RATE-CONTROLLED CONSTRAINED EQUILIBRIUM: A BASIS FOR EFFECTIVE COUPLING OF COMPREHENSIVE CHEMICAL KINETICS AND CFD

Lead Research Organisation: Imperial College London
Department Name: Mechanical Engineering

Abstract

Modelling of combustion processes remains an outstanding technical problem with wide implications, both scientific and practical. By far the largest percentage of our energy is produced via combustion equipment such as internal combustion engines for cars, turbines for aircraft or industrial burners for power generation. These processes also account for the generation of a wide variety of pollutants, such as NOx and soot, as well as for the generation of greenhouse gases. It is widely acknowledged that there is large potential for improvement of those processes, resulting in great environmental benefits. Combustion modelling requires the coupling of fluid dynamics equations, solved numerically through a Computational Fluid Dynamics (CFD) code, with a comprehensive chemical kinetics model. Practical combustion devices are invariably turbulent, which necessitates a further element, the turbulence-chemistry interaction model. Coupling all of these elements results in a formidable computational problem, and the main cause of the bottleneck is the chemical kinetics part of the calculation. Comprehensive chemical kinetics include very large numbers of species and reactions: even for the simplest fuels, such as methane, more than 50 species are necessary, while for commercial fuels hundreds of species and reactions can easily be present. Each species introduces an additional differential equation to the problem, and integration is further hampered by the excessive stiffness that is often exhibited by such systems. Yet the incorporation of comprehensive mechanisms is essential if the formation of pollutants is to be predicted. The mathematical modelling of combustion can be significantly simplified by taking advantage of the time scale separation to assume that fast reactions, typically associated with intermediate species, are in a state of local equilibrium. The proposed research will explore a promising concept for deriving the low-dimensional models on the basis of time-scale separation: Rate-Controlled Constrained Equilibrium (RCCE). In this approach, the kinetically controlled species are allowed to evolve according to the relevant differential equations including the chemical kinetics of the original detailed mechanism, whilst the equilibrated species are determined by minimising the free energy of the mixture, subject to the additional constraints (apart from conservation of mass, energy and elements) that the kinetically controlled species must retain the concentrations given by the solution of their governing equations. Previous work by the authors has provided evidence that RCCE has the potential to develop into a method that is both theoretically rigorous and practically feasible for the implementation of large chemical mechanisms into CFD codes. Having established proof of concept, further work is now required to bring RCCE to the stage where it is ready for application in practical problems. Furthermore, several important questions about the fundamentals of RCCE remain unanswered, such as its relation to other methods of mechanism reduction such as Computational Singular Perturbation (CSP). The two methods are complementary and it is possible that a combination of them will prove a very powerful tool.
 
Description Modelling of combustion processes is an outstanding technical problem with wide implications, both scientific and practical. By far the largest percentage of our energy is produced via combustion equipment such as internal combustion engines for cars, turbines for aircraft or industrial burners for power generation. These processes also account for the generation of a wide variety of pollutants, such as NOx and soot, as well as for the generation of greenhouse gases. It is widely acknowledged that there is large potential for improvement of combustion processes, resulting in great environmental benefits. Combustion modelling requires coupling of fluid dynamics equations, solved numerically with a Computational Fluid Dynamics (CFD) code, with a comprehensive chemical kinetics model. Combustion processes are invariably turbulent, and their prediction requires a turbulence-chemistry interaction model. Coupling all of these elements results in a formidable computational problem, in which the main cause of the bottleneck is the chemical kinetics part of the calculation, where a very large numbers of species and reactions are involved, each species requiring an extra differential equation to be solved.

This project has made significant steps towards the realisation of the long-term aim of developing a methodology for computer modelling of reactive flows and pollutant production in realistic turbulent flow conditions. Central to this methodology is the concept of Rate-Controlled Constrained Equilibrium (RCCE) for deriving the low-dimensional models on the basis of time-scale separation. RCCE allows us to describe combustion using a model that, although derived from a comprehensive chemical mechanism, consists of much fewer variables. An important parameter in RCCE is the choice of the reduced variables, and for this reason we explored the potential of a synergy between RCCE and Computational Singular Perturbation (CSP) - a method for investigating the time scales associated with various chemical species and determining which ones should be retained in the RCCE-derived reduced mechanism. The concept proved very fruitful, and good results were obtained for the simulation of laminar premixed flames, an ideal test case to prove the value of the concept. Even the reduced model requires a significant amount of time to be integrated, however, and for this purpose we developed an approach based on Artificial Neural Networks (ANNs) for replacing the real-time integration of the RCCE differential equations with an algebraic model, trained with results from model computations. The development of a methodology for generating training sets for ANNs and the generation and training of them in an appropriate way for predicting the conditions encountered in turbulent flames was a major outcome of the project. The ANN approach was tested and excellent results were obtained.

The overall approach was finally applied to the simulation of turbulent flames in conjunction with a CFD code incorporating Large-Eddy-Simulation (LES) and the Stochastic Fields method for solving the transported Probability Density Function (PDF) approach to turbulence-chemistry coupling. These methods represent the state of the art in combustion modelling, but require excessive amounts of CPU time when used with comprehensive chemistry. The methodology developed here enabled us to perform LES-PDF simulations with reduced chemistry in a small fraction of the time required for the integration of complete kinetics, therefore proving that the simulation of turbulent combustion incorporating comprehensive models of both fluid dynamics and chemistry is feasible. The availability of computer models able to account for the combined effects of fluid dynamics, thermodynamics and chemistry in a comprehensive way has great potential to aid the engineers' efforts in designing more clean and environment friendly combustion equipment and processes.
Exploitation Route The findings of this project have led to developments in the incorporation of detailed chemical kinetics to CFD codes for turbulent reacting flows. This will enable both further developments in academic studies of turbulent combustion and improvements in combustion processes in industry, particularly for mitigation of pollutant emissions.
Sectors Energy,Environment
 
Description The outcomes from this research project have led to the development of methods and software tools incorporating methods for efficient modelling of combustion processes. These tools are currently being disseminated for use in the design of improved combustion devices, with view to energy saving and mitigation of pollutant emissions.
First Year Of Impact 2017
Sector Aerospace, Defence and Marine,Energy,Environment
Impact Types Economic