Elsevier

Combustion and Flame

Volume 197, November 2018, Pages 49-64
Combustion and Flame

Experimental and chemical kinetic modeling investigation of methyl butanoate as a component of biodiesel surrogate

https://doi.org/10.1016/j.combustflame.2018.06.033Get rights and content

Abstract

Biodiesel is a potential alternative to fossil diesel. In combustion simulations, in order to circumvent the difficulty in integrating reaction schemes for biodiesels, which are typically of a large size and not well understood, a surrogate approach to simplify the representation of its long chain methyl ester components is adopted. In this work, a compact reaction scheme for methyl butanoate, which is a potentially important candidate for biodiesel surrogates, is derived from a detailed reference mechanism (Dooley et al., 2008). An existing well-validated model for n-dodecane (Narayanaswamy et al., 2014) oxidation, which is a suitable base to model biodiesel surrogates, is augmented with the oxidation pathways of methyl butanoate. The resulting combined mechanism is comprehensively assessed for methyl butanoate kinetic description. Several rate constants pertaining to methyl butanoate kinetics are updated in the resulting chemical mechanism based on recent rate recommendations from the literature in a consistent manner. The revised kinetic model has been validated comprehensively against a wide range of experimental data and found to be satisfactory. In addition, auto-ignition delay times of methyl butanoate have been measured in a rapid compression machine (RCM). The ignition delay time measurements cover a wide range of experimental conditions: temperatures of 850–1100 K and pressures of 10–40 bar. The impact of varying equivalence ratios on ignition delay times has also been investigated for ϕ = 0.5–1.5 and ignition delay times are reported for the rich mixtures for the first time as a part of this work. No two-stage ignition or negative temperature coefficient (NTC) behavior has been observed for methyl butanoate in the experimental investigation. The effect of addition of low-temperature chemistry pathways to the methyl butanoate chemical kinetic mechanism has also been explored.

Introduction

Increase in the use of renewable alternative fuels will decrease our dependence on fossil fuels and help reduce greenhouse gas emissions. Biodiesel is one such potential alternative to partially or completely replace fossil diesel [1]. It consists of long chain saturated as well as unsaturated methyl esters ranging from C14–C24 [2]. These constituents are present in varied compositions based on the source of biodiesel. A detailed kinetic mechanism developed for these constituents runs into several thousands of species and reactions [3]. To circumvent the difficulty in utilizing such a large kinetic scheme in engine simulations, several studies have investigated the use of various surrogates for biodiesel [4], [5], [6], [7], [8], [9], which have been recently summarized in Ref. [10].

In developing a reaction mechanism for a surrogate fuel, it is crucial to capture the component kinetics accurately in order to make meaningful assessment about suitability of the surrogate to represent the real fuel. Thus, although methyl decanoate has been used in recent studies [7], [8], [9] as a surrogate component owing to its ability to reproduce the reactivity, negative temperature coefficient (NTC) behavior, and early CO2 rise, characteristic to the long chain methyl esters in biodiesels, methyl butanoate (MB), which is the most comprehensively investigated methyl ester in terms of kinetic studies [11], is selected here to represent the ester content in biodiesels. Methyl butanoate has not been found to exhibit any NTC behavior in the conditions where longer esters did show NTC behavior and it lacks the reactivity characteristic of long chain ester molecules. Nonetheless, methyl butanoate, in combination with n-alkanes is found to predict combustion and emission characteristics of biodiesel [19], which can therefore be considered as a promising candidates for biodiesel surrogates.

Fisher et al. [12] developed the earliest model for methyl butanoate oxidation and validated it against pressure measurements in a constant volume chamber. Their model exhibited a weak NTC and was in qualitative agreement with the available experimental data at that time. Several detailed mechanisms have been developed [11], [13], [14], [15] thereafter, along with a wide variety of experimental studies for auto-ignition and pyrolysis of methyl butanoate [11], [15], [29], [56], [57], [58] and its flames [13], [37], [46], [47]. These kinetic descriptions are mainly derived from the relatively well understood alkane kinetics by accounting for ester specific effects.

Dooley et al. [11] developed a comprehensive reaction mechanism for methyl butanoate and validated it against a wide range of experiments. This model did not include any low-temperature chemistry pathways. Gail et al. [13], [16] performed an experimental and kinetic modeling study of methyl butanoate and methyl crotonate. They investigated the effects of unsaturation and identified reaction pathways responsible for differences between saturated and unsaturated methyl ester. Hakka et al. [15] generated a detailed kinetic mechanism for methyl butanoate using the mechanism generation software EXGAS [17]. Gail et al. [13] and Hakka et al. [15] models included the pathways for low-temperature oxidation of methyl butanoate although NTC behavior has not been observed in any of the existing auto-ignition experiments.

Complementing the kinetic modeling efforts, several researchers have examined methyl butanoate kinetics using theoretical techniques [18], [19], [20], [21], [22], [23], [24]. Huynh et al. [25] developed a sub-mechanism for methyl butanoate based on a detailed ab-initio study. This sub-mechanism was verified against shock tube pyrolysis experiments. Some researchers [20], [21], [26] also investigated the important reactions for auto-ignition such as H-atom abstraction from methyl butanoate by different radicals using different levels of theories. Low-temperature chemistry pathways important for methyl butanoate oxidation have also been explored recently [22], [23] using quantum chemical calculations. Although no NTC behavior is observed, these studies suggest that the inclusion of low-temperature oxidation pathways might be important for predicting auto-ignition at low temperatures.

Auto-ignition of methyl butanoate has already been investigated experimentally using shock tubes and rapid compression machines (RCM). Dooley et al. [11] measured ignition delays of methyl butanoate in a shock tube (P = 1,4 bar, T = 1250–1760 K and ϕ = 0.25–1.5) and RCM (P = 10–40 bar, T = 640–949 K and ϕ = 0.33–1.00). Hakka et al. [15] also studied auto-ignition of methyl butanoate in shock tube at higher pressure (P = 8 bar, T= 1250–2000  K and ϕ = 0.25–2). Additional measurements of ignition delays have also been obtained in RCM facilities [27], [28], [29]. Of these, Kumar and Sung [29] have recently explored a wide range of conditions (P = 15–75 bar, T = 833–1112 K and ϕ = 0.25–1.00). Notably, auto-ignition of rich MB mixtures has not been investigated yet at intermediate temperature (850 K  <  T  <  1100 K) under engine relevant conditions.

The primary goal of this work is to: (a) present additional auto-ignition data for methyl butanoate at conditions not investigated earlier along with (b) a compact reaction scheme for methyl butanoate oxidation, yet thoroughly examined for its kinetic description and validated against an array of experimental configurations. This work is organized as follows. Firstly, ignition delay time measurements for MB in a rapid compression machine covering a wide range of operating conditions (P = 10–40 bar, T = 850–1100 K and ϕ = 0.5–1.5) are presented in Section 2. It is to be highlighted that ignition delays for rich MB mixtures are reported for the first time in the intermediate temperature (850–1100 K) regime, thereby providing valuable data for kinetic model validation at these conditions. Thereafter, the development of the kinetic scheme is described in Section 3. The oxidation pathways of methyl butanoate are derived from a detailed mechanism [11] and incorporated into a well-characterized model for n-dodecane oxidation [30], considering the potential of this long chain alkane as a component of a possible biodiesel surrogate [19], [63], [64]. The kinetic description of methyl butanoate oxidation in the resulting mechanism is revised and updated based on rate parameter recommendations for methyl butanoate oxidation from recent theoretical studies, which have not been utilized yet for model development. The proposed model is then comprehensively validated against available methyl butanoate experimental data as well as the new data-sets obtained in the present work (Section 4). The revised model is found to Result in improved model predictions for methyl butanoate.

The existing set of experiments, including the ones presented in this work, do not show NTC or two-stage ignition. Nonetheless, the addition of low-temperature chemistry pathways has also been explored here for completeness. Since the validity of the low-temperature model cannot be ascertained with the available experimental data, this discussion is presented separately in Section 5. This investigation points toward potential experimental studies required to assess the low-temperature chemistry of methyl butanoate in future.

Section snippets

Experimental methodology

The rapid compression machine used in this study is located at Physikalisch-Technische Bundesanstalt (PTB), which is similar to that used by Mittal and Sung [31]. It consists of a single piston design, where a pneumatically driven and hydraulically controlled creviced piston compresses the mixture inside the reaction chamber to a desired end of compression pressure (PC) and temperature (TC). The reaction chamber has a maximum working pressure of 200 bar and an operating temperature range of

Skeletal mechanism

Starting with a detailed reaction scheme for methyl butanoate oxidation (275 species, 1545 reactions) proposed by Dooley et al. [11], a compact mechanism is derived using the DRGEP [34] method. The database used to carry out mechanism reduction includes homogeneous isochoric reactor configurations at low to high temperatures T=700–1500 K, pressure P=13.5bar, and equivalence ratio ϕ=1. The resulting reduced mechanism consists of 89 species and 560 reactions. Figure 2 shows a comparison between

Results and discussions

The IITM high T model described previously is comprehensively validated against a wide range of experiments here. These include (i) ignition delay time measurements in shock tubes and RCMs, (ii) species profile measurements in a jet stirred reactor (JSR) and variable pressure flow reactor (VPFR), (iii) laminar burning velocity measurements, and (iv) species concentrations in a counter-flow diffusion flame and a flat flame burner setup. Table 2 compiles a list of all the experimental data sets

Addition of low-temperature chemistry pathways

The reference methyl butanoate mechanism [11] used in this study does not include any reactions pertaining to the low-temperature chemistry. The low-temperature chemistry pathways, involving addition of O2 to the fuel radical and the subsequent reactions, lead to the non-Arrhenius behaviour shown by several hydrocarbons at T ∼ 900 K depending on the pressure and the type of the fuel (such as shown by Refs. [38], [39]). This behavior can be characterized by a negative temperature co-efficient

Conclusions

A compact kinetic mechanism has been developed for methyl butanoate, which is a suitable candidate to represent the ester content in biodiesel surrogates. A detailed reaction mechanism for methyl butanoate (Dooley et al., 2008) has been reduced using DRGEP technique [34] and combined in a consistent manner with a well validated n-dodecane model (Narayanaswamy et al., 2014), in view of the potential of this long chain alkane along with methyl butanoate as a component of biodiesel surrogate. The

Acknowledgments

This material is based upon work supported as a part of the innoINDIGO BiofCFD project. The authors like to thank Dr. Perrine Pepiot from Cornell University for sharing the source code for DRGEP technique and the mechanism combination tool. The authors acknowledge support from the National Center for Combustion Research and Development (NCCRD), India for providing access to CHEMKIN-PRO software. The last author gratefully acknowledges support from the New Faculty Initiation Grant, Project no.

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