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The formation of carbon nanoparticles in flames involves a nucleation step that remains poorly understood. Experimentally, carbon nuclei formation is known to depend strongly on the electrical aspects of combustion, but modes of interaction between charged species in the flame and carbon precursors have yet to be found. We present evidence for flexoelectrically polarized aromatics contributing to carbon nanoparticulate nucleation. We imaged the nascent nanoparticles using high resolution transmission electron microscopy, which revealed that the majority of aromatics in the early carbon nanoparticles are fullerene-like and curved. The curvature induces a significant molecular flexoelectric dipole moment in the polyaromatic hydrocarbons. This electric polarization allows these molecules to strongly interact with chemi-ions produced during combustion, which we demonstrate using electronic structure calculations. The results indicate that the physical interaction between fullerene-like polar aromatics and che...

© 2018 The Combustion Institute. In this paper, we consider the impact of polar curved polycyclic aromatic hydrocarbons (cPAH) on the process of soot formation by employing electronic structure calculations to determine the earliest onset of curvature integration and the binding energy of curved homodimers. The earliest (smallest size) onset of curvature integration was found to be a six ring PAH with at least one pentagonal ring. The σ bonding in the presence of pentagons led to curvature, however, the π bonding strongly favored a planar geometry delaying the onset of curvature and therefore the induction of a flexoelectric dipole moment. The binding energies of cPAH dimers were found to be of similar magnitude to flat PAH containing one or two pentagons, with an alignment of the dipole moments vectors. For the more curved structures, steric effects reduced the dispersion interactions to significantly reduce the interaction energy compared with flat PAH. Homogeneous nucleation of cPAH at flame temperatures then appears unlikely, however, significant interactions are expected between chemi-ions and polar cPAH molecules suggesting heterogeneous nucleation should be explored.

A newly developed experimental set-up for studying liquid hydrocarbon combustion in the well-established Yale burner was used to investigate the correlation between fuel composition and its sooting propensity. Soot particle size distributions (PSDs) and flame temperatures along the centreline of an n-heptane/toluene co-flow diffusion flame are reported. The results are compared to soot temperature and volume fraction profiles obtained using colour ratio pyrometry. The addition of toluene (0, 5, 10, and 15 mol%) to heptane moved soot inception to lower heights above the burner (HAB). The earlier inception extended the soot growth zone in the toluene-laden flames, leading to larger soot primary and agglomerate particles. Toluene addition had little influence on the maximum soot number density, indicating that the observed increase in soot volume fraction can mainly be attributed to the increase in particle size. The reported PSDs inside a vapour-fed diffusion flame are the first of their kind and provide a comprehensive dataset for future studies of combustion chemistry and soot particle models. National Research Foundation (NRF) Accepted version This project is funded by the National Research Foundation (NRF), Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme.

The occurrence of deposits on fuel injectors used in gasoline direct injection engines can lead to fuel preparation and combustion events which lie outside of the intended engine design envelope. The fundamental mechanism for deposit formation is not well understood. The present work describes the development of a computational model and its application to a direct injection gasoline engine in order to describe the formation of injector deposits and quantify their effect on injector operation. The formation of fuel-derived deposits at the injector tip and inside the nozzle channel is investigated. After the end of an injection event, a fuel drop may leak out of the nozzle and wet the injector tip. The model postulates that the combination of high temperature and the presence of NOx produced by the combustion leads to the initiation of a reaction between the leaked fuel and the oxygen dissolved in it. Subsequently, the oxidation products attach at the injector surface as a polar proto-deposit phase. The rate of deposit formation is predicted for two limiting mechanisms: adsorption and precipitation. The effects of the thermal conditions within the engine and of the fuel composition are investigated. Branched alkanes show worse deposit formation tendency than n-alkanes. The model was also used to predict the impact of injector nozzle deposit thickness on the rate of fuel delivery and on the temperature of the injector surface. NRF (Natl Research Foundation, S’pore) Accepted version

The influence of the chemical structure on the sooting characteristics of some paraffin class hydrocarbons which are found in gasoline and diesel fuel is studied experimentally. The experiment involves the combustion of the paraffin in a wick-fed burner. Differential mobility spectrometry is used to measure the particle size distribution (PSD) at different flame heights. The wick-fed laminar diffusion flame is sampled at the tip; the flame height is modified systematically from small heights to large heights. Normal, iso and cyclo paraffins PSDs evolve in a similar way with flame height. At very low flame heights the PSD is unimodal, but rapidly evolves into a multi-modal one. The total number of particles peaks at small heights, and then decreases as flame height increase until it approaches constant values for all considered fuels. The mean soot particle diameter increases with flame height until a height where a maximum is achieved and sustained. Among each type of fuel, a systematic decrease in the maximum mean soot particle diameter was observed as the number of carbon atoms in the molecule increased. At all flame heights, comparing fuels with the same carbon number, cyclic paraffins presented the largest mean soot particles sizes, followed by iso-paraffins and the smallest particles for normal paraffins.

In this work, the formation of soot in a Direct Injection Spark Ignition (DISI) engine is simulated using the Stochastic Reactor Model (SRM) engine code. Volume change, convective heat transfer, turbulent mixing, direct injection and flame propagation are accounted for. In order to simulate flame propagation, the cylinder is divided into an unburned, entrained and burned zone, with the rate of entrainment being governed by empirical equations but combustion modelled with chemical kinetics. The model contains a detailed chemical mechanism as well as a highly detailed soot formation model, however computation times are relatively short. The soot model provides information on the morphology and chemical composition of soot aggregates along with bulk quantities, including soot mass, number density, volume fraction and surface area. The model is first calibrated by simulating experimental data from a Gasoline Direct Injection (GDI) Spark Ignition (SI) engine. The model is then used to simulate experimental data from the literature, where the numbers, sizes and derived mass particulate emissions from a 1.83 L, 4-cylinder, 4 valve production DISI engine were examined. Experimental results from different injection and spark timings are compared with the model and the qualitative trends in aggregate size distribution and emissions match the exhaust gas measurements well.

This paper presents experimental results and a new computational model that investigate cycle to cycle variations (CCV) in a spark ignition (SI) engine. An established stochastic reactor model (SRM) previously used to examine homogeneous charge compression ignition (HCCI) combustion has been extended by spark initiation, flame propagation and flame termination sub-models in order to simulate combustion in SI engines. The model contains a detailed chemical mechanism but relatively short computation times are achieved. The flame front is assumed to be spherical and centred at the spark location, and a pent roof and piston bowl geometry are accounted for. The model is validated by simulating the pressure profile and emissions from an iso-octane fuelled single cylinder research engine that showed low CCV. The effects of key parameters are investigated. Experimental results that show cycle to cycle fluctuations in a four-cylinder naturally aspirated gasoline fuelled SI engine are presented. The model is then coupled with GT-Power, a one-dimensional engine simulation tool, which is used to simulate the breathing events during a multi-cycle simulation. This allows an investigation of the cyclic fluctuations in peak pressure. The source and magnitude of nitric oxide (NO) emissions produced by different cycles are then investigated. It was found that faster burning cycles result in increased NO emissions compared with cycles that have a slower rate of combustion and that more is produced in the early stages of combustion compared with later in the cycle. The majority of NO was produced via the thermal mechanism just after combustion begins.

In this work, we present a detailed model for the formation of soot in internal combustion engines describing not only bulk quantities such as soot mass, number density, volume fraction, and surface area but also the morphology and chemical composition of soot aggregates. The new model is based on the Stochastic Reactor Model (SRM) engine code, which uses detailed chemistry and takes into account convective heat transfer and turbulent mixing, and the soot formation is accounted for by SWEEP, a population balance solver based on a Monte Carlo method. In order to couple the gas-phase to the particulate phase, a detailed chemical kinetic mechanism describing the combustion of Primary Reference Fuels (PRFs) is extended to include small Polycyclic Aromatic Hydrocarbons (PAHs) such as pyrene, which function as soot precursor species for particle inception in the soot model. Apart from providing averaged quantities as functions of crank angle like soot mass, volume fraction, aggregate diameter, and the number of primary particles per aggregate for example, the integrated model also gives detailed information such as aggregate and primary particle size distribution functions. In addition, specifics about aggregate structure and composition, including C/H ratio and PAH ring count distributions, and images similar to those produced with Transmission Electron Microscopes (TEMs), can be obtained. The new model is applied to simulate an n-heptane fuelled Homogeneous Charge Compression Ignition (HCCI) engine which is operated at an equivalence ratio of 1.93. In-cylinder pressure and heat release predictions show satisfactory agreement with measurements. Furthermore, simulated aggregate size distributions as well as their time evolution are found to qualitatively agree with those obtained experimentally through snatch sampling. It is also observed both in the experiment as well as in the simulation that aggregates in the trapped residual gases play a vital role in the soot formation process.

At the University of Cambridge, the formation of soot was studied in an n-heptane fuelled Homogeneous Charge Compression Ignition (HCCI) engine, operated at a rich equivalence ratio of 1.93, by means of in-cylinder snatch sampling as well as by applying a new engine model which features a highly detailed description of soot. This new computationally efficient model is capable of providing not only averaged quantities as functions of crank angle like soot mass, number density, volume fraction, aggregate diameter, and the number of primary particles per aggregate for example, but also aggregate and primary particle size distribution functions and additionally can give detailed information on aggregate morphology and chemical composition.

A previously developed Stochastic Reactor Model (SRM) is used to simulate combustion in a four cylinder in-line four-stroke naturally aspirated direct injection Spark Ignition (SI) engine modified to run in Homogeneous Charge Compression Ignition (HCCI) mode with a Negative Valve Overlap (NVO). A portion of the fuel is injected during NVO to increase the cylinder temperature and enable HCCI combustion at a compression ratio of 12:1. The model is coupled with GT-Power, a one-dimensional engine simulation tool used for the open valve portion of the engine cycle. The SRM is used to model in-cylinder mixing, heat transfer and chemistry during the NVO and main combustion. Direct injection is simulated during NVO in order to predict heat release and internal Exhaust Gas Recycle (EGR) composition and mass. The NOx emissions and simulated pressure profiles match experimental data well, including the cyclic fluctuations. The model predicts combustion characteristics at different fuel split ratios and injection timings. The effect of fuel reforming on ignition timing is investigated along with the causes of cycle to cycle variations and unstable operation. A detailed flux analysis during NVO unearths interesting results regarding the effect of NOx on ignition timing compared with its effect during the main combustion. © 2009 SAE International.

A storage/retrieval scheme has been implemented for a Stochastic Reactor Model (SRM) for Homogeneous Charge Compression Ignition (HCCI) engines which enables fast evaluation in transient multi-cycle simulations. The SRM models combustion, turbulent mixing, and convective heat transfer during the closed-volume part of the engine cycle employing detailed chemical kinetics. In contrast to previously developed storage/retrieval techniques which tabulate chemistry only, our method stores, retrieves, and interpolates output quantities of the entire internal combustion engine model, i.e. the SRM. These quantities include ignition timing, cumulative heat release, maximum pressure rise rate, and emissions of CO, CO2, unburnt hydrocarbons, and NOx, as functions of equivalence ratio, octane number, and inlet temperature for instance. The new tool is intended to be used for performing a variety of otherwise exceedingly expensive computational tasks such as multi-cycle multi-cylinder simulations, transient operation a...

The thermal decomposition of titanium tetraisopropoxide (TTIP) is investigated using quantum chemistry, statistical thermodynamics, and equilibrium composition analysis. A set of 981 Ti-containing candidate species are proposed systematically on the basis of the thermal breakage of bonds within a TTIP molecule. The ground state geometry, vibrational frequencies and hindrance potentials are calculated for each species at the B97-1/6-311+G(d,p) level of theory. Thermochemical data are computed by applying statistical thermodynamics and, if unknown, the standard enthalpy of formation is estimated using balanced reactions. Equilibrium composition calculations are performed under typical combustion conditions for premixed flames. The thermodynamically stable decomposition products for different fuel mixtures are identified. A strong positive correlation is found between the mole fractions of Ti species containing carbon and the TTIP precursor concentration.

In this paper, a new explicit algorithm for the numerical solution of homogeneous gas-phase combustion systems is proposed, which is shown to outperform the solver SENKIN by more than two orders of magnitude for moderate accuracy and very large systems in the high temperature regime. Further speedup is achieved by identifying and removing irrelevant reactions from the mechanism whilst retaining all species. We show that in terms of computational efficiency this brings about another factor of at least 5 at an acceptable loss of precision. Due to its immediate relationship to stochastic direct simulation, our new (deterministic) algorithm can also be used as an easily applicable tool for the reaction flow analysis of mechanisms. Another characteristic of our method is that reactions in partial equilibrium are effectively removed from the mechanism, which can be regarded as an automatic separation of the fast from the slow timescales. The new algorithm and its usefulness for the elimination of reactions are investigated numerically for a mechanism that models the combustion of n-decane at constant pressure and contains 1218 species and 4825 reversible reactions. Further advantages of our method are its exceptional simplicity of implementation and negligible start-up costs, both of which can be attributed to the explicit nature of the algorithm.

A dual-fuel approach to control combustion in HCCI engine is investigated in this work. This approach involves controlling the combustion heat release rate by adjusting fuel reactivity according to the conditions inside the cylinder. Experiments were performed on a single-cylinder research engine fueled with different ratios of primary reference fuels and operated at different speed and load conditions, and results from these experiments showed a clear potential for the approach to expand the HCCI engine operation window. Such potential is further demonstrated dynamically using an optimized stochastic reactor model integrated within a MATLAB code that simulates HCCI multi-cycle operation and closed-loop control of fuel ratio. The model, which utilizes a reduced PRF mechanism, was optimized using a multi-objective genetic algorithm and then compared to a wide range of engine data. The optimization objectives, selected based on relevance to this control study, were the cylinder pressure history, pressure rise rate, and gross indicated mean effective pressure (IMEPg). The closed-loop control of fuel ratio employed in this study is based on a search algorithm, where the objective is to maximize the gross work rather than directly controlling the combustion phasing to match preset values. This control strategy proved effective in controlling pressure rise rate and combustion phasing while not needing any prior knowledge or preset information about them. It also ensured that the engine was always delivering maximum work at each operation condition. This is in a sense analogous to the use of maximum brake torque timing in spark-ignition engines. The dynamic model allowed for convenient examination of the dual-fuel approach beyond the limits tested in the experiments, and thus helped in performing an overall assessment of the approach’s potential and limitations.

In this paper, we outline the future of modelling in reaction engineering. Specifically, we use the example of particulate emission formation in internal combustion engines to demonstrate what modelling can achieve at present, and to illustrate the ultimately inevitable steps that need to be taken in order to create a new generation of engineering models.

A detailed chemical model was implemented in the KIVA3V two dimensional CFD code to investigate the effects of the spray cone angle and injection timing on the PCCI combustion process and emissions in an optical research diesel engine. A detailed chemical model for Primary Reference Fuel (PRF) consisting of 157 species and 1552 reactions was used to simulate diesel fuel chemistry. The model validation shows good agreement between the predicted and measured pressure and emissions data in the selected cases with various spray angles and injection timings. If the injection is retarded to -50° ATDC, the spray impingement at the edge of the piston corner with 100° injection angle was shown to enhance the mixing of air and fuel. The minimum fuel loss and more widely distributed fuel vapor contribute to improving combustion efficiency and lowering uHC and CO emissions in the engine idle condition. Finally, the coupling of CFD and multi-zone Stochastic Reactor Model (SRM) was demonstrated to show improvement in CO and uHC emissions prediction.

Two-stage fuel direct injection (DI) has the potential to expand the operating region and control the autoignition timing in a Diesel fuelled homogeneous charge compression ignition (HCCI) engine. In this work, to investigate the dual-injection HCCI combustion, a stochastic reactor model, based on a probability density function (PDF) approach, is utilized. A new wall-impingement sub-model is incorporated into the stochastic spray model for direct injection. The model is then validated against measurements for combustion parameters and emissions carried out on a four stroke HCCI engine. The initial results of our numerical simulation reveal that the two-stage injection is capable of triggering the charge ignition on account of locally rich fuel parcels under certain operating conditions, and consequently extending the HCCI operating range. Furthermore, both simulated and experimental results on the effect of second injection timing on combustion indicate that there exists an optimal second injection timing to gain maximum engine output work for a given fuel split ratio.

We numerically simulate a Homogeneous Charge Compression Ignition (HCCI) engine fuelled with a blend of ethanol and diethyl ether by means of a stochastic reactor model (SRM). A 1D CFD code is employed to calculate gas flow through the engine, whilst the SRM accounts for combustion and convective heat transfer. The results of our simulations are compared to experimental measurements obtained using a Caterpillar CAT3401 single-cylinder Diesel engine modified for HCCI operation. We consider emissions of CO, CO2 and unburnt hydrocarbons as functions of the crank angle at 50% heat release. In addition, we establish the dependence of ignition timing, combustion duration, and emissions on the mixture ratio of the two fuel components. Good qualitative agreement is found between our computations and the available experimental data. The performed numerical simulations predict that the addition of diethyl ether to ethanol neither spreads out the combustion nor lowers light-off temperatures significantly, both in accordance with experimental observations.

New stochastic algorithms for the numerical solution of systems of ordinary differential equations (ODEs) are proposed. Furthermore, a correspondence principle is established between these algorithms, which are based on the theory of Markov jump processes, and deterministic schemes. For one of the proposed stochastic algorithms, a detailed numerical study of some of its properties is carried out using examples from high-temperature homogeneous gas-phase combustion. One deterministic method yielded by our correspondence principle is used to shed light on various aspects of the considered stochastic algorithm. In addition, we use the widespread stiff ODE-solver package DASSL for comparison. Advantages of our methods include among others their exceptional simplicity of implementation and negligible start-up costs. For a large system at moderate accuracy requirements, the proposed stochastic algorithms exhibit computational efficiency in the same order of magnitude as implicit solvers, assuming multiple runs. In view of the stiffness of the considered systems and the explicit nature of our algorithms, this is rather surprising. Limitations of our methods concerning the choice of system, initial conditions, and accuracy requirements are also addressed.

Regulations on emissions from diesel and gasoline fuelled engines are becoming more stringent in all parts of the world. Hence there is a great deal of interest in developing advanced combustion systems that offer the efficiency of a diesel engine, but with low PM and NOx. One promising approach is that of Partially-Premixed Compression Ignition (PPCI) or Low Temperature Combustion (LTC). Using this approach, PM can be reduced in compression ignition engines by promoting the mixing of fuel and air prior to combustion. This paper describes the application of an advanced combustion simulator for fuels, combustion and emissions to analyze the key processes which occur in PPCI combustion mode. A detailed chemical kinetic model with advanced PM population balance submodel is employed in a PPCI engine context to examine the impact of ignition resistance on combustion, mixing, ignition and emissions. The ignition and combustion of a diesel-like fuel (n-heptane) and low octane gasoline-like fuel (84PRF) are compared using the model highlighting how the diesel-like fuel ignites at very rich equivalence ratios whereas the gasoline-like fuel ignites on the lean side. Sources of exhaust gas emissions are also identified. For the first time, a computational model is employed to demonstrate the trade-off between low PM emissions and “over-mixing” (sensitivity to cycle-to-cycle variations and combustion instability) for a full range of fuels with increasing ignition resistance. These results are then discussed noting that conventional hydrocarbon fuels which fulfill either a conventional diesel or gasoline standards are not necessarily consistent with those required to run an engine operating at it’s optimal point in terms of PM emissions and combustion stability.

In recent decades, “physics-based” gas-dynamics simulation tools have been employed to reduce development timescales of IC engines by enabling engineers to carry out parametric examinations and optimisation of alternative engine geometry and operating strategy configurations using desktop PCs. However to date, these models have proved inadequate for optimisation of in-cylinder combustion and emissions characteristics thus extending development timescales through additional experimental development efforts. This research paper describes how a Stochastic Reactor Model (SRM) with reduced chemistry can be employed to successfully determine in-cylinder pressure, heat release and emissions trends from a diesel fuelled engine operated in compression ignition direct injection mode using computations which are completed in 147 seconds per cycle. The model was successfully validated against 46 steady state operating points in terms of in-cylinder pressure and exhaust gas emissions over a three dimensional matrix comprising ranges of EGR, boost pressure and injection timing. The resulting model was then employed to examine the local in-cylinder temperatures and equivalence ratios and to highlight the main sources of excessive exhaust gas emissions. With a view of identifying the optimal operating strategy, a parametric sweep comprised of 968 computations were then completed, the results of which were narrowed based on satisfying stable operating limits (i.e. peak pressure, knocking combustion). Excessive exhaust gas emissions were identified to highlight the most suitable regime for minimal emissions. Finally, the potential of this technology is examined by discussing aspects of engine development process which can be accelerated using the tool.