Flow, Turbulence and Combustion最新文献

We present a machine learning–based framework for blending data-driven turbulent closures in the Reynolds-Averaged Navier–Stokes (RANS) equations, aimed at improving their generalizability across diverse flow regimes. Specialized models (hereafter referred to as “experts”) are trained via sparse Bayesian learning and symbolic regression for distinct flow classes, including turbulent channel flows, separated flows, and a near sonic axisymmetric jet. These experts are then combined intrusively within the RANS equations using weighting functions, initially derived via a Gaussian kernel on a dataset spanning equilibrium shear conditions to separated flows. Finally, a Random Forest Regressor is trained to map local physical features to these weighting functions, enabling deployment in previously unseen scenarios. We evaluate the resulting blended model on three representative test cases: a turbulent zero-pressure-gradient flat plate, a wall-mounted hump, and a NACA0012 airfoil at various angles of attack, ranging from fully attached to near-stall conditions. Results for these 2D flows show that the proposed strategy adapts to local flow characteristics, effectively leveraging the strengths of individual models and consistently selecting the most suitable expert in each region. Notably, the blended model also demonstrates robustness for flow configurations not included in the training set, underscoring its potential as a practical and generalizable framework for RANS turbulence modeling.

In this paper we report on Large Eddy Simulations of natural convection in water pools with evaporation across the free surface and at the hard turbulence regime. The free surface is approximated as a free-slip top boundary. The loss of water is estimated via a dynamic and inhomogeneous evaporation model. Also, the descent of the free surface is accounted for by regularly reducing the computational domain and applying a remeshing procedure. We present results for 4 different Rayleigh numbers, ranging from (boldsymbol{Ra = 1.35 times {10^8}}) to (boldsymbol{Ra{ = 10^{10}}}). Our simulations predict a slow decrease of the free-surface temperature and evaporation rate over time. This may be attributed to the descent of the free surface due to evaporation which tends to reduce the intensity of turbulent motions. On the other hand, the flow structure remains the same throughout the duration of the simulations. More specifically, the flow is organized in a large scale circulation aligned in a diagonal plane with smaller convective rolls near the corners of the domain. Also, the absence of a top hydrodynamic boundary layer enhances turbulent mixing and convective heat transfer near the free surface. This enhancement is manifested by a shift of the profile of the mean surface temperature towards the upper part of the domain, with the shift becoming more pronounced as the turbulence intensity increases. Herein we also provide results for the Nusselt number (boldsymbol{Nu}) and present a new (boldsymbol{Nu - Ra}) scaling for convection in pools and cavities that covers a large range of turbulence intensities.

The presence of obstacles in confined spaces results in high overpressure from premixed flame combustion and the specific obstacle configurations significantly affect flame dynamics. Although linear plate-type obstacles had been extensively explored for flame acceleration, the present study focused on obstacles with volume blockage. This paper investigated the effects of different shapes of such obstacles and their configurations on the flame propagation characteristics inside a partially confined geometry. Four different flame surface density models were tested: Algebraic Flame Surface Wrinkling model, Turbulent Flame Speed Closure, Algebraic model and Transport model. The Transport model by Weller was selected with the dynamic k-equation Large Eddy Simulation model for turbulence modelling. Four shapes of obstacles, triangular, rectangular, elliptical and circular were examined. The effect of separation distance (standard-100 mm, spaced-out-150 mm and squeezed-in-70 mm) between the obstacles was investigated, along with their number and configuration (in-line and staggered). The results revealed that for standard separation, the overpressure peak is maximum for triangular and minimum for circular obstacles. Staggering the obstacles reduced the peak overpressure. Further, the overpressure peak reduced with both increasing and reducing separation compared to the standard case for triangle, ellipse, and circle-shaped obstacles, whereas it increased with greater separation for rectangular obstacles. The most significant reduction across all cases was observed upon reducing the separation distance. Oscillatory pressure behaviour owing to combustion in unburnt mixture pockets is reported for rectangle and triangle obstacles, attributed to their minimal sphericity. The flame surface area, representative of the turbulence generated, is observed to be directly correlated with the peak overpressure value across the dataset.

Large Eddy Simulations (LES) are increasingly used in industry due to their superior accuracy compared to traditional statistical methods like Reynolds-Averaged Navier-Stokes (RANS) simulation. However, their high computational cost remains a major obstacle to performing daily parametric studies in engineering design offices. The objective of this work is to improve the efficiency of LES-based parametric studies through multi-fidelity surrogate modeling. Taking into account the computational cost of each turbulence modeling approach, multi-fidelity technic propose to combine limited number of LES results with more numerous RANS simulations. To achieve this, we use Artificial Neural Networks (ANN), which are particularly effective at capturing complex relationships between fidelity levels and handling discontinuities. To further reduce computational cost, we propose a new adaptive sampling strategy that selects high-fidelity LES points based on an estimation of interpolation error. This approach enhances the accuracy of the multi-fidelity method by efficiently allocating computational resources where they are most needed. The proposed strategy is first validated on an analytical test case before being applied to the study of the lift coefficient as a function of the angle of attack for a NACA0012 airfoil. We demonstrate that with only five LES evaluations, our method accurately captures the main features of this function, including the stall angle. This work paves the way for more efficient LES-based parametric studies.

A scaling relation has been derived to link the fractal dimension of a flame surface with the ratio of the normalised 3D flame surface area to its 2D counterpart. This derivation assumes an isotropic distribution of angles between the measurement plane and the flame’s normal vector, as well as a uniform distribution of angles between the principal direction and the flame’s tangent vector. The validity of the newly derived relation was assessed using an existing Direct Numerical Simulation (DNS) database of statistically planar turbulent premixed flames, encompassing a range of different Karlovitz numbers. The DNS data-based assessment revealed that the newly derived relations are reasonably accurate for the thin reaction zones regime flames, with the precision of predictions based on isotropy improving, as the Karlovitz number increases. Moreover, 2D measurements of the flame surface fractal dimension and the flame wrinkling factor can be effectively used to predict the actual 3D flame wrinkling factor for flames with Karlovitz numbers much greater than unity. Alternatively, the ratio of the 3D wrinkling factor to its 2D counterpart can provide a reasonable estimate of the 3D fractal dimension for flames in the thin reaction zones regime. The newly derived relations provide an estimation for the value of fractal dimension in the limit of high Karlovitz number using an alternative route.

An extension to multi-species and reacting flows of Doak’s “Momentum Potential Theory of Energy Flux carried by Momentum Fluctuations” is proposed as a general and comprehensive framework for thermoacoustic characterization of combustor systems. This framework is applied here for the first time in its extended form to analyze simulation data relative to the flow in a bluff-body stabilized combustor, in stable operating conditions. The proposed thermoacoustic model is able to: (i) unambiguously separate turbulent, acoustic, thermal, and mixture fluctuations; (ii) effectively describe the interaction between turbulent, acoustic, thermal, and mixture dynamics; (iii) highlight the main characteristics of the combustion noise emitted by the systems. By means of the performed analysis, the thermal phenomena are found to dominate the dynamics interaction. All convective quantities interact in the shear layer at the flame border and feature a similar, low-frequency spectral behavior. As expected, the acoustics does not couple directly with the convective quantities, due to the considered stable conditions. Although, the acoustic spectrum is strongly characterized by three peaks, which can be attributed to secondary, high-frequency thermal fluctuations. The modes related to these peaks can be seen, therefore, as a representation of the combustion noise emitted by the flame. The new terms related to the mixture do not seem to effectively contribute to the dynamics interaction and to the acoustic production, at least for the considered configuration and operating conditions.

In internal combustion engines (ICE), ongoing research focuses on improving efficiency and reducing environmental emissions. As part of this effort, synthetic fuels like E-Fuels and Syngas have gained attention as promising alternatives to conventional fossil fuels. This study investigates the performance and emission characteristics of four different E-Fuels (E-Hydrogen, E-Methanol, E-Kerosene, and E-Ammonia) and three different Syngas compositions in comparison to conventional gasoline in an i-DSI engine. A validated 3D Computational Fluid Dynamics (CFD) model, based on reference experimental data obtained with gasoline, was used to simulate in-cylinder combustion characteristics. The analysis evaluated in-cylinder pressure, torque, indicated power (IP), indicated mean effective pressure (IMEP), indicated specific fuel consumption (ISFC), and thermal efficiency for each fuel. Significant variations in combustion and performance metrics were observed across the eight fuels. E-Hydrogen exhibited the highest in-cylinder pressure and torque increase (17.95%), along with the highest thermal efficiency improvement (up to 55.20%). In contrast, E-Ammonia showed the lowest performance, with a 16.68% reduction in torque. Among the Syngas compositions, Syngas-C (with the highest H₂ content) achieved the best performance. CO₂, CO, and HC emissions were zero for carbon-free fuels (E-Hydrogen and E-Ammonia), while NO_x emissions were highest with E-Hydrogen and lowest with gasoline. Additionally, performance metrics were normalized by each fuel’s lower heating value (LHV), revealing that Syngas blends—especially Syngas-C—offered strong energy-based efficiency. This study uniquely presents a comparative and systematic evaluation of E-Fuels and Syngas as next-generation fuel alternatives for ICEs, using CFD-based combustion modeling validated by experimental reference data.

Displacement speed and flame stretch are analysed in the vicinity of critical points defining local topology using a direct numerical simulation dataset of a turbulent premixed flame. The analysis categorises local topology types as; reactant pocket, tunnel closure, tunnel formation, and product pocket. The influence of local topology on global flame propagation is discussed. Cylindrical topologies are shown to contribute both positively and negatively towards flame stretch while spherical topologies mainly cause local destruction of flame area. The rate of stretch is shown to follow the curvature profile for all topologies. On the other hand, displacement speed is seen to scale the influence of curvature, while together the two determine whether area is produced or destroyed. The role of local diffusion in displacement speed and the role of curvature in defining the stretch rate profile emerge as the main actors for the local change in area. These local changes are shown to impact the global surface area and consequently the global propagation of the flame.

Experimental and theoretical studies on liquid unloading in gas wells show that the critical gas velocities for carrying droplets upward is much smaller than the critical gas velocity for carrying liquid film upward. The latest studies show that the hydrophobic coating can change solid surface wettability, reduce contact area between liquid droplet and solid surface, and can promote the droplet formation from liquid film in annular flow. It is speculated that tubing with a hydrophobic wall can reduce the critical gas rate of liquid unloading under certain production conditions. However, how hydrophobic tubing modifies gas wells liquid unloading is still unknown. This study presents the experimental results of air-water two phase flow in hydrophobic pipe. First, a hydrophobic coating was sprayed on the inner wall of a transparent pipe, and an experimental loop with a height of 8 m and an inner diameter of 40 mm was built for air-water two phase flow. A comparative experiment was conducted in the pipe with and without hydrophobic coating. The influence of hydrophobic coating on flow pattern characteristics, flow pattern transition conditions, pressure gradient, liquid holdup, droplet entrainment fraction, and critical gas velocity were measured. The mechanism of hydrophobic coating improves the liquid carrying capacity of gas stream has been revealed from multiple perspectives.