Large eddy simulation of multi-regime turbulent combustion with modal partially stirred reactor models

The complex interactions among turbulence, combustion and spray in liquid-fuel burners are modeled and simulated via a new two-phase Lagrangian-Eulerian-Lagrangian large eddy simulation (LES) methodology. In this methodology, the spray is modeled with a Lagrangian mathematical/computational method which allows two-way mass, momentum and energy coupling between phases. The subgrid gas-liquid combustion is based on the two-phase filtered mass density function (FMDF) that has several advantages over “conventional” two-phase combustion models. The LES/FMDF is employed in conjunction with non-equilibrium reaction and droplet models. Simulations of turbulent combustion in a spray-controlled double-swirl burner are conducted via LES/FMDF. The generated results are used for better understanding of spray combustion in realistic turbulent flow configurations. The effects of spray angle, mass loading ratio, fuel type, droplet size distribution, wall and inflow/outflow conditions on the flow and combustion are investigated. The LES/FMDF predictions are shown to be consistent with the experimental results.

Advances in high-performance computational capabilities enable scientific simulations with increasingly realistic physical representations. This situation is especially true of turbulent combustion involving multiscale interactions between turbulent flow, complex chemical reaction, and scalar transport. A fundamental understanding of combustion processes is crucial to the development and optimization of next-generation combustion technologies operating with alternative fuels, at higher pressures, and under less stable operating conditions, such as highly dilute, stratified mixtures. Direct numerical simulations (DNS) of turbulent combustion resolving all flow and chemical features in canonical configurations are used to improve fundamental understanding of complex flow processes and to provide a database for the development and validation of combustion models. A description of the DNS solver and its optimization for use in massively parallel simulations is presented. Recent DNS results from a series of three combustion configurations are presented: soot formation and transport in a nonpremixed ethylene jet flame, the effect of fuel stratification in methane Bunsen flames, and extinction and reignition processes in nonpremixed ethylene jet flames.

<div class="section abstract"><div class="htmlview paragraph">Downsizing or higher compression ratio of SI engines is an appropriate way to achieve considerable improvements of part load fuel efficiency. As the compression ratio directly impacts the engine cycle thermal efficiency, it is important to increase the compression ratio in order to reduce the specific fuel consumption. However, when operating a highly boosted / downsized SI engine at full load, the actual combustion process deviates strongly from the ideal Otto cycle due to the increased effective loads requiring ignition timing delay to suppress abnormal combustion phenomena such as engine knocking. This means that for an optimal design of an SI engine between balances must be found between part load and full load operation. If the knocking characteristic can be accurately predicted beforehand when designing the combustion chamber, a reduction of design time and /or an increase in development efficiency would be possible. A turbulent combustion simulation is required to estimate the pressure and temperature trace in the cylinder for knocking analysis.</div><div class="htmlview paragraph">In this research, the verification for the turbulent combustion and knocking were done by using the detailed chemistry solver with multi-zone modeling integrated into CONVERGE CFD code. Thereby, it was found that a reduced reaction model can reproduce turbulent combustion and knocking phenomenon under some operation conditions. The verification results show that the pressure trace in the cylinder, Knocking timing and position can be validated with experiment results accurately.</div></div>

A combustion model based on the flame surface density (FSD) concept is developed and implemented for large eddy simulation of turbulent nonpremixed combustion of wood pyrolysis gas and air. In this model, the filtered reaction rate ω̇̄α of species α is estimated as the product of the consumption rate per unit surface area ṁα and the filtered FSD Σ̄. This approach is attractive since it decouples the chemical problem from the description of the turbulence combustion interaction. The filtered FSD is modeled as the product of the conditional filtered gradient of mixture fraction and the filtered probability density function. This approach is validated from direct numerical simulation (DNS) using spatial filtering operation. Results show that the proposed FSD model provides a good description for the filtered reaction rate of wood pyrolysis gas. Temperature predicted by large eddy simulation agrees well with that filtered from DNS data.

This paper presents an analysis of the discretization errors in the non-equilibrium models for the subfilter variance of the mixture fraction, a key quantity to model in large eddy simulation (LES) of turbulent mixing and combustion. Two discretely distinct formulations of the non-equilibrium models that solve the transport equations to obtain the subfilter variance, i.e., the second moment transport equation (STE) and the variance transport equation (VTE), are analyzed. By deriving discrete equations for the evolution of subfilter variance by the two formulations, it is seen that the difference originates primarily from the product rule of differentiation applied to the scalar convection term, which does not hold discretely. LES of scalar mixing in a planar jet is performed to illustrate the outcome of the analysis. Results show that the discrete product rule error is significant and of the same order as the production and dissipation terms on average. A priori analysis using direct numerical simulation (DNS) data for scalar mixing in homogeneous isotropic turbulence is also performed. From the analysis, it is seen that the VTE model under-predicts the subfilter variance, whereas the STE model over-predicts it substantially with sharp oscillations.

The conditional filtering method is proposed as a subfilter combustion model for large-eddy simulation (LES) of turbulent nonpremixed combustion. The novel method is based on conditional filtering of a reactive scalar field and an extension of conditional moment closure (CMC) for LES. Filtering conditioned on isosurfaces of the mixture fraction is adopted to resolve small-scale mixing and chemical reactions in nonpremixed combustion. The conditionally filtered equations are derived and the closure assumptions are discussed. A priori tests are performed using direct numerical simulation data for reacting mixing layers. The primary closure assumption on the subfilter flux in mixture fraction space is shown to work much better than the corresponding closure for the Reynolds averaged CMC due to resolved large-scale fluctuations of the scalar dissipation rate and of reactive scalars. Results show that first-order closure of the reaction rate performs well except for the boundaries of flame holes. In the boundaries of flame holes, fluctuations of reactive scalars around the conditionally filtered values are large enough for the effects of higher-order correlations to be significant. The accuracy of the first-order closure is less sensitive to the level of local extinction than that of first-order CMC, since large-scale fluctuations of reactive scalars on isosurfaces of the mixture fraction are resolved. This shows that extinction processes occur primarily over length scales comparable to the large scales of the turbulence. The integrated conditional filtering approach is introduced to reduce the computational cost and to resolve the low probability problem in the conditional filtering method. While the assumption of homogeneity in the integration direction is not as good as in the conditional average, the integrated formulation is shown to represent the extinction process caused by large-scale fluctuations of the scalar dissipation rate quite well.

Many modeling approaches in large eddy simulation (LES) of turbulent combustion employ a projection of the thermochemical state onto a low-dimensional manifold within state space to reduce the number of transported variables and hence computational cost. Flamelet-generated manifolds (FGM) is an example of a well-established, physics-based approach, but increasingly, principal component analysis (PCA) is being used as a data-driven method for generating manifold models. For both approaches, the nonlinear relationship between the location on the predefined manifold and the outputs of interest, such as reaction rates, can be tabulated or encoded in a neural network. This work proposes a new approach for manifold modeling that extends these existing approaches. A modified neural network structure simultaneously encodes the definition of the manifold variables, the nonlinear mapping, and the subfilter closure for LES. This allows all three of these aspects of the model to be co-optimized, generating a model from any source of combustion thermochemical state data. The manifold parameterizing variables are constrained to be linear combinations of species, as in FGM and PCA-based models, to aid in interpretability and implementation. For LES, subfilter variances of the manifold variables are also included as inputs. Two types of a priori analysis are performed to evaluate the new approach. In the first, the model is trained on data from one-dimensional premixed flames. In this case, the approach recovers the behavior of flamelet-based manifold approaches, and in fact slightly improves performance by identifying an optimized progress variable. The approach is also applied to data from direct numerical simulations of spherical ignition kernels in isotropic turbulence. For any specified manifold dimensionality, the new approach provides substantially lower prediction errors than a PCA-based model developed from the same data set. Additionally, the LES formulation of the new approach can provide accurate predictions for filtered reaction rates across a variety of filter widths.

We have developed adaptive high-resolution methods for numerical simulations of turbulent combustion of chemical/biological (C/B) clouds in thermobaric explosions. The code is based on our (Adaptive Mesh Refinement) technology that was used successfully to simulate distributed energy release in explosions, such as: afterburning in TNT explosions and turbulent combustion of Shock-Dispersed Fuel (SDF) charges in confined explosions. Versions of the methodology specialized for low-Mach number flows have also been developed and extensively validated on a number of laboratory scale laminar and turbulent flames configurations. In our formulation, we model the gas phase by the multi-component form of the reacting gas-dynamics equations, while the particle-phase is modeled by continuum mechanics laws for 2-phase reacting flows, as formulated by Nigmatulin. Mass, momentum, and energy interchange between phases are taken into account using Khasainov's model. Both the gas and particle phase conservation laws are integrated with their own second-order Godunov algorithms that incorporate the non-linear wave structure associated with such hyperbolic systems. Specialized ordinary differential equation (ODE) methods are used to integrate chemical kinetics and interphase terms. Adaptive grid methods are used to capture the energy-bearing scales of the turbulent flow (the MILES approach of J. Boris) without resorting to traditional turbulence models. The code is built on an framework that manages the grid hierarchy. Our work-based load-balancing algorithm is designed to run efficiently on massively-parallel computers. Gas-phase combustion in the explosion products (EP) cloud is modeled in the fast-chemistry limit, while Aluminum particle combustion in the EP cloud is based on the finite-rate empirical burning law of Ingignoli. The thermodynamic properties of the components are specified by the Cheetah code. At the 19th HPCUG meeting in 2009, we summarized recent progress in: AMR Code Simulations of Turbulent Combustion in Confined and Unconfined SDF Explosions. These models were used successfully to simulate the simultaneous after-burning of booster products and combustion of Aluminum (Al) in SDF explosion clouds. Computed pressure histories were shown to be in excellent agreement with the data -- thereby proving the validity of our combustion modeling of such explosions. This year, the modeling has been extended to include the mixing and combustion of C/B clouds in such explosion fields. Here we will establish how the cloud consumption by combustion depends on chamber environments.

Analysis of dynamic models for large eddy simulations of turbulent premixed combustion

We propose a model for assessing the unresolved wrinkling factor in the large eddy simulation of turbulent premixed combustion. It relies essentially on a power-law dependence of the wrinkling factor on the filter size and an original expression for the ‘active’ corrugating strain rate. The latter is written as the turbulent strain multiplied by an efficiency function that accounts for viscous effects and the kinematic constraint of Peters. This yields functional expressions for the fractal dimension and the inner cut-off length scale, the latter being (i) filter-size independent and (ii) consistent with the Damköhler asymptotic behaviours at both large and small Karlovitz numbers. A new expression for the wrinkling factor that incorporates finite Reynolds number effects is further proposed. Finally, the model is successfully assessed on an experimental filtered database.

Implementation of a dynamic thickened flame model for large eddy simulations of turbulent premixed combustion

A subgrid scale model for large eddy simulations of turbulent premixed combustion is developed and validated. The approach is based on the concept of artificially thickened flames, keeping constant the laminar flame speed sl0. This thickening is simply achieved by decreasing the pre-exponential factor of the chemical Arrhenius law whereas the molecular diffusion is enhanced. When the flame is thickened, the combustion–turbulence interaction is affected and must be modeled. This point is investigated here using direct numerical simulations of flame–vortex interactions and an efficiency function E is introduced to incorporate thickening effects in the subgrid scale model. The input parameters in E are related to the subgrid scale turbulence (velocity and length scales). An efficient approach, based on similarity assumptions, is developed to extract these quantities from the resolved velocity field. A specific operator is developed to exclude the dilatational part of the velocity field from the estimation of turbulent fluctuations. The combustion model is then implemented in a compressible parallel finite volume–element solver able to handle hybrid grids to simulate a lateral injections combustor (LIC). Results are in agreement with the available experimental data.

A laboratory-scale chamber is convenient for combustion scenarios in the practical analysis of industrial explosions and devices such as internal combustion engines. The safety risks in hazardous areas can be assessed and managed during accidents. Increased hydrogen usage in renewable energy production requires increased attention to the safety issues since hydrogen produces higher explosion overpressures and flame speed and can cause more damage than methane or propane. This paper reports numerical simulation of turbulent hydrogen combustion and flame propagation in the University of Sydney's small-scale combustion chamber. It is used for the investigation of turbulent premixed propagating flame interaction with several solid obstacles. Obstructions in the direction of flow cause a complex flame front interaction with the turbulence generated ahead of it. For numerical analysis, OpenFOAM CFD software was chosen, and a custom-built turbulent combustion solver based on the progress variable model—flameFoam—was used. Numerical results for validation purposes show that the pressure behaviour and flame propagation obtained using RANS and TFC models were well reproduced. The interaction between larger-scale flow features and flame dynamics was obtained corresponding to the experimental or mode detailed LES modelling results from the literature. The analysis revealed that as the propagating flame reached and interacted with obstacles and the recirculation wake was created behind solid obstacles, leaving traces of an unburned mixture. The expansion of flames due to narrow vents generates turbulent eddies, which cause wrinkling of the flame front.

This study is concerned with 3D RANS simulation of turbulent flow and combustion in a 5 MW commercial gas turbine combustor. The combustor under consideration is a reverse flow, dry low NOx type, in which methane and air are partially mixed inside swirl vanes. We evaluated different turbulent combustion models to provide insights into mixing, temperature distribution, and emission in the combustor. Validation is performed for the models in STAR-CCM+ against the measurement data for a simple swirl flame (http://public.ca.sandia.gov/TNF/swirlflames.html). The standard k-ε model with enhanced wall treatment is employed to model turbulent swirl flow, whereas eddy break-up (EBU), presumed probability density function laminar flamelet model, and partially premixed coherent flame model (PCFM) are tried for reacting flow in the combustor. Independent simulations are carried out for the main and pilot nozzles to avoid flashback and to provide realistic inflow boundary conditions for the combustor. Geometrical details such as air swirlers, vane passages, and liner holes are all taken into account. Tested combustion models show similar downstream distributions of the mean flow and temperature, while EBU and PCFM show a lifted flame with stronger effects of swirl due to limited increase in axial momentum by expansion.

Large eddy simulation (LES)/ Probability Density Function (PDF) approaches are now well established and can be used for simulating challenging turbulent combustion configurations with strong turbulence chemistry interactions. Transported PDF methods are known to be computationally expensive compared to flamelet-like turbulent combustion models. The pre-partitioned adaptive chemistry (PPAC) methodology was developed to address this cost differential. PPAC entails an offline preprocessing stage, where a set of reduced models are generated starting from an initial database of representative compositions. At runtime, this set of reduced models are dynamically utilised during the reaction fractional step leading to computational savings. We have recently combined PPAC with in-situ adaptive tabulation (ISAT) to further reduce the computational cost. We have shown that the combined method reduced the average wall-clock time per time step of large-scale LES/particle PDF simulations of turbulent combustion by 39%. A key assumption in PPAC is that the initial database used in the offline stage is representative of the compositions encountered at runtime. In our previous study this assumption was trivially satisfied as the initial database consisted of compositions extracted from the turbulent combustion simulation itself. Consequently, a key open question remains as to whether such databases can be generated without having access to the turbulent combustion simulation. Towards answering this question, in the current work, we explore whether the compositions for forming such a database can be extracted from computationally-efficient low-dimensional simulations such as 1D counterflow flames and partially stirred reactors. We show that a database generated using compositions extracted from a partially stirred reactor configuration leads to performance comparable to the optimal case, wherein the database is comprised of compositions extracted directly from the LES/PDF simulation itself.