Search Results

Detailed chemistry and turbulence-chemistry interaction need to be properly taken into account for a realistic combustion simulation of IC engines where advanced combustion modes, multiple injections and stratified combustion involve a wide range of combustion regimes and require a proper description of several phenomena such as auto-ignition, flame stabilization, diffusive combustion and lean premixed flame propagation. To this end, different approaches are applied and the most used ones rely on the well-stirred reactor or flamelet assumption. However, well-mixed models do not describe correctly flame structure, while unsteady flamelet models cannot easily predict premixed flame propagation and triple flames. A possible alternative for them is represented by transported probability density functions (PDF) methods, which have been applied widely and effectively for modeling turbulent reacting flows under a wide range of combustion regimes.

A new multi-zone model for the simulation of HCCI engine is here presented. The model includes laminar and turbulent diffusion and conduction exchange between the zones and the last improvements on the numerical aspects. Furthermore, a new strategy for the zone discretization is presented, which allows a better description of the near-wall zones. The aim of the work is to provide a fast and reliable model for carrying out chemical analysis with detailed kinetic schemes. A preliminary sensitivity analysis allows to verify that 10 zones are a convenient number for a good compromise between the computational effort and the description accuracy. The multi-zone predictions are then compared with the CFD ones to find the effective turbulence parameters, with the aim to describe the near-wall phenomena, both in a reactive and non-reactive cases.

Multi-dimensional models represent today consolidated tools to simulate the combustion process in HCCI and diesel engines. Various approaches are available for this purpose, it is however widely accepted that detailed chemistry represents a fundamental prerequisite to obtain satisfactory results when the engine runs with complex injection strategies or advanced combustion modes. Yet, integrating such mechanisms generally results in prohibitive computational cost. This paper presents a comprehensive methodology for fast and efficient simulations of combustion in internal combustion engines using detailed chemistry. For this purpose, techniques to tabulate the species reaction rates and to reduce the chemical mechanisms on the fly have been coupled.

Partially premixed combustion (PPC) can be applied to decrease emissions and increase fuel efficiency in direct injection, compression ignition (DICI) combustion engines. PPC is strongly influenced by the mixing of fuel and oxidizer, which for a given fuel is controlled mainly by (a) the fuel injection, (b) the in-cylinder flow, and (c) the geometry and dynamics of the engine. As the injection timings can vary over a wide range in PPC combustion, detailed knowledge of the in-cylinder flow over the whole intake and compression strokes can improve our understanding of PPC combustion. In computational fluid dynamics (CFD) the in-cylinder flow is sometimes simplified and modeled as a solid-body rotation profile at some time prior to injection to produce a realistic flow field at the moment of injection. In real engines, the in-cylinder flow motion is governed by the intake manifold, the valve motion, and the engine geometry.

A three dimensional numerical simulation of the ECN “Spray A” is presented. Both primary and secondary breakup of the spray are included. The fuel is n-Dodecane. The n-Dodecane kinetic mechanism is modeled using a skeletal mechanism that consists of 103 species and 370 reactions [9]. The kinetic mechanism is computationally heavy when coupled with three dimensional numerical simulations. Multidimensional chemistry coordinate mapping (CCM) approach is used to speedup the simulation. CCM involves two-way mapping between CFD cells and a discretized multidimensional thermodynamic space, the so called multidimensional chemistry coordinate space. In the text, the cells in the discretized multidimensional thermodynamic space are called zone to discriminate them from the CFD cells. In this way, the CFD cells which are at the similar thermodynamic state are identified and grouped into a unique zone. The stiff ODEs operates only on the zones containing at least one CFD cell.