The present work is concerned with the simulation of combustion, emission formation and fuel effects in Diesel engines. The simulation process is built around a zero-dimensional (0D) direct injection stochastic reactor model (DI-SRM), which is based on a probability density function (PDF) approach. An emphasis is put on the modelling of mixing time to improve the representation of turbulence-chemistry interactions in the 0D DI-SRM. The mixing time model describes the intensity of mixing in the gas-phase for scalars such as enthalpy and species mass fraction. On a crank angle basis, it governs the composition of the gas mixture that is described by PDF distributions for the scalars. The derivation of the mixing time is based on an extended heat release analysis that has been fully automated using a genetic algorithm. The predictive nature of simulations is achieved through the parametrisation of the mixing time model with known engine operating parameters such as speed, load and fuel injection strategy. It is shown that crank angle dependency of the mixing time improves the modelling of local inhomogeneity in the gas-phase for species mass fraction and temperature. In combination with an exact treatment of the non-linearity of reaction kinetics, it enables an accurate prediction of the rate of heat release, in-cylinder pressure and exhaust emissions, such as nitrogen oxides, unburned hydrocarbons and soot, from differently composed fuels. The method developed is particularly tailored for computationally efficient applications that focus on the details of reaction kinetics and the locality of combustion and emission formation in Diesel engines.