Large-scale Flow Features Research Articles

A multi-directional redundant 3D-LPT system for ship–flight–deck wind interactions

In the past years, volumetric velocimetry measurements with helium-filled soap bubbles as tracer particles have been introduced in wind tunnel experiments and performed at large-scale, enabling the study of complex body aerodynamics. A limiting factor is identified in the field of wind engineering, where the flow around ships is frequently investigated. Considering multiple wind directions, the optical access for illumination and 3D imaging rapidly erodes the measurement regions due to shadows and incomplete triangulation. This work formalizes the concepts of volumetric losses and camera redundancy, and examines the performance of multi-directional illumination and imaging for monolithic and partitioned modes. The work is corroborated by experiments around a representative ship model. The study shows that a redundant system of cameras yields the largest measurement volume when partitioned into subsystems. The 3D measurements employing two illumination directions and seven cameras, yield the time-averaged velocity field around the ship. Regions of flow separation and recirculation are revealed, as well as sets of counter-rotating vortices in several stations from the ship bow to the flight–deck. The unsteady regime at the flight–deck is examined by proper orthogonal decomposition, indicating that the technique is suited for the analysis of large-scale unsteady flow features.

Extinction of buoyant turbulent non-premixed flames under reduced oxygen concentrations

Local and global extinction of 10 kW buoyant turbulent non-premixed flames of methane from a 13.7 cm diameter burner under oxygen concentrations (OCs) from 20.9 % to 12 % are investigated using a combination of OH* chemiluminescence imaging and exhaust-gas sampling. Local flame extinction, indicated by holes or discontinuities in the OH* images, is only observed at OC lower than 17 %. For OC below 16 %, large-scale turbulent flow dynamics causes rapid creation of large extinction holes that do not reclose, and the overall combustion efficiency (η) decreases rapidly as local extinction becomes more probable. Direct observation of local extinction in buoyant turbulent flames provides important physical insights and validation data for models of extinction and re-ignition by distinguishing their respective contributions to η. We observe that local extinction events are associated with large-scale flow features, leading us to hypothesize that extinction behavior correlates with resolved-scale strain rates from large-eddy simulation (LES) in excess of the laminar extinction limit. This idea is investigated by performing LES for the target flame, extracting strain-rate statistics on the flame surface, and comparing these to both the extinction limits for canonical counterflow diffusion flames and to the experimentally observed extinction behavior. Results show that the cumulative distribution of turbulent flame strain rates up to the laminar extinction limit closely follows the measured OC dependence of η. This approach to η works well for different OCs and other fuels such as propane and ethylene, which suggests great potential for the development of computationally efficient extinction models for fire suppression.

A parameter-free LES model for anisotropic mesh adaptivity

Balancing accuracy and computational cost is a challenge in the modelling of turbulent flows. A widely used method for turbulence modelling is large–eddy simulation (LES). LES allows one to describe large scale flow features at a reasonable computational cost compared to the more accurate direct numerical simulation (DNS), making it a popular choice for engineering applications. One strategy to balance accuracy and cost with LES is through the use of mesh adaptivity, which allows the degrees of freedom in a problem to be reduced by changing spatial discretisation. However, mesh adaptivity can affect accuracy when using the standard Smagorinsky LES model with an implicit filter, considering that the parameter Cs is highly dependent on the filter width, which depends on mesh resolution. This work is aimed to develop an LES model that does not require any user–defined parameters and is suitable for mesh adaptivity with implicit filter. In this study we introduce a parameter–free LES model incorporating an anisotropic eddy–viscosity formulation combined with anisotropic mesh adaptivity. In our model, the parameter Cs in the eddy–viscosity formulation of the Smagorinsky model, is replaced by a function that evaluates the relative location of turbulence fluctuations in each element with respect to the turbulence spectrum inertial range. The anisotropic formulation of the eddy–viscosity allows for the application of an appropriate filter width in different directions, improving accuracy. Additionally, the mesh adaptivity algorithm assesses the local turbulence fluctuations via local Reynolds number and vortex identification criteria. This assessment leads to the refinement of regions with higher turbulence fluctuations down to the smallest scale limit in the inertial range in the corresponding direction, and also leads to the coarsening of regions without turbulence fluctuation up to largest scale limit in the inertial range. This method is tested using a flow past a sphere test case. The results are compared both qualitatively and quantitatively to results obtained with the standard Smagorinsky model, and demonstrate the better performance of our method with lower computational cost. This allows us to simulate large Reynolds number cases and compare our quantitative results to experimental results found in the literature, emphasising that our method produces good results at reasonable computational cost.

Comparing LES and URANS results with a reference DNS of the transitional airflow in a patient-specific larynx geometry during exhalation

Air exhalation in the laryngeal area produces a complex transitional flow. A detailed investigation of the resulting flow features is very interesting from a fundamental point of view and useful to support medical researchers regarding treatment options. In the current study, the highly complex, unsteady, transitional flow in a patient-specific geometry has been described by three different numerical approaches, (1) using the unsteady Reynolds-averaged Navier–Stokes (URANS) equations with the k−ω shear stress transport (SST) turbulence model, (2) by large-eddy simulation (LES) with the WALE subgrid-scale model, and finally (3) using direct numerical simulation (DNS) – without any model needed. These three approaches deliver different pictures of the resulting flow, obviously with noticeable differences in terms of accuracy, but also regarding the associated computational efforts. The present article is devoted to the detailed comparison of these three approaches, using the DNS results as a reference. It has been found that even though URANS is able to predict with a fair accuracy the large-scale features of velocity and pressure in an average sense, it fails to predict correctly most relevant turbulent features; large differences are found concerning fluctuations, power spectral density, or spectral entropy. On the other hand, LES is able to reproduce both small-scale and large-scale flow features in a good agreement compared to DNS; additionally, LES delivers an appropriate description of the evolution of spectral entropy and can thus be used to predict flow transition. Obviously, DNS delivers an even more detailed and accurate view of the flow properties, but this comes with a tremendous increase in computing effort. For this configuration, a high-quality LES appears as best compromise between accuracy and computational requirements and, therefore, best suitable for medical studies of transitional airflows. All data-sets are publicly available under Abdelsamie et al. [1].

Numerical investigations of pipe flow downstream a flow conditioner with bundle of tubes

Flow conditioners are widely utilized in pipeline systems to improve the precision of flow rate measurement in the pipeline systems of the offshore and subsea oil and gas industry. There is a lack of knowledge about the influences of the conditioners on the flow inside a bend pipe due to the measurement inaccuracy caused by geometries complexity. In this study, numerical simulations are carried out solving the three-dimensional Reynolds-averaged Navier-Stokes (RANS) equations with the κ–ω SST model to investigate the large-scale flow characteristics inside a double bend pipe and the performance of a conditioner with a bundle of 19 tubes. The obtained axial velocity inside a double bend pipe flow with no flow conditioner are compared with those of the previously published numerical simulations results and experimental data as the validation study. Helical flow structures are found behind the double bend and effectively removed by the flow conditioner. The performance of the flow conditioner is evaluated based on the axial flow velocity profiles, the swirl intensities and the deviation from the flow inside a straight pipe. The effects of Reynolds numbers and the lengths of the tube bundle on the flow downstream the flow conditioner are discussed.

Evaluation of Turbulence and Dispersion in Multiscale Atmospheric Simulations over Complex Urban Terrain during the Joint Urban 2003 Field Campaign

Abstract This paper evaluates the representation of turbulence and its effect on transport and dispersion within multiscale and microscale-only simulations in an urban environment. These simulations, run using the Weather Research and Forecasting Model with the addition of an immersed boundary method, predict transport and mixing during a controlled tracer release from the Joint Urban 2003 field campaign in Oklahoma City, Oklahoma. This work extends the results of a recent study through analysis of turbulence kinetic energy and turbulence spectra and their role in accurately simulating wind speed, direction, and tracer concentration. The significance and role of surface heat fluxes and use of the cell perturbation method in the numerical simulation setup are also examined. Our previous study detailed the model development necessary for our multiscale simulations, examined model skill at predicting wind speeds and tracer concentrations, and demonstrated that dynamic downscaling from mesoscale to microscale through a sequence of nested simulations can improve predictions of transport and dispersion relative to a microscale-only simulation forced by idealized meteorology. Here, predictions are compared with observations to assess qualitative agreement and statistical model skill at predicting wind speed, wind direction, tracer concentration, and turbulent kinetic energy at locations throughout the city. We also investigate the scale distribution of turbulence and the associated impact on model skill, particularly for predictions of transport and dispersion. Our results show that downscaled large-scale turbulence, which is unique to the multiscale simulations, significantly improves predictions of tracer concentrations in this complex urban environment. Significance Statement Simulations of atmospheric transport and mixing in urban environments have many applications, including pollution modeling for urban planning or informing emergency response following a hazardous release. These applications include phenomena with spatial scales spanning from millimeters to kilometers. Most simulations resolve flow only within the urban area of interest, omitting larger scales of turbulence and regional influences. This study examines a method that resolves both the small and large-scale flow features. We evaluate simulation accuracy by comparing predictions with observations from an experiment involving the release of a tracer gas in Oklahoma City, Oklahoma, with emphasis on correctly modeling turbulent fluctuations. Our results demonstrate the importance of resolving large-scale flow features when predicting transport and dispersion in urban environments.

CT-Based Analysis of Left Ventricular Hemodynamics Using Statistical Shape Modeling and Computational Fluid Dynamics.

BackgroundCardiac computed tomography (CCT) based computational fluid dynamics (CFD) allows to assess intracardiac flow features, which are hypothesized as an early predictor for heart diseases and may support treatment decisions. However, the understanding of intracardiac flow is challenging due to high variability in heart shapes and contractility. Using statistical shape modeling (SSM) in combination with CFD facilitates an intracardiac flow analysis. The aim of this study is to prove the usability of a new approach to describe various cohorts.Materials and MethodsCCT data of 125 patients (mean age: 60.6 ± 10.0 years, 16.8% woman) were used to generate SSMs representing aneurysmatic and non-aneurysmatic left ventricles (LVs). Using SSMs, seven group-averaged LV shapes and contraction fields were generated: four representing patients with and without aneurysms and with mild or severe mitral regurgitation (MR), and three distinguishing aneurysmatic patients with true, intermediate aneurysms, and globally hypokinetic LVs. End-diastolic LV volumes of the groups varied between 258 and 347 ml, whereas ejection fractions varied between 21 and 26%. MR degrees varied from 1.0 to 2.5. Prescribed motion CFD was used to simulate intracardiac flow, which was analyzed regarding large-scale flow features, kinetic energy, washout, and pressure gradients.ResultsSSMs of aneurysmatic and non-aneurysmatic LVs were generated. Differences in shapes and contractility were found in the first three shape modes. Ninety percent of the cumulative shape variance is described with approximately 30 modes. A comparison of hemodynamics between all groups found shape-, contractility- and MR-dependent differences. Disturbed blood washout in the apex region was found in the aneurysmatic cases. With increasing MR, the diastolic jet becomes less coherent, whereas energy dissipation increases by decreasing kinetic energy. The poorest blood washout was found for the globally hypokinetic group, whereas the weakest blood washout in the apex region was found for the true aneurysm group.ConclusionThe proposed CCT-based analysis of hemodynamics combining CFD with SSM seems promising to facilitate the analysis of intracardiac flow, thus increasing the value of CCT for diagnostic and treatment decisions. With further enhancement of the computational approach, the methodology has the potential to be embedded in clinical routine workflows and support clinicians.

Development of turbulent heat flux model for unsteady forced convective heat transfer of small-to-medium Prandtl-number fluids based on deep learning

Turbulent heat flux (THF) models are used for the closure of the THF term when solving the steady/unsteady Reynolds-averaged scalar transport equation to simulate the turbulent heat transfer in industry. It is known that the simple gradient diffusion hypothesis (SGDH) has deficiencies under complex conditions with flow separations. To develop a more general THF model, this paper firstly establishes a high-fidelity database of forced convective heat transfer passing a circular cylinder under different Prandtl number (Pr) conditions at the Reynolds number (Re) of 500 via the direct numerical simulations. Proper orthogonal decomposition method is then employed for the triple decomposition on unsteady turbulent flow with the first two orders of eigenmodes reconstructing the large-scale field and the remaining reconstructing the turbulent field. Then, architectures using different neural network structures based on tensor basis neural network (TBNN), including MLP-TBNN-THF which adopts the multilayer perceptron (MLP) and ResNet-TBNN-THF that uses the residual network (ResNet), are constructed to predict normalized THF from large-scale flow features and Pr. Posterior tests are carried out on different Prs and three different Res: 500, 5000 and 16900 using the well-trained TBNN-THF models to evaluate their performance and generalization capability. Most models proposed in this paper predict the heat transfer more accurately than the SGDH model, even when extended to conditions out of the range trained. The failure of the isotropic assumption of SGDH model is observed in most regions. In that case, it is vitally necessary to use a model like proposed in this paper to simulate the THF term more accurately. In conclusion, the THF model, which is appropriate for complex working conditions and fluids with small-to-medium range of Pr, obtained by deep learning method in this paper, is helpful to improve the prediction accuracy of temperature field or concentration field by steady or unsteady Reynolds-averaged Naiver-Stokes approach in engineering. Besides, the current framework can be generalized to scalar-flux modeling under other conditions with the supplement of more databases in the future.

On eddy transport in the ocean. Part I: The diffusion tensor

This study provides an interpretation of isopycnal eddy transport for mass and passive tracers in double-gyre eddy-resolving oceanic circulation. This paper focuses on a transport/diffusion tensor representation of the eddy tracer flux, and a companion paper will focus on advective eddy-induced tracer and mass transports. We use a spatial filter to separate the large and small scales, which leads to results distinct from those obtained via a temporal Reynolds eddy decomposition. To work towards a parameterisation, we relate the eddy tracer flux to the large-scale tracer gradient via the transport tensor K. The symmetric part of K is the diffusion tensor, S, which parameterises diffusive fluxes and whose mixing properties are determined by the signs of its eigenvalues. The eigenvalues of S are robustly of opposite sign (polar) and thus quantify filamentation of the tracer via both up- and down-gradient fluxes. Given the prevalence of polar eigenvalues – which are also obtained for Reynolds eddy fluxes – representing their associated effects should be a target of future eddy tracer transport closures. Given the inherent inhomogeneity and anisotropy of the eddy-induced transport, we argue that a full transport tensor is better suited to this task than scalar coefficients or diagonal tensors. The diffusion axis, which represents the direction of preferential mixing, tends to align with the large-scale velocity vector and contours of large-scale relative vorticity and layer thickness. Strong shears can inhibit this alignment. We show that the large-scale velocity gradient matrix may be suitable for parameterising the transport tensor, in particular at depth. Furthermore, since entries of K and S exhibit probabilistic distributions when conditioned on certain large-scale flow features, we suggest that a stochastic closure for the eddy transport would be most suitable.

Combining 4D Flow MRI and Complex Networks Theory to Characterize the Hemodynamic Heterogeneity in Dilated and Non-dilated Human Ascending Aortas

Motivated by the evidence that the onset and progression of the aneurysm of the ascending aorta (AAo) is intertwined with an adverse hemodynamic environment, the present study characterized in vivo the hemodynamic spatiotemporal complexity and organization in human aortas, with and without dilated AAo, exploring the relations with clinically relevant hemodynamic and geometric parameters. The Complex Networks (CNs) theory was applied for the first time to 4D flow magnetic resonance imaging (MRI) velocity data of ten patients, five of them presenting with AAo dilation. The time-histories along the cardiac cycle of velocity-based quantities were used to build correlation-based CNs. The CNs approach succeeded in capturing large-scale coherent flow features, delimiting flow separation and recirculation regions. CNs metrics highlighted that an increasing AAo dilation (expressed in terms of the ratio between the maximum AAo and aortic root diameter) disrupts the correlation in forward flow reducing the correlation persistence length, while preserving the spatiotemporal homogeneity of secondary flows. The application of CNs to in vivo 4D MRI data holds promise for a mechanistic understanding of the spatiotemporal complexity and organization of aortic flows, opening possibilities for the integration of in vivo quantitative hemodynamic information into risk stratification and classification criteria.

The links between the Madden-Julian Oscillation and European weather regimes

Skillful weather forecasting on sub-seasonal timescales is important to enable users to make cost-effective decisions. Forecast skill can be expected to be mediated by the prediction of atmospheric flow patterns, often known as weather regimes, over the relevant region. Here, we show how the Grosswetterlagen (GWL), a set of 29 European weather regimes, can be modulated by the extra-tropical teleconnection from the Madden-Julian Oscillation (MJO). Together, these GWL regimes represent the large-scale flow characteristics observed in the four North Atlantic-European classical weather regimes (NAE-CWRs), while individually capturing synoptic scale flow details. By matching each GWL regime to the nearest NAE-CWR, we reveal GWL regimes which occur during the transition stages between the NAE-CWRs and show the importance of capturing the added synoptic detail of GWL regimes when determining their teleconnection pattern from the MJO. The occurrence probabilities of certain GWL regimes are significantly changed 10–15 days after certain MJO phases, exhibiting teleconnection patterns similar to their NAE-CWR matches but often with larger occurrence anomalies, over fewer consecutive MJO phases. These changes in occurrence probabilities are likely related to MJO-induced changes in the persistence and transition probabilities. Other GWL regimes are not significantly influenced by the MJO. These findings demonstrate how the MJO can modify the preferred evolution of the NAE atmospheric flow, which is important for sub-seasonal weather forecasting.

On data-driven augmentation of low-resolution ocean model dynamics

The problem of augmenting low-resolution ocean circulation models with the information extracted from the data relevant to the unresolved subgrid processes is addressed. A highly nonlinear model of eddy-resolving oceanic circulation – quasigeostrophic wind-driven double gyres – is considered. The model solutions are characterized by a vigorous dynamic coupling between the resolved large-scale and small-scale (eddy) flow features. This solution provides the data for augmenting the low-resolution model with the same configuration. The eddy forcing field, which contains the essential information about coupling between the large and eddy scales, is obtained, modified, coarse-grained and added to augment the low-resolution model. The implemented modification involves novel data-adaptive harmonic decomposition analysis and dynamical constraining based on the low-resolution nonlinear advection operator. The resulting augmentation of the low-resolution model significantly improves the solution, including its time-mean circulation and low-frequency variability. This result also paves the way for a systematic data-driven emulation of unresolved and under-resolved scales of motion.

Role of large scale flow features on cycle-to-cycle variations of spark-ignited flame-initiation and its transition to turbulent combustion

This study investigates the influence of large-scale flow features, including flow structure and velocity magnitude, on the early-burn period variability in a homogenous-charge spark-ignited engine fueled with premixed propane-air mixture. Particle image velocimetry and in-cylinder pressure measurement data from a previous study - were processed to enable simultaneous flow characterization and flame-front tracking as well as apparent heat-release analysis. By combining probability analysis of flame development with conditional sampling of fast and slow early-burn cycles using 10% fuel mass fraction burned, it is shown that an undesirable flow structure produces an asymmetric flame development at the initial flame growth period. This asymmetric flame structure persists through the whole initial-to-turbulent transition period until the flame becomes fully turbulent. The undesirable flow condition is characterized by large-scale convective flows near spark plug rather than flows that lead to increased flame spread in multiple directions. The simultaneous flow and flame characterization enables the quantifications of flame-front propagation speed, unburned fuel-air mixture velocity ahead of flame front and local burning velocity at flame surface. Here the local burning velocity is referred to as laminar or turbulent flame speed. A simplified approach is introduced to derive integrated values for these quantities per crank-angle-degree, enabling the quantitative comparison of the trend-wise difference in these integrated metrics between fast and slow early-burn cycles. It is revealed that for the transition period, the CCV in the velocity magnitude of unburned fuel-air mixture ahead of the flame front accounts for nearly 50% to the variability of flame propagation speed. The burning velocity provides the remaining source of the flame propagation variability in this period. The flame propagation variations in the initial flame growth and fully turbulent periods are smaller than those in the transition period and are primarily dependent on the variability of large-scale flow features.

Estimating large-scale structures in wall turbulence using linear models

A dynamical systems approach is used to devise a linear estimation tool for channel flow at a friction Reynolds number of $Re_{\unicode[STIX]{x1D70F}}=1000$. The estimator uses time-resolved velocity measurements at a single wall-normal location to estimate the velocity field at other wall-normal locations (the data coming from direct numerical simulations). The estimation tool builds on the work of McKeon & Sharma (J. Fluid Mech., vol. 658, 2010, pp. 336–382) by using a Navier–Stokes-based linear model and treating any nonlinear terms as unknown forcings to an otherwise linear system. In this way nonlinearities are not ignored, but instead treated as an unknown model input. It is shown that, while the linear estimator qualitatively reproduces large-scale flow features, it tends to overpredict the amplitude of velocity fluctuations – particularly for structures that are long in the streamwise direction and thin in the spanwise direction. An alternative linear model is therefore formed in which a simple eddy viscosity is used to model the influence of the small-scale turbulent fluctuations on the large scales of interest. This modification improves the estimator performance significantly. Importantly, as well as improving the performance of the estimator, the linear model with eddy viscosity is also able to predict with reasonable accuracy the range of wavenumber pairs and the range of wall-normal heights over which the estimator will perform well.

Dispersion of Entropy Perturbations Transporting through an Industrial Gas Turbine Combustor

In the context of combustion noise and combustion instabilities, the transport of entropy perturbations through highly simplified turbulent flows has received much recent attention. This work performs the first systematic study into the transport of entropy perturbations through a realistic gas turbine combustor flow-field, exhibiting large-scale hydrodynamic flow features in the form of swirl, separation, recirculation zones and vortex cores, these being ubiquitous in real combustor flows. The reacting flow-field is simulated using low Mach number large eddy simulations, with simulations validated by comparison to available experimental data. A generic artificial entropy source, impulsive in time and spatially localized at the flame-front location, is injected. The conservation equation describing entropy transport is simulated, superimposed on the underlying flow-field simulation. It is found that the transport of entropy perturbations is dominated by advection, with both thermal diffusion and viscous production being negligible. It is furthermore found that both the mean flow-field and the large-scale unsteady flow features contribute significantly to advective dispersion — neither can be neglected. The time-variation of entropy perturbation amplitude at combustor exit is well-modelled by a Gaussian profile, whose dispersion exceeds that corresponding to a fully-developed pipe mean flow profile roughly by a factor of three. Finally, despite the attenuation in entropy perturbation amplitude caused by advective dispersion, sufficient entropy perturbation strength is likely to remain at combustor exit for entropy noise to make a meaningful contribution at low frequencies.

Use of DES in mildly separated internal flow: dimples in a turbulent channel

ABSTRACTDetached eddy simulation (DES) is investigated as a means to study an array of shallow dimples with depth to diameter ratios of 1.5% and 5% in a turbulent channel. The DES captures large-scale flow features relatively well, but is unable to predict skin friction accurately due to flow modelling near the wall. The current work instead relies on the accuracy of DES to predict large-scale flow features, as well as its well-documented reliability in predicting flow separation regions to support the proposed mechanism that dimples reduce drag by introducing spanwise flow components near the wall through the addition of streamwise vorticity. Profiles of the turbulent energy budget show the stabilising effect of the dimples on the flow. The presence of flow separation however modulates the net drag reduction. Increasing the Reynolds number can reduce the size of the separated region and experiments show that this increases the overall drag reduction.

Multilevel cloud structures over Svalbard.

The presented picture of the month is a superposition of space-borne lidar observations and high-resolution temperature fields of the ECMWF integrated forecast system (IFS). It displays complex tropospheric and stratospheric clouds in the Arctic winter 2015/16. Near the end of December 2015, the unusual northeastward propagation of warm and humid subtropical air masses as far north as 80°N lifted the tropopause by more than 3 km in 24 h and cooled the stratosphere on a large scale. A widespread formation of thick cirrus clouds near the tropopause and of synoptic-scale polar stratospheric clouds (PSCs) occurred as the temperature dropped below the thresholds for the existence of cloud particles. Additionally, mountain waves were excited by the strong flow at the western edge of the ridge across Svalbard, leading to the formation of mesoscale ice PSCs. The most recent IFS cycle using a horizontal resolution of 8 km globally reproduces the large-scale and mesoscale flow features and leads to a remarkable agreement with the wave structure revealed by the space-borne observations.

Two-Dimensional Evaluation of ATHAM-Fluidity, a Nonhydrostatic Atmospheric Model Using Mixed Continuous/Discontinuous Finite Elements and Anisotropic Grid Optimization

AbstractThis paper presents the first attempt to apply the compressible nonhydrostatic Active Tracer High-Resolution Atmospheric Model–Fluidity (ATHAM-Fluidity) solver to a series of idealized atmospheric test cases. ATHAM-Fluidity uses a hybrid finite-element discretization where pressure is solved on a continuous second-order grid while momentum and scalars are computed on a first-order discontinuous grid (also known as ). ATHAM-Fluidity operates on two- and three-dimensional unstructured meshes, using triangular or tetrahedral elements, respectively, with the possibility to employ an anisotropic mesh optimization algorithm for automatic grid refinement and coarsening during run time. The solver is evaluated using two-dimensional-only dry idealized test cases covering a wide range of atmospheric applications. The first three cases, representative of atmospheric convection, reveal the ability of ATHAM-Fluidity to accurately simulate the evolution of large-scale flow features in neutral atmospheres at rest. Grid convergence without adaptivity as well as the performances of the Hermite–Weighted Essentially Nonoscillatory (Hermite-WENO) slope limiter are discussed. These cases are also used to test the grid optimization algorithm implemented in ATHAM-Fluidity. Adaptivity can result in up to a sixfold decrease in computational time and a fivefold decrease in total element number for the same finest resolution. However, substantial discrepancies are found between the uniform and adapted grid results, thus suggesting the necessity to improve the reliability of the approach. In the last three cases, corresponding to atmospheric gravity waves with and without orography, the model ability to capture the amplitude and propagation of weak stationary waves is demonstrated. This work constitutes the first step toward the development of a new comprehensive limited area atmospheric model.

Characterization of the effect of intake air swirl motion on time-resolved in-cylinder flow field using quadruple proper orthogonal decomposition

The control of intake air swirl motion is often used in spark-ignition direct-injection (SIDI) engine to improve its in-cylinder fuel–air mixing process especially under engine idle and low load conditions. In this experimental investigation, a novel technique combining the time-resolved particle image velocimetry (PIV) with quadruple proper orthogonal decomposition (POD) is implemented to analyze the time-resolved in-cylinder velocity measurements in an optically-accessible SIDI engine. The intake air swirl motion is introduced into the engine cylinder by a control valve installed in one of two air intake ports. Experimental results show that a strong linear correlation exists between the intake flow swirl ratio and vorticity flow field in the cylinder. This correlation ensures high data reliability of swirl motion control and provides a novel basis to directly compare the flow field measurements under different swirl ratio conditions. The quadruple proper orthogonal decomposition analysis is then applied to the velocity flow fields to separate the highly dynamic in-cylinder flow characteristics into four distinct categories: (1) dominant flow structure; (2) coherent structure; (3) turbulent structure; and (4) noise structure. The results show that the dominant flow structure varies strongly with swirl ratio, and its kinetic energy is also directly related to the swirl ratio. The coherent structure captures the large scale flow characteristics, but its kinetic energy is much lower and exhibits larger cycle-to-cycle variations. The turbulent structure contains similar level of kinetic energy at different swirl ratios but without much cycle-to-cycle variation. Finally, the noise structure contains very low kinetic energy which only alters the dynamic nature of the flow field slightly. In summary, the effect of swirl ratio on in-cylinder flow field is mostly captured by the dominant flow structure and partially captured by the coherent flow structure. The turbulent flow structure can characterize the high-order flow variation. The noise structure can be neglected due to the low energy captured.

Resolution effects in compressible, turbulent boundary layer simulations

This paper presents the first systematic study of resolution in compressible, turbulent boundary simulations, and the best-resolved simulation carried out to date. Direct numerical simulation (DNS) and wall-resolved, implicit large-eddy simulation (ILES-NWR) were carried out for a turbulent boundary layer at a Mach number of M=2.3 and maximum momentum thickness Reynolds number of Reθi=2×103. The wall temperature was fixed at a constant value corresponding to the nominal adiabatic wall temperature. The flow was developed spatially from a laminar boundary layer similarity solution specified at the inflow, and transition to turbulence was promoted with an artificial body force trip. The effects of spatial resolution in the range of ILES-NWR, conventional DNS, and very strict DNS were considered. The finest grid in the spatial resolution study consisted of 3.3 × 1010 points, and maintained max(Δx1+,Δx2+,Δx3+)≤1 everywhere. With the resolution at the wall held at (Δx2+)w<1, statistics characterizing large-scale flow features converged for max(Δxi+)≤10, and agreed well with experimental data. Velocity spectra in the outer part of the boundary layer agreed well at low wavenumber for all grids in this range of mesh spacing, and increasing resolution acted to fill out the high-wavenumber end of the spectrum. In all cases, the resolved region of the spectrum agreed well with a well-validated model of the spectrum of isotropic turbulence. Thus, ILES-NWR can be concluded to converge seamlessly to DNS as the spatial resolution is increased. The low-wavenumber aspect of spatial resolution was examined by varying the width of the computational domain, with a fixed level of small-scale resolution. The primary influence of increasing domain width was to capture additional spectral content in low spanwise wavenumbers; other statistics were found to be identical. Further, turbulence statistics were found to be essentially independent of the domain width for values between two and eight times the maximum boundary layer thickness. This work predicts computationally, for the first time, the full velocity spectrum in the outer part of the boundary layer. In doing so, it justifies use of the ILES-NWR approach as long as the maximum grid spacing is less than 10 in inner units, and the domain width is at least two times the maximum boundary layer thickness.