This paper presents a new chemical kinetic model developed for the simulation of auto-ignition and combustion of engine surrogate fuel mixtures sensitized by the presence of NOx. The chemical mechanism is based on the PRF auto-ignition model (n-heptane/iso-octane) of Buda et al. [1] and the NO/n-butane/n-pentane model of Glaude et al. [2]. The later mechanism has been taken as a reference for the reactions of NOx with larger alcanes (n-heptane, iso-octane). A coherent two components engine fuel surrogate mechanism has been generated which accounts for the influence of NOx on auto-ignition. The mechanism has been validated for temperatures between 700 K and 1100 K and pressures between 1 and 10 atm covering the temperature and pressure ranges characteristic of engine post-oxidation thermodynamic conditions. Experiments used for validation include jet stirred reactor conditions for species evolution as a function of temperature, as well as diesel HCCI engine experiments for auto-ignition delay time measurements.
Auto-ignition process of stoichiometric mixture of methane-air is investigated using detailed chemical kinetics in a single-zone combustion chamber. Effect of initial temperature on start of combustion (SOC). The Arrhenius expression for the specific reaction rate are calculated and auto-ignition was evaluated based on the species fractions and sensitivity analysis. Our results suggest that the SOC is directly related to initial temperature and the auto-ignition will not occur if the initial temperature low enough.
A systematic investigation on the effects of roaming radical reactions on global combustion properties for transportation fuels is presented. New software was developed that can automatically discover all the possible roaming pathways within a given chemical kinetic mechanism. This novel approach was applied to two mechanisms taken from the literature, one for heptane and one for butanol. Ignition delay times and laminar flame speeds were computed over a broad range of conditions, while testing varying degrees of roaming. As the degree of roaming is increased, the ignition delays increased, co…
Since detonation is the only established theory that allows rapid burning producing a high pressure that can be sustained in open areas, the generally accepted opinion was that the mechanism explaining the high rate of combustion in dust explosions is deflagration-to-detonation transition. We propose a theoretical substantiation of an alternative mechanism explaining the origin of the secondary explosion producing high speeds of combustion and high overpressures in unconfined dust explosions. We show that the clustering of dust particles in a turbulent flow ahead of the advancing flame gives r…
The ignition delay of a fuel/air mixture is an important quantity in designing combustion devices, and these data are also used to validate chemical kinetic models for combustion. One of the typical experimental devices used to measure the ignition delay is called a Rapid Compression Machine (RCM). This paper presents UConnRCMPy, an open-source Python package to process experimental data from the RCM at the University of Connecticut. Given an experimental measurement, UConnRCMPy computes the thermodynamic conditions in the reaction chamber of the RCM during an experiment along with the ignitio…
Combustion modes in locally stratified dual-fuel (DF) mixtures are numerically investigated for methanol n-dodecane blends under engine-relevant pressures. In the studied constant-volume numerical setup, methanol acts as a background low-reactivity fuel (LRF) while n-dodecane serves as high-reactivity fuel (HRF), controlling local ignition delay time. The spatial distribution of n-dodecane is modeled as a sinusoidal function parametrized by stratification amplitude (Y) and wavelength (0.01 mm<$λ$<15 mm). In contrast, methanol is assumed to be fully premixed with air at equivalence ratio 0.8. F…
Direct fired supercritical CO2 (sCO2) power cycles allow for the combustion of gaseous fuels under oxyfuel conditions with inherent carbon capture. As the CO2 is captured intrinsically, the efficiency penalty of capture on the overall plant is small, meaning that power plants achieve a similar efficiency to traditional fossil fuel power plants without carbon capture and storage. However, at high pressures and in large dilutions of CO2, combustion mechanisms are poorly understood. Therefore, in this paper sensitivity and quantitative analysis of four established chemical kinetic mechanisms have…
In this study, biodiesel fuel produced from crambe abyssinica plant using KOH and NaOH catalysts was mixed with standard diesel fuel and the effects on engine performance, combustion and emission were experimentally investigated. Standard diesel fuel and 6 different fuel mixtures were tested at 3.75, 7.5, 11.25 and 15 Nm engine loads. During the experiment, in-cylinder pressure data were specified depending on crank angle for each test fuel and engine load. In addition, measurements of HC, NOx, CO and smoke emissions were carried out. With the obtained experimental data, parameters such as hea…
New experimental data are collected for methyl-cyclohexane (MCH) autoignition in a heated rapid compression machine (RCM). Three mixtures of MCH/O2/N2/Ar at equivalence ratios of $ϕ$=0.5, 1.0, and 1.5 are studied and the ignition delays are measured at compressed pressure of 50 bar and for compressed temperatures in the range of 690-900 K. By keeping the fuel mole fraction in the mixture constant, the order of reactivity, in terms of inverse ignition delay, is measured to be $ϕ$=0.5 > $ϕ$=1.0 > $ϕ$=1.5, demonstrating the dependence of the ignition delay on oxygen concentration. In addition, an…
Distributed combustion, often associated with the low-oxygen condition, offers ultra-low NOX emission. However, it was recently achieved without combustion air dilution or internal flue gas recirculation, using a distinct approach called Mixture Temperature-Controlled combustion. Here, the fuel-air stream is cooled at the inlet to delay ignition and hence foster homogeneous mixture formation. The aim of this numerical study aims to understand the operation of this combustion concept better and present a robust framework for distributed combustion modeling in a parameter range where such operat…
The autoignition delays of mixtures of methyl-cyclohexane (MCH), oxygen, nitrogen, and argon have been studied in a heated rapid compression machine under the conditions $P_C$ = 50 bar, $T_C$ = 690 - 910K. Three different mixture compositions were studied, with equivalence ratios ranging from $ϕ$ = 0.5 - 1.5. The trends of the ignition delay measured at 50 bar were similar to the trends measured in earlier experiments at $P_C$ = 15.1 and 25.5 bar. The experimentally measured ignition delays were compared to a newly updated chemical kinetic model for the combustion of MCH. The model has been up…
The autoignition delays of iso-butanol, oxygen, and nitrogen mixtures have been measured in a heated rapid compression machine (RCM). At compressed pressures of 15 and 30 bar, over the temperature range 800-950 K, and for equivalence ratio of $ϕ$ = 0.5 in air, no evidence of an NTC region of overall ignition delay is found. By comparing the data from this study taken at $ϕ$ = 0.5 to previous data collected at $ϕ$ = 1.0 (Weber et al. 2013), it was found that the $ϕ$ = 0.5 mixture was less reactive (as measured by the inverse of the ignition delay) than the $ϕ$ = 1.0 mixture for the same compres…
Due to the rapid combustion nature of gasolines, most of the experimental measurements of research octane number (RON) could only yield macroscopic quantities such as ignition delay time and pressure variations, but fail to yield microscopic quantities such as the time evolution of number of species, which limits deep understanding of combustion mechanisms. In this work, molecular simulation was employed to reveal the correlation between the RON of gasoline surrogates and their combustion behaviors. Results show that the time of turning point obtained from the potential energy profile exhibits…
Different simplified and detailed chemical models and their impact on simulations of combustion regimes initiating by the initial temperature gradient in methane/air mixtures are studied. The limits of the regimes of reaction wave propagation depend upon the spontaneous wave speed and the characteristic velocities of the problem. The present study mainly focus to identify conditions required for the development a detonation and to compare the difference between simplified chemical models and detailed chemistry. It is shown that a widely used simplified chemical schemes, such as one-step, two-s…
Reactivity Controlled Compression Ignition (RCCI) is a new advanced engine concept that uses a dual fuel mode of operation to achieve significant improvements in fuel economy and emissions output. The fuels that are typically used in this mode include a low- and a high-reactivity fuel in varying proportions to control ignition timing. As such, understanding the interaction effects during autoignition of binary fuel blends is critical to optimizing these RCCI engines. In this work, we measure the autoignition delays of binary blends of dimethyl ether (C$_2$H$_6$O, DME) and methanol (CH$_4$O, Me…
Combustion process can become more energy efficient and environment friendly if used with appropriate fuel additive. Discovery of fuel additive can be accelerated by applying hybrid approach of using of chemical kinetics and Machine Learning (ML). In this work, we present a framework that takes the robustness of Machine Learning and accuracy of chemical kinetics to predict the effect of fuel additive on autoignition process. We present a case of making predictions for Ignition Delay Time (IDT) of biofuel n-butanol ($C_4H_9OH$) with several fuel additives. The proposed framework was able to pre…
Chemical kinetics mechanisms are essential for understanding, analyzing, and simulating complex combustion phenomena. In this study, a Neural Ordinary Differential Equation (Neural ODE) framework is employed to optimize kinetics parameters of reaction mechanisms. Given experimental or high-cost simulated observations as training data, the proposed algorithm can optimally recover the hidden characteristics in the data. Different datasets of various sizes, types, and noise levels are tested. A classic toy problem of stiff Robertson ODE is first used to demonstrate the learning capability, effici…
Butanol has received significant research attention as a second-generation biofuel in the past few years. In the present study, skeletal mechanisms for four butanol isomers were generated from two widely accepted, well-validated detailed chemical kinetic models for the butanol isomers. The detailed models were reduced using a two-stage approach consisting of the directed relation graph with error propagation and sensitivity analysis. During the reduction process, issues were encountered with pressure-dependent reactions formulated using the logarithmic pressure interpolation approach; these is…
A wide variety of real life complex networks are prohibitively large for modeling, analysis and control. Understanding the structure and dynamics of such networks entails creating a smaller representative network that preserves its relevant topological and dynamical properties. While modern machine learning methods have enabled identification of governing laws for complex dynamical systems, their inability to produce white-box models with sufficient physical interpretation renders such methods undesirable to domain experts. In this paper, we introduce a hybrid black-box, white-box approach for…
Developing efficient and accurate algorithms for chemistry integration is a challenging task due to its strong stiffness and high dimensionality. The current work presents a deep learning-based numerical method called DeepCombustion0.0 to solve stiff ordinary differential equation systems. The homogeneous autoignition of DME/air mixture, including 54 species, is adopted as an example to illustrate the validity and accuracy of the algorithm. The training and testing datasets cover a wide range of temperature, pressure, and mixture conditions between 750-1200 K, 30-50 atm, and equivalence ratio …
A New Data-Driven Sparse-Learning Approach to Study Chemical Reaction Networks
Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109--2125, USA（电气工程与计算机科学系，密歇根大学，安娜堡，MI 48109--2125，美国）；Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109--2125, USA（机械工程系，密歇根大学，安娜堡，MI 48109--2125，美国）；Departments of Chemical Engineering, Biomedical Engineering, Macromolecular Science and Engineering, Biophysics Program, University of Michigan, Ann Arbor, MI 48109--2125, USA（化学工程、生物医学工程、大分子科学与工程、生物物理项目系，密歇根大学，安娜堡，MI 48109--2125，美国）
