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This work concerns the modelling of soot formation process in diesel spray combustion under engine-like conditions. The key aim is to investigate the soot formation characteristics at different ambient temperatures. Prior to simulating the diesel combustion, numerical models including a revised multi-step soot model is validated by comparing to the experimental data of n-dodecane fuel in which the associated chemistry is better understood. In the diesel spray simulations, a single component n-heptane mechanism and the multi-component Diesel Oil Surrogate (DOS) model are adopted. A newly developed C16-based model which comprises skeletal mechanisms of n-hexadecane, heptamethylnonane, cyclohexane and toluene is also implemented. Comparisons of the results show that the simulated liftoff lengths are reasonably well-matched to the experimental measurement, where the relative differences are retained to below 18%.

This work is an extension to a previously reported work on chemical kinetic mechanism reduction scheme for large-scale mechanisms. Here, Perfectly Stirred Reactor (PSR) was added as a criterion of data source for mechanism reduction instead of using only auto-ignition condition. As a result, a reduced n-hexadecane mechanism with 79 species for diesel fuel surrogate was successfully derived from the detailed mechanism. Following that, the reduced n-hexadecane mechanism was validated under auto-ignition and PSR conditions using zero-dimensional (0-D) closed homogeneous batch reactor in CHEMKIN-PRO software. Agreement was achieved between the reduced and detailed mechanisms in ignition timing predictions and the reduced n-hexadecane mechanism was able to reproduce species concentration profiles with a maximum error of 40%. Accordingly, two-dimensional (2-D) Computational Fluid Dynamic (CFD) simulations were performed to study the spray combustion phenomena within a constant volume bomb.

Modeling the combustion process of a diesel-biodiesel fuel spray in a 3-dimensional (3D) computational fluid dynamics (CFD) domain remains challenging and time-consuming despite the recent advancement in computing technologies. Accurate representation of the in-cylinder processes is essential for CFD studies to provide invaluable insights into these events, which are typically limited when using conventional experimental measurement techniques. This is especially true for emerging new fuels such as biodiesels since fundamental understanding of these fuels under combusting environment is still largely unknown. The reported work here is dedicated to evaluating the Adaptive Local Mesh Refinement (ALMR) approach in OpenFOAM® for improved simulation of reacting biodiesel fuel spray. An in-house model for thermo-physical and transport properties is integrated to the code, along with a chemical mechanism comprising 113 species and 399 reactions.

The aim of this study is to evaluate the existing chemical kinetic mechanism reduction techniques. From here, an appropriate reduction scheme was developed to create compact yet comprehensive surrogate models for both diesel and biodiesel fuels for diesel engine applications. The reduction techniques applied here were Directed Relation Graph (DRG), DRG with Error Propagation, DRG-aided Sensitivity Analysis, and DRG with Error Propagation and Sensitivity Analysis. Nonetheless, the reduced mechanisms generated via these techniques were not sufficiently small for application in multi-dimensional computational fluid dynamics (CFD) study. A new reduction scheme was therefore formulated. A 68-species mechanism for biodiesel surrogate and a 49-species mechanism for diesel surrogate were successfully derived from the respective detailed mechanisms.

This paper reports the developmental work of skeletal biodiesel surrogate mechanisms specifically for integration with computational fluid dynamics (CFD) solvers. The fuels of interests here were methyl esters of coconut, palm and soybean. Their combustion kinetics were collectively represented by a detailed mechanism with appropriate components of a biodiesel surrogate (methyl decanoate/methyl-9-decenoate) and a diesel surrogate (n-heptane). As a result of computational complexity induced by the detailed mechanism with 3299 species and 10806 reactions, several mechanism reduction methods were employed such as directed relation graph, isomer lumping and temperature sensitivity analysis. Three different skeletal mechanisms, with the inclusion of low- and high-temperature chemistries, were built as a result of different governing reaction pathways in each fuel.