基于催化重整分子级模型的物质流量分析方法

doi:10.11949/0438-1157.20250732

摘要/Abstract

摘要：

催化重整是提高汽油辛烷值、生产高附加值芳烃和氢气的重要炼油工艺，针对催化重整转化过程开展分子水平的反应与物质转化规律的研究具有重要意义。利用分子重构和完备反应网络构造方法，构建了催化重整分子级模型，从而能够准确模拟不同条件下的产物组成。在此基础上，提出了针对分子级模型的物质流量分析方法。该方法首先利用反应网络的结构化表示矩阵，构造物质在反应之间的流转方程组，解析单一反应、关键组分，以及集总后的各类型反应、各类烃分子的物质流转规律，分析其在催化重整完整反应体系中的作用。提出了多尺度网络结构图与反应-物质流桑基图相结合的可视化方法，清晰、直观地展示和分析核心组分之间、不同烃类与反应类型之间的物质流量转化关系和重要性对比。还研究了不同反应温度、反应压力下的催化重整反应体系中物质流转规律的变化趋势，从分子级反应层面解释操作条件对产物组成的影响。物质流量分析方法实现了微观的物质流量和宏观的反应规律间的连接，为探究催化重整反应机理、制定生产调度方案、优化工艺流程提供了新的视角和思路。

关键词: 动力学模型, 优化, 系统工程, 催化重整, 分子级, 反应网络, 物质流量

Abstract:

Catalytic reforming is an important refining process for improving gasoline octane number and producing high-value-added aromatics and hydrogen. Studying the molecular-level reactions and material transformations in the catalytic reforming conversion process is of great significance. This study developed a molecular-level model for catalytic reforming process by molecular reconstruction and comprehensive reaction network construction method, with calculated product mass fractions within ±1% absolute error across the measured temperature and pressure ranges. Based on this, the substance flow analysis method was presented. First, molecular and kinetic information in the reaction network was converted into structure matrix. And then a system of linear equations was established to quantitatively describe transformation of substance through reactions. Patterns of molecule transformation were analyzed in terms of single reaction, key components and grouped types of reaction and molecules. And roles of these parts were examined in the complete catalytic reforming reaction system. A visualization method combining the multi-scale network structure figure with the reaction-substance flow Sankey figure was presented. The transformation relationships and importance comparison of substance flows between key components, as well as between different types of hydrocarbons and reactions, were clearly and intuitively presented and analyzed. Furthermore, this work investigated the variation trends in substance flow within catalytic reforming reaction system under different temperatures and pressures, explaining influence of operating conditions on product composition from the perspective of molecular-level reaction. Substance flow analysis method established a connection between microscopic substance flow and macroscopic reaction mechanisms. This study focused on key information of reaction network, and provided reliable support for investigation of reaction mechanisms and optimization of industrial processes.

Key words: kinetic modeling, optimization, systems engineering, catalytic reforming, molecular-level, reaction network, substance flow

中图分类号:

TQ 015

陶一, 张晨, 朱洪翔, 邱彤. 基于催化重整分子级模型的物质流量分析方法[J]. 化工学报, 2025, 76(12): 6465-6476.

Yi TAO, Chen ZHANG, Hongxiang ZHU, Tong QIU. Substance flow analysis method based on molecular-level model for catalytic reforming process[J]. CIESC Journal, 2025, 76(12): 6465-6476.

图/表 15

图1 分子级模型的研究框架

Fig.1 Framework of molecule-level model

图2 基于分子级反应模型的物质流量分析流程图

Fig.2 Flowchart of substance flow analysis method based on molecular-level model

图3 原料重构分子库中的典型核心结构

Fig.3 Typical core structures in the reconstructed molecular library of feed

图4 典型反应规则示例

Fig.4 Examples of typical reaction rules

表1 反应网络结构化矩阵的信息

Table 1 Information in the structured matrices of reaction networks

矩阵名称	矩阵维度	矩阵元素含义
M₁	$R m × n$	$(i, j)$ 位置的元素表示第 $j$ 个反应中第 $i$ 个分子作为反应物的化学计量数
M₂	$R m × n$	$(i, j)$ 位置的元素表示第 $j$ 个反应中第 $i$ 个分子作为生成物的化学计量数
$K$	$R n × n$	对角矩阵， $(j, j)$ 位置的元素表示第 $j$ 个反应的反应速率常数（以反应物为基准）

表1 反应网络结构化矩阵的信息

Table 1 Information in the structured matrices of reaction networks

矩阵名称	矩阵维度	矩阵元素含义
M₁	$R m × n$	$(i, j)$ 位置的元素表示第 $j$ 个反应中第 $i$ 个分子作为反应物的化学计量数
M₂	$R m × n$	$(i, j)$ 位置的元素表示第 $j$ 个反应中第 $i$ 个分子作为生成物的化学计量数
$K$	$R n × n$	对角矩阵， $(j, j)$ 位置的元素表示第 $j$ 个反应的反应速率常数（以反应物为基准）

图5 网络中无流出环形反应和纯生成物的处理方法

Fig.5 Methods for handling cyclic reaction without outflow and pure products in networks

表2 实验操作条件

Table 2 Experimental operating conditions

序号	反应温度/℃	反应压力/MPa	质量空速/h^-1	进料量/(g/h)	催化剂种类
1	482	0.6	1.94	293	1
2	487	0.6	1.94	293	1
3	492	0.6	1.94	293	1
4	497	0.6	1.94	293	1
5	502	0.6	1.94	293	1
6	497	0.4	1.94	293	2
7	497	0.5	1.94	293	2
8	497	0.6	1.94	293	2
9	497	0.7	1.94	293	2
10	497	0.8	1.94	293	2

图6 原料石脑油分子重构结果

Fig.6 Molecular reconstruction results of naphtha feedstock

图7 不同反应温度下的产物组成

Fig.7 Product composition at different reaction temperatures

图8 不同反应压力下的产物组成

Fig.8 Product composition at different reaction pressures

图9 实验1的完整反应网络

Fig.9 Complete reaction network of experiment 1

图10 反应流量较大的C7化合物子网络

Fig.10 Sub-network of C7 compounds with large material flows

图11 苯和正己基苯的主要反应及摩尔流量

Fig.11 Important reactions and molar flow rates of benzene and n-hexylbenzene

图12 不同温度下的反应-物质流桑基图

Fig.12 Reaction-substance flow Sankey figures at different reaction temperatures

图13 不同压力下的反应-物质流桑基图

Fig.13 Reaction-substance flow Sankey figures at different reaction pressures

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