Liang Enzhi, Zhang Song, Liu Bin, Qi Bujin, Nie Yanpei, Yuan Zhihong
State Key Laboratory of Chemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China.
China Sunsine Chemical Holdings Ltd., Shanxian City, Shandong 274300, China.
ACS Omega. 2022 Feb 21;7(8):6963-6977. doi: 10.1021/acsomega.1c06646. eCollection 2022 Mar 1.
As an important chemical intermediate, 2-mercaptobenzothiazole (MBT) is widely used in various processes, especially in the rubber industry. However, there is no first-principles model that describes the synthetic process of MBT. This paper focuses on the formulation of a reliable mathematical model represented by a series of differential and algebraic equations for the industrial batch MBT production process. It is difficult to estimate all of the unknown parameters in the model because of the lack of sufficient industrial/experimental data. Thus, a reduced estimable parameter set is derived by performing estimability analysis on the original estimation problem. A multiple-starting-point strategy is then applied to numerically solve the non-convex parameter estimation problem with the weighted least-squares approach. Subsequently, a cross-validation technique is employed to evaluate the generalizability of the proposed model. Finally, it is confirmed that the proposed model produces encouraging prediction performance with regard to independent test data.
作为一种重要的化学中间体,2-巯基苯并噻唑(MBT)广泛应用于各种工艺过程,尤其是橡胶工业。然而,目前尚无描述MBT合成过程的第一性原理模型。本文重点在于为工业间歇式MBT生产过程建立一个由一系列微分方程和代数方程表示的可靠数学模型。由于缺乏足够的工业/实验数据,难以估计模型中的所有未知参数。因此,通过对原始估计问题进行可估计性分析,导出了一个简化的可估计参数集。然后应用多起点策略,采用加权最小二乘法对非凸参数估计问题进行数值求解。随后,采用交叉验证技术来评估所提出模型的泛化能力。最后,证实所提出的模型对于独立测试数据具有令人鼓舞的预测性能。