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首页> 外文期刊>Crystal growth & design >Model-Based Evaluation of Direct Nucleation Control Approaches for the Continuous Cooling Crystallization of Paracetamol in a Mixed Suspension Mixed Product Removal System
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Model-Based Evaluation of Direct Nucleation Control Approaches for the Continuous Cooling Crystallization of Paracetamol in a Mixed Suspension Mixed Product Removal System

机译：基于模型的直接成核控制方法对混合悬浮混合产物去除系统连续冷却结晶的直接核切割方法

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src="http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/cgdefu/2017/cgdefu.2017.17.issue-10/acs.cgd.7b00860/20170928/images/medium/cg-2017-00860v_0001.gif">Direct nucleation control (DNC) is a model-free feedback control approach based on the measurement of particle number in the crystallization process. The experimental implementation has demonstrated that this approach is efficient to produce large and uniform crystals in batch crystallization, or to reduce startup duration and suppress disturbance in continuous crystallization. In this work, five different DNC frameworks/strategies are proposed for a continuous mixed suspension mixed product removal (MSMPR) crystallization of paracetamol–water system and evaluated systematically using a model-based approach. It is found that the reverse DNC framework could provide the best control performance in terms of startup, set-point change, and disturbance suppression. In addition, an optimal heating/cooling rate of about 0.6 °C/min was determined. These observations are applicable for the model compound studied (paracetamol) and should be investigated for other systems. This study provides a general guidance of designing a DNC framework with the best control performance for continuous MSMPR crystallization.
机译：src =“http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/cgdefu/2017/cgdefu.2017.17.issue-10/acs.cgd.7b00860/20170928/images/medium /c-2017-00860V_0001.GIF"ENEDIRECT成核控制（DNC）是一种无模型反馈控制方法，基于结晶过程中的粒子数的测量。实验实施已经证明了这种方法有效地在批量结晶中产生大型且均匀的晶体，或减少在连续结晶中抑制扰动并抑制干扰。在这项工作中，提出了五种不同的DNC框架/策略，用于扑热息油 - 水系统的连续混合悬浮混合产物去除（MSMPR）结晶，并系统地使用基于模型的方法进行评估。发现反向DNC框架可以在启动，设定点变化和干扰抑制方面提供最佳控制性能。另外，确定约0.6℃/ min的最佳加热/冷却速率。这些观察结果适用于所研究的模型化合物（扑热息痛），并应研究其他系统。本研究提供了设计DNC框架的一般指导，具有用于连续MSMPR结晶的最佳控制性能。

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  • 来源
    《Crystal growth & design》 |2017年第10期|共7页
  • 作者

    David Acevedo; Yang Yang; Daniel J. Warnke; Zoltan K. Nagy;

  • 作者单位

    Davidson School of Chemical Engineering Purdue University West Lafayette Indiana 47907 United States;

    Davidson School of Chemical Engineering Purdue University West Lafayette Indiana 47907 United States;

    Davidson School of Chemical Engineering Purdue University West Lafayette Indiana 47907 United States;

    Davidson School of Chemical Engineering Purdue University West Lafayette Indiana 47907 United States;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 晶体学;
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