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Surrogate Models for Online Monitoring and Process Troubleshooting of NBR Emulsion Copolymerization

机译:NBR乳液共聚在线监测和过程故障排除的替代模型

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Chemical processes with complex reaction mechanisms generally lead to dynamic models which, while beneficial for predicting and capturing the detailed process behavior, are not readily amenable for direct use in online applications related to process operation, optimisation, control, and troubleshooting. Surrogate models can help overcome this problem. In this research article, the first part focuses on obtaining surrogate models for emulsion copolymerization of nitrile butadiene rubber (NBR), which is usually produced in a train of continuous stirred tank reactors. The predictions and/or profiles for several performance characteristics such as conversion, number of polymer particles, copolymer composition, and weight-average molecular weight, obtained using surrogate models are compared with those obtained using the detailed mechanistic model. In the second part of this article, optimal flow profiles based on dynamic optimisation using the surrogate models are obtained for the production of NBR emulsions with the objective of minimising the off-specification product generated during grade transitions.
机译:具有复杂反应机制的化学过程通常会生成动态模型,该模型虽然有利于预测和捕获详细的过程行为,但不易于直接用于与过程操作,优化,控制和故障排除相关的在线应用程序中。代理模型可以帮助克服此问题。在本研究文章中,第一部分着重于获取丁腈橡胶(NBR)乳液共聚的替代模型,该模型通常在一系列连续搅拌釜反应器中生产。将使用替代模型获得的几种性能特征(例如转化率,聚合物颗粒数,共聚物组成和重均分子量)的预测和/或分布图与使用详细机械模型获得的预测和/或分布图进行比较。在本文的第二部分中,获得了使用替代模型基于动态优化的最佳流动曲线,用于生产NBR乳液,目的是最大程度地减少等级转换过程中产生的不合格产品。

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