Multi-Scale Screening of Diesel Surrogate Mechanisms for Combustion, NOx, and Late-Cycle Species in a Methanol–Diesel Marine Engine

Methanol is a promising low-carbon fuel for large marine engines, but reliable simulation of methanol–diesel combustion depends on selecting diesel-surrogate chemistry that remains credible for both ignition and emissions. Four diesel-surrogate mechanisms were therefore assessed through engine-scale CFD validation and controlled homogeneous-reactor calculations before application to a low-speed two-stroke marine engine. At the diesel-only full-load validation point, all four mechanisms reproduced the measured pressure history, although their combustion-phasing, fuel-consumption, and NOx predictions differed. LLNL 3.0 gave the closest peak pressure and CA50, whereas the Pei mechanism provided the most balanced agreement across pressure, phasing, fuel consumption, and NOx. Closed adiabatic constant-volume calculations at 960 K, 160 bar, and φ = 1.0 revealed substantial differences in ignition delay and radical evolution, confirming that similar engine pressure traces can conceal distinct intrinsic kinetic responses. Pei was consequently applied to cases with 0%, 50%, 75%, and 90% methanol energy substitution at the baseline full-load boundary conditions. As only the diesel-only condition was experimentally validated, the substitution results represent relative model predictions rather than validated absolute values. Relative to diesel-only operation, 50% substitution advanced CA50 by 5.02 °CA, increased indicated thermal efficiency from 48.4% to 52.3%, and increased predicted NOx by 92.5%. At higher substitution, this response weakened: the 90% case returned CA50 and NOx close to the diesel baseline and strongly reduced CO, whereas predicted unburned methanol and formaldehyde reached their maxima at 75% substitution. These results show that mechanism screening is essential before interpreting methanol-substitution effects and reveal an efficiency–NOx–incomplete-oxidation trade-off under the modeled full-load condition.