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Development of an Optimized Skeletal Chemical Kinetic Mechanism for Methane Combustion for Marine Engine Applications Nikolaos Fokas, Foivos Perdikaris, Dimitris Kazangas, George Skevis, and Lambros Kaiktsis Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.8b01118 • Publication Date (Web): 22 May 2018 Downloaded from http://pubs.acs.org on May 22, 2018
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Development of an Optimized Skeletal Chemical Kinetic Mechanism for Methane Combustion for Marine Engine Applications
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N. Fokas1, F. Perdikaris1, D. Kazangas1, G. Skevis2, L. Kaiktsis1
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1. Division of Marine Engineering, Department of Naval Architecture and Marine Engineering, National Technical University of Athens, Athens, Greece 2. Aerosol & Particle Technology Laboratory, CPERI/CERTH, Thessaloniki, Greece
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ABSTRACT
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The goal of the present study is to develop an optimized skeletal chemical kinetic mechanism for methane combustion, for conditions relevant to dual fuel marine engines. To this end, a systematic approach is developed, consisting of the following steps: (a) Assessment of three widely used detailed mechanisms, by comparing simulation results against three sets of indirect experimental data pertinent to methane combustion, (b) Sensitivity analysis – identification of important reactions (species), (c) Selection of one detailed mechanism, and production of a skeletal mechanism by means of the SEM-CM method, (d) Uncertainty analysis of the rate constants of important reactions, and (e) Optimization of the skeletal mechanism for the rate constant parameters of the important reactions. The resulting optimized skeletal mechanism, consisting of 28 species and 119 elementary reactions, accurately reproduces experimental data in a wide range of conditions, and is an important development for CFD studies in dual fuel marine engines.
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INTRODUCTION
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The increased environmental interest for reducing pollutant emissions from the marine industry has forced the International Maritime Organization (IMO) and national authorities to set strict emission control regulations in specific geographical areas (Emission Control Areas - ECAs)1. These regulations concern nitric oxide (NOx) emissions, as well as sulfur oxide (SOx) emissions. Dual fuel marine engines, mainly operated with natural gas (NG), consist a competitive means for meeting the recent emission regulations. Dual fuel engines can be operated in the liquid mode, i.e., as conventional Diesel engines, or in the gas mode. Engine design for gas mode operation is characterized by the timing of introducing the gas fuel in the engine cylinders. Two main concepts are followed thereby: (i) low pressure gas admission, resulting in adequate fuel-air mixing for lean premixed combustion, after ignition (commonly enabled via liquid pilot fuel injection), (ii) high pressure gas admission, resulting in non-premixed combustion. Evidently, SOx emissions are reduced to nearly zero levels. Due to the structure of methane molecule and the higher energy content of methane per unit mass, carbon dioxide (CO2) emissions are reduced by about 25%. Finally, due to the low temperature levels associated with lean premixed combustion, low gas admission provides low levels of NOx emissions, complying with the latest (Tier III) regulations of IMO. 1 ACS Paragon Plus Environment
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In the frame of Computational Fluid Dynamics (CFD) studies, effective modeling of dual fuel engine combustion and emissions formation requires a proper – accurate and computationally affordable – representation of chemistry; this can be accomplished in the context of skeletal chemical kinetic mechanisms. Given that methane is the main component of NG, in a percentage of up to 98% v/v, it is essential to develop effective validated skeletal mechanisms for methane combustion. Assessing the performance of different detailed mechanisms against experiments may include ignition delay times, premixed laminar flame speeds, as well as concentration profiles in fundamental devices (such as jet stirred reactors), in a proper range of conditions (pressure, temperature, stoichiometry). Accounting for the operation of dual fuel marine engines, for both the low pressure and high pressure gas admission concepts, should consider a wide range of pressure and temperature, for lean (low pressure gas admission) and locally rich (high pressure gas admission) combustion. The development of skeletal kinetic mechanisms involves the identification of redundant species and reactions, and, in a second stage, the removal of reactions that may involve important species but are secondary to the overall problem dynamics2,3. There are mainly four approaches for mechanism reduction and creation of lower order mechanisms. Sensitivity based approaches, such as the Simulation Error Minimization Connectivity Method (SEM-CM)4, identify redundant species through the investigation of the local Jacobian matrix. For large systems, this can be coupled with Principal Component Analysis to identify the relative importance of different reactions4. Reduction methods using Direct Relation Graphs (DRG) identify groups of species that are internally coupled, albeit not strongly, to the important species that comprise the skeletal mechanism5. Mechanism reduction methods based on timescale splitting, such as CSP, introduced by Lam and Goussis6,7, and ILDM, introduced by Maas and Pope8, have also been used for the generation of skeletal mechanisms9. Finally, methodologies based on global constrained optimization, involving genetic algorithms, have also been proposed2. In the present study, an optimized skeletal chemical kinetic mechanism for methane combustion is developed, with the main goal of being applicable in a wide range of conditions relevant for dual fuel marine engine operation. There is a wide range of skeletal mechanisms for methane oxidation and combustion in the literature. Nagy and Turanyi4 used a sensitivity-based approach to reduce a detailed scheme for methane partial oxidation (345 species, 6874 irreversible reactions) to a compact skeletal mechanism of 47 species and 246 reactions. Zsely et al.10, also using the SEMCM methodology, produced a skeletal mechanism of 50 species and 186 reactions for natural gas combustion under gas turbine conditions (up to 40 bar). Recently, Chen and Chen11 obtained a 19-species and 79-reactions mechanism for high-temperature methane auto-ignition, starting from the GRI3.0 mechanism using DRG; a more recent extension of this work also accounts for laminar flame speeds12. Further, Stagni et al.13 obtained a 27-species and 181-reactions mechanism for atmospheric pressure, high temperature combustion using sensitivity analysis concepts. However, there are no skeletal mechanisms available in the literature relevant to marine engine operating conditions. Nagy and Turanyi4 have demonstrated that SEM-CM is overall a very effective approach, resulting in a mechanism of small size, for a given level of error; thus, SEMCM is also adopted in the present study. Further, skeletal (or detailed) mechanisms can be optimized for the parameters of specific reaction rate constants (k). In this context, a more rigorous approach, including identification of the limits of k, by means of uncertainty analysis, has been suggested by Varga et al.14. 2 ACS Paragon Plus Environment
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A common characteristic of the literature skeletal mechanisms derived for methane combustion is that, either they are not applicable to the entire range of conditions relevant for engine combustion, or their size is quite large for engine CFD. The present study thus attempts to develop one, optimized, skeletal mechanism, relevant for the entire range of conditions of interest, and of small size. It is noted that engine CFD studies are commonly based on single-step chemistry, with few recent efforts using skeletal mechanisms; these include15-17, for automotive HCCI and RCCI engines. Recently, first CFD studies for large two-stroke marine Diesel engine combustion using detailed chemistry in the form of skeletal mechanisms have been reported18. To our knowledge, no such CFD studies have been performed for dual fuel marine engine applications. Building primarily on the work presented in refs 4 and 14, the development of the present optimized skeletal mechanism has been accomplished in five stages, as follows: (a) Assessment of three widely used detailed chemical kinetic mechanisms pertinent to methane combustion, (b) Sensitivity analysis, identifying the important reactions and species, (c) Selection of one detailed mechanism (NUIG-NGM), and development of a skeletal mechanism by means of the Simulation Error Minimization Connectivity Method (SEM-CM), (d) Uncertainty analysis of the rate constants of important reactions, and (e) Optimization of the skeletal mechanism for the rate constant parameters of the important reactions. Thus, the present work proposes a systematic path for developing optimized skeletal mechanisms, and applies it to methane combustion. The outcome of the present study is an optimized skeletal mechanism, which accurately accounts for experimental data in a wide range of conditions relevant to dual fuel marine engines, thus forming a solid basis for detailed CFD studies.
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2. METHODOLOGY OUTLINE
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The initial step towards developing an optimized skeletal mechanism for methane combustion is the selection of a proper detailed mechanism. To this end, three widely used detailed mechanisms are evaluated here, in particular, (i) the CRECK High and Low temperature mechanism19,20, (ii) the NUIG-NGM mechanism21-25, and (iii) ELTE 2016-Optimized Ethanol mechanism26. Mechanism assessment is performed by comparing present simulation results against indirect experimental data pertinent to the oxidation of CH4 mixtures, for three prototype problems, namely: (i) ignition delay times based on shock tube experiments, (ii) species concentration (mole fraction) profiles in jet stirred reactors (JSRs), and (iii) laminar flame speeds. (It is noted that, throughout the paper, we adopt the definition of indirect data as data not corresponding to a (direct) measurement of a specific rate constant.) The experimental data sets correspond to a wide range of temperature (900-2100 K), pressure (1-260 atm), and equivalence ratio (φ = 0.1-6.0), thus covering the entire range of interest for dual fuel marine engine operation in the gas mode, both for low- and high pressure gas admission engines. The overall assessment process has shown a very good performance of the NUIG-NGM mechanism, consisting of 293 species and 1593 elementary reactions, which was thus selected as the basis for developing the skeletal mechanism. The second step has been the local sensitivity analysis. Sensitivity analysis has been performed for all three prototype problems considered, in a wide range of conditions. For each problem/condition, the goal of sensitivity analysis is to identify 3 ACS Paragon Plus Environment
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the important elementary reactions, and thus also the species incorporated in them; here, these species will be referred to as important species. The final identification of important reactions and species has utilized all results produced. Identification of important reactions is crucial for the computational cost of optimization, as it limits the number of the problem design variables to the specific rate constant parameters of these reactions (constant of pre-exponential factor, temperature exponent of preexponential factor, activation energy). Identification of important species is of equal significance, as it forms a prerequisite for implementing the reduction method used in the present study. Further, sensitivity analysis has shown how the important chemical species and reactions change during methane oxidation, for the range of conditions considered. The third step has been the development of the skeletal mechanism. Here, the initial set of important species, as identified by sensitivity analysis, is extended by including other species, which are important to the variation of the initially chosen (important) ones. In the context of SEM-CM, the possible choices with regard to these species are derived from the calculation of the Jacobian matrix. Thus, skeletal mechanisms of increasing size were developed and tested for representative conditions in a jet stirred reactor, in terms of calculating an overall deviation of results with respect to the NUIG-NGM detailed mechanism. A skeletal mechanism with 28 species and 119 elementary reactions was finally developed. The fourth step has been the uncertainty analysis, for identifying the limits of all specific rate constants of the important reactions (as identified by the sensitivity analysis). Uncertainty analysis utilizes direct experimental data, theoretical approaches and other literature data. This process is particularly important, as it ensures that the rate constants, k, of the important reactions lie within the uncertainty limits, and therefore are physically meaningful. This also contributes to a significant reduction of the optimization computational cost (fifth step), as it limits the associated range of the problem design variables (parameters of the corresponding specific reaction rate constants). The final, fifth, step of the present study has been the optimization of the skeletal mechanism developed in the third step, in terms of optimizing the specific rate constant parameters of the important elementary reactions. This has been accomplished by minimizing a properly defined error function, as defined in ref 14, which quantifies the overall deviation with respect to experiments. The optimized skeletal mechanism is thus characterized by a very good performance with respect to experiments, for all three problems considered, in a wide range of conditions.
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3. MECHANISM ASSESSMENT
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A large set of indirect experimental data pertinent to methane combustion were collected and used in the present study; they correspond to ignition delay times, concentration profiles in JSRs, and laminar flame speeds, and are widely used for validating methane combustion kinetics. Experimental data of ignition delay times were obtained from five literature references. In particular, five detailed data sets were obtained from Seery and Bowman27; they correspond to a wide range of temperature (1300-1900 K), pressure (1.82-3.92 atm) and equivalence ratio (φ=0.2-5). Four data sets of Eubank et al.28 were used, corresponding to the following conditions: temperature: 1150-1850 K, pressure: 4 atm, equivalence ratio: φ=0.1-0.4. Five data sets of Lifshitz et al.29 were used, 4 ACS Paragon Plus Environment
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corresponding to: temperature: 1450-2100 K, pressure: 9.21-11.81 atm, equivalence ratio: φ=0.5-2.0. Five data sets of Spadaccini and Colket30 were used, corresponding to: temperature: 1250-2000 K, pressure: 5.70-9.22 atm, equivalence ratio: φ=0.45-1.25. Twenty three data sets of Petersen et al.31 were used, corresponding to: temperature: 900-1600 K, pressure: 40-260 atm, equivalence ratio: φ=0.4-6.0. One data set of El Merhubi et al.32 was used, corresponding to: temperature: 1400-2700 K, pressure: 40 bar, equivalence ratio: φ=0.5. An important remark in ref 32 is that the experimental results of earlier studies, as those of ref 31, are accurate. Experimental data of concentration measurements of species in jet stirred reactors (JSRs) were obtained from three literature references. Seven data sets of Cong and Dagaut33 were used, corresponding to: temperature: 900-1450 K, pressure: 1-10 atm, equivalence ratio: φ=0.1-1.5. One data set of Dagaut et al.34 was used, corresponding to: temperature: 1080-1220 K, pressure: 1 atm, equivalence ratio: φ=0.1. Three data sets of Cong et al.35 were used, corresponding to: temperature: 900-1200 K, pressure: 1-10 atm, equivalence ratio: φ=0.3. Experimental data of laminar flame speeds were obtained from three literature references. Three data sets of Park et al.36 were used, corresponding to: inlet temperature (298 K), pressure: 1-4 atm, equivalence ratio φ=0.65-1.3. One data set of Veloo et al.37 was used, corresponding to: inlet temperature: 343 K, pressure: 1 atm, equivalence ratio: φ=0.7-1.4. Finally, five data sets of Hu et al.38 were used, corresponding to: inlet temperature: 300 K, pressure: 1-20 bar, equivalence ratio: φ= 0.65-1.4. As indicated in the previous section, three widely used detailed mechanisms are evaluated in the present study towards developing an optimized skeletal mechanism for methane combustion, namely, CRECK High and Low temperature19,20, NUIG-NGM2125 and ELTE 2016-Optimized Ethanol26. Table 1 presents the number of species and elementary reactions included in each detailed mechanism. Table 1. Number of species and elementary reactions included in the three detailed mechanisms used in the present study.
Detailed mechanism CRECK High and Low temperature NUIG - NGM ELTE 2016 - Optimized Ethanol 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239
Number of species 107 293 47
Number of reactions 2642 1593 251
Mechanism assessment has been carried out by comparing simulation results against experiments, for all three detailed mechanisms considered. Simulations have been performed using CHEMKIN-II39. Identification of ignition delay time in simulations is commonly based either on the maximum of the OH radical concentration, or on the temperature inflection point. A careful processing of our results has shown that the second criterion is more appropriate for the present problem and conditions; thus, all computed ignition delay times reported subsequently correspond to a zero second derivative of temperature in time. Representative computational results for ignition delay times are presented in Fig. 1 (φ = 3.0 and φ = 0.5, for pressures of approximately 40 atm) and in Fig. 2 (φ = 3.0, for P = 85 atm). Computed representative speciation profiles in JSRs are shown in Fig. 3 (P = 1.0 atm, φ = 0.1), and in Fig. 4 (P = 10.0 atm, φ = 0.3). Finally, computed laminar flame speeds of methane-air mixtures at P = 1.0 atm and unburned mixture temperature Tun = 343 K are shown in Fig. 5.
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Ignition Delay Time (µs)
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(b) Ignition Delay Time (µs)
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Figure 1. Ignition delay time profiles versus initial temperature for (a) φ = 3.0, P = 40 atm, mixture composition per volume: 20.0% CH4, 13.3% O2, 66.7% Ar, experimental data from ref 31, and (b) φ = 0.5, P = 39.5 atm, mixture composition per volume: 1.0% CH4, 4.0% O2, 95.0% Ar, experimental data from ref 32.
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Figure 2. Ignition delay time profiles versus initial temperature for P = 85 atm, φ = 3.0. Mixture composition per volume: 20.0% CH4, 13.3% O2, 66.7% Ar. Experimental data from ref 31.
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Figure 3. Mole fraction profiles of water vapor versus temperature in a Jet Stirred Reactor at P = 1 atm, φ = 0.1. Mixture composition per volume: 1% CH4, 20% O2, 79% N2. Experimental data from ref 33.
Figure 4. Mole fraction profiles of CH4 versus temperature in a Jet Stirred Reactor at P = 10.0 atm, φ = 0.3. Mixture composition per volume: 1% CH4, 6.67% O2, 92.33% N2. Experimental data from ref 35.
Figure 5. Laminar flame speed versus equivalence ratio for methane-air mixtures at P = 1.0 atm, Tun = 343 K. Experimental data from ref 37.
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Careful inspection of the above results indicates that all three mechanisms accurately predict ignition time delays in rich high pressure (P = 40 atm) mixtures, while they all perform less satisfactorily in the case of lean mixtures. For higher pressures (P = 80 atm), NUIG-NGM generally exhibits the best level of agreement, with CRECK under-predicting and ELTE over-predicting experimental ignition delay times. The results with NUIG-NGM compare very well to JSR experimental data; on the other hand, both ELTE and CRECK over-estimate the rate of methane conversion at temperatures below 1100 K. Finally, NUIG-NGM accurately reproduces laminar flame speeds, with CRECK over-predicting and ELTE under-predicting experimental values. In conclusion, for all three prototype problems, the NUIG-NGM mechanism consistently reproduces the experimental data, in the entire range of parameters considered. Thus, NUIG-NGM is chosen as the basis to develop a skeletal mechanism for methane combustion.
4. SENSITIVITY ANALYSIS As indicated above, the next step after selecting a proper (“stable”) detailed mechanism (here: NUIG-NGM) is sensitivity analysis, for identifying the important elementary reactions and species. In the present study, local sensitivity analysis has been performed with respect to the pre-exponential factor, A. In the frame of sensitivity analysis, normalized sensitivity coefficients are calculated for conditions corresponding to the three prototype problems considered here, as follows: =
(1)
where Yi is the concentration of species i, and Aj is the initial value of the preexponential factor of reaction j (as given by the detailed mechanism). Thus, the normalized sensitivity coefficient expresses the variation of a particular species concentration to a small change in the value of pre-exponential factor of a certain reaction. In the present study, the CH4 concentration has been used for calculating normalized sensitivity coefficients. Thus, computed negative values of correspond to reactions enhancing reactivity, while positive values correspond to reactions inhibiting fuel consumption. A high absolute value of normalized sensitivity coefficient signals an important reaction. Results of sensitivity analysis for selected conditions of the laminar premixed flame problem computed with the NUIG-NGM mechanism are shown in Figs. 6-8. Figure 6 presents the most important reactions for lean (φ = 0.7) atmospheric pressure methane-air mixtures, while the corresponding reactions for rich (φ = 1.256) mixtures are shown in Fig. 7. Interesting changes in flame dynamics as a function of stoichiometry are observed. The most notable of these is related to changes in the relative importance of H and OH radicals as we move from lean to rich conditions. In this context, the highly chain branching reaction H+O2↔OH+O inhibits the overall reaction in rich flames, as it consumes H radicals, which are necessary for the major chain propagating reaction CH4+H↔CH3+H2. Further, it is interesting to note that the chain terminating reaction CH3+CH3+M↔C2H6+M actually promotes the overall reaction, since it competes directly with the major inhibiting reaction 8 ACS Paragon Plus Environment
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CH3+H+M↔CH4+M, thus preserving H radicals. The effects of pressure are outlined in Fig. 8, which illustrates that the increased pressure (p=20 bar) favours third body reactions, so that H+O2+M↔HO2+M becomes the major inhibiting step.
Figure 6. Local Sensitivity coefficients for the laminar premixed flame problem of CH4 in air, for P = 1.0 atm, Tun = 298 K, φ = 0.7, using the NUIG-NGM detailed mechanism. The conditions correspond to the experiments reported in ref 36. Local Sensitivity coefficients calculated for T = 1160 K.
Figure 7. Local Sensitivity coefficients for the laminar premixed flame problem of CH4 in air, for P = 1.0 atm, Tun = 298 K, φ = 1.256, using the NUIG-NGM detailed mechanism. The conditions correspond to the experiments reported in ref 36. Local Sensitivity coefficients calculated for T = 1195 K.
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Figure 8. Local Sensitivity coefficients for the laminar premixed flame problem of CH4 in air, for P = 20 bar, Tun = 300 K, φ = 0.7, using the NUIG-NGM detailed mechanism. The conditions correspond to the experiments reported in ref 38. Local Sensitivity coefficients calculated for T = 1190 K.
By processing all sensitivity analysis results, the ten most important elementary reactions were identified, according to the present investigation, for the present conditions and processing of results; these reactions are presented in Table 2. Table 2. The ten most important reactions of CH4 combustion, as identified by the present sensitivity analysis.
Important Reactions of Methane Combustion H + O2 ↔ OH + O CH3 + H (+M) ↔ CH4 (+M) CH4 + OH ↔ H2O + CH3 2CH3 (+M) ↔ C2H6 (+M) HO2 + CH3 ↔ CH3O + OH CH3 + O2 ↔ CH2O + OH HCO (+M) ↔ CO + H (+M) HCO + O2 ↔ CO + HO2 H+ OH (+M) ↔ H2O (+M) Η + Ο2 (+Μ) ↔ ΗΟ2 (+Μ)
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Further, the dependence of the important reactions identified (Table 2) on pressure and equivalence ratio was investigated, taking into account the entire set of the present detailed chemistry computational results, for all three prototype problems considered. Depending on the combination of equivalence ratio (φ1.0) and pressure (low, intermediate), six regimes are considered, and shown in Table 3. Processing of the present results shows that the important reactions do not change significantly with the variation of pressure and equivalence ratio. In particular, the chain branching reaction H + O2 ↔ OH + O remains the most important one in the entire range of conditions considered. The present investigation has also identified cases of elementary reactions that do not maintain their significance in the entire range of conditions considered. In particular, elementary reaction CH4 + OH ↔ H2O + CH3 is not present in the set of important reactions for φ>1.0 and low pressure, while 10 ACS Paragon Plus Environment
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elementary reaction CH3 + H (+M) ↔ CH4 (+M) is not present for φ
