Fossil fuel reserves are projected to be decreasing, and emission regulations are becoming more stringent due to increasing atmospheric pollution. Alternative fuels for power generation in industrial gas turbines are thus required able to meet the above demands. Examples of such fuels are synthetic gas, blast furnace gas and coke oven gas. A common characteristic of these fuels is that they are multi-component fuels, whose composition varies greatly depending on their production process. This implies that their combustion characteristics will also vary significantly. Thus, accurate and yet flexible enough combustion sub-models are required for such fuels, which are used during the design stage, to ensure optimum performance during practical operating conditions.

Most combustion sub-model development and validation is based on Direct Numerical Simulation (DNS) studies. DNS however is computationally expensive. This, has so far limited DNS to single-component fuels such as methane and hydrogen. Furthermore, the majority of DNS conducted to date used one-step chemistry in 3D, and skeletal chemistry in 2D only. The need for 3D DNS using skeletal chemistry is thus apparent. In this study, an accurate reduced chemical mechanism suitable for multi-component fuel-air combustion is developed from a skeletal mechanism. Three-dimensional DNS of a freely propagating turbulent premixed flame is then conducted using both mechanisms to shed some light into the flame structure and turbulence-scalar interaction of such multi-component fuel flames.

It is found that for the multi-component fuel flame heat is released over a wider temperature range contrary to a methane flame. This, results from the presence of individual species reactions zones which do not all overlap. The performance of the reduced mechanism is also validated using the DNS data. Results suggest it to be a good substitute of the skeletal mechanism, resulting in significant time and memory savings. The flame markers commonly used to visualize heat release rate in laser diagnostics are found to be inadequate for the multi-component fuel flame, and alternative markers are proposed. Finally, some popular mean reaction rate closures are tested for the multi-component fuel flame. Significant differences are observed between the models’ performance at the highest turbulence level considered in this study. These arise from the chemical complexity of the fuel, and further parametric studies using skeletal chemistry DNS would be useful for the refinement of the models.