Flow, Turbulence and Combustion最新文献

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.

Modern turbomachinery blades are facing increasingly pronounced aeroelastic challenges with the increase of unsteady loads and the widespread use of lightweight materials. Conventional coupling methods fail to analyze this issue efficiently due to tremendous dimensionality difference between fluid and structure domains. To address this critical bottleneck, a novel parameterized reduced-order model (PROM), based on deep neural networks (DNN) and proper orthogonal decomposition (POD), was proposed and validated in this study. The framework operates through two synergistic phases. The first stage was dimensionality reduction, in which, POD was employed to extract flow field modes and determine corresponding mode coefficients. The second stage was parameters mapping, where a DNN model was constructed and trained to learn the nonlinear relationship between design parameters and mode coefficients. Finally, the efficacy and robustness of the PROM approach are demonstrated using Rotor 67, a typical transonic axial-flow compressor. The results show that the proposed PROM has an excellent performance in flow field prediction and the maximum relative error less than 5%. Moreover, a well-trained PROM can accurately determine the pressure distribution over the surfaces of compressor blade in just 0.03 s, effectively enabling real-time simulations. This advancement holds significant promise for enhancing aeroelastic analysis in turbomachinery blade design.

The objectives of this study were (i) to create a unique test case of an unsteady flow around a cone in a Ludwieg tube for the purpose of validating computational codes; (ii) to test a new method for determining non-stationary aerodynamic loads using a strain-gauge balance; and (iii) to test a new method for determining unsteady pressure using a Pitot-Prandtl-type probe with a cavity between the sensor and the flow. The results of testing of a 10° cone in the TsAGI short-duration UT-1M Ludwieg-type tube at Mach number M = 6 are presented. During the runs, the following parameters were measured simultaneously: non-stationary aerodynamic loads using an internal six-component strain-gauge balance, dynamic behavior of the cone and balance using three-axis accelerometers, unsteady pressure on the cone surface, total and static pressure using a Pitot-Prandtl-type probe, cone surface temperature using a temperature sensitive paint, flow parameter fluctuations on the cone surface using a constant voltage film thermoanemometer. In some tests, the flow was visualized using the Schlieren method. Before the tests, numerical calculations of the flow around the cone in the facility were performed with the EWT-TsAGI software package to select the location of the oversized cone and the Pitot-Prandtl-type probe in the test section. The conducted studies confirmed the applicability of the new methods for measuring non-stationary forces and unsteady pressure in short-duration wind tunnels.

It is well-known that kinetic energy produced artificially by an inadequate numerical discretization of nonlinear transport terms may lead to a blow-up of the numerical solution in simulations of fluid dynamical problems such as incompressible turbulent flows. However, the community seems to be divided whether this problem should be resolved by the use of discretely energy-preserving or dissipative discretization schemes. The rationale for discretely energy-preserving schemes is often based on the expectation of exact conservation of kinetic energy in the inviscid limit, which mathematically relies on the assumption of sufficient regularity of the solution. There is the (contradictory) phenomenological observation in turbulence that flows dissipate energy in the limit of vanishing molecular viscosity, an “anomalous” phenomenon termed dissipation anomaly or the zeroth law of turbulence. As already conjectured by Onsager, the Euler equations may dissipate kinetic energy through the formation of singularities of the velocity field. With the proof of Onsager’s conjecture in recent years, a consequence for designing numerical methods for turbulent flows is that the smoothness assumption behind conservation of energy in the inviscid limit becomes indeed critical for turbulent flows. The velocity field rather has to be expected to show singular behavior towards the inviscid limit, supporting the dissipation of kinetic energy. Our main argument is that designing numerical methods against the background of this physical behavior is a strong rationale for the construction of dissipative (or dissipation-aware) numerical schemes for convective terms. From that perspective, numerical dissipation does not appear artificial, but as an important ingredient to overcome problems introduced by energy-conserving numerical methods such as the inability to represent anomalous dissipation as well as the accumulation of energy in small scales, which is known as thermalization. This work discusses stabilized (H^1), (L^2), and (H(mathrm{div}))-conforming finite element methods for incompressible flows with a focus on the energy-stability of the numerical method and its dissipation mechanisms to predict inertial dissipation. Finally, we discuss the achievable convergence rate for the kinetic energy in under-resolved turbulent flow simulations.

The consideration of the inherently non-local characteristics of turbulence is an open challenge and subject to many investigations. Recent approaches rely on the utilization of spatially configured Neural Networks such as e.g. Convolutional Neural Networks to account for non-local effects (Comput. Methods Appl. Mech. Eng. 384:113927, 2021). Nevertheless, approaches featuring Neural Networks are not easily available for Gene Expression Programming. An alternative option, to consider non-local effects, is the use of partial differential equations (PDE) like an additional convection-diffusion equation as is done for example in several transition models such as the (gamma)- model by Menter et al. (Flow Turbul. Combust. 583–619, 2015). Consequently, instead of only modeling a local correction factor directly using GEP, we equip the input quantities with an additional optional convection-diffusion equation of which we model the production term, diffusion constants and boundary type. The methodology is applied on a set of low pressure turbine testcases in order to find transition models. Resulting expressions are further analysed in terms of underlying mechnims and logical foundations.

This work examines the momentum boundary layer evolution on the piston top of the Darmstadt optically accessible Internal Combustion Engine (ICE). For this purpose, a 3D-CFD wall-resolved Large Eddy Simulation (LES) under motored conditions was deployed. The piston wall is resolved down to 25 (upmu)m, corresponding to ({y^ + } < 1). For statistical purposes and to compare with experimental data, 33 consecutive engine cycles are simulated. A large-scale tumble motion characterizes the flow field. This flow impinges on the piston on the exhaust side, it moves along the flat piston wall and detaches on the intake side. The near-wall velocities of the simulations align well with the experiment. Analysis revealed regions of Favorable Pressure Gradient (FPG) on the exhaust side and Adverse Pressure Gradient (APG) on the intake side, separated by a sharp pressure inversion zone. The near-wall flow accelerates and then decelerates until detachment. Analysis of the non-dimensional ({u^ + } - {y^ + }) profiles reveals the absence of a logarithmic region in the boundary layer. This scaling procedure is sensitive to thermo-physical properties like density and viscosity that vary across the boundary layer, which complicates comparisons with canonical studies. The shape factor of the boundary layer suggests a fully turbulent state despite the low momentum thickness-based Reynolds number. The boundary layer height increases from the exhaust towards the intake side, especially in the presence of strong pressure gradients. Pressure gradients acting perpendicular to the boundary layer are observed. The comparison of ensemble-averaged and single-cycle instantaneous data shows high levels of cyclic fluctuations.

Turbulent impinging jet (TIJ) flows are a canonical type of flow that is present in nature and in a wide range of industrial applications, making their study indispensable. Among them, multiple co-flowing and angled jets offer possibilities for various practical applications. However, fundamental information on these particular jet configurations is scarce, and there is also a lack of data for validating numerical simulations of these jet flows. Therefore, this paper presents an experimental analysis of isothermal plane turbulent impinging co-flowing and angled jets at moderate Reynolds numbers (Re_jet ≈ 8,700 and 10,000) and height-to-width ratio (γ = 40.5) utilizing 2D particle image velocimetry (PIV). It also validates the results of several RANS turbulence models that are commonly used for simulating single straight TIJs: standard k-ε (SKE) model, realizable k-ε model (RKE), renormalization group (RNG) k-ε model, baseline (BSL) k-ω model, shear-stress transport (SST) k-ω model, and a Reynolds-stress model (RSM). The analysis and validation focus on detailed velocity measurements while also providing insights into turbulence parameters. Results reveal strong similarities between the two analyzed TIJs and single straight TIJs at the developed free-jet (or combined jet region for the co-flowing jets configuration) and impingement regions. The validation study demonstrates that relatively inexpensive RANS simulations in combination with typical k-ε turbulence models are capable of resolving the mean velocity field of the two investigated TIJ configurations with good accuracy, which is especially the case for the RNG k-ε turbulence model that yields a very good match with the PIV data throughout.