Understanding forced ignition in turbulence is relevant to the development of next generation highefficiency, low-emission engines. However, the dynamic of ignition kernel evolution under very intense turbulence conditions has still not been fully understood due to the complex interactions between turbulent eddies and the ignition kernel. The traditional view of turbulence effects on ignition kernel formation is that turbulence renders ignition more difficult due to turbulence dissipation and the transition in the combustion mode. However, this classic conclusion is recently challenged by the discovery of turbulence facilitated ignition in mixtures with Lewis number sufficiently greater than unity [1-3]. According to the latest findings, in the presence of turbulence, the otherwise spherical flame with a uniform, positive, curvature will be wrinkled, leading to an embryonic flame structure with both locally positive and negative curvatures. For mixtures with Lewis number sufficiently greater than unity, the wrinkled flame kernel segments with negative stretch can enhance reaction rate through differential diffusion and move away from incipient extinction to serve as local ignition sources for successful flame propagation. Therefore, the effects of turbulence on ignition kernel stretch are brought into sight. Ignition of reactants with sufficiently large Lewis numbers by an energy deposition is a common scenario in spark-ignition engines, which mainly burn lean heavy hydrocarbon/air mixtures. So far, none of the available models can describe this experimental phenomenon in these mixtures. Therefore, it is necessary to understand the detailed mechanism of turbulence effects on ignition kernel evolution in turbulent mixtures. For detailed investigation of turbulence facilitated ignition, threedimensional (3D) direct numerical simulations need to be performed to assess the turbulence-chemistry interaction with respect to the experimental conditions of Wu et al. [1] and Shy et al. [2]. These comprehensive simulations require high computational capacity as all time and length scales of the flow field and the chemical reactions need to be resolved. The findings will later on be used to derive simplified models to reduce computational costs.