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Although the application of cylinder pressure sensors to gain insight into the combustion process is not a novel topic itself, the recent availability of inexpensive in-cylinder pressure sensors has again prompted an upcoming interest for the utilization of the cylinder pressure signal within engine control and monitoring. Besides the use of the in-cylinder pressure signal for combustion analysis and control the information can also be used to determine related quantities in the exhaust or intake manifold. Within this work two different methods to estimate the pressure inside the exhaust manifold are proposed and compared. In contrary to first principle based approaches, which may require time extensive parameterization, alternative data driven approaches were pursued. In the first method a Principle Component Analysis (PCA) is applied to extract the cylinder pressure information and combined with a polynomial model approach.

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.

Modeling combustion of transportation fuels remains a difficult task due to the extremely large number of species constituting commercial gasoline and diesel. However, for this purpose, multi-component surrogate fuel models with a reduced number of key species and dedicated reaction subsets can be used to reproduce the physical and chemical traits of diesel and gasoline, also allowing to perform CFD calculations. Recently, a detailed surrogate fuel kinetic model, named C3 mechanism, was developed by merging high-fidelity sub-mechanisms from different research groups, i.e. C0-C4 chemistry (NUI Galway), linear C6-C7 and iso-octane chemistry (Lawrence Livermore National Laboratory), and monocyclic aromatic hydrocarbons (MAHs) and polycyclic aromatic hydrocarbons (PAHs) (ITV-RWTH Aachen and CRECK modelling Lab-Politecnico di Milano).

Cycle-To-Cycle Variability (CCV) must be properly considered when modeling the ignition process in SI engines operating with ultra-lean mixtures. In this work, a strategy to model the impact of the ignition type on the CCV was developed using the RANS approach for turbulence modelling, performing multi-cycle simulations for the power-cycle only. The spark-discharge was modelled through a set of Lagrangian particles, introduced along the sparkgap and interacting with the surrounding Eulerian gas flow. Then, at each discharge event, the velocity of each particle was modified with a zero-divergence perturbation of the velocity field with respect to average conditions. Finally, the particles velocity was evolved according to the Simplified Langevin Model (SLM), which keeps memory of the initial perturbation and applies a Wiener process to simulate the stochastic interaction of each channel particle with the surrounding gas flow.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

The thorough understanding of the effects due to the fuel direct injection process in modern gasoline direct injection engines has become a mandatory task to meet the most demanding regulations in terms of pollutant emissions. Within this context, computational fluid dynamics proves to be a powerful tool to investigate how the in-cylinder spray evolution influences the mixture distribution, the soot formation and the wall impingement. In this work, the authors proposed a comprehensive methodology to simulate the air-fuel mixture formation into a gasoline direct injection engine under multiple operating conditions. At first, a suitable set of spray sub-models, implemented into an open-source code, was tested on the Engine Combustion Network Spray G injector operating into a static vessel chamber. Such configuration was chosen as it represents a typical gasoline multi-hole injector, extensively used in modern gasoline direct injection engines.

A computational, three-dimensional approach to investigate the behavior of diesel soot particles in the micro-channels of wall-flow Diesel Particulate Filters is presented. The KIVA3V CFD code, already extended to solve the 2D conservation equations for porous media materials [1], has been enhanced to solve in 2-D and 3-D the governing equations for reacting and compressible flows through porous media in non axes-symmetric geometries. With respect to previous work [1], a different mathematical approach has been followed in the implementation of the numerical solver for porous media, in order to achieve a faster convergency as source terms were added to the governing equations. The Darcy pressure drop has been included in the Navier-Stokes equations and the energy equation has been extended to account for the thermal exchange between the gas flow and the porous wall.

Today, Direct-Injection systems are widely used on Spark-Ignition engines in combination with turbo-charging to reduce the fuel-consumption and the knock risks. In particular, the spread of Gasoline Direct Injection (GDI) systems is mainly related to the use of new generations of multi-hole, high-pressure injectors whose characteristics are quite different with respect to the hollow-cone, low-pressure injectors adopted in the last decade. This paper presents the results of an experimental campaign conducted on the spray produced by a GDI six-holes injector into a constant volume vessel with optical access. The vessel was filled with air at atmospheric pressure. Different operating conditions were considered for an injection pressure ranging from 3 to 20 MPa. For each operating condition, spray images were acquired by a CCD camera and then post processed to evaluate the spray penetration and cone angles.

The implementation and the combination of advanced boundary conditions and subgrid scale models for Large Eddy Simulation (LES) in the multi-dimensional open-source CFD code OpenFOAM® are presented. The goal is to perform reliable cold flow LES simulations in complex geometries, such as in the cylinders of internal combustion engines. The implementation of a boundary condition for synthetic turbulence generation upstream of the valve port and of the compressible formulation of the Wall-Adapting Local Eddy-viscosity sgs model (WALE) is described. The WALE model is based on the square of the velocity gradient tensor and it accounts for the effects of both the strain and the rotation rate of the smallest resolved turbulent fluctuations and it recovers the proper y₃ near-wall scaling for the eddy viscosity without requiring dynamic procedure; hence, it is supposed to be a very reliable model for ICE simulation.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

This paper is focused on the development and application of a CFD methodology that can be applied to predict the fuel-air mixing process in stratified charge, sparkignition engines. The Eulerian-Lagrangian approach was used to model the spray evolution together with a liquid film model that properly takes into account its effects on the fuel-air mixing process into account. However, numerical simulation of stratified combustion in SI engines is a very challenging task for CFD modeling, due to the complex interaction of different physical phenomena involving turbulent, reacting and multiphase flows evolving inside a moving geometry. Hence, for a proper assessment of the different sub-models involved a detailed set of experimental optical data is required. To this end, a large experimental database was built by the authors.

This paper exploits the possibilities of achieving an efficient performance optimization methodology to be applied to different spark ignition engine configurations. The objective of the task described here is to determine the combination of parameters which provides the highest volumetric efficiency and effective torque. The definition of general strategy requires first the identification and grouping of the geometric and operating variables to be optimized (duct diameters and lengths, valve timing, spark advance, etc…). The high number of possibilities entails critical choices to reduce, from an engineering design point of view before than from a mathematical point of view, the required computational time. Once proper thermo-fluid dynamic decisions are taken, the most efficient optimization methodology is required. The application of Design of Experiments techniques allows to screen the design space and give a first estimation of the optimal point.

The paper investigates the interaction between soil and tractor tires through a 2D numerical model. The tire is schematized as a rigid ring presenting a series of rigid tread bars on the external circumference. The outer profile of the tire is divided into a series of elements, each one able to exchange a normal and a tangential contact force with the ground. A 2D soil model was developed to compute the forces at the ground-tire interface: the normal force is determined on the basis of the compression of the soil generated by the sinking of the tire. The soil is modeled through a layer of springs characterized by two different stiffness for the loading (lower stiffness) and unloading (higher stiffness) condition. This scheme allows to introduce a memory effect on the soil which results stiffer and keeps a residual sinking after the passage of the tire. The normal contact force determines the maximum value of tangential force provided before the soil fails.

Objective of this work is the incorporation of the flame stretch effects in an Eulerian-Lagrangian model for premixed SI combustion in order to describe ignition and flame propagation under highly inhomogeneous flow conditions. To this end, effects of energy transfer from electrical circuit and turbulent flame propagation were fully decoupled. The first ones are taken into account by Lagrangian particles whose main purpose is to generate an initial burned field in the computational domain. Turbulent flame development is instead considered only in the Eulerian gas phase for a better description of the local flow effects. To improve the model predictive capabilities, flame stretch effects were introduced in the turbulent combustion model by using formulations coming from the asymptotic theory and recently verified by means of DNS studies. Experiments carried out at Michigan Tech University in a pressurized, constant-volume vessel were used to validate the proposed approach.

The scope of the work presented in this paper was to apply the latest open source CFD achievements to design a state of the art, direct-injection (DI), heavy-duty, natural gas-fueled engine. Within this context, an initial steady-state analysis of the in-cylinder flow was performed by simulating three different intake ducts geometries, each one with seven different valve lift values, chosen according to an estabilished methodology proposed by AVL. The discharge coefficient (Cd) and the Tumble Ratio (TR) were calculated in each case, and an optimal intake ports geometry configuration was assessed in terms of a compromise between the desired intensity of tumble in the chamber and the satisfaction of an adequate value of Cd. Subsequently, full-cycle, cold-flow simulations were performed for three different engine operating points, in order to evaluate the in-cylinder development of TR and turbulent kinetic energy (TKE) under transient conditions.

Extensive prior art within the Engine Combustion Network (ECN) using a Bosch single axial-hole injector called ‘Spray A’ in constant-volume vessels has provided a solid foundation from which to evaluate modeling tools relevant to spray combustion. In this paper, a new experiment using a Bosch three-hole nozzle called ‘Spray B’ mounted in a 2.34 L heavy-duty optical engine is compared to sector-mesh engine simulations. Two different approaches are employed to model combustion: the ‘well-mixed model’ considers every cell as a homogeneous reactor and employs multi-zone chemistry to reduce the computational time. The ‘flamelet’ approach represents combustion by an ensemble of laminar diffusion flames evolving in the mixture fraction space and can resolve the influence of mixing, or ‘turbulence-chemistry interactions,’ through the influence of the scalar dissipation rate on combustion.

The development of thermally durable zeolite NH3/Urea-SCR formulations coupled with that of high porosity filters substrates has opened the way to integrate PM and NOx control into a single device, namely an SCR-coated Diesel Particulate Filter (SCRF). A few experimental works are already present in the literature regarding SCRF systems, mainly addressing the DeNOx performances of the system (in both presence and absence of soot) under both steady state and transient conditions. The purpose of the present work is to perform a simulation study focused on phenomena which are expected to play key roles in SCRF systems, such as coupling of reaction and diffusion phenomena, soot effect on DeNOx activity, SCR coating effect on soot regeneration and filtration efficiency and competition between soot oxidation and DeNOx processes involving NO2.

Partially premixed compression ignition combustion is one of the low temperature combustion techniques which is being actively investigated. This approach provides a significant reduction of both soot and NOx emissions. Comparing to the homogeneous charge compression ignition mode, PPCI combustion provides better control on ignition timing and noise reduction through air-fuel mixture stratification which lowers heat release rate compared to other advanced combustion modes. In this work, CFD simulations were conducted for a low and a high air-fuel mixture stratification cases on a light-duty optical engine operating in PPCI mode. Such conditions for PRF70 as fuel were experimentally achieved by injection timing and spray targeting at similar thermodynamic conditions.

A detailed understanding of Gasoline Direct Injection (GDI) techniques applied to spark-ignition (SI) engines is necessary as they allow for many technical advantages such as increased power output, higher fuel efficiency and better cold start performances. Within this context, the extensive validation of multi-dimensional models against experimental data is a fundamental task in order to achieve an accurate reproduction of the physical phenomena characterizing the injected fuel spray. In this work, simulations of different Engine Combustion Network (ECN) Spray G conditions were performed with the Lib-ICE code, which is based on the open source OpenFOAM technology, by using a RANS Eulerian-Lagrangian approach to model the ambient gas-fuel spray interaction.

Direct-injection represents a consolidated technology to increase performance and efficiency in spark-ignition engines. It reduces the knock tendency and makes engine downsizing possible through the use of turbocharging. Better control of CO and HC emissions at cold-start is also ensured since there is no wall-impingement in the intake port. However, to take advantages of all the theoretical benefits derived from GDI technology, detailed investigations of both fuel-air mixing and combustion processes are necessary to extend the stratified charge operations in the engine map and to reduce soot emissions, that are now severely regulated by emission standards. In this work, the authors developed a CFD methodology to investigate and optimize the fuel-air mixing process in direct-injection, spark-ignition engines. The Eulerian-Lagrangian approach is used to model the evolution of the fuel spray emerging from a multi-hole injector.