presents a comparison between pure methane and hydrogen enriched methane/air combustions, with and without combustion air humidification, in a typical mGT combustion chamber (Turbec T100) using Large Eddy Simulations (LES) analysis. In a first step, the necessary minimal water dilution, to reach stable and low emissions combustion with hydrogen, was assessed using a one-dimensional (1D) approach. The one-dimensional unstretched laminar flame is computed for both pure methane (reference case) and hydrogen enriched methane/air combustion cases. The results of this comparison show that, for the hydrogen enriched combustion, the same level of flame speed as in the reference case can be reached by adding 10% (in mass fraction) of water. In a second step, the feasibility and flexibility of humidified hydrogen enriched methane/air combustion in an industrial mGT combustor have been demonstrated by performing high fidelity LES on a 3D geometry. Results show that steam dilution helped to lower the reactivity of hydrogen, and thus prevents flashback, enabling the use of hydrogen blends in the mGT at similar CO levels, compared to the reference case. These results will help to design future combustor toward more stability.

Supersonic Turbulent Boundary-Layer Separation Control Using a Morphing Surface

Separated flows arising due to shock-wave/turbulent boundary-layer interactions can cause problematic low-frequency unsteadiness with potentially severe structural response. High-fidelity large-eddy simulations are employed to examine surface morphing as a way to reduce the size of the separation region, and thus favorably alter the unsteadiness characteristics. The configuration considers a turbulent Mach 2.7 flow at a Reynolds number of subjected to an impinging shock system with a pressure ratio of , which results in separation and the presence of structurally relevant low-frequency unsteadiness. The control surface, centered about the shock impingement location and extending over the separation region, is allowed to deform under material property-based realizability constraints until an asymptotic state is achieved. The criterion for deformation uses a measure proportional to the directional surface shear stress. At an asymptotic state, the deformed surface reveals a shape consistent with aerostructural optimization and a maximum height of . Control mitigates the sharp initial pressure gradient of the uncontrolled flow to delay and reduce separation extent (by 50%) with diminution of low-frequency content and turbulent kinetic energy. Modal decomposition highlights these effects in the energy content of the prominent modes. Morphing may thus provide a means to adjust the local surface deflection in a manner that reduces some of the problems associated with turbulent separation.

On the impact of fuel injection angle in Euler–Lagrange large eddy simulations of swirling spray flames exhibiting thermoacoustic instabilities

This study deals with the fundamental problem of combustion dynamics in gas turbine combustors operating with liquid fuel. In this framework the present work proposes the study of an academic liquid fueled combustor sensitive to thermoacoustic instabilities, simulated via high-fidelity Large Eddy Simulations. The experimental setup addressed is SICCA-spray from EM2C laboratory featuring both stable and unstable flames depending on the combustion chamber length. The proposed analysis, based on the Euler-Lagrange modeling approach, studies the impact of the spray injection angle θ on both the stable flame and the triggering of the longitudinal combustor acoustic mode when using a longer quartz tube. For the liquid injection modeling, the FIM-UR semi-empirical model is adopted with three different θ values: θ=35∘,45° and 60°. In stable conditions, the spray angle is proven to have a negligible impact on the flame anchoring point, however, the mean flame length and fuel distribution are found to be slightly modified by the velocity at which droplets enter the combustion chamber. For the thermoacoustically unstable conditions, two well-established stable limit cycles with the same frequency and similar amplitudes are obtained when fuel is injected at θ=45∘ and 60°. Contrarily, the system stabilizes when θ=35∘ pointing to the importance of the dynamics of the liquid film layer formed inside the injector for this setup. Likewise, this liquid film layer dynamics and its modeling appear critical as already suggested by previous studies on the same configuration. The detailed analysis of the thermoacoustically unstable different predictions is then performed through the investigation of the spatial fields of the local Rayleigh index obtained following the novel extension in the frequency domain of the Rayleigh criterion complemented by the application of Dynamic Mode Decomposition. It confirms that the injection angle of the liquid spray has a significant effect on the thermoacoustic response of the system. Indeed the influence of θ on the dynamics of the liquid fuel when entering the combustion chamber is proven to have an impact on the synchronization mechanism governing the liquid phase with respect to acoustics sustaining the observed limit cycles. More specifically, couplings at the liquid phase level are evidenced by introducing two novel indices correlating the fluctuations of liquid fuel volume fraction and evaporation rate with pressure.

Industry-Relevant Implicit Large-Eddy Simulation of a High-Performance Road Car via Spectral/hp Element Methods

We present a successful deployment of high-fidelity large-eddy simulation (LES) technologies based on spectral/$hp$ element methods to industrial flow problems, which are characterized by high Reyn...

Large eddy simulation of a linear turbine cascade with a trailing edge cutback

In this work, the effects of trailing edge (TE) cutback on the turbulent flow field and the aerodynamic loss of a turbine blade are investigated by Large-Eddy-Simulation (LES). A high-fidelity LES code was first developed based on a high-order finite difference method and applied to the simulation. The effects of the TE cutback on the blade surface boundary layer, pressure distribution, and loss generation are then discussed on the basis of time-mean flow fields of LES. The results represent that the cutback changed the boundary layer thickness just upstream of the TE and the base pressure around the TE, resulting in larger aerodynamic loss. Next, the time-dependent flow dynamics in the cascade is investigated. The results indicate that the dominant pressure fluctuation after the blade was influenced by the cutback. Furthermore, the phase-locked flow field is analyzed to reveal the flow dynamics responsible for the pressure fluctuation. Finally, the LES approach could clarify the underlying mechanisms of performance degradation of a turbine blade that caused by TE cutback.

Large eddy simulation of natural convection heat transfer and fluid flow around a horizontal cylinder

Natural convection around a single horizontal cylinder has been extensively studied for heat transfer characteristics, but when coupled with fluid flow, the laminar-to-turbulent transition in buoyant plume poses severe challenge on modelling fidelity and physical interpretability. To address this challenge, this paper conducts detailed verification, validation and analysis of high-fidelity large eddy simulation (LES) for an unconfined horizontal cylinder in water with a Rayleigh number of 8 × 107, complemented by Reynolds-Averaged Navier-Stokes (RANS) computations. To the best of the authors' knowledge, this is the first LES study with acceptable accuracy as validate by experimental data for buoyant plume above a single horizontal cylinder. It is found that LES is far more sensitive to mesh resolution and boundary condition setting than RANS. An alarm is set for the use of periodic condition in LES on lateral boundaries of computational domain due to its inferior accuracy than RANS with transition SST model. The finely-tuned LES with pressure condition on lateral boundaries shows satisfactory agreement with experimental data in terms of heat transfer on cylinder surface and buoyant plume velocity, based on which new physical insight on transitional behavior of thermal plume is obtained. It is found that after leaving the cylinder, buoyant plume is laminar and accelerates, subject to work input from buoyancy force, while its temperature keep decreasing due to heat loss to atmosphere. Flow instability appears first in upward velocity at a streamwise Grashof number of 1.5 × 108, where transition to turbulence onsets. Thermal plume continues to accelerate until it begins to sway horizontally, where energy dissipation into turbulence becomes the major loss mechanism of mean flow energy. Thus, cross-stream diffusivity is augmented notably due to turbulent stresses, leading to smoothing of transverse velocity distribution and reduction of transversely-averaged mean kinetic energy. Transversely-averaged turbulent kinetic energy keeps increasing in transitional regime until the streamwise Grashof number reaches 7 × 109 and then declines to approach an asymptotic value, signifying the end of transition. Overall speaking, buoyancy work dominates the change in mean flow energy, while mean shear outweighs buoyancy in producing turbulent kinetic energy.

High-fidelity simulations and field measurements for characterizing wind fields in a utility-scale wind farm

Characterizing wind farm flow fields at high temporal and spatial resolutions is critical prerequisite for the optimal design and operation of utility-scale wind farms and for reducing the levelized cost of energy. However, due to the large disparity of underlying scales, measurements or simulations alone cannot provide high resolution wind fields, which are informed by and account for the effect of both large scale (i.e. hour, day, month and year) and small scale (i.e. second and minute) site-specific variations in the atmosphere. We explore the feasibility of integrating field measurements and high-fidelity large-eddy simulation (LES) to characterize the wind field in a utility-scale wind farm while accounting for flow phenomena across multiple temporal scales. Specifically, we employ field measurements to characterize the monthly wind speed and wind direction distributions and investigate the wind characteristics in turbine wakes. It was found that the probability density function (PDF) of the wind speed in turbine wakes can be reasonably represented using the Weibull distribution but with shape factors smaller than those not in the wake. LES of the wind farm under statistically steady inflow is subsequently carried out for one wind direction. The LES predictions are compared with the measured data conditionally averaged based on the wind speed, wind direction and the root-mean-square of wind speed fluctuations over time intervals of 30 min. Good agreement is obtained for both mean wind speed and turbulence intensity. The present work shows the possibility of integrating field measurements and high-fidelity simulations for improved characterization of the site-specific wind fields in utility-scale wind farms.

Two Corrections for Turbulent Kinetic Energy Generated by Wind Farms in the WRF Model

AbstractAs wind farms grow in number and size worldwide, it is important that their potential impacts on the environment are studied and understood. The Fitch parameterization implemented in the Weather Research and Forecasting (WRF) Model since version 3.3 is a widely used tool today to study such impacts. We identified two important issues related to the way the added turbulent kinetic energy (TKE) generated by a wind farm is treated in the WRF Model with the Fitch parameterization. The first issue is a simple “bug” in the WRF code, and the second issue is the excessive value of a coefficient, called CTKE, that relates TKE to the turbine electromechanical losses. These two issues directly affect the way that a wind farm wake evolves, and they impact properties like near-surface temperature and wind speed at the wind farm as well as behind it in the wake. We provide a bug fix and a revised value of CTKE that is one-quarter of the original value. This 0.25 correction factor is empirical; future studies should examine its dependence on parameters such as atmospheric stability, grid resolution, and wind farm layout. We present the results obtained with the Fitch parameterization in the WRF Model for a single turbine with and without the bug fix and the corrected CTKE and compare them with high-fidelity large-eddy simulations. These two issues have not been discovered before because they interact with one another in such a way that their combined effect is a somewhat realistic vertical TKE profile at the wind farm and a realistic wind speed deficit in the wake. All WRF simulations that used the Fitch wind farm parameterization are affected, and their conclusions may need to be revisited.

Stabilization mechanisms of CH4 premixed swirled flame enriched with a non-premixed hydrogen injection

High-fidelity Large Eddy Simulations (LES) are performed to study the effect of hydrogen injection on a lean turbulent CH4/Air premixed flame. An Analytically Reduced Chemistry (ARC) mechanism is used to achieve a detailed description of CH4/Air-H2 chemistry. First, a validation of this kinetic scheme against the detailed GRI-Mech 3.0 mechanism is presented considering both simplified and complex transport properties. When hydrogen is added to the mixture, large variations of the mixture Prandtl and of the N2 Schmidt numbers are observed depending on the local species concentrations, features that are missed by simplified models. LES is then applied to study the structure and stabilization mechanisms of a lean (ϕ = 0.8) premixed CH4/Air swirled flame enriched with hydrogen by using different transport modeling strategies. First, the fully premixed CH4/Air case is considered and results are found to validate the LES approach. In agreement with experiments, a classical V-shape flame is stabilized in the low-velocity region near the flame holder created by a central recirculation zone (CRZ). Then, hydrogen enrichment is achieved injecting 2% of the CH4 thermal power with a central fuel injection lance. Both premixed and diffusion flame branches are present in this case, impacting flame stabilization and flame angle. The flame root of the main premixed flame is stabilized by a diffusion flame kernel created by the injected hydrogen reacting with the oxygen in excess of the premixed stream. Moreover, the H2 consumed with the remaining oxygen in burnt gases leads to the formation of a second flame branch inside the CRZ which is responsible of an increase of the flame angle. Given the high concentration of hydrogen, an impact of the molecular transport models is observed on the flame lift-off height highlighting the importance of using complex transport properties in any LES involving hydrogen combustion.

Design Space Exploration of Turbulent Multiphase Flows Using Machine Learning-Based Surrogate Model

This study focuses on establishing a surrogate model based on machine learning techniques to predict the time-averaged spatially distributed behaviors of vaporizing liquid jets in turbulent air crossflow for momentum flux ratios between 5 and 120. This surrogate model extends a previously developed Gaussian-process-based framework applicable to laminar flows to accommodate turbulent flows and demonstrates that in addition to detailed fields of primitive variables, second-order turbulence statistics can also be predicted using machine learning techniques. The framework proceeds in 3 steps—(1) design of experiment studies to identify training points and conducting high-fidelity calculations to build the training dataset; (2) Gaussian process regression (supervised training) for the range of operating conditions under consideration for gaseous and dispersed phase quantities; and (3) error quantification of the surrogate model by comparing the machine learning predictions with the truth model for test conditions (i.e., conditions not used for training). The framework was trained using data generated by high-fidelity large eddy simulation (LES)-based calculations (also referred to as the truth model), which solves the complete set of conservation equations for mass, momentum, energy, and species in an Eulerian reference frame, coupled with a Lagrangian solver that tracks the dispersed phase. Simulations were conducted for the range of momentum flux ratios between 5 and 120 for liquid water injected into crossflowing air at a pressure of 1 atm and temperature of 600 K. Results from the machine-learned surrogate model, also called emulations, were compared with the truth model under testing conditions identified by momentum flux ratios of 7 and 40. L1 errors for time-averaged field quantities, including velocity magnitudes, pressure, temperature, vapor fraction of the evaporated liquid, and turbulent kinetic energy in the gas phase, and spray penetration and Sauter mean diameters in the dispersed phase are reported. Speedup of 65 was achieved with this emulator when compared against LES simulation of the same test conditions with errors for all quantities below 14%, thus demonstrating the potential benefits of using machine learning techniques for design space exploration of devices that are based on turbulent multiphase fluid flows. This is the first effort of its kind in the literature that demonstrates the application of machine learning techniques on turbulent multiphase flows.

The effect of dynamic near-wake modulation on utility-scale wind turbine wake development

High-resolution field-scale experiments using flow visualization with natural snowfall and high-fidelity large eddy simulations are combined to investigate the effect of dynamic turbine operation and atmospheric conditions on wind turbine wake mixing and recovery in the wake of a 2.5 MW wind turbine. Instantaneous near-wake expansion and deflection in response to changes in blade pitch and wind direction, termed dynamic wake modulation, is quantified using both techniques, demonstrating excellent agreement. The simulations are used to extend these results by calculating the energy flux into the wake 7 rotor diameters downstream, showing that dynamic turbine-atmospheric interactions enhance mixing in the far-wake. This finding is exhibited under both uniform and turbulent inflow conditions. Under turbulent flow, a synergistic relationship is also observed between dynamic wake modulation and wake meandering, as wake recovery can be further accelerated when the two phenomena occur together. The results of this study have implications for the development of more realistic far-wake models that include the significant impact of dynamic wake modulation on wake mixing and development. Additionally, the findings from the current study can be used to develop advanced control algorithms to speed up wake breakdown and recovery, further improving wind farm efficiency.

Numerical Investigation of Combustion Instabilities in a Single-Element Lean Direct Inject Combustor Using Flamelet Based Approaches

Abstract In this paper, high-fidelity large eddy simulations (LES) along with flamelet-based combustion models are assessed to predict combustion dynamics in low-emission gas turbine combustor. A model configuration of a single-element lean direct injection (LDI) combustor from Purdue University (Huang et al., 2014, “Combustion Dynamics Behavior in a Single-Element Lean Direct Injection (LDI) Gas Turbine Combustor,” 50th AIAA/ASME/SAE/ASEE Joint Propulsion Conference, Cleveland, OH, July 28–30.) is used for the validation of simulation results. Two combustion models based on the flamelet concept, i.e., steady diffusion flamelet (SDF) model and flamelet generated manifold (FGM) model are employed to predict combustion instabilities. Simulations are carried out for two equivalence ratios of φ = 0.6, and 0.4. The results in the form of mode shapes, peak to peak pressure amplitude and power spectrum density (PSD) are compared with the experimental data of Huang et al. (2014, “Combustion Dynamics Behavior in a Single-Element Lean Direct Injection (LDI) Gas Turbine Combustor,” 50th AIAA/ASME/SAE/ASEE Joint Propulsion Conference, Cleveland, OH, July 28–30.). The effect of variation in the time-step size hence acoustic courant number is studied. Further, two numerical solver options, i.e., pressure-based segregated solver and pressure-based coupled solver, are used to understand their effect on the solution convergence regarding the number of time-steps required to reach the limit cycle of the pressure oscillations. A truncated (half) domain simulation is performed by applying an appropriate acoustic impedance boundary condition at the truncated location. Overall, the simulation results compare well with the experimental data and trends are captured accurately in all simulations. It builds confidence in flamelet-based combustion models for the use in combustion instability modeling which is traditionally done using finite rate chemistry models based on reduced kinetics.

On the genesis and evolution of barchan dunes: Hydrodynamics

Barchans are an important signature of turbulent atmospheric and aquatic flows on parts of the Earth’s surface where the supply of sediments is scarce. Khosronejad and Sotiropoulos [“On the genesis and evolution of barchan dunes: Morphodynamics,” J. Fluid Mech. 815, 117–148 (2017)] demonstrated that high-fidelity hydro-morphodynamic large-eddy simulation (LES) can replicate sub-aqueous barchan fields exhibiting the geometric features and morphodynamic interactions observed in nature. Herein, we first validate the ability of our LES method to simulate mean flow and turbulence statistics over a frozen barchan dune created in a control laboratory experiment. We then analyze our high-fidelity LES datasets to elucidate the hydrodynamic phenomena that drive the previously identified morphodynamic interactions at various stages of subaqueous barchan dune evolution, from flatbed to quasi-equilibrium. We uncover and quantify the hydrodynamic mechanisms that cause (i) the initiation of crescent microfeatures on the initial flatbed; (ii) the development of three-dimensional barchan dunes; and (iii) several other phenomena that occur during the barchan field maturation, such as the birth of new small barchans and the exposure of the underlying bedrock in the wake of the barchans. Defining a dimensionless timescale, i.e., the saturation timescale, as a function of the saturation length scale, we attempt to categorize for the first time various temporal stages of barchan field development. We show that the barchan field has specific characteristics corresponding to each of the barchan stage developments in terms of both the flow field and the bed topology. Comparing the simulation results of transverse and barchan dunes, we illustrate that the two dune types have similar topographic and hydrodynamics characteristics until bedrock exposure occurs.

Recurrence analysis and time extrapolation of a confined turbulent jet using modal decomposition

We investigated the long-term dynamics of a turbulent, submerged jet at Re = 16 400 to develop a strategy for data-assisted, fast calculations of passive species transport. We obtained our data from high-fidelity large eddy simulations LES, which we validated against in-house particle image velocimetry measurements. The flow was split into coherent and incoherent fields using the method of proper orthogonal decomposition (POD). Depending on the number of POD modes to construct coherent velocity fields, different patterns in the recurrence plot of the system were found. For low mode numbers, line segments parallel to the main diagonal were present, which indicated that close states evolved similarly for a finite duration. Strong turbulent fluctuations in the original velocity fields, on the other hand, hid any large-scale recurrences and caused a structureless recurrence statistics. Using an iterated method of analogs, we time-extrapolated a short time series of coherent, distinctly recurring velocity fields of 50 s to 250 s and performed a study of species transport. We found that coherent dynamics alone could not reproduce LES results due to the lack of turbulent, small-scale fluctuations, but already a small set of incoherent flow fields sufficed to cure this shortcoming considerably. Surprisingly, time extrapolation of the original database without decomposition and without any obvious recurrences led to the best results in very close agreement with LES but with high demands regarding memory. Our data-assisted simulations outperformed LES on the same computational mesh by a speed-up factor of 15.

Analysis of in-cylinder pressure oscillation and its effect on wall heat transfer

In-cylinder pressure oscillations in internal combustion engines have been associated with increased heat losses and damages to the engine components. The links between the acoustic waves and the increased heat transfer (and potentially ensuing engine damages) have not yet been well understood. In this study, a high-fidelity large eddy simulation model incorporating an auto-ignition model is used to simulate the combustion process and the associated pressure oscillation at various engine operating conditions. The study serves to develop a better understanding of the acoustic waves in a combustion chamber and their effect on wall heat transfer. First, a simplified model of the pressure oscillations is proposed and shown to accurately characterize the pressure in the combustion chamber. Second, the simplified pressure model and acoustic theory are leveraged to develop a model of the in-cylinder gas velocities. Finally, a heat transfer model is presented that takes into consideration the pressure/velocity oscillations and the inherent acoustic properties of the trapped gas. The increase in heat transfer is shown to primarily stem from an increased heat transfer coefficient due to the velocity oscillations of the trapped gas. The results are consistent with previously observed experimental measurements of the heat flux in the presence of pressure oscillations.

Quantifying turbulence model uncertainty in Reynolds-averaged Navier–Stokes simulations of a pin-fin array. Part 2: Scalar transport

The accuracy of Reynolds-averaged Navier-Stokes results for turbulent scalar transport are affected by epistemic uncertainty in the Reynolds stress model in two ways: by altering the mean velocity field that advects the scalar, and by altering the inputs required for scalar flux models. We investigate these effects by propagating uncertainty in the Reynolds stress model to the prediction of scalar quantities in simulations of a pin-fin heat exchanger. The Reynolds stress model uncertainty is quantified by perturbing the anisotropy of the predicted stress tensor towards the three limiting realizable states. This uncertainty is then propagated to the scalar turbulence transport via the conservation law for the mean scalar and the turbulent scalar flux model. We consider three different scalar flux models that explicitly take the Reynolds stresses as input, and evaluate the performance of the models by verifying if high-fidelity large eddy simulation results are encompassed by the model predictions. The results indicate that the predicted uncertainty depends on both the general level of momentum transport and the most-relevant stress component, which is affected by the anisotropy perturbations. The predictions provide a similar bounding behavior for the overall temperature field as for the momentum field, but fail in bounding the local heat transfer rates in several locations. The bounding behaviors are further analyzed in terms of the predicted uncertainty in the flux magnitude, direction, and divergence to identify opportunities for further improvement of the proposed methods.