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This paper presents the simulation of in-cylinder stratified mixture formation, spray motion, combustion and emissions in a four-stroke and four valves direct injection spark ignition (DISI) engine with a pent-roof combustion chamber by the computational fluid dynamics (CFD) code. The Extended Coherent Flame Combustion Model (ECFM), implemented in the AVL-Fire codes, was employed. The key parameters of spray characteristics related to computing settings, such as skew angle, cone angle and flow per pulse width with experimental measurements were compared. The numerical analysis is mainly focused on how the tumble flow ratio and geometry of piston bowls affect the motion of charge/spray in-cylinder, the formation of stratified mixture and the combustion and emissions (NO and CO₂) for the wall-guided stratified-charge spark-ignition DISI engine.

The present work discusses a novel oxy-fuel combustion cycle utilized in compression ignition internal combustion engine. The most prominent feature of this cycle is that the air intake is replaced by oxygen; therefore nitric oxide (NOX) emission is eliminated. The enrichment of oxygen leads to higher flame speed and mass fraction consumption rate; on the other hand, the high concentration of oxygen presented during combustion will result in intense pressure rise rate which may cause severe damage to engine hardware. As water injection is already utilized in gasoline engine to control knocking, the utilization of water injection in optimizing oxy-fuel combustion process has been tested in this study. To understand the relationship between water injection strategy and cycle efficiency, computational fluid dynamics (CFD) simulations were carried out. The model was carefully calibrated with the experimental results; the errors were controlled within 3%.

Ammonia is employed as the carbon-free fuel in the future engine, which is consistent with the requirements of the current national dual-carbon policy. However, the great amount of NOx and unburned NH3/H2 in the exhaust emissions is produced from combustion of ammonia and is one kind of the most strictly controlled pollutants in the emission regulation. This paper aims to investigate the NOx and unburned NH3/H2 generative process and emission characteristics by CFD simulation during the engine combustion. The results show that the unburned ammonia and hydrogen emissions increase with an increase of equivalence ratio and hydrogen blending ratio. In contrast, the emission concentrations of NOx, NO, and NO2 decrease with the increasing of equivalence ratio, but increase with hydrogen blending ratio rising. The emission concentration of N2O is highly sensitive to the O/H group and temperature, and it is precisely opposite to that of NO and NO2.

Detailed knowledge of hydrocarbon fuel combustion chemistry has grown tremendously in recent years. However, the gap between detailed chemistry and computational fluid dynamics (CFD) remains, because of the high cost of solving detailed chemistry in a large number of computational cells. This paper presents the results of applying a suite of techniques aimed at closing this gap. The techniques include use of a surrogate blend optimizer and a guided mechanism reduction methodology, as well as advanced methods for efficiently and accurately coupling the pre-reduced kinetic models with the multidimensional transport equations. The advanced methods include dynamic adaptive chemistry (DAC) and dynamic cell clustering (DCC) algorithms.

Designing advanced, clean and fuel-efficient engines requires detailed understanding of fuel chemistry. While knowledge of fuel combustion chemistry has grown rapidly in recent years, the representation of conventional fossil fuels in full detail is still intractable. A popular approach is to use a model-fuel or surrogate blend that can mimic various characteristics of a conventional fuel. Despite the use of surrogate blends, there remains a gap between detailed chemistry and its utilization in computational fluid dynamics (CFD), due to the prohibitive computational cost of using thousands of chemical species in large numbers of computational cells. This work presents a set of software tools that help to enable the use of detailed chemistry in representing conventional fuels in CFD simulation. The software tools include the Surrogate Blend Optimizer and a suite of automated mechanism reduction strategies.

A methodology has been implemented to calculate local turbulent flame speeds for spark ignition engines accurately and on-the-fly in 3-D CFD modeling. The approach dynamically captures fuel effects, based on detailed chemistry calculations of laminar flame speeds. Accurately modeling flame propagation is critical to predicting heat release rates and emissions. Fuels used in spark ignition engines are increasingly complex, which necessitates the use of multi-component fuels or fuel surrogates for predictive simulation. Flame speeds of the individual components in these multi-component fuels may vary substantially, making it difficult to define flame speed values, especially for stratified mixtures. In addition to fuel effects, a wide range of local conditions of temperature, pressure, equivalence ratio and EGR are expected in spark ignition engines.