The Design Institute for Physical Properties (DIPPR) maintains the DIPPR 801 database for the American Institute of Chemical Engineers. Autoignition temperature (AIT) is one of the properties included in the database and is the focus of this work including improvement of the overall state of AIT in the database. Phenomena related to AIT as well as the relevant literature are reviewed. Likewise, the database is presented to respond to significant misuse of the DIPPR 801 database in the literature. The database is evaluated, respecting AIT, as a whole to show where improvement is needed. An experimental study of minimum autoignition temperatures reveals unexpected behavior of pure n-alkanes not predicted by current current phenomenological understanding of autoignition processes. Measurements show an increase at C16 and a dramatic and previously unexplained step increase between C25 and C26. Experimental modifications are presented to compensate the effect of altitude. Measured values for several n-alkanes are reported and compared to the literature. Other ignition experiments and decomposition measurements using differential scanning calorimetry are also reported and examined to elucidate the unexpected trends. Explanations for these trends are proposed. Finally, the implications of this for trends in other chemical families are discussed. A comprehensive examination of AIT family trends reveals variation from the n-alkane family trend. Measured AIT values are presented and discussed. Evaluated AIT values are recommended for several single-group chemical families. Phenomenological explanations for observed differences are proposed and discussed along with the broader implications for these trends. Methods for predicting autoignition temperatures (AIT) have been historically inaccurate and are rarely based on the underlying physical phenomena leading to observed AIT. An improved method for predicting AIT based on the method by the late Dr. William H. Seaton is presented and discussed. The method of Seaton is described in detail. An evaluated data set is used to regress new parameters for the Seaton method parameters. Improvements to Seaton's model and underlying principles are presented and discussed. Finally, an improved AIT prediction method is presented and recommended.

Heavy-duty natural gas engines offer air pollution and energy diversity benefits. However, current homogeneous-charge lean-burn engines suffer from impaired efficiency and high unburned fuel emissions. Natural gas direct-injection engines offer the potential of diesel-like efficiencies, but require further research. To improve understanding of the autoignition and emission characteristics of natural gas direct-injection compression-ignition combustion, the effects of key operating parameters (including injection pressure, injection duration, and pre-combustion temperature) and gaseous fuel composition(including the effects of ethane, hydrogen and nitrogen addition) were studied. An experimental investigation was carried out on a shock tube facility. Ignition delay, ignition kernel location, and NOx emissions were measured. The results indicated that the addition of ethane to the fuel resulted in a decrease in ignition delay and a significant increase in NOx emissions. The addition of hydrogen to the fuel resulted in a decrease in ignition delay and a significant decrease in NOx emissions. Diluting the fuel with nitrogen resulted in an increase in ignition delay and a significant decrease in NOx emissions. Increasing pre-combustion temperature resulted in a significant reduction in ignition delay, and a significant increase in NOx emissions. Modest increase in injection pressure reduced the ignition delay; increasing injection pressure resulted in higher NOx emissions. The effects of ethane, hydrogen, and nitrogen addition on the ignition delay of methane were also successfully predicted by FlameMaster simulation. OH radical distribution in the flame was visualized utilizing Planar Laser Induced Fluorescence (PLIF). Single-shot OH-PLIF images revealed the stochastic nature of the autoignition process of non-premixed methane jets. Examination of the convergence of the ensemble-averaged OH-PLIF images showed that increasing the number of repeat experiments was the most effective way to achieve a more converged result. A combustion model, which incorporated the Conditional Source-term Estimation(CSE) method for the closure of the chemical source term and the Trajectory Generated Low-Dimensional Manifold (TGLDM) method for the reduction of detailed chemistry, was applied to predict the OH distribution in a combusting non-premixed methane jet. The model failed to predict the OH distribution as indicated by the ensemble-averaged OH-PLIF images, since it cannot account for fluctuations in either turbulence or chemistry.

Autoignition of high pressure methane jets at engine relveant conditions within a shock tube is investigated using Conditional Moment Closure (CMC). The impact of two commonly used approximations applied in previous work is examined, the assumption of homogeneous turbulence in the closure of the micro-mixing term and the assumption of negligible radial variation of terms within the CMC equations. In the present work two formulations of an inhomogeneous mixing model are implemented, both utilizing the β -PDF, but differing in the respective conditional velocity closure that is applied. The common linear model for conditional velocity is considered, in addition to the gradient diffusion model. The validity of cross-stream averaging the CMC equations is examined by comparing results from two-dimensional (axial and radial) solution of the CMC equations with cross-stream averaged results. The CMC equations are presented and all terms requiring closure are discussed. So- lution of the CMC equations is decoupled from the flow field solution using the frozen mixing assumption. Detailed chemical kinetics are implemented. The CMC equations are discretized using finite differences and solved using a fractional step method. To maintain consistency between the mixing model and the mixture fraction variance equation, the scalar dissipation rate from both implementations of the inhomogeneous model are scaled. The autoignition results for five air temperatures are compared with results obtained using homogeneous mixing models and experimental data. The gradient diffusion conditional velocity model is shown to produce diverging be- haviour in low probability regions. The corresponding profiles of conditional scalar dis- sipation rate are negatively impacted with the use of the gradient model, as unphysical behaviour at lean mixtures within the core of the fuel jet is observed. The predictions of ignition delay and location from the Inhomogeneous-Linear model are very close to the homogeneous mixing model results. The Inhomogeneous-Gradient model yields longer ig- nition delays and ignition locations further downstream. This is influenced by the higher scalar dissipation rates at lean mixtures resulting from the divergent behaviour of the gradient conditional velocity model. The ignition delays obtained by solving the CMC equations in two dimensions are in excellent agreement with the cross-stream averaged values, but the ignition locations are predicted closer to the injector.

Autoignition of high pressure methane jets at engine relveant conditions within a shock tube is investigated using Conditional Moment Closure (CMC). The impact of two commonly used approximations applied in previous work is examined, the assumption of homogeneous turbulence in the closure of the micro-mixing term and the assumption of negligible radial variation of terms within the CMC equations. In the present work two formulations of an inhomogeneous mixing model are implemented, both utilizing the β -PDF, but differing in the respective conditional velocity closure that is applied. The common linear model for conditional velocity is considered, in addition to the gradient diffusion model. The validity of cross-stream averaging the CMC equations is examined by comparing results from two-dimensional (axial and radial) solution of the CMC equations with cross-stream averaged results. The CMC equations are presented and all terms requiring closure are discussed. So- lution of the CMC equations is decoupled from the flow field solution using the frozen mixing assumption. Detailed chemical kinetics are implemented. The CMC equations are discretized using finite differences and solved using a fractional step method. To maintain consistency between the mixing model and the mixture fraction variance equation, the scalar dissipation rate from both implementations of the inhomogeneous model are scaled. The autoignition results for five air temperatures are compared with results obtained using homogeneous mixing models and experimental data. The gradient diffusion conditional velocity model is shown to produce diverging be- haviour in low probability regions. The corresponding profiles of conditional scalar dis- sipation rate are negatively impacted with the use of the gradient model, as unphysical behaviour at lean mixtures within the core of the fuel jet is observed. The predictions of ignition delay and location from the Inhomogeneous-Linear model are very close to the homogeneous mixing model results. The Inhomogeneous-Gradient model yields longer ig- nition delays and ignition locations further downstream. This is influenced by the higher scalar dissipation rates at lean mixtures resulting from the divergent behaviour of the gradient conditional velocity model. The ignition delays obtained by solving the CMC equations in two dimensions are in excellent agreement with the cross-stream averaged values, but the ignition locations are predicted closer to the injector.

Heavy-duty natural gas engines offer air pollution and energy diversity benefits. However, current homogeneous-charge lean-burn engines suffer from impaired efficiency and high unburned fuel emissions. Natural gas direct-injection engines offer the potential of diesel-like efficiencies, but require further research. To improve understanding of the autoignition and emission characteristics of natural gas direct-injection compression-ignition combustion, the effects of key operating parameters (including injection pressure, injection duration, and pre-combustion temperature) and gaseous fuel composition(including the effects of ethane, hydrogen and nitrogen addition) were studied. An experimental investigation was carried out on a shock tube facility. Ignition delay, ignition kernel location, and NOx emissions were measured. The results indicated that the addition of ethane to the fuel resulted in a decrease in ignition delay and a significant increase in NOx emissions. The addition of hydrogen to the fuel resulted in a decrease in ignition delay and a significant decrease in NOx emissions. Diluting the fuel with nitrogen resulted in an increase in ignition delay and a significant decrease in NOx emissions. Increasing pre-combustion temperature resulted in a significant reduction in ignition delay, and a significant increase in NOx emissions. Modest increase in injection pressure reduced the ignition delay; increasing injection pressure resulted in higher NOx emissions. The effects of ethane, hydrogen, and nitrogen addition on the ignition delay of methane were also successfully predicted by FlameMaster simulation. OH radical distribution in the flame was visualized utilizing Planar Laser Induced Fluorescence (PLIF). Single-shot OH-PLIF images revealed the stochastic nature of the autoignition process of non-premixed methane jets. Examination of the convergence of the ensemble-averaged OH-PLIF images showed that increasing the number of repeat experiments was the most effective way to achieve a more converged result. A combustion model, which incorporated the Conditional Source-term Estimation(CSE) method for the closure of the chemical source term and the Trajectory Generated Low-Dimensional Manifold (TGLDM) method for the reduction of detailed chemistry, was applied to predict the OH distribution in a combusting non-premixed methane jet. The model failed to predict the OH distribution as indicated by the ensemble-averaged OH-PLIF images, since it cannot account for fluctuations in either turbulence or chemistry.

Heavy-duty natural gas engines offer air pollution and energy diversity benefits. However, current homogeneous-charge lean-burn engines suffer from impaired efficiency and high unburned fuel emissions. Natural gas direct-injection engines offer the potential of diesel-like efficiencies, but require further research. To improve understanding of the autoignition and emission characteristics of natural gas direct-injection compression-ignition combustion, the effects of key operating parameters (including injection pressure, injection duration, and pre-combustion temperature) and gaseous fuel composition(including the effects of ethane, hydrogen and nitrogen addition) were studied. An experimental investigation was carried out on a shock tube facility. Ignition delay, ignition kernel location, and NOx emissions were measured. The results indicated that the addition of ethane to the fuel resulted in a decrease in ignition delay and a significant increase in NOx emissions. The addition of hydrogen to the fuel resulted in a decrease in ignition delay and a significant decrease in NOx emissions. Diluting the fuel with nitrogen resulted in an increase in ignition delay and a significant decrease in NOx emissions. Increasing pre-combustion temperature resulted in a significant reduction in ignition delay, and a significant increase in NOx emissions. Modest increase in injection pressure reduced the ignition delay; increasing injection pressure resulted in higher NOx emissions. The effects of ethane, hydrogen, and nitrogen addition on the ignition delay of methane were also successfully predicted by FlameMaster simulation. OH radical distribution in the flame was visualized utilizing Planar Laser Induced Fluorescence (PLIF). Single-shot OH-PLIF images revealed the stochastic nature of the autoignition process of non-premixed methane jets. Examination of the convergence of the ensemble-averaged OH-PLIF images showed that increasing the number of repeat experiments was the most effective way to achieve a more converged result. A combustion model, which incorporated the Conditional Source-term Estimation(CSE) method for the closure of the chemical source term and the Trajectory Generated Low-Dimensional Manifold (TGLDM) method for the reduction of detailed chemistry, was applied to predict the OH distribution in a combusting non-premixed methane jet. The model failed to predict the OH distribution as indicated by the ensemble-averaged OH-PLIF images, since it cannot account for fluctuations in either turbulence or chemistry. / Applied Science, Faculty of / Mechanical Engineering, Department of / Graduate

As powertrains and IC engines continue to grow in complexity, many vehicle manufacturers (OEMs) are turning to simulation in an effort to reduce design validation and calibration costs. Ultimately, their aim is to complete this process entirely within the virtual domain, without the need for any physical testing. Practical simulation techniques for the prediction of knock in spark ignition (SI) engines rely on empirical ignition delay correlations (IDCs). These IDCs are used to approximate the complex ignition delay characteristics of real and surrogate fuel compositions with respect to temperature, pressure and mixture composition. Over the last 40 years, a large number of IDCs have been put forward in the literature, spanning a broad range of fuels, operating conditions and calibration methods. However, the applicability of these tools has yet to be verified at the high brake mean effective pressure (BMEP) operating conditions relevant to highly boosted, downsized engines. Here, the applicability of 16 gasoline-relevant IDCs for predicting knock onset at high loads (BMEP > 30bar) has been investigated by comparing the knock predictions from each IDC against experimentally measured knock onset times. Firstly, a detailed investigation into cylinder pressure data processing techniques was performed to determine which knock detection and angle of knock onset (aKO) measurement methods were most appropriate at high loads. A method based on the maximum amplitude pressure oscillation (MAPO) during knock-free operation best estimated cycle classifications, whilst Shahlari’s Signal Energy Ratio technique [1] most accurately predicted knock onset. To the author’s knowledge, this is the first time that such a comprehensive study on the accuracy of these techniques at such high loads has been conducted. Importantly, these findings represent a valuable framework to inform other researchers in the field of knocking combustion on which techniques are needed to extract accurate and relevant information from measured cylinder pressure records. Secondly, the data processing techniques derived were applied to experimental data collected across a wide range of high BMEP operating conditions (up to a maximum of 32 bar) using a 1.6 litre, 4-cylinder SI engine. Trapped charge composition and temperature were predicted using a calibrated 1D model of the engine, whilst the temperature of a hypothetical hotspot in the unburned zone was estimated separately by assuming adiabatic compression from a point after intake valve closing and by mapping γ (the ratio of specific heat capacities) as a function of temperature. This revealed that none of the IDCs tested performed well at conditions relevant to modern, downsized engines. The IDC that achieved the best overall balance between aKO accuracy and cycle-classification agreement was the “cool-flame” correlation for iso-octane proposed by Ma [2]. However, this had an unacceptably high average aKO error of ±3.5° compared to the ±2°CA limit observed within the literature, and its average cycle-classification accuracy was below 60%. The main reason for this relatively modest accuracy was a large number of false-positive cycle classifications, which mainly occurred in slow or late burning cycles. Further work should therefore focus on methods to reduce the number of false positive classifications obtained with this correlation, which could be achieved using empirical correlations to describe the latest point in the cycle for which knock would be permitted to occur in terms other measureable combustion parameters. Overall, this research has generated a unique insight into combustion at very high loads, as well as an extensive dataset that can be used for future research to improve the accuracy of empirical knock modelling techniques. Furthermore, this work has demonstrated that for the purposes of virtual spark timing calibration and the avoidance of knock, the current crop of practical simulation tools is not accurate enough at the conditions relevant to modern SI engines and has provided a better understanding of their limitations. These findings represent a major contribution to the field from both a research perspective and for industrial applications.

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This dissertation deals with the numerical investigation of the physics of sprays autoigniting at diesel engine conditions using Direct Numerical Simulations (DNS), and with the modelling of droplet related effects within the Conditional Moment Closure (CMC) method for turbulent non-premixed combustion. The dissertation can be split in four different sections, with the content of each being summarized below. The first part of the dissertation introduces the equations that govern the temporal and spatial evolution of a turbulent reacting flow, and provides an extensive review of the CMC method for both single and two-phase flows. The problem of modelling droplet related effects in the CMC transport equations is discussed in detail, and physically-sound models for the unclosed terms that appear in these equations and that are affected by the droplet presence are derived. The second part of the dissertation deals with the application of the CMC method to the numerical simulation of several n-heptane sprays igniting at conditions relevant to diesel engine combustion. Droplet-related terms in the CMC equations were closed with the models developed in the first part of the dissertation. For all conditions investigated, CMC could correctly capture the ignition, propagation and anchoring phases of the spray flame. Inclusion of droplet terms in the CMC equations had little influence on the numerical predictions, in line with the findings of other authors. The third part of the dissertation presents a DNS study on the autoignition of n-heptane sprays at high pressure / low temperature conditions. The analysis revealed that spray ignition occurs first in well-mixed locations with a specific value of the mixture fraction. Changes in the operating conditions (initial turbulence intensity of the background gas, global equivalence ratio in the spray region, initial droplet size distribution) affected spray ignition through changes in the mixture formation process. For each spray, a characteristic ignition delay time and a characteristic droplet evaporation time could be defined. The ratio between these time scales was suggested as a key parameter for controlling the ignition delay of the spray. The last part of the dissertation exploits the DNS simulations to perform an a priori analysis of the applicability of the CMC method to autoigniting sprays. The study revealed that standard models for the mixing quantities used in CMC provide poor approximations in two-phase flows, and are partially responsible for the poor prediction of the ignition delay time. It was also observed that first-order closure of the chemical source terms performs poorly during the onset of ignition, suggesting that second-order closures may be more appropriate for studying spray autoignition problems. The contribution of the work presented in this dissertation is to provides a detailed insight into the physics of spray autoignition at diesel engine conditions, to propose and derive original methods for incorporating droplet evaporation effects within CMC in a physically-sound manner, and to assess the applicability and shortcomings of the CMC method to autoigniting sprays.

The successful transition to global clean energy is contingent upon meeting the increasing worldwide energy demand for power while simultaneously curbing greenhouse gas emissions. This study delves into the complexities of transitioning to cleaner energy sources and the challenges posed by utilizing hydrogen and hydrogen/natural gas mixtures as a potential fuel source alternative to traditional carbon-based combustion cycles. By addressing the technical intricacies and conducting thorough testing, researchers aim to enhance our understanding of auto-ignition behavior in different fuel-air mixtures under varying conditions, ultimately contributing to the development of safer and more efficient energy solutions in the pursuit of clean and sustainable power generation. This study outlines the test methodology employed to assess conditions leading to auto-ignition for various fuel-air mixtures operating at different pressures (1 - 30 atm) and temperatures. The testing encompassed 100% H2 and multiple H2/NG blends at stoichiometric conditions. Similar testing was conducted for 100% NG to validate the test procedures and data collection methods referenced in previous literature. Under atmospheric conditions, 0-1 ATM, H2 exhibits a broader flammability range of EQs where ignition is more likely to occur compared to methane. H2's flammability ranges from 4% to 75% molar (volume) fuel concentration, corresponding to an EQ range of 0.137 - 2.57, while methane's flammability limit spans from 5% to 15% molar (volume) or an EQ between 0.53 – 1.58. Previous studies have explored the effect of longer hydrocarbons present in natural gas mixtures, with ethane (C2H6) and propane (C3H8) shown to decrease the ignition temperature (AIT) of natural gas, particularly at elevated pressures. These longer hydrocarbons are inclined to promote ignition in richer conditions, whereas methane tends to ignite more readily in slightly lean conditions. Besides pressure, fuel, and EQ, numerous variables such as chamber volume size, chamber materials, presence of diluents, and other factors can influence the AIT. The results revealed that, at atmospheric pressures, an increase in H2 concentration led to a reduced AIT. However, at 30 atm, a higher presence of H2 increased the AIT. At pressures exceeding 10 atm, an increased equivalence ratio resulted in a decreased AIT for all mixtures, with NG, exhibiting the greatest sensitivity to equivalence ratio variations.