An improved manifold-projection trajectory based method for chemical kinetic mechanism reduction

IF 4.1 2区 工程技术 Q2 ENGINEERING, CHEMICAL Chemical Engineering Science Pub Date : 2024-06-22 DOI:10.1016/j.ces.2024.120416
Yuqiang Li , Shoulong Lin , Xueming Zhou , Gang Wu
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Abstract

An improved manifold-projection trajectory based dimension reduction algorithm (MTDR) to automatically generate skeletal chemical kinetic mechanisms was proposed and validated in this study. This algorithm is implemented by constructing an approximate manifold-based trajectory of the combustion system using Euclidean distances between two adjacent points and cosine similarities between two adjacent vectors in the manifold space, and then evaluating the importance of species by calculating the error of manifold-based trajectories before and after the projection of the manifold. In this method, the nature of the combustion system is well reflected since the combustion process information can be captured by the location of the state point in the manifold space. The calculation during the reduction process is simplified by using the manifold-based trajectory instead of the complex differential equations. Compared to our previous work, this study improves the prediction accuracy of the reduced mechanisms through a more comprehensive error evaluation in the mechanism reduction process. The detailed mechanisms of fuels including iso-cetane, iso-octane and gasoline surrogate mixtures of toluene, iso-octane and n-heptane were reduced to portray the prowess of the algorithm. It’s demonstrated that the number of species of the fuels is reduced from 492, 254 and 1389 to 95, 87 and 427 within an acceptable error, respectively. Meanwhile, the case of iso-octane mechanism reduction was chosen to compare the performance of MTDR with traditional methods including path flux analysis (PFA) and directed relation graph with error propagation and sensitivity analysis (DRGEPSA), and it is shown that the MDTR can generate more compact mechanism under a broad range of error limits.

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基于流形投影轨迹的化学动力学机制还原改进方法
本研究提出并验证了一种改进的基于流形投影轨迹的降维算法(MTDR),用于自动生成骨架化学动力学机制。该算法是利用流形空间中相邻两点间的欧氏距离和相邻两向量间的余弦相似度构建燃烧系统的近似流形轨迹,然后通过计算流形投影前后基于流形轨迹的误差来评估物种的重要性。这种方法能很好地反映燃烧系统的性质,因为燃烧过程信息可以通过状态点在流形空间中的位置来捕捉。通过使用基于流形的轨迹而不是复杂的微分方程,简化了还原过程中的计算。与我们之前的工作相比,本研究通过在机理还原过程中进行更全面的误差评估,提高了还原机理的预测精度。研究还原了包括异十六烷、异辛烷以及甲苯、异辛烷和正庚烷的汽油代用混合物在内的燃料的详细机理,以展示算法的卓越性能。结果表明,在可接受的误差范围内,燃料的种类数分别从 492、254 和 1389 种减少到 95、87 和 427 种。同时,以异辛烷机理还原为例,比较了 MTDR 与传统方法(包括路径通量分析法(PFA)和带误差传播和敏感性分析的有向关系图法(DRGEPSA))的性能,结果表明 MDTR 可以在广泛的误差限制范围内生成更紧凑的机理。
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来源期刊
Chemical Engineering Science
Chemical Engineering Science 工程技术-工程:化工
CiteScore
7.50
自引率
8.50%
发文量
1025
审稿时长
50 days
期刊介绍: Chemical engineering enables the transformation of natural resources and energy into useful products for society. It draws on and applies natural sciences, mathematics and economics, and has developed fundamental engineering science that underpins the discipline. Chemical Engineering Science (CES) has been publishing papers on the fundamentals of chemical engineering since 1951. CES is the platform where the most significant advances in the discipline have ever since been published. Chemical Engineering Science has accompanied and sustained chemical engineering through its development into the vibrant and broad scientific discipline it is today.
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