Flow, Turbulence and Combustion最新文献

The characteristics of a novel partially premixed pure hydrogen-oxygen combustion triple nozzle cluster unit are investigated by direct numerical simulation using a detailed chemical mechanism, mainly focusing on the mixing progress. Reactants are injected into the computational domain through a triple nozzle unit, with twin lateral oxidizer nozzles inclined inwards to impinge on a central fuel jet downstream of the inlets, creating a zone of intense turbulent mixing and heat release ignited by hot recirculated burnt products. The mixture fraction, normalized flame index and product-based reaction progress variable are analyzed to systematically describe reaction characteristics and the formation of premixed flame branches in the downstream neighborhood of the impingement point. Analysis of the transport budgets of elemental mixture fraction suggests that the improved overall mixing from jet impingement is due to an intensification of convective transport dispersing the fuel and oxidizer jets resulting in a larger diffusive interface. Turbulent combustion characteristics are explored for impingement angles of 60° and 75°, revealing a dominant effect on mixing intensity, heat concentration, flame length and alignment across premixed and non-premixed combustion regimes. These results shed light on the underlying reaction dynamics and parametric dependencies of the proposed multi-cluster configuration, providing a numerical reference for the development of advanced hydrogen partially premixed combustion systems utilizing jet impingement mixing.

Numerical experiments of targeted grid refinement are reported for stress-based wall-modeled large-eddy simulation (WMLES) of turbulent smooth-body separation. The flow over a Gaussian bump at a length-based (height-based) Reynolds number of 2 million (0.17 million) is simulated using an unstructured polyhedral solver on isotropic grids, and compared to high-fidelity Direct Numerical Simulation (DNS) data. The baseline coarse grid with 16 points per boundary-layer thickness in the upstream region does not capture smooth-body separation, while the baseline fine grid with double the resolution over half the boundary layer accurately captures the separated flow region indicating the importance of near-wall refinement. Refining the regions in the vicinity of the apex of the bump where the pressure gradient effects are expected to be dominant gave similar predictions to the baseline fine grid. Past DNS studies have noted the presence of an internal layer that begins to develop in the favorable pressure gradient region upstream of the bump apex, where its thickness is under 10% of the local boundary-layer thickness. However, the importance of sufficiently resolving the internal layer in predicting the flow separation accurately is unclear. Near-wall refinement just upstream of the apex targeted at the developing internal layer did not produce any flow separation, while near-wall refinement downstream of the apex in the vicinity of separation produced reasonable predictions, indicating that the latter is more critical for WMLES. While the present simulations contain uncertainties/errors due to the choice of grid topology, subgrid and wall model, these targeted grid refinement results provide useful insights to design optimal grids to capture turbulent smooth-body flow separation.

Based on the symmetry-theoretical analysis of the infinite hierarchy of multi-point moment equations, we rigorously derive the self-similar structure of velocity moments of arbitrary order in the turbulent round jet. Therein, we discover the dependency on a new parameter in the axial scaling laws. It has its roots in the statistical scaling symmetry which is connected to intermittency. This new parameter allows different states of self-similarity depending on the inflow condition, as postulated by George (in Arndt, R., George, W.K. (eds), Advances in Turbulence, pp. 39–73, 1989). However, the comparison with data fixes this parameter to zero, i.e. the classical scaling is recovered. Hence, intermittent effects are hidden when only considering the axial scaling laws. However, the influence of intermittency is still visible in the self-similar radial profiles. We find that a Gaussian-type curve fits the self-similar radial profiles of moments of arbitrary order of the axial velocity with high accuracy. The prefactors in the Gauss-function exponent exhibit a clear nonlinear dependency on the moment order, significantly deviating from a dimensional scaling. We attribute this to external or large-scale intermittency, which is likewise visible in the velocity PDF with increasing distance from the axis as we have found in a previous work (Nguyen and Oberlack, Phys. Rev. Fluids. 9(7), 074608, 2024). Furthermore, the statistical scaling symmetry reappears in the symmetry properties of the equations giving rise to the Gaussian profiles.

We perform Large-Eddy Simulations (LES) on the accelerating flow around streamwise-elongated rectangular cylinders with chord-to-depth ratios of 3:1 and 5:1 using Gaussian-type inflow accelerations of different intensities. The Reynolds numbers, defined with the freestream velocity and the crossflow dimension of the cylinder, range from Re = 17200 to Re = 65360. For both 3:1 and 5:1 rectangular cylinders the vortex shedding is characterized by constant-frequency time cells as observed in the literature for a square cylinder. For the 3:1 case, the Strouhal number variation range and the crossflow-force fluctuations within each time cell are the same for all cells. The results obtained under stationary inflow conditions for the rectangular 3:1 cylinder match well the statistical values computed in each time cell. On the other hand, for the 5:1 case, the cell-averaged recirculation region along the lateral side reduces in size during acceleration, leading to a narrower wake, decreased lift fluctuations, and higher Strouhal numbers. The shortening of the mean recirculation region with increasing Reynolds number for the 5:1 rectangular cylinder occurs at higher Reynolds numbers for accelerating inflows compared to stationary-inflow conditions. Finally, in agreement with what was observed for the square cylinder, for both considered aspect ratios the Strouhal number behaviors for accelerations of different severity collapse when plotted as a function of the Reynolds number.

Detailed modeling of combustion processes involving hydrogen poses challenges due to the high diffusivities of the light hydrogen molecule ((text{H}_2)) and radical (H) compared to other species. Thermodiffusion, also known as the Soret effect, describes the diffusive flux of species induced by gradients of temperature. The Soret effect becomes important if the fuel species is much lighter (or heavier) than the mean molar mass of the mixture. While accurate models for Soret diffusion exist, e.g. the multicomponent diffusion model, they are usually computationally expensive. In this work, modeling strategies for approximating Soret diffusion available in popular software packages as well as additional models from the literature are assessed in terms of their accuracy. Four methods for computing reduced collision integrals are compared and three formulations for the thermodiffusion coefficients are investigated for hydrogen and ammonia combustion. All tested approaches for computing collision integrals are found to yield good results. The approximate Soret diffusion model by Chapman and Cowling has shown the best prediction accuracy for typical hydrogen flames and ammonia/hydrogen blends when compared to the multicomponent diffusion model. Results are also compared to the model by Hirschfelder and Warnatz, implemented in the popular software packages Chemkin and STAR-CD, and the model by Bartlett and coworkers, which is available in Ansys Fluent, using different benchmark cases. This work shall serve as a review of implementation details of common models as well as a guideline for accurate and efficient Soret diffusion modeling in future hydrogen and ammonia combustion simulations.

This paper investigates the time-averaged and fluctuating aerodynamics of two slightly rough square-section prisms with rounded lateral edges of r/D = 0.16, positioned in-line at a centre-to-centre distance S/D = 4.0. For that purpose, distributions of the time-dependent surface pressures along both prisms’ mid-span cross-sections, the derived mean sectional pressure drag, lift, and pitch moment coefficients, as well as spanwise-integrated fluctuating fluid loads on the downstream prism and the frequency of the eddy shedding in its wake were measured simultaneously for Reynolds numbers between 100,000 and 7 million. Evaluation of the data and comparison with the results of an identical single prism revealed substantial changes of the flow over both prisms with Reynolds number for all studied incidence angles between ({0^ circ }) and ({45^ circ }) in the form of mutual aerodynamic influences due to proximity and wake-interference effects. For most studied flow parameters, a good agreement of the trends of the aerodynamic coefficients with incidence angle between the upstream and reference prism are obtained. Proximity effects are nevertheless clearly visible in the surface pressures, particularly at (alpha = 25.5{^ circ} ). Contrarily, wake-interference effects lead to a much lower and even negative drag on the downstream prism. The impingement of the shear layers coming from the upstream prism or of the eddies, formed in the gap between both prisms, dominates the aerodynamics of the downstream prism. This leads not only to transitions between the adjacent separation and wedge flow regimes, as well as between the co-shedding and reattachment flow states, but also triggers the vortex shedding processes between both prisms.

The Flame Spray Pyrolysis (FSP) process is a versatile and scalable method for controlled nanoparticle synthesis, with applications across various industrial sectors. FSP enables precise manipulation of nanoparticle properties, crucial for diverse applications. Carbon black (CB), important in emerging energy technologies like batteries and fuel cells, can be efficiently synthesized via FSP due to its controlled environment. Understanding CB formation is essential, given its impact on material properties. Computational Fluid Dynamics (CFD) simulations provide insights into nanoparticle formation and growth dynamics within FSP reactors, aiding in understanding process variables’ influence. This study models and analyzes CB nanoparticle formation within a specific enclosed FSP reactor with controlled coflow. The modeling approach is validated through a benchmarking ethylene sooting flame, and results are compared with existing experiments and previous models. The model accurately describes soot formation in the benchmarking case, providing reliable predictions of temperature, soot, and mean particle size. After validation, the model is extended to the FSP case. Two- and three-equation models describe soot and CB formation, with particle dynamics thoroughly discussed. The semi-empirical models assume spherical primary particles, and in the three-equation model, a population balance transport equation is solved for primary particle number density. Our investigation includes parametric sensitivity analysis, highlighting the significance of reliable model parameters, including the radiative effects of carbon particles. This work advances the understanding and predictive modeling of CB synthesis via FSP, promoting simpler alternative models compared to intricate quadrature-solved population balance approaches in the literature.

High-fidelity computational fluid dynamics (CFD) is widely used to understand turbulence and guide engineering design. While effective in predicting complex flow phenomena, CFD simulations at high Reynolds numbers require fine grids, resulting in prohibitive computational costs for parametric studies. To address this, we proposed a framework that uses machine learning (ML) to predict fine-grid results from coarse-grid simulations in a previous work. Coarsening the grid increases grid-induced error and affects turbulence prediction, necessitating a data-driven surrogate model to predict and correct these errors. A Random Forest (RF) regression was used to construct the surrogate model. The proposed framework was tested using a turbulent flow configuration consisting of an enclosed duct with a triangular bluff body acting as a blockage to the incoming flow. The chosen input features (IFs) were shown to be critical in predicting the turbulent flow field. In the current paper, we introduce further enhancements to the framework to allow it to be more robust in its prediction and application. These extensions also serve to reduce the computational cost of the approach without compromising on the accuracy. The proposed extensions include (i) adoption of Multivariate Random Forest (MRF) to replace the RF approach; (ii) identification and reduction of the IFs required for training and prediction using Variable IMportance Prediction (VIMP); (iii) predictions of flow field with changes in the bluff body configurations. The present paper aims to investigate the capability of the proposed extensions within the framework. We show that (i) the MRF allows for the accurate prediction of multiple outputs within one training instance but with a reduced computational cost relative to the RF approach. (ii) the impact of the IFs on the training can be understood via VIMP, and applying the MRF model with reduced IFs selected through VIMP does not cause any detriment to the accuracy of the prediction (iii) the extended framework trained with different bluff body configurations could be robustly applied to predict the flow field in an unseen configuration that is different from those trained. The predictive capability of the approach with these proposed extensions is demonstrated.

Scale-resolving simulations possess considerable benefits over modeled approaches because of their ability to access the underlying nonlinear fluid dynamics, and thus to predict not only the correct phenomenology, but also to generate insights on strategies to mitigate or eliminate undesirable features. The expense of resolving all pertinent turbulent scales becomes prohibitive however, as the size of the problem, typically measured by the Reynolds number based on a suitable set of reference parameters, becomes large, as is the case with flows of industrial interest such as full aircraft or their complex subsystems. This paper provides an assessment of scale-resolving methods, including some of the main benefits as well as barriers for use on large problems, together with a perspective on historical and recent trends that appear promising in the quest for routine industrial use. The factors that constitute the biggest hurdles to achieving acceptable wall-clock times and costs include meshing of complicated geometries, numerical schemes that are robust as well as accurate, suitable initial and boundary conditions, economical yet appropriate representation of near-wall turbulence, code parallelism, scalability and portability, and post-processing of the resulting big datasets. Considerations for these interrelated aspects are highlighted in the context of several 3D problems of increasing complexity, from wing sections without and with sweep, to aircraft wakes, propulsion subsystems, scramjet flowpaths and finally, full aircraft including empennages. Collectively, these examples feature the benefits of scale-resolving simulations. An illustrative approach that has reached a relatively high level of maturity using automatic mesh generation, a non-dissipative yet robust scheme, wall-modeling of turbulence, superior scalability and requiring little user intervention beyond providing the surface model, is used to demonstrate the potential of scale-resolving simulations for industry, achievable at modest cost and in reasonable wall-clock time.

Modeling the combustion of liquid oxygen (LOx) and methane (CH4) under subcritical conditions remains challenging due to the complex interactions between two-phase flow, atomization, and combustion processes. This study uses Large Eddy Simulation (LES) with a diffuse interface method to investigate the behavior of a LOx/GCH4 single-injector rocket combustor. The proposed multifluid approach captures phase transition phenomena while maintaining computational efficiency. Numerical results are compared against experimental data, highlighting the model ability to predict flow features, such as the wall pressure distribution and wall heat fluxes. This study emphasizes the importance of accounting for the liquid core, or the dense phase, within the Eulerian framework, rather than relying on Lagrangian injection models, resulting in enhanced predictions of flame topology and heat flux distributions. Although the model exhibits good agreement with experimental measurements, it underestimates heat flux by approximately 10% at the end of the domain, likely due to limitations in the chemical kinetics model. These results show that the diffuse interface method is a promising tool for the simulation of subcritical liquid rocket combustion.