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Monitoring batch suspension polymerization process based on calorimetric-state estimation technique.

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Title: Monitoring batch suspension polymerization process based on calorimetric-state estimation technique.
Authors: Sreeja, E. S.1 (AUTHOR), Dhanya Ram, V.1 (AUTHOR) dhanyaram@nitc.ac.in
Source: Chemical Engineering Communications. 2025, Vol. 212 Issue 4, p589-602. 14p.
Subjects: Heat transfer coefficient, Data conversion, Batch processing, Heat losses, Heat capacity
Abstract: This work introduces an approach to enhance the real-time monitoring of batch suspension polymerization processes through the integration of real-time calorimetry and state estimation techniques. The challenges inherent in monitoring dynamic and complex processes, particularly in the absence of direct measurements, are effectively addressed through the proposed approach. A dynamic model equation specific to batch operation is employed to assess conversion throughout the process, with timely updates of dynamic parameters in the model equation. A nonlinear high gain cascaded observer with calorimetric measurements estimates the overall heat transfer coefficient and reaction heat. Variations in other parameters such as heat capacity and density are derived from estimated conversion data and updated in the model equation. The study also accounts for the heat loss to the surroundings during isoperibolic batch processes. Validation of the proposed soft sensor model is carried out by comparing the estimated and experimental conversion data by conducting MMA suspension polymerization in a reaction calorimeter. Results demonstrate the potential of calorimetric state estimation as an alternative to direct conversion measurements, offering comprehensive and enhanced monitoring of the batch suspension polymerization process. [ABSTRACT FROM AUTHOR]
Copyright of Chemical Engineering Communications is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Monitoring batch suspension polymerization process based on calorimetric-state estimation technique.
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  Data: <searchLink fieldCode="JN" term="%22Chemical+Engineering+Communications%22">Chemical Engineering Communications</searchLink>. 2025, Vol. 212 Issue 4, p589-602. 14p.
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  Data: <searchLink fieldCode="DE" term="%22Heat+transfer+coefficient%22">Heat transfer coefficient</searchLink><br /><searchLink fieldCode="DE" term="%22Data+conversion%22">Data conversion</searchLink><br /><searchLink fieldCode="DE" term="%22Batch+processing%22">Batch processing</searchLink><br /><searchLink fieldCode="DE" term="%22Heat+losses%22">Heat losses</searchLink><br /><searchLink fieldCode="DE" term="%22Heat+capacity%22">Heat capacity</searchLink>
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  Label: Abstract
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  Data: This work introduces an approach to enhance the real-time monitoring of batch suspension polymerization processes through the integration of real-time calorimetry and state estimation techniques. The challenges inherent in monitoring dynamic and complex processes, particularly in the absence of direct measurements, are effectively addressed through the proposed approach. A dynamic model equation specific to batch operation is employed to assess conversion throughout the process, with timely updates of dynamic parameters in the model equation. A nonlinear high gain cascaded observer with calorimetric measurements estimates the overall heat transfer coefficient and reaction heat. Variations in other parameters such as heat capacity and density are derived from estimated conversion data and updated in the model equation. The study also accounts for the heat loss to the surroundings during isoperibolic batch processes. Validation of the proposed soft sensor model is carried out by comparing the estimated and experimental conversion data by conducting MMA suspension polymerization in a reaction calorimeter. Results demonstrate the potential of calorimetric state estimation as an alternative to direct conversion measurements, offering comprehensive and enhanced monitoring of the batch suspension polymerization process. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Chemical Engineering Communications is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1080/00986445.2024.2426163
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      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 589
    Subjects:
      – SubjectFull: Heat transfer coefficient
        Type: general
      – SubjectFull: Data conversion
        Type: general
      – SubjectFull: Batch processing
        Type: general
      – SubjectFull: Heat losses
        Type: general
      – SubjectFull: Heat capacity
        Type: general
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      – TitleFull: Monitoring batch suspension polymerization process based on calorimetric-state estimation technique.
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              Text: 2025
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              Y: 2025
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