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Uncertainty quantification for chromatography model parameters by Bayesian inference using sequential Monte Carlo method
http://hdl.handle.net/2237/0002002206
http://hdl.handle.net/2237/00020022068c700973-33a3-4650-8ad8-6a7a2d84de93
名前 / ファイル | ライセンス | アクション |
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Download is available from 2023/10/31.
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Item type | itemtype_ver1(1) | |||||||||||
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公開日 | 2022-03-11 | |||||||||||
タイトル | ||||||||||||
タイトル | Uncertainty quantification for chromatography model parameters by Bayesian inference using sequential Monte Carlo method | |||||||||||
言語 | en | |||||||||||
著者 |
Yamamoto, Yota
× Yamamoto, Yota
× Yajima, Tomoyuki
× Kawajiri, Yoshiaki
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アクセス権 | ||||||||||||
アクセス権 | embargoed access | |||||||||||
アクセス権URI | http://purl.org/coar/access_right/c_f1cf | |||||||||||
権利 | ||||||||||||
言語 | en | |||||||||||
権利情報 | © 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ | |||||||||||
内容記述 | ||||||||||||
内容記述 | Many model-based optimization methods have been proposed for chromatographic processes to ensure product quality and efficiency, but uncertainty of model parameters should be considered to assure robust design and operation. In this study, we developed a sequential Monte Carlo (SMC) parameter estimation method for chromatographic processes to estimate the parameter uncertainty rigorously within a reasonable amount of computation time. As an example, separation of glucose and fructose is considered. Through the example using artificial data, we confirmed that SMC can perform estimations more efficiently than the existing method, Markov chain Monte Carlo. Furthermore, through the example using lab-scale experimental data, we confirm that the time and effort for the sample analysis to identify the concentration of each component can be eliminated. We also examined the relationship between the number of cores and computation time for parallel implementation of SMC. | |||||||||||
言語 | en | |||||||||||
内容記述タイプ | Abstract | |||||||||||
出版者 | ||||||||||||
言語 | en | |||||||||||
出版者 | Elsevier | |||||||||||
言語 | ||||||||||||
言語 | eng | |||||||||||
資源タイプ | ||||||||||||
資源タイプresource | http://purl.org/coar/resource_type/c_6501 | |||||||||||
タイプ | journal article | |||||||||||
出版タイプ | ||||||||||||
出版タイプ | AM | |||||||||||
出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||||||||
関連情報 | ||||||||||||
関連タイプ | isVersionOf | |||||||||||
識別子タイプ | DOI | |||||||||||
関連識別子 | https://doi.org/10.1016/j.cherd.2021.09.003 | |||||||||||
収録物識別子 | ||||||||||||
収録物識別子タイプ | PISSN | |||||||||||
収録物識別子 | 0263-8762 | |||||||||||
書誌情報 |
en : Chemical Engineering Research and Design 巻 175, p. 223-237, 発行日 2021-11-01 |
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ファイル公開日 | ||||||||||||
日付 | 2023-11-01 | |||||||||||
日付タイプ | Available |