The accuracy of large eddy simulation (LES) for turbulent combustion depends on suitably implemented numerical schemes and chemical mechanisms. In the original KIVA3V code, finite difference schemes such as QSOU (Quasi-second-order upwind) and PDC (Partial Donor Cell Differencing) cannot achieve good results or even computational stability when using coarse grids due to large numerical diffusion. In this paper, the MUSCL (Monotone Upstream-centered Schemes for Conservation Laws) differencing scheme is implemented into KIVA3V-LES code to calculate the convective term. In the meantime, Lu's n-heptane reduced 58-species mechanisms (Lu, 2011) is used to calculate chemistry with a parallel algorithm. Finally, improved models for spray injection are also employed. With these improvements, the KIVA3V-LES code is renamed as KIVALES-CP (Chemistry with Parallel algorithm) in this study. The resulting code was used to study the gas-liquid two phase jet and combustion under various diesel engine-like conditions in a constant volume vessel. The results show that using the MUSCL scheme can accurately capture the spray shape and fuel vapor penetration using even a coarse grid, in comparison with the Sandia experimental data. Similarly good results are obtained for three single-component fuels, i-Octane (C8H18), n-Dodecanese (C12H26), and n-Hexadecane (C16H34) with very different physical properties. Meanwhile the improved methodology is able to accurately predict ignition delay and flame lift-off length (LOL) under different oxygen concentrations from 10% to 21% with ambient density increasing from 14.8 kg/m(3) to 30.0 kg/m(3) and ambient temperatures from 850 K to 1300 K in a constant volume combustion chamber. With increasing oxygen concentration, the ignition delay time and consequently the flame LOL decrease, as the flame moves upstream as expected. On the other hand, reduction in the ambient temperature from 1000 K to 900 K retards the auto-ignition time and moves the burning location downstream under different oxygen concentrations. (C) 2015 Elsevier Ltd. All rights reserved.