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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 Relevant published and unpublished work from prior ECN workshops is reviewed.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.

Many concepts of premixed diesel combustion at reduced temperatures have been investigated over the last decade as a means to simultaneously decrease engine-out particle and oxide of nitrogen (NO ) emissions. To overcome the trade-off between simultaneously low particle and NO emissions versus high "diesel-like" combustion efficiency, a new dual-fuel technique called Reactivity Controlled Compression Ignition (RCCI) has been researched. In the present study, particle size distributions were measured from RCCI for four gasoline:diesel compositions from 65%:35% to 84%:16%, respectively. Previously, fuel blending (reactivity control) had been carried out by a port fuel injection of the higher volatility fuel and a direct in-cylinder injection of the lower volatility fuel. With a recent mechanical upgrade, it was possible to perform injections of both fuels directly into the combustion chamber.

The effects of different Research Octane Number [RON] fuels on a multi-cylinder light-duty compression ignition [CI] engine were investigated at light load conditions. Experiments were conducted on a GM 1.9L 4-cylinder diesel engine at Argonne National Laboratory, using two different fuels, i.e., 75 RON and 93 RON. Emphasis was placed on 5 bar BMEP load, 2000 rev/min engine operation using two different RON fuels, and 2 bar BMEP load operating at 1500 rev/min using 75 RON gasoline fuel. The experiments reveal difficulty in controlling combustion at low load points using the higher RON fuel. In order to explain the experimental trends, simulations were carried out using the KIVA3V-Chemkin Computational Fluid Dynamics [CFD] Code. The numerical results were validated with the experimental results and provided insights about the engine combustion characteristics at different speeds and low load conditions using different fuels.

Advanced combustion systems that simultaneously address PM and NOx while retaining the high efficiency of modern diesel engines, are being developed around the globe. One of the most difficult problems in the area of advanced combustion technology development is the control of combustion initiation and retaining power density. During the past several years, significant progress has been accomplished in reducing emissions of NOx and PM through strategies such as LTC/HCCI/PCCI/PPCI and other advanced combustion processes; however control of ignition and improving power density has suffered to some degree - advanced combustion engines tend to be limited to the 10 bar BMEP range and under. Experimental investigations have been carried out on a light-duty DI multi-cylinder diesel automotive engine. The engine is operated in low temperature combustion (LTC) mode using 93 RON (Research Octane Number) and 74 RON fuel.

In automotive industry it has been a challenge to retain diesel-like thermal efficiency while maintaining low emissions. Numerous studies have shown significant progress in achieving low emissions through the introduction of common-rail injection systems, multiple injections and exhaust gas recirculation and by using a high octane number fuel, like gasoline, to achieve adequate premixing. On the other hand, low temperature combustion strategies, like HCCI and PCCI, have also shown promising results in terms of reducing both NOx and soot emissions simultaneously. With the increasing capacity of computers, multi-dimensional CFD engine modeling enables a reasonably good prediction of combustion characteristics and pollutant emissions, which is the motivation behind the present research. The current research effort presents an optimization study of light-duty compression ignition engine performance, while meeting the emission regulation targets.

An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline (termed GDICI for Gasoline Direct-Injection Compression Ignition) in the low temperature combustion (LTC) regime is presented. As an aid to plan engine experiments at full load (16 bar IMEP, 2500 rev/min), exploration of operating conditions was first performed numerically employing a multi-dimensional CFD code, KIVA-ERC-Chemkin, that features improved sub-models and the Chemkin library. The oxidation chemistry of the fuel was calculated using a reduced mechanism for primary reference fuel combustion. Operation ranges of a light-duty diesel engine operating with GDICI combustion with constraints of combustion efficiency, noise level (pressure rise rate) and emissions were identified as functions of injection timings, exhaust gas recirculation rate and the fuel split ratio of double-pulse injections.

Several diffusion combustion scaling models were experimentally tested in two geometrically similar single-cylinder diesel engines with a bore diameter ratio of 1.7. Assuming that the engines have the same in-cylinder thermodynamic conditions and equivalence ratio, the combustion models primarily change the fuel injection pressure and engine speed in order to attain similar performance and emissions. The models tested include an extended scaling model, which scales diffusion flame lift-off length and jet spray penetration; a simple scaling model, which only scales spray penetration at equal mean piston speed; and a same speed scaling model, which holds crankshaft rotational velocity constant while also scaling spray penetration. Successfully scaling diffusion combustion proved difficult to accomplish because of apparent differences that remained in the fuel-air mixing and heat transfer processes.

A vaporization model for realistic multi-component fuel sprays is described. The equilibrium at the interface between liquid droplets and the surrounding gas is obtained based on the UNIFAC method, which considers non-ideal molecular interactions that can greatly enhance or suppress the vaporization of the components in the system compared to predictions from ideal mixing using Raoult's Law, especially for polar fuels. The present results using the UNIFAC method are shown to be able to capture the azeotropic behaviors of polar molecule blends, such as mixtures of benzene and ethanol, benzene and iso-propanol, and ethanol and water [1]. Predicted distillation curves of mixtures of ethanol and multi-component gasoline surrogates are compared to those from experiments, and the model gives good improvements on predictions of the distillation curves for initial ethanol volume fractions ranging from 0% to 100%.

RNG k-ε closure turbulence dissipation equations are evaluated employing the CFD code KIVA-3V Release 2. The numerical evaluations start by considering simple jet flows, including incompressible air jets and compressible helium jets. The results show that the RNG closure turbulence model predicts lower jet tip penetration than the "standard" k-ε model, as well as being lower than experimental data. The reason is found to be that the turbulence kinetic energy is dissipated too slowly in the downstream region near the jet nozzle exit. In this case, the over-predicted R term in RNG model becomes a sink of dissipation in the ε-equation. As a second step, the RNG turbulence closure dissipation models are further tested in complex engine flows to compare against the measured evolution of turbulence kinetic energy, and an estimate of its dissipation rate, during both the compression and expansion processes.

Resolution of droplet-scale processes occurring within engine sprays in multi-dimensional Computational Fluid Dynamics (CFD) simulations is not possible because impractically refined numerical meshes or time steps would be required. As a result, simulations that use coarse meshes and large time steps suffer from inaccurate predictions of mass, momentum and energy transfer between the spray drops and the combustion chamber gas, or poor prediction of droplet breakup and collision and coalescence processes. Several new spray models have been proposed to address these deficiencies, including use of an unsteady gas jet model to improve momentum transfer predictions in under-resolved regions of the spray, a vapor particle model to minimize numerical diffusion effects, and a Radius of Influence drop collision model to ensure consistent collision computations on different meshes.

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.