Naphtha characterization based on a molecular-type homologous series vector representation
MEI Hua, DU Yupeng, WANG Zhenlei, QIAN Feng
Key Laboratory of Advanced Control and Optimization for Chemical Processes of the Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
Abstract:A novel homologous series vector representation method was developed for naphtha in which each homologous molecule of naphtha is defined as a state variable and all these variables are then used to construct a high dimension vector space. Thus, any variation of naphtha as one point in this vector space can be blended linearly by a group of independent naphthas named Basis Oils. These basis oils are obtained using the non-negative matrix factorization (NMF) method with the components data matrix of a huge number of naphtha samples factorized into a characteristic matrix with a lower dimension and its coefficient matrix. In a case study, a naphtha model containing 21 groups of naphtha bases was extracted from 59 groups of naphtha samples with a maximum representation error of less than 2.5 percent of the original data.
梅华, 杜玉鹏, 王振雷, 钱锋. 基于分子同系物向量表示的石脑油特征提取方法[J]. 清华大学学报(自然科学版), 2016, 56(7): 723-727.
MEI Hua, DU Yupeng, WANG Zhenlei, QIAN Feng. Naphtha characterization based on a molecular-type homologous series vector representation. Journal of Tsinghua University(Science and Technology), 2016, 56(7): 723-727.
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