{"title":"推进精准发酵:通过机理建模最大限度降低工业规模生物反应器的动力需求","authors":"Ali Jahanian , Jerome Ramirez , Ian O'Hara","doi":"10.1016/j.compchemeng.2024.108755","DOIUrl":null,"url":null,"abstract":"<div><p>Minimizing power consumption in large-scale aerobic fermentation is essential for cost-effective operations. A mechanistic model of aerobic precision fermentation was developed integrating microbial growth parameters, thermodynamic data, and bioreactor properties. Results showed that agitation power dominated energy consumption at low oxygen transfer rates (<span><math><mrow><mi>O</mi><mi>T</mi><mi>R</mi></mrow></math></span>), shifting to aeration power (70 % of total) at high cell growth rates. In high <span><math><mrow><mi>O</mi><mi>T</mi><mi>R</mi><mi>s</mi></mrow></math></span>, mixing time reduced to 60 s from an initial value of 211 s. Scale-up from 5 m³ to 100 m³ decreased total specific power by 88 %. Operating at elevated headspace pressure lowered agitation speed, reducing total power consumption at high <span><math><mrow><mi>O</mi><mi>T</mi><mi>R</mi></mrow></math></span>. Impeller to bioreactor diameter ratio impacted the required agitation speed without significantly altering total power demand. Experimental data in a 100 L case study indicated a 0.43 kW.m⁻³ average power requirement across a 96-hour fermentation period. Our model demonstrates effective strategies for minimization of power consumption in industrial-scale aerobic fermentations.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":null,"pages":null},"PeriodicalIF":3.9000,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S009813542400173X/pdfft?md5=68e9b0fbc2e0292a4d713de3f0125f1c&pid=1-s2.0-S009813542400173X-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Advancing precision fermentation: Minimizing power demand of industrial scale bioreactors through mechanistic modelling\",\"authors\":\"Ali Jahanian , Jerome Ramirez , Ian O'Hara\",\"doi\":\"10.1016/j.compchemeng.2024.108755\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Minimizing power consumption in large-scale aerobic fermentation is essential for cost-effective operations. A mechanistic model of aerobic precision fermentation was developed integrating microbial growth parameters, thermodynamic data, and bioreactor properties. Results showed that agitation power dominated energy consumption at low oxygen transfer rates (<span><math><mrow><mi>O</mi><mi>T</mi><mi>R</mi></mrow></math></span>), shifting to aeration power (70 % of total) at high cell growth rates. In high <span><math><mrow><mi>O</mi><mi>T</mi><mi>R</mi><mi>s</mi></mrow></math></span>, mixing time reduced to 60 s from an initial value of 211 s. Scale-up from 5 m³ to 100 m³ decreased total specific power by 88 %. Operating at elevated headspace pressure lowered agitation speed, reducing total power consumption at high <span><math><mrow><mi>O</mi><mi>T</mi><mi>R</mi></mrow></math></span>. Impeller to bioreactor diameter ratio impacted the required agitation speed without significantly altering total power demand. Experimental data in a 100 L case study indicated a 0.43 kW.m⁻³ average power requirement across a 96-hour fermentation period. Our model demonstrates effective strategies for minimization of power consumption in industrial-scale aerobic fermentations.</p></div>\",\"PeriodicalId\":286,\"journal\":{\"name\":\"Computers & Chemical Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-06-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S009813542400173X/pdfft?md5=68e9b0fbc2e0292a4d713de3f0125f1c&pid=1-s2.0-S009813542400173X-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Chemical Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S009813542400173X\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Chemical Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S009813542400173X","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Advancing precision fermentation: Minimizing power demand of industrial scale bioreactors through mechanistic modelling
Minimizing power consumption in large-scale aerobic fermentation is essential for cost-effective operations. A mechanistic model of aerobic precision fermentation was developed integrating microbial growth parameters, thermodynamic data, and bioreactor properties. Results showed that agitation power dominated energy consumption at low oxygen transfer rates (), shifting to aeration power (70 % of total) at high cell growth rates. In high , mixing time reduced to 60 s from an initial value of 211 s. Scale-up from 5 m³ to 100 m³ decreased total specific power by 88 %. Operating at elevated headspace pressure lowered agitation speed, reducing total power consumption at high . Impeller to bioreactor diameter ratio impacted the required agitation speed without significantly altering total power demand. Experimental data in a 100 L case study indicated a 0.43 kW.m⁻³ average power requirement across a 96-hour fermentation period. Our model demonstrates effective strategies for minimization of power consumption in industrial-scale aerobic fermentations.
期刊介绍:
Computers & Chemical Engineering is primarily a journal of record for new developments in the application of computing and systems technology to chemical engineering problems.