Auto-ignition and heat release of alternative engine fuels.

Diversification of energy sources and transport decarbonisation are growing concerns of modern societies. Alternative fuels play an important role in addressing these challenges. For the spark ignition (SI) engine, the propensity of the fuel and fuel blends to auto-ignite is a critical characteristic that limits engine efficiency, which can be assessed by the ignition delays (τi). Severity of knock is also dependent upon the duration of heat release rate - the excitation time (τe). In this thesis, detailed evaluations of τi and τe are employed to study the tendency of methane to detonate in comparison with other fuels, employing the detonation peninsula on the ξ/ɛ diagram. The ξ parameter is the ratio of acoustic to auto-ignitive velocity, whereas ε is the ratio of the acoustic wave resistance time in a hot spot to the τe. It is shown that stoichiometric methane/air exhibits very good anti-knock properties in comparison with other fuels under turbocharged engine running conditions. The changes in the auto-ignition behaviour caused by the progressive addition of n-butanol (at 10%, 20%, 40% and 85% vol n-butanol) to gasoline (RON 95, MON 86.6) and its toluene reference fuel (TRF) are studied computationally and experimentally in a rapid compression machine (RCM) under stoichiometric condition at 2 MPa and at 678-916 K. At low temperatures, n-butanol acts as an octane enhancer, reducing low temperature heat release and increasing ignition delays, with marginal additional effects for blends above 40%. This is supported by the results from ξ /ɛ diagram, where higher n-butanol blends lie further away from the developing detonation region. A brute-force sensitivity analysis of the surrogate model suggests that the main reaction inhibiting ignition at low temperatures is H abstraction from the α-site of n-butanol, even for the 10% blend. At higher temperatures, the behaviour reverses as the chain branching routes from H abstraction by OH from the γ-site of n-butanol and from the α-site by HO2 become more dominant, promoting ignition. For the lower blends, the largest discrepancies between simulations and experiments are found in the negative temperature coefficient (NTC) region, where a larger number of reactions contribute to the uncertainty in predicting τi. For the higher blends, the largest discrepancies occur at low temperatures, indicating that uncertainties within the low temperature n-butanol chemistry need to be resolved. Regarding τe, the addition of n-butanol to the TRF blends has a negligible effect. Furthermore, τe, is not influenced by NTC chemistry

EXPERIMENTAL AND MODELING STUDY OF IGNITION-RESISTANT FUELS

This research investigates relative ignition behavior of some oxygenated fuels and their blends with gasoline surrogates. It seeks to identify fuels with higher resistance to ignition and validate tentative kinetic models intended to predict their combustion chemistry. It also develops a method for simplified ignition delay time correlation that can allow for a more rapid estimation of the ignition behavior of a given fuel at known thermodynamic conditions. The work is motivated by the fact that in spark-ignition (SI) engines, increasing energy conversion efficiency through increasing the engine compression ratio is limited by the phenomenon of undesired autoignition known as engine knock. This is controlled by the chemical kinetics of the fuels which can be modified toward higher resistance using fuels of higher ignition resistance. In this study, the ignition behavior of the representative fuels is studied using both shock tube experiments and simulations of the kinetics of homogeneous chemical reactors. Specifically, we study: 1) propanol isomers, which are alcohols with three carbon atoms and promising alternative fuels for gasoline fuels; 2) MTBE and ETBE, which are effective ignition-resistant fuel components; 3) blends of a gasoline with ETBE or iso-propanol, to establish the kinetic interactions. The resulting experimental data are used to validate current chemical kinetics models of the individual fuels. To further facilitate the use of fuel blends suggested by this study, combined chemical kinetic models are developed of iso-octane as a gasoline surrogate and each of ignition resistant fuels identified. In order to reduce the computational cost of using the validated detailed models of the fuels studied, reduced kinetic models are developed. These reduced versions are of two kinds. The first uses the model reduction method known as Alternate Species Elimination (ASE) to derive smaller versions of the detailed models. The second reduction approach focuses on the prediction of the chemical time scale associated with ignition. Here a generalized ignition format is developed and detailed model simulations are used to obtain the constraining data. This makes it possible to predict ignition time scales based on knowledge of temperature, pressure, and composition of the combustible mixture. The work advances understanding of biofuels combustion by characterizing ignition properties of promising fuel additives and the effects of fuel blend on ignition. The resulting experimental data sets are useful for validating existing and future kinetic models. The combined models will allow for better insight into the combustion chemistry of ignition-resistant fuels formed from blending iso-octane with iso-propanol or ETBE

Flammability Characteristics of Combustible Vapor Mixtures from Bio Oil

Study of fire and explosion is very important mainly in industrial activities due to several accidents which have been reported in the past and present. This study investigates the possibility of the occurrence of fire accident occasioned by the vaporization of hydrocarbon components derived from bio oil sample. In this study, bio oil liquid sample containing mixtures of hydrocarbon products were produced by fast pyrolysis process using palm oil kernel shell as the main biomass source. The bio oil-liquid phase was analysed using Gas Chromatography Mass Spectrometry (GCMS) and Gas Chromatography Flame Ionization Detector (GC-FID) to examine the compositions of the sample Mole fractions of components in the liquid phase were obtained from the GC-FID analysis while the mole fractions of the components in gas phase were calculated via modified Raoult' s law. In this study, the gas mixture is considered as a real solution. The activity coefficients were calculated using Universal Functional Activity Coefficient (UNIFAC) method; while the fugacity coefficients were obtained by using Peng-Robinson method, which is implemented in ThermoSolver software. LFL and UFL values for mixture (LFLmix and UFLmix) were calculated according to Le Chatelier equation. The LFLmix and UFLmix values were used to construct the flannnability diagram and subsequently used to determine the flannnability of the mixture. In this study, the LFLmix for the mixture is calculated at 3.89vol% and 12.4vol% for UFLmix Meanwhile, the Limiting Oxygen Concentration (LOC) for the mixture is 1 0.69vol%. The findings of this study can be used to propose suitable inherent safer methods to prevent the flammable mixture from occurring and to minimizing the loss of properties, business and life due to fire accidents in bio oil production. The findings of this study also may assist in minimizing fire hazards associated with presence of hydrocarbon vapours derived from bio oil storage system

Development of a generalised kinetic model for the combustion of hydrocarbon fuels

Includes abstract.Includes bibliographical references (leaves 73-76).The aim of this work is to find a generalised model for the combustion of hydrocarbons. Predicted temperature-time profiles can be obtained from detailed combustion kinetics, which can be used to derive a generalised model. If the generalised model can predict results from the detailed model it can be applied in computational fluid dynamics code where detailed kinetic mechanisms cannot.A generalised kinetic model is proposed, adapting the Schreiber model (Schreiber et al., 1994) to accurately predict the combustion behaviour of hydrocarbon fuels. The combustion behaviour is described through the characteristics of the temperature-time profiles and the ignition delay diagram, which include two stage ignition and the negative temperature co-efficient region. The Schreiber model is specifically adapted to improve the description of the very low temperature rise before and between ignitions and the auto-catalytic temperature rises during ignition. Using a Genetic Algorithm to optimise the prediction of the proposed model, the pre-exponent factor Ai and the activation energy Eai are the adjustable parameters which are optimised for each reaction in the model. These parameters have been optimised for three fuels: i-octane, n-heptane and methanol. The ignition delays of the pure fuels were accurately predicted. The temperature-time profiles in the instances of two stage ignition are relatively inaccurate. The temperature profiles are however an improvement on the temperature profiles predicted by the Schreiber model, particularly in terms of the slow temperature rise during the ignition delay andthe sharp temperature rise during ignition. The combustion of the binary blends of the three fuels have been predicted using model parameters which are found using the rate constants of each fuel, the blends composition and binary interaction rules. The binary interaction parameters were also optimised using a Genetic Algorithm. The binary interaction rules are based on the Peng-Robinson mixing rules. Overall the ignition delays of binary fuel blends were accurately predicted using binary interactions. However, when modelling the blends between methanol and n-heptane, where one fuel has extreme NTC behaviour and the other fuel has no NTC behaviour, the predictions were less accurate. These binary interaction rules are then used to model ternary mixtures. It is shown that the combustion behaviour of ternary mixtures of the three fuels can be accurately predicted without any further regression or parameter fitting. The accuracy of the ternary prediction is dependent on the accuracy of the binary predictions

Chemical Kinetic Insights into the Octane Number and Octane Sensitivity of Gasoline Surrogate Mixtures

Gasoline octane number is a significant empirical parameter for the optimization and development of internal combustion engines capable of resisting knock. Although extensive databases and blending rules to estimate the octane numbers of mixtures have been developed and the effects of molecular structure on autoignition properties are somewhat understood, a comprehensive theoretical chemistry-based foundation for blending effects of fuels on engine operations is still to be developed. In this study, we present models that correlate the research octane number (RON) and motor octane number (MON) with simulated homogeneous gas-phase ignition delay times of stoichiometric fuel/air mixtures. These correlations attempt to bridge the gap between the fundamental autoignition behavior of the fuel (e.g., its chemistry and how reactivity changes with temperature and pressure) and engine properties such as its knocking behavior in a cooperative fuels research (CFR) engine. The study encompasses a total of 79 hydrocarbon gasoline surrogate mixtures including 11 primary reference fuels (PRF), 43 toluene primary reference fuels (TPRF), and 19 multicomponent (MC) surrogate mixtures. In addition to TPRF mixture components of iso-octane/n-heptane/toluene, MC mixtures, including n-heptane, iso-octane, toluene, 1-hexene, and 1,2,4-trimethylbenzene, were blended and tested to mimic real gasoline sensitivity. ASTM testing protocols D-2699 and D-2700 were used to measure the RON and MON of the MC mixtures in a CFR engine, while the PRF and TPRF mixtures' octane ratings were obtained from the literature. The mixtures cover a RON range of 0-100, with the majority being in the 70-100 range. A parametric simulation study across a temperature range of 650-950 K and pressure range of 15-50 bar was carried out in a constant-volume homogeneous batch reactor to calculate chemical kinetic ignition delay times. Regression tools were utilized to find the conditions at which RON and MON best correlate with simulated ignition delay times. Furthermore, temperature and pressure dependences were investigated for fuels with varying octane sensitivity. This analysis led to the formulation of correlations useful to the definition of surrogates for modeling purposes and allowed one to identify conditions for a more in-depth understanding of the chemical phenomena controlling the antiknock behavior of the fuels