Construction and research of bioreactor simulation scale-up model
Objective: Building a perfect bioreactor scale-up model provides convenience for enterprise production, and a guidance for reactor manufacturers. Methods: Through the test of 1.5, 5, 20, 200 L scale reactor, the correlation and parameters of the volume dissolved oxygen coefficient kLa and mixing tim...
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| Format: | Article |
| Language: | English |
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The Editorial Office of Food and Machinery
2023-04-01
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| Series: | Shipin yu jixie |
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| Online Access: | http://www.ifoodmm.com/spyjxen/article/abstract/20230104 |
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| author | HU Yi-wen HAN Fei-fei JIN Kui-qi SUN Yang |
| author_facet | HU Yi-wen HAN Fei-fei JIN Kui-qi SUN Yang |
| author_sort | HU Yi-wen |
| collection | DOAJ |
| description | Objective: Building a perfect bioreactor scale-up model provides convenience for enterprise production, and a guidance for reactor manufacturers. Methods: Through the test of 1.5, 5, 20, 200 L scale reactor, the correlation and parameters of the volume dissolved oxygen coefficient kLa and mixing time tm were optimized and explored, the simulation amplification model of bioreactor was established, and the Scaleuper amplification system was built by MATLAB. Results: Compared with the test results, the simulation deviation of kLa was within ±15%. By introducing the definition of critical speed into the correlation of tm, the overall simulation deviation of tm was reduced by 17.4% compared with the original formula. Within ±10%, the simulation deviation of kLa was reduced by embedding BP neural network. The minimum simulation deviation of BP model can reach 0.1% for the training data range. Conclusion: The scale-up model of the reactor based on the empirical correlation has better simulation results after the relevant parameters are measured. It is feasible to use neural network to simulate and amplify the reactor, but it still needs more data training support. |
| format | Article |
| id | doaj-art-c8a4b9c237404ce79749045789743d1a |
| institution | OA Journals |
| issn | 1003-5788 |
| language | English |
| publishDate | 2023-04-01 |
| publisher | The Editorial Office of Food and Machinery |
| record_format | Article |
| series | Shipin yu jixie |
| spelling | doaj-art-c8a4b9c237404ce79749045789743d1a2025-08-20T02:22:37ZengThe Editorial Office of Food and MachineryShipin yu jixie1003-57882023-04-01391182310.13652/j.spjx.1003.5788.2022.80403Construction and research of bioreactor simulation scale-up modelHU Yi-wen0HAN Fei-fei1JIN Kui-qi2SUN Yang3 School of Life Sciences, Henan University, Kaifeng, Henan 475004 , China BIO-YD-Pharmaceutical-Since, Chengdu, Sichuan 610105 , China BIO-YD-Pharmaceutical-Since, Chengdu, Sichuan 610105 , China School of Life Sciences, Henan University, Kaifeng, Henan 475004 , China Objective: Building a perfect bioreactor scale-up model provides convenience for enterprise production, and a guidance for reactor manufacturers. Methods: Through the test of 1.5, 5, 20, 200 L scale reactor, the correlation and parameters of the volume dissolved oxygen coefficient kLa and mixing time tm were optimized and explored, the simulation amplification model of bioreactor was established, and the Scaleuper amplification system was built by MATLAB. Results: Compared with the test results, the simulation deviation of kLa was within ±15%. By introducing the definition of critical speed into the correlation of tm, the overall simulation deviation of tm was reduced by 17.4% compared with the original formula. Within ±10%, the simulation deviation of kLa was reduced by embedding BP neural network. The minimum simulation deviation of BP model can reach 0.1% for the training data range. Conclusion: The scale-up model of the reactor based on the empirical correlation has better simulation results after the relevant parameters are measured. It is feasible to use neural network to simulate and amplify the reactor, but it still needs more data training support.http://www.ifoodmm.com/spyjxen/article/abstract/20230104 mixing time volumetric dissolved oxygen coefficient bioreactor scale-up neural network scale-up model |
| spellingShingle | HU Yi-wen HAN Fei-fei JIN Kui-qi SUN Yang Construction and research of bioreactor simulation scale-up model Shipin yu jixie mixing time volumetric dissolved oxygen coefficient bioreactor scale-up neural network scale-up model |
| title | Construction and research of bioreactor simulation scale-up model |
| title_full | Construction and research of bioreactor simulation scale-up model |
| title_fullStr | Construction and research of bioreactor simulation scale-up model |
| title_full_unstemmed | Construction and research of bioreactor simulation scale-up model |
| title_short | Construction and research of bioreactor simulation scale-up model |
| title_sort | construction and research of bioreactor simulation scale up model |
| topic | mixing time volumetric dissolved oxygen coefficient bioreactor scale-up neural network scale-up model |
| url | http://www.ifoodmm.com/spyjxen/article/abstract/20230104 |
| work_keys_str_mv | AT huyiwen constructionandresearchofbioreactorsimulationscaleupmodel AT hanfeifei constructionandresearchofbioreactorsimulationscaleupmodel AT jinkuiqi constructionandresearchofbioreactorsimulationscaleupmodel AT sunyang constructionandresearchofbioreactorsimulationscaleupmodel |