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Predicting In-Cylinder Soot in a Heavy-Duty Diesel Engine for Variations in SOI and TDC Temperature Using the Conditional Moment Closure Model

机译:预测重型柴油发动机中的缸内烟灰,使用条件时刻闭合模型进行SOI和TDC温度的变化

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Numerical simulations of in-cylinder soot evolution in the optically accessible heavy-duty diesel engine of Sandia National Laboratories have been performed with the multidimensional conditional moment closure (CMC) model using a reduced n-heptane chemical mechanism coupled with a two-equation soot model. Simulation results are compared to the high-fidelity experimental data by means of pressure traces, apparent heat release rate (AHRR) and time-resolved in-cylinder soot mass derived from optical soot luminosity and multiple wavelength pyrometry in conjunction with high speed soot cloud imaging. In addition, spatial distributions of soot relevant quantities are given for several operating conditions. A broad range of operating conditions has been considered: a sweep in start of injection (SOI) at unchanged top dead center (TDC) ambient conditions and a sweep in TDC temperature at an ambient oxygen volume fraction of 12.7 percent, corresponding to a high level of exhaust gas recirculation (EGR). Ignition delays were captured very well, using unaltered model constants and kinetic parameters. The model was found to reproduce pressure and AHRR traces fairly well, although the premixed portion of combustion was in general slightly underpredicted. Concerning emissions, a quantitative comparison of soot mass evolution is presented. Considering the broad range of conditions the model was capable to reproduce the soot trends well; the predicted peak soot mass agreed within a factor of approximately two for almost all operating conditions considered. Overall, the findings suggest that the presented semi-empirical soot model integrated into the CMC framework is a highly promising approach for the prediction of in-cylinder soot evolution for various diesel engine operating conditions.
机译:在Sandia国家实验室的光学访问的重型柴油发动机的缸内的烟灰演进的数值模拟已经与多维条件矩闭合使用耦合用两方程煤烟模型减小的正庚烷的化学机制被执行(CMC)模型。模拟结果由压力迹线,表观热释放速率(AHRR)和装置相比,高保真实验数据时间分辨缸内烟灰质量从光学煤烟光度和多波长高温计在高速烟灰云成像结合衍生。此外,烟尘相关量的空间分布,给出了几个工作条件。的操作条件的宽范围的已被认为:对应于一高电平不变上死点(TDC)的环境条件,并以12.7%的环境中的氧的体积分数在TDC温度扫描中喷射(SOI)的开始的扫描,废气再循环(EGR)。点火延迟被抓获非常好,用不变的模型常数和动力学参数。该模型被发现再生压力和AHRR痕迹相当好,虽然燃烧的预混合部是在一般略微underpredicted。关于排放量,烟尘质量演变的定量比较呈现。考虑到宽范围的条件下的模型是能够重现烟灰趋势井;预计峰值煤烟质量的大约两倍的范围内进行考虑,几乎所有的操作条件达成一致。总的来说,结果表明,整合到CMC框架所呈现的半经验模型烟灰是用于缸内煤烟进化预测关于各种柴油发动机工况高度希望的方法。

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