Michael E. Mueller

Large eddy simulation of soot evolution in an aircraft combustor

An integrated kinetics-based Large Eddy Simulation (LES) approach for soot evolution in turbulent reacting flows is applied to the simulation of a Pratt & Whitney aircraft gas turbine combustor, and the results are analyzed to provide insights into the complex interactions of the hydrodynamics, mixing, chemistry, and soot. The integrated approach includes detailed models for soot, combustion, and the unresolved interactions between soot, chemistry, and turbulence. The soot model is based on the Hybrid Method of Moments and detailed descriptions of soot aggregates and the various physical and chemical processes governing their evolution. The detailed kinetics of jet fuel oxidation and soot precursor formation is described with the Radiation Flamelet/Progress Variable model, which has been modified to account for the removal of soot precursors from the gas-phase. The unclosed filtered quantities in the soot and combustion models, such as source terms, are closed with a novel presumed subfilter PDF approach ...

Large eddy simulation subfilter modeling of soot-turbulence interactions

The small-scale interactions between turbulence, chemistry, and soot have a profound effect on the soot formation, growth, and destruction processes in turbulent reacting flows. In this work, the small-scale subfilter interactions between turbulence and soot are modeled using a presumed subfilter PDF for the statistical moments of the soot number density function. Due to a very large (infinite) Schmidt number, soot is confined to very thin structures. In addition, soot is formed initially from Polycyclic Aromatic Hydrocarbons, which exhibit a strong sensitivity to the local scalar dissipation rate in the flow field. These interactions of soot with the gas-phase chemistry, molecular transport, and turbulence result in very high spatial and temporal intermittency. Therefore, the soot subfilter PDF is presumed to be a pair of delta distributions with a sooting mode and a non-sooting mode. In addition to the mean values of the scalars, one additional parameter is needed to specify this distribution. The presu...

LES of a sooting flame in a pressurized swirl combustor

Large eddy simulations (LES) of a model aircraft combustor at different pressure and operating conditions are conducted. Detailed models for soot formation and evolution is used along with minimally-dissipative numerical schemes in a fully unstructured mesh simulation of this complex geometry flow. Two slightly different swirl combustors, one operated at atmospheric pressure and the other at higher pressures (3-5 bars) are used. Both combustors are stabilized by strong swirl generated by inlet swirlers. In both cases, a set of secondary injection ports are present that mimic the rich-quench-lean combustor design. The objective of this work is to explore the role of soot trajectories on the intermittent nature of particulate generation. It is found that soot intermittency comes from the trajectories traveled by the soot particles. Only a small portion of the combustor exhibit conditions suitable for soot particle growth. Due to the chaotic nature of the turbulent flow, only a small fraction of the fluid elements pass through this region, which leads to spatial and temporal intermittency. Simulations at various pressures show that with increasing pressure, jet breakdown and mixing is more efficient, which somewhat curtails the generation of fuel-rich pockets needed for particle growth. It is also observed that intensity of soot-turbulence interaction becomes stronger as the operating pressure increases.

Lagrangian Analysis of Mixing and Soot Transport in a Turbulent Jet Flame

Soot particles are formed during rich combustion of fossil fuels in technical devices such as internal combustion

Comparative analysis of methods for heat losses in turbulent premixed flames using physically-derived reduced-order manifolds

Heat losses have the potential to substantially modify turbulent combustion processes, especially the formation of pollutants such as nitrogen oxides. The chemistry governing these species is strongly temperature sensitive, making heat losses critical for an accurate prediction. To account for the effects of heat loss in large eddy simulation (LES) using a precomputed reduced-order manifold approach, thermochemical states must be precomputed not only for adiabatic conditions but also over a range of reduced enthalpy states. However, there are a number of methods for producing reduced enthalpy states, which invoke different implicit assumptions. In this work, a set of a priori and a posteriori LES studies have been performed for turbulent premixed flames considering heat losses within a precomputed reduced-order manifold approach to determine the sensitivity to the method by which reduced enthalpy states are generated. Two general approaches are explored for generating these reduced enthalpy states and are compared in detail to assess any effects on turbulent flame structure and emissions. In the first approach, the enthalpy is reduced at the boundary of the one-dimensional (1D) premixed flame solution, resulting in a single enthalpy deficit for a single premixed flame solution. In the second approach, a variable heat loss source term is introduced into the 1D flame solutions by mimicking a real heat loss to reduce the post-flame enthalpy. The two approaches are compared in methane–air piloted turbulent premixed planar jet flames with different diluents that maintain a constant adiabatic flame temperature but experience different radiation heat losses. Both a priori and a posteriori results, as well as a chemical pathway analysis, indicate that the manner by which the heat loss is accounted for in the manifold is of secondary importance compared to other model uncertainties such as the chemical mechanism, except in situations where heat loss is unphysically fast compared to the flame time scale. A new theoretical framework to explain this insensitivity is also proposed, and its validity is briefly assessed.

Dynamic mode decomposition of a direct numerical simulation of a turbulent premixed planar jet flame: convergence of the modes

Dynamic Mode Decomposition (DMD) is a technique that enables investigation of unsteady and dynamic phenomena by decomposing data into coherent modes with corresponding growth rates and oscillatory frequencies. Because the method identifies structures unbiased by energy, it is particularly well suited to exploring dynamic processes having phenomena that span disparate temporal and spatial scales. In turbulent combustion, DMD has been previously applied to the analysis of narrowband phenomena such as combustion instabilities utilising both experimental and computational data. In this work, DMD is used as a tool to analyse broadband turbulent combustion phenomena from a three-dimensional direct numerical simulation of a low Mach number spatially-evolving turbulent planar premixed hydrogen/air jet flame. The focus of this investigation is on defining the metric of convergence of the DMD modes for broadband phenomena when both the temporal resolution and number of data snapshots can be varied independently. The residual is identified as an effective, even if imperfect, metric for judging convergence of the DMD modes. Other metrics – specifically, the convergence of the mode eigenvalues and the decay of the amplitudes of the modes – fail to capture convergence of the modes independently but do complete the information needed to evaluate the quality of the DMD analysis.

Numerically accurate computational techniques for optimal estimator analyses of multi-parameter models

Abstract Modelling unclosed terms in partial differential equations typically involves two steps: First, a set of known quantities needs to be specified as input parameters for a model, and second, a specific functional form needs to be defined to model the unclosed terms by the input parameters. Both steps involve a certain modelling error, with the former known as the irreducible error and the latter referred to as the functional error. Typically, only the total modelling error, which is the sum of functional and irreducible error, is assessed, but the concept of the optimal estimator enables the separate analysis of the total and the irreducible errors, yielding a systematic modelling error decomposition. In this work, attention is paid to the techniques themselves required for the practical computation of irreducible errors. Typically, histograms are used for optimal estimator analyses, but this technique is found to add a non-negligible spurious contribution to the irreducible error if models with multiple input parameters are assessed. Thus, the error decomposition of an optimal estimator analysis becomes inaccurate, and misleading conclusions concerning modelling errors may be drawn. In this work, numerically accurate techniques for optimal estimator analyses are identified and a suitable evaluation of irreducible errors is presented. Four different computational techniques are considered: a histogram technique, artificial neural networks, multivariate adaptive regression splines, and an additive model based on a kernel method. For multiple input parameter models, only artificial neural networks and multivariate adaptive regression splines are found to yield satisfactorily accurate results. Beyond a certain number of input parameters, the assessment of models in an optimal estimator analysis even becomes practically infeasible if histograms are used. The optimal estimator analysis in this paper is applied to modelling the filtered soot intermittency in large eddy simulations using a dataset of a direct numerical simulation of a non-premixed sooting turbulent flame.