一种反应结构识别算法的发展

János Kontos, L. R. Tóth, T. Varga
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引用次数: 0

摘要

化学反应器设计过程中最重要的一步是了解将在该反应器中发生的化学反应网络(CRN)。CRN的结构作为反应机理的表示,包含了将试剂转化为产物所需的所有基本反应步骤。反应机理分析的目的是确定体系从初始状态到最终状态的路径。为了做到这一点,需要大量的化学知识,并辅以一些分析测量。在这项工作中,我们专注于一种算法的开发,该算法需要一些数据输入来揭示在反应堆设计观点中重要的所有反应步骤。如果不确定属于该结构的模型参数,就不能确定动态系统的结构,这是微不足道的。因此,本文所报道的算法可以用来获得每一个已识别的化学反应的反应速率方程的参数。首先,确定结构,然后确定其参数。在本研究中,处理后的数据由一个CRN发生器获得,并应用该发生器根据某些指定参数生成随机CRN,以达到最大反应阶数。基于随机生成的CRN进行模拟,得到了在特定反应速率常数组合下表征每个CRN的浓度曲线。所开发的反应机理识别算法基于一种改进的线性最小二乘法(LLSM),由于反应速率常数不能为负值,因此搜索变量必须大于零。通过实例验证了该算法在反应结构识别过程中的适用性,结果表明,通过进一步改进,该算法可用于解决更复杂的识别任务。
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Development of a Reaction Structure Identification Algorithm
The most important step in the design procedure of a chemical reactor is the understanding the chemical reaction network (CRN), which will take place in that reactor. The structure of a CRN as representation of the reaction mechanism contains all the elementary reaction steps that are required to convert the reagents into products. The aim of the reaction mechanism analysis is the identification of the route how the system goes from its initial to the end state. In order to do this, a lot of knowledge is required about chemistry supplemented with some analytical measurements. In this work, we focus on the development of an algorithm, which requires a few data inputs to reveal all the reaction steps that are important in the reactor design point of view. It is trivial that the structure of a dynamic system cannot be determined without the identification of the model parameters that belong to that structure. Hence, the algorithm reported here can be used to obtain the parameters of the reaction rate equations for each identified chemical reaction. First, the structure is identified followed by its parameters. In this study the processed data are obtained by a CRN generator, which is applied to generate random CRNs based on some specified parameters to reach maximal reaction order. Concentration profiles, which characterize each CRN at a specific reaction rate constants combination, are obtained as a result of simulations based on the randomly generated CRNs. The developed algorithm for reaction mechanism identification is based on a modified type of linear least-squares method (LLSM) in which the searching variables must be higher than zero, since the reaction rate constants cannot have negative values. The developed algorithm is tested in different cases to check the applicability of LLSM in reaction structure identification procedure and the obtained results show that with some further improvements the proposed algorithm can be applied solving more complex identification tasks.
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