正庚烷对冲扩散火焰中多环芳烃形成机理的简化

使用敏感性分析对正庚烷对冲扩散燃烧火焰中多环芳烃生成的详细反应机理(包括108种组分、572个基元反应)进行简化,得到了可与CFD多维模型耦合计算的简化机理,该机理包括56种组分、83个基元反应.简化机理和详细机理的计算结果非常吻合,表明得到的简化机理能够精确地描述正庚烷对冲扩散火焰的燃烧特性,并且能够定量预测多环芳烃(例如苯、萘、菲、芘等)的生成.     

生物柴油甲酯简化低温燃烧反应机理的构建

通过耦合反应路径分析、路径通量分析(PFA)、同分异构体整合和敏感性分析(SA)共4种简化方法，对一个以生物柴油真实组分中5种典型长链甲基酯为燃油组分的详细反应机理(5 027个组分和19 988个反应)进行简化，构建了一个包含183个组分和748个反应的简化机理．通过与原始机理进行着火延迟、瞬时温度、基于完全搅拌反应器(PSR)燃烧状态的比较以及与基于激波管的着火延迟试验数据、射流搅拌反应器(JSR)中重要组分摩尔分数试验数据的比较，对简化机理进行了全面验证．结果表明：笔者采取的综合性简化方法能够完整保留原始机理的关键反应特性，得到的简化机理能够较好地预测生物柴油的燃烧特性和排放特性．     

等离子体发生器内高温空气化学反应流场分析

空气在高温环境下会发生离解、电离等化学反应使组分发生变化，从而引起流场状态的改变。以一个低温等离子发生器模型为例，应用数值模拟的方法对七种组分，七个化学反应的流场求解，并与纯空气流场的求解结果进行比较．分析化学反应流场流动和传热的特点。在数值模拟过程中采用了局部热力学平衡流体模型，数值格式用SIMPLEC算法，采用贴体坐标的网格模型。计算结果给出了温度场、速度场及组分变化分布图。     

用元素扩散方程和化学平衡热力计算的方法求解多组分反应流场

提出了一种新的方法来计算多组分化学反应流场。它首先引入了元素的分布方程，然后根据化学平衡的热力计算方法求解每一位置的组分及温度。这样，在计算低速流场时，就避免了处理化学反应源项引起的数值计算过程中的方程刚性问题，也减少了组分方程的数量。计算结果表明，这种方法的计算结果比EBU模型的计算结果更好的反应了物质热解离的情况。     

正庚烷部分预混燃烧下多环芳烃生成的简化机理

采用反应流与敏感性分析方法对小分子烃类燃料预混燃烧下多环芳烃生成的详细机理(101种组分,544个基元反应)进行了简化,得到了包括52种组分,83个基元反应的简化机理.采用该简化机理对乙烷预混燃烧下多环芳烃的生成规律进行了数值计算.结果表明,采用该简化机理计算得到的反应物与部分生成物摩尔分数的变化趋势与实验值基本吻合;在该简化机理上加入正庚烷分解和氧化的主要反应(27种组分,36个基元反应),构成了庚烷火焰中多环芳烃生成的简化机理(62种组分,1 19个基元反应);同时对该简化机理在正庚烷部分预混燃烧下多环芳烃的生成规律进行了数值计算,结果表明,采用该简化机理进行计算时所得到的温度分布、主要反应物与部分生成物的摩尔分数的变化趋势与实验值基本吻合.     

某汽轮机中压缸流场的快速分析

采用一种快速求解三维流场的计算方法求解某超超临界汽轮机中压缸流场.介绍了用来模拟叶轮机械内部流动黏性效果的体积力模型,详细叙述了一种求解黏性体积力的方法,并对计算结果进行了分析,为汽轮机气动设计的选择提供了一种新途径.     

一种生物柴油替代物简化机理的构建与验证

选取MD9D、癸酸甲酯(MD)和正庚烷三组分作为生物柴油替代混合物,建立详细化学动力学反应机理。在此基础上,通过误差传递直接关系图法(DRGEP)、同分异构体简化法(Isomer Lumping)、基于DRGEP敏感性分析法3种简化方法耦合的方式对详细化学动力学反应机理进行简化,构建一个简化机理,利用CHEMKIN-PRO软件对简化机理进行模拟计算,并与试验结果进行对比分析。结果表明:简化机理对生物柴油燃烧过程中着火延迟期和重要中间产物CO、CO_2、CH_4、C_2H_4、C_3H_6等有较好的预测能力;在750~900K的低温阶段能再现生物柴油燃烧过程中的负温度系数现象,并且能够在低温燃烧时预测早期CO_2的生成。     

基于直接关系图类方法的丙烯详细机理骨架简化

耦合MATLAB与CHEMKIN-PRO平台,使用直接关系图法(directedrelationgraph,DRG)、基于误差传播的直接关系图法(directed relation graph with error propagation,DRGEP)、两步DRG以及DRG联合DRGEP 4种方法,建立了燃料详细动力学机理骨架简化程序.针对目标工况对丙烯详细机理进行骨架简化,对比4种算法的简化效果,选用DRG联合DRGEP方法,在10%的误差范围内,剔除了约62%的组分和58%的反应,构建了包含187个组分和1 139个反应的丙烯骨架机理.使用该机理计算了简化工况下的着火延迟时间、层流火焰速度和平推流反应器(laminar flow reactor,LFR)模型中的重要组分浓度变化,并与详细机理以及实验数据对比,验证了简化机理的可靠性与简化程序的有效性.     

基于人工神经网络的甲烷富氧燃烧机理优化

采用带误差传播的直接关系图法、全物种敏感性分析和人工神经网络(ANN)联合方法,以点火延迟时间和CO摩尔分数为优化目标,通过对甲烷富氧燃烧详细机理USC mech2.0的简化和优化,提出了基于人工神经网络的甲烷富氧燃烧优化机理(ANN-OMOC)。甲烷富氧燃烧模拟计算和对比分析的结果表明：相比于甲烷富氧燃烧简化机理FSSA的预测误差,优化机理ANN-OMOC对点火延迟时间、层流火焰速度的预测误差分别从2.53%、24.38%降到0.50%、14.41%;与甲烷富氧燃烧的简化机理DRGEP和FSSA相比,优化机理ANN-OMOC对点火延迟时间、OH摩尔分数峰值和CO摩尔分数峰值的预测结果最佳,其相对误差均在10%以下。     

汽油车三效催化转化器反应流的数值模拟

建立了三效催化转化器载体单个孔道内的二维流场模型，并且加入了详细化学反应机理，该机理考虑了8种气体组分和23种表面物质，共有61个基元反应。用计算流体力学软件对反应流进行了数值模拟，得到转化率随温度的变化情况，与试验值吻合良好。并且对模拟得到的气体组分的质量分数分布图进行了分析，得到了流场与催化剂表面化学性质之间的关系，对如何提高三效催化转化器转化率具有重要的参考价值。     

Study on Characteristics of Co-firing Ammonia/Methane Fuels under Oxygen Enriched Combustion Conditions

Having a background of utilising ammonia as an alternative fuel for power generation, exploring the feasibility of co-firing ammonia with methane is proposed to use ammonia to substitute conventional natural gas. However, improvement of the combustion of such fuels can be achieved using conditions that enable an increase of oxygenation, thus fomenting the combustion process of a slower reactive molecule as ammonia. Therefore, the present study looks at oxygen enriched combustion technologies, a proposed concept to improve the performance of ammonia/methane combustion. To investigate the characteristics of ammonia/methane combustion under oxygen enriched conditions, adiabatic burning velocity and burner stabilized laminar flame emissions were studied. Simulation results show that the oxygen enriched method can help to significantly enhance the propagation of ammonia/methane combustion without changing the emission level, which would be quite promising for the design of systems using this fuel for practical applications. Furthermore, to produce low computational-cost flame chemistry for detailed numerical analyses for future combustion studies, three reduced combustion mechanisms of the well-known Konnov’s mechanism were compared in ammonia/methane flame simulations under practical gas turbine combustor conditions. Results show that the reduced reaction mechanisms can provide good results for further analyses of oxygen enriched combustion of ammonia/methane. The results obtained in this study also allow gas turbine designers and modellers to choose the most suitable mechanism for further combustion studies and development.     

Performance predictions of a tubular SOFC operating on a partially reformed JP-8 surrogate

This paper uses chemically reacting flow models to explore the effect of upstream JP-8 steam reforming on the performance of a tubular, anode-supported, solid-oxide fuel cell. In all cases studied in this paper, a steam–carbon ratio of 3 is used for the reformer inlet. However, by varying the reformer temperature, the methane concentration in the reformate stream can be varied. In this study methane mole fractions are varied between 0 and 20%, on a dry basis. The methane mole fraction is found to have a substantial effect on fuel-cell efficiency, power density, and heat-release profiles. The paper also explores the effects of internal reforming chemistry and electrochemical charge transfer on the gas-phase kinetics and propensity for deposit formation. A detailed reaction mechanism is used to describe methane steam reforming on Ni within the anode, while a detailed gas-phase mechanism is used to predict the gas-phase composition in the fuel channel.     

A dynamic multi-timescale method for combustion modeling with detailed and reduced chemical kinetic mechanisms

A new on-grid dynamic multi-timescale (MTS) method is presented to increase significantly the computation efficiency involving multi-physical and chemical processes using detailed and reduced kinetic mechanisms. The methodology of the MTS method using the instantaneous timescales of different species is introduced. The definition of the characteristic time for species is examined and compared with that of the computational singular perturbation (CSP) and frozen reaction rate methods by using a simple reaction system. A hybrid multi-timescale (HMTS) algorithm is constructed by integrating the MTS method with an implicit Euler scheme, respectively, for species with and without the requirement of accurate time histories at sub-base timescales. The efficiency and the robustness of the MTS and HMTS methods are demonstrated by comparing with the Euler and VODE solvers for homogenous ignition and unsteady flame propagation of hydrogen, methane, and n-decane-air mixtures. The results show that both MTS and HMTS reproduce well the species and temperature histories and are able to decrease computation time by about one-order with the same kinetic mechanism. Compared to MTS, HMTS has slightly better computation efficiency but scarifies the stability at large base time steps. The results also show that with the increase of mechanism size and the decrease of time step, the computation efficiency of multi-timescale method increases compared to the VODE solver. In addition, it is shown that the integration of the multi-timescale method with the path flux analysis based mechanism reduction approach can further increase the computation efficiency. Unsteady simulations of outwardly propagating spherical n-decane-air premixed flames demonstrate that the multi-timescale method is rigorous for direct numerical simulations with both detailed and reduced chemistry and can dramatically improve the computation efficiency.     

A model of particulate and species formation applied to laminar, nonpremixed flames for three aliphatic-hydrocarbon fuels

A detailed kinetic mechanism is developed that includes aromatic growth and particulate formation. The model includes reaction pathways leading to the formation of nanosized particles and their coagulation and growth to larger soot particles using a sectional approach for the particle phase. It is tested against literature data of species concentrations and particulate measurements in nonpremixed laminar flames of methane, ethylene, and butene. Reasonably good predictions of gas and particle-phase concentrations and particle sizes are obtained without any change to the kinetic scheme for the different fuels. The model predicts the low concentration of particulates in the methane flame (about 0.5 ppm) and the higher concentration of soot in the ethylene and butene flames (near 10 ppm). Model predictions show that in the methane flame small precursor particles dominate the particulate loading, whereas soot is the major component in ethylene and butene flames, in accordance with the experimental data. The driving factors in the model responsible for the quite different soot predictions in the ethylene and butene flames compared with the methane flame are benzene and acetylene concentrations, which are higher in the ethylene and butene flames. Soot loadings in the ethylene flame are sensitive to the acetylene soot growth reaction, whereas particle inception rates are linked to benzene in the model. A coagulation model is used to obtain collision efficiencies for some of the particle reactions, and tests show that the modeled results are not particularly sensitive to coagulation at the rates used in our model. Soot oxidation rates are not high enough to correctly predict burnout, and this aspect of the model needs further attention.     

正辛醇/正丁醚骨架机理的构建及验证

采用定向关联图误差传播敏感度分析法(DRGEPSA)、同分异构体合并和峰值浓度分析法对正丁醚和正辛醇的详细机理进行简化,并将简化后的正丁醚和正辛醇机理合并,获得了包含117个组分和601个基元反应的骨架机理.利用正丁醚和正辛醇详细机理的着火延迟、正丁醚层流火焰速度的试验数据和正辛醇在射流搅拌反应器(JSR)中组分摩尔浓...     

Selecting the optimum quasi-steady-state species for reduced chemical kinetic mechanisms using a genetic algorithm

A genetic optimization algorithm has been applied to the selection of quasi-steady-state (QSS) species in reduced chemical kinetic mechanisms. The algorithm seeks to minimize the error between reduced and detailed chemistry for simple reactor calculations approximating conditions of interest for a computational fluid dynamics simulation. The genetic algorithm does not guarantee that the global optimum will be found, but much greater accuracy can be obtained than by choosing QSS species through a simple kinetic criterion or by human trial and error. The algorithm is demonstrated for methane–air combustion over a range of temperatures and stoichiometries and for homogeneous charge compression ignition engine combustion. The results are in excellent agreement with those predicted by the baseline mechanism. A factor of two reduction in the number of species was obtained for a skeletal mechanism that had already been greatly reduced from the parent detailed mechanism.     

Zero-dimensional single zone engine modeling of an SI engine fuelled with methane and methane-hydrogen blend using single and double Wiebe Function: A comparative study

Combustion modeling plays a key role in an engine simulation to predict in-cylinder pressure development and engine performance with a high level accuracy. Wiebe function, representing mass fraction burned (MFB) as a function of crank angle position, is widely used to predict the combustion process. The work presents a predictive zero-dimensional (Zero-D) single zone engine modeling of an SI engine fuelled with methane and methane-hydrogen blend. In this work, the single and double forms of Wiebe function were used to estimate the combustion process in the modeling. For this purpose, the single and double-Wiebe functions' parameters were calculated using the least squares method by fitting to the MFB curves calculated from experimental pressure data. These Wiebe functions were, then, introduced to the Zero-D single zone engine model developed for the methane and methane-hydrogen blend fueled SI engine to obtain in-cylinder pressure development and gross indicated mean effective pressure (GIMEP) for the engine performance prediction. The results show that the model with double-Wiebe Function fit better than that with single-Wiebe function. In addition, the fitted double-Wiebe function has a significant improvement in the GIMEP prediction for methane-hydrogen blend fueled SI engine modeling rather than the methane-fueled modeling.     

Autoignition and structure of nonpremixed CH4/H2 flames: Detailed and reduced kinetic models

The ignition dynamics and subsequent flame evolution of hydrogen-enriched methane mixtures are investigated numerically in a reacting vortex ring configuration. The CH₄/H₂ combustion is studied using a detailed reaction mechanism (GRI-Mech v3.0) and two augmented reduced mechanisms (11-step and 12-step). The main objective of this study is to identify the extent that the current reduced mechanisms can go in replicating the dynamics of the ignition process and flame structure in an unsteady nonpremixed configuration. The parameters of the numerical simulations are adjusted such that flame ignition occurs during either the formation or the postformation of the ring. The quasi-steady state assumption for O in the 12-step reduced kinetic model leads to shorter ignition delay times than those in the other kinetic models. For formation-phase ignition runs, the flame structure near the stoichiometric region is captured well by the 12-step model compared to GRI-Mech 3.0. For postformation ignition runs, the 12-step model predicts larger heat release rates and main species mole fractions compared to GRI-Mech 3.0. The 11-step model predicts well the ignition delay time. At later times the fuel-rich side of the flame predicted by this reduced mechanism exhibits differences from the detailed model. Counterflow diffusion flame results are used to further compare the fuel-rich chemistry for the detailed and augmented reduced kinetic models.     

Combined dimension reduction and tabulation strategy using ISAT–RCCE–GALI for the efficient implementation of combustion chemistry

Computations of turbulent combustion flows using detailed chemistry involving a large number of species and reactions are computationally prohibitive, even on a distributed computing system. Here, we present a new combined dimension reduction and tabulation methodology for the efficient implementation of combustion chemistry. In this study, the dimension reduction is performed using the rate controlled constrained-equilibrium (RCCE) method, and tabulation of the reduced space is performed using the in situ adaptive tabulation (ISAT) algorithm. The dimension reduction using RCCE is performed by specifying a set of represented (constrained) species, which in this study is selected using a new Greedy Algorithm with Local Improvement (GALI) (based on the greedy algorithm). This combined approach is found to be particularly fruitful in the probability density function (PDF) approach, wherein the chemical composition is represented by a large number of particles in the solution domain. In this work, the combined approach has been tested and compared to reduced and skeletal mechanisms using a partially-stirred reactor (PaSR) for premixed combustion of (i) methane/air (using the 31-species GRI-Mech 1.2 detailed mechanism and the 16-species ARM1 reduced mechanism) and (ii) ethylene/air (using the 111-species USC-Mech II detailed mechanism, a 38-species skeletal mechanism and a 24-species reduced mechanism). Results are presented to quantify the relative accuracy and efficiency of three different ways of representing the chemistry: (i) ISAT alone (with a detailed mechanism); (ii) ISAT (with a reduced or skeletal mechanism); and (iii) ISAT–RCCE with represented species selected using GALI. We show for methane/air: ISAT (with ARM1 reduced mechanism) incurs 6% error, while ISAT–RCCE incurs the same error using just 8 or more represented species, and less than 1% error using 11 or more represented species, with a twofold speedup relative to using ISAT alone with the GRI-Mech 1.2 detailed mechanism. And we show for ethylene/air: ISAT incurs 7% and 3% errors with the reduced and skeletal mechanisms, respectively, while ISAT–RCCE achieves the same levels of error 7% with just 18 and 3% with just 25 represented species, and also provides 15-fold speedup relative to using ISAT alone with the USC-Mech II detailed mechanism. With fewer species to track in the CFD code, this combined ISAT–RCCE–GALI reduction–tabulation algorithm provides an accurate and efficient way to represent combustion chemistry.     

Effect of hydrogen addition in the co-flow of a methane diffusion flame in reducing nitric oxide emissions

The paper presents numerical simulations of a core methane jet diffusion flame with a fuel lean mixture (consisting of methane and hydrogen, in different proportions) in the co-flow. A comprehensive numerical model, which employs a detailed chemical kinetic mechanism with 25 species and 121 reaction steps, variable thermo-physical properties, multi-component diffusion and an optically thin radiation sub-model, has been used. The results of the numerical model are validated against the experimental data from literature. The validated model is used to study the characteristics of core methane jet diffusion flames with methane and hydrogen in the co-flow. A detailed study of various quantities such as temperature, sensible enthalpies of combustion and nitric oxide emissions is carried out, for different compositions of the fuel in the co-flow oxidizer stream. The co-flow composition which results in minimum nitric oxide emissions is examined.