Flow, Turbulence and Combustion最新文献

A comparative analysis is undertaken to explore the impact of various roughness characterization methods as input variables on the performance of data-driven predictive models for estimating the roughness equivalent sand-grain size (k_s). The first type of model, denoted as (text {ENN}_text {PS}), incorporates the roughness height probability density function (p.d.f.) and power spectrum (PS), while the second type of model, (text {ENN}_text {PA}), utilizes a finite set of 17 roughness statistical parameters as input variables. Furthermore, a simplified parameter-based model, denoted as (text {ENN}_text {PAM}), is considered, which features only 6 input roughness parameters. The models are trained based on identical databases and evaluated using roughness samples similar to the training databases as well as an external testing database based on literature. While the predictions based on p.d.f. and PS achieves a stable error level of around 10% among all considered testing samples, a notable deterioration in performance is observed for the parameter-based models for the external testing database, indicating a lower extrapolating capability to diverse roughness types. Finally, the sensitivity analysis on different types of roughness confirms an effective identification of distinct roughness effects by (text {ENN}_text {PAM}), which is not observed for (text {ENN}_text {PA}). We hypothesize that the successful training of (text {ENN}_text {PAM}) is attributed to the enhanced training efficiency linked to the lower input dimensionality.

This paper aims at identifying the noise sources in an axial turbine stage and their relative importance. The Large eddy simulation (LES) has been carried out on a geometry containing single rotor and stator passages and the mesh of the rotor domain is circumferentially sliding. The proper orthogonal decomposition (POD) is applied to data matrices constructed with the pressure fields in order to distinctly extract the coherent structures responsible for noise generation. The results show that the rotor–stator interaction contributes up to 50% of the total sound energy, the flow fluctuations are influenced by the rotor–stator interaction even in the very upstream region of the stator passage due to the massive pressure wave reflections between the stator vane row and the rotor blade row. Therefore, the tonal noise at the blade passing frequency and its second harmonic frequency are the dominant noise of the turbine stage. An aerodynamic-acoustic feedback loop is observed in the stator passage and it is mainly due to the emission, reflection and interference of the pressure waves generated by the trailing edge vortex shedding. The surface pressure levels of the rotor blade surface are lower than those of the stator vane surface, thus the rotor blades have a smaller contribution to the overall noise level of the turbine stage than the stator vanes, since there is no aerodynamic-acoustic feedback loop in the rotor passage.

For this work, conditional averaging and Proper Orthogonal Decomposition (POD) were used to analyze the salient three-dimensional structures in the wake of a DrivAer fastback model with smooth underbody. Conditional averaging revealed that the bi-stable structure of the wake consists of a ring-like structure with three vortex legs, which includes a vortex pair on the side associated with the bi-stability and one on the opposite side associated with the wheel vortex. POD revealed the entrainment of low-momentum fluid from the wheel wake into the vortex pair leads to an induced spanwise crossflow which drives a feedback loop for the bi-stability. The resultant bi-stable structure was dependent on the state of the wheels. With stationary wheels, the feedback mechanism is enhanced, leading to higher spanwise crossflow that breaks the ring-like vortex. A different structure was observed when the wheels rotate, wherein the ring-like structure is unbroken and pierced by the vortex pair. The feedback mechanism and resultant vortex structure are similar to those found in simplified square-back models. Given the similarity in bi-stability between realistic and simplified vehicles, the suppression of the bi-stability in realistic vehicles could initially be based on the same mechanism as that for simplified square-back models.

The manuscript deals with continuous adjoint companions of prominent explicit Large Eddy Simulation (LES) methods grounding on the eddy viscosity assumption for incompressible fluids. The subgrid-scale approximations considered herein address the classic Smagorinsky-Lilly, the Wall-Adapting Local Eddy-Viscosity (WALE), and the Kinetic Energy Subgrid-Scale (KESS) model, whereby only static implementations, i.e., those without dynamically adjusted model parameters, are considered. The associated continuous adjoint systems and resulting shape sensitivity expressions are derived. Information on the consistent discrete implementation is provided that benefits from the self-adjoint primal discretization of convective and diffusive fluxes via unbiased, symmetric approximations, frequently performed in explicit LES studies to minimize numerical diffusion. Algebraic primal subgrid-scale models yield algebraic adjoint LES relationships that resemble additional adjoint momentum sources. The KESS one equation model introduces an additional adjoint equation, which enlarges the resulting continuous adjoint KESS system with potentially increased numerical stiffness. The different adjoint LES methods are tested and compared against each other on a flow around a circular cylinder at (text{Re}_text{D} = {140000,}) for a boundary (drag) and volume (deviation from target velocity distribution) based cost functional. Since all primal implementations predict similar flow fields, it is possible to swap the associated adjoint systems –i.e., applying an adjoint WALE method to a primal KESS result– and still obtain plausible adjoint results. Due to the LES’s inherent unsteady character, the adjoint solver requires the entire primal flow field over the cost-functional relevant time horizon. Even for the academic cases studied herein, the storage capacities are in the order of terabytes and refer to a practical bottleneck. However, in the case of suitable, time-averaged cost functional, the time-averaged primal flow field can be used directly in a steady adjoint solver, which results in a drastic effort reduction.

An outwardly propagating premixed flame in homogeneous isotropic turbulence at constant pressure is considered one of canonical configurations to study turbulent premixed flames. In this paper, a surface forcing method to prevent the undesirable influence of the boundary-condition-induced backflow on the flame evolution, while maintaining the constant pressure, in the simulation of the outwardly propagating flame is presented. The method is validated for laminar and turbulent flames. The results show that the present method well preserves the characteristics of turbulence and of an outwardly propagating flame, without the undesirable influence of the boundary condition, by feeding the homogeneous turbulence relative to the velocity field induced by the volume expansion due to heat release to the domain in which the flame develops.

The validity of the usual laws of the wall for Favre mean values of the streamwise velocity component and temperature for non-reacting flows has been assessed for turbulent premixed flame-wall interaction using Direct Numerical Simulation (DNS) data. Two different DNS databases corresponding to friction velocity-based Reynolds number of 110 and 180 representing unsteady head-on quenching of statistically planar flames within turbulent boundary layers have been considered. The usual log-law based expressions for the Favre mean values of the streamwise velocity and temperature for the inertial layer have been found to be inadequate at capturing the corresponding variations obtained from DNS data. The underlying assumptions of constant shear stress and the equilibrium of production and dissipation of turbulent kinetic energy underpinning the derivation of the usual log-law for the mean streamwise velocity have been found to be rendered invalid within the usual inertial layer during flame-wall interaction for both cases considered here. The heat flux does not remain constant within the usual inertial layer, and the turbulent flux of temperature exhibits counter-gradient transport within the so-called inertial layer for the cases considered in this work. These render the assumptions behind the derivation of the usual log-law for temperature to be invalid for application to turbulent flame-wall interaction. It has been found that previously proposed empirical modifications to the existing laws of the wall, which account for density and kinematic viscosity variations with temperature, do not significantly improve the agreement with the corresponding DNS data in the inertial layer and the inaccurate approximations for the kinematic viscosity compensated wall normal distance and the density compensated streamwise velocity component contribute to this disagreement. The DNS data has been utilised here to propose new expressions for the kinematic viscosity compensated wall normal distance and the density compensated streamwise velocity component, which upon using in the empirically modified law of wall expressions have been demonstrated to provide reasonable agreement with DNS data.

A novel technique is presented to improve the initialization of compressible combustion LES, DNS or URANS by numerically turning the flame into a damper to quickly remove (artificial) pressure fluctuations and acoustic energy from the system. This is achieved by modifying the pressure dependency of the heat release rate, effectively modifying the Rayleigh Integral to achieve negative values, so that the acoustic energy is quickly removed from the system. The technique can (a) reduce the cost of simulations (by shortening the initialization), (b) contribute to stabilize the simulation, (c) help to avoid unrealistic thermoacoustic modes and, (d) potentially, be modified to compensate for excessive numerical dissipation of acoustic energy. Examples from LES of a thermoacoustic test case are presented to demonstrate the effective stabilization achieved.

Ignition and combustion behavior in the second stage of a sequential combustor are investigated numerically at atmospheric pressure for pure ({text{CH}}_{4}) fueling and for two ({text{CH}}_{4})-({text{H}}_{2}) fuel blends in 24:1 and 49:1 mass ratios , respectively, using Large Eddy Simulation (LES). Pure ({text{CH}}_{4}) fueling results in a turbulent propagating flame anchored by the hot gas recirculation zones developed near the inlet of the sequential combustion chamber. As the ({text{H}}_{2}) content increases, the combustion process changes drastically, with multiple auto-ignition kernels produced upstream of the main flame brush. Analysis of the explosive modes indicates that, for the highest ({text{H}}_{2}) amount investigated, flame stabilization in the combustion chamber is strongly supported by auto-ignition chemistry. The analysis of fuel decomposition pathways highlights that radicals advected from the first stage flame, in particular OH, induce a rapid fuel decomposition and cause the reactivity enhancement that leads to auto-ignition upstream of the sequential flame. This behavior is promoted by the relatively large mass fraction of OH radicals found in the flow reaching the second stage, which is approximately one order of magnitude greater than it would be at chemical equilibrium. The importance of the out-of-equilibrium vitiated air on the ignition behavior is proven via an additional LES that features weak auto-ignition kernel formation when equilibrium is artificially imposed. It is therefore concluded that parameters affecting the relaxation towards chemical equilibrium of the vitiated flow can have an important influence on the operability of sequential combustors fueled with varying fractions of ({text{H}}_{2}) blending.

A data-driven wall function estimation approach is proposed, aimed at accounting for non-equilibrium effects in turbulent boundary layers in RANS simulations of wall bounded flows. While keeping key simplifying hypothesis of standard wall functions and their general structure, the law-of-the-wall is replaced by a fully connected feed-forward neural network. The latter is trained to infer wall friction from the local flow state at the first of-wall nodes, described by an extended set of flow variables and gradients. For this purpose, the neural network is trained on high-fidelity wall resolved simulation data. It is then applied to formulate two different wall functions trained on high-fidelity data: a backward-facing step and a round jet impacting a flat wall. After integration into an industrial CFD code, they are applied to perform RANS simulations of the flow configurations they were trained for, and are shown to yield a largely improved prediction of wall friction as compared to standard wall functions. Finally, key issues related to the practical usability in RANS applications of the proposed data-driven approach are critically discussed.