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Mobile Multi-Parameter Measurements for the Dynamic Analysis of Gradients in Brewing Vessels = = Ortsunabhangige Multi-Parameter Messungen fur die dynamische Analyse von Gradienten in Braureaktoren.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Mobile Multi-Parameter Measurements for the Dynamic Analysis of Gradients in Brewing Vessels =/
其他題名:	Ortsunabhangige Multi-Parameter Messungen fur die dynamische Analyse von Gradienten in Braureaktoren.
作者:	Bockisch, Anika.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	194 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-01.
Contained By:	Dissertations Abstracts International82-01.
標題:	Electrical engineering. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27610108
ISBN:	9781392713464

Mobile Multi-Parameter Measurements for the Dynamic Analysis of Gradients in Brewing Vessels = = Ortsunabhangige Multi-Parameter Messungen fur die dynamische Analyse von Gradienten in Braureaktoren.
Bockisch, Anika.

Mobile Multi-Parameter Measurements for the Dynamic Analysis of Gradients in Brewing Vessels =Ortsunabhangige Multi-Parameter Messungen fur die dynamische Analyse von Gradienten in Braureaktoren. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 194 p.

Source: Dissertations Abstracts International, Volume: 82-01.

Thesis (Ph.D.)--Technische Universitaet Berlin (Germany), 2018.

This item must not be sold to any third party vendors.

Industrial processes have to be competitive and thus efficient. Products have to be produced with a high reproducibility and quality. At the same time, the scale of these processes reaches up to several 100 m3 and was even increasing in recent years. This is challenging since the power input is limited in large-scale processes. Therefore, mixing times are increasing in parallel to the volume, whereas heat and mass transfer rates are decreasing. This leads to spatial gradient formation, e.g. for the pH-value, dissolved oxygen (DO), dissolved carbon dioxide (DCO2), temperature or cell concentration. Hence, substrate consumption and metabolite synthesis rates are often altered during scale-up. Since the available sensor technology, which is usually located at an arbitrarily chosen spot in large-scale reactors, is not designed for the consideration of heterogeneities, the knowledge about gradients and their magnitude is rather low. Off-line or on-line data obtained with devices installed at one single position of the tank are not representative for the major part of the liquid phase. Computational fluid dynamics do not necessarily contribute to a better process understanding, if uncoupled from kinetic models, which consider consumption and synthesis rates. In addition, cellular synthesis rates can be affected by the gradient formation, which would also lead to false assumptions in the models. In this thesis, mobile, multi-parameter sensor tools have been developed for in-situ and on-line measurements of various process parameters in order to improve process monitoring in industrial bioreactors. Sensors for the pH-, DO-, DCO2-value, redox potential, conductivity, temperature, and pressure were integrated into sensor units. These monitoring tools were applied in various brewing tanks of different geometries and scales and frequently moved along the height of the liquid phase in the 3 m3, 24 m3, and 170/199 m3 scale. The time-dependent and spatial parameter distribution was correlated to data from off-line metabolite analysis (carbohydrates, main carbon metabolites, sterols). The long-term application of miniaturized sensors with a small membrane diameter and electrolyte volume is challenging in complex brewing media due to the risk of clogging or toxification of the electrolyte by chemical compounds, e.g. DCO2. This negatively affects the measurement stability and sensor drift. With larger sensors, however, the pH-value, redox potential, temperature, and DO-value were measured in brewing fermentations of up to 220 h with a pressure of up to 1.9 bar without significant losses in the measurement stability and with a negligible increase in the sensor drift. In the brewing processes, only a few spatial gradients were detected along the tank height, e.g. for the redox potential with a maximum of 66 mV during the onset of the fermentation and for the pH-value with a maximum of 0.17 pH-units during the main fermentation in the 170/199 m3 scale. During the filling process, even larger gradients of up to 110 mV for the redox potential and 0.2 pH-units were determined. In the 3 m3 scale, the gradients were maximum 23 mV and 0.04 pH-units during the onset of the fermentation. Monitoring of gradients during this operation step allows for real-time adaption of the filling process, reducing time and energy losses. Correlation analyses of on-line sensor data with off-line data from metabolite analysis showed that the carbohydrate concentrations, especially for glucose and fructose, correlated best with the on-line data (pH-, DO-value, redox potential, temperature) (R2 > 0.9), followed by the total sterol content. The mobile multi-parameter measurement devices developed and applied in this thesis allow for a fast detection of gradients in large-scale processes. By the correlation of the sensor data from multi-position measurements with the data from metabolite analysis, the impact of gradients on the bioprocess performance can be described. Hence, critical reactor zones and process phases can be identified rapidly and the filling process as well as tank geometries in combination with filling levels can be optimized for anaerobic fermentation processes.

ISBN: 9781392713464Subjects--Topical Terms:

649834
Electrical engineering.
Subjects--Index Terms:

Biotechnology

Mobile Multi-Parameter Measurements for the Dynamic Analysis of Gradients in Brewing Vessels = = Ortsunabhangige Multi-Parameter Messungen fur die dynamische Analyse von Gradienten in Braureaktoren.
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500 $a Source: Dissertations Abstracts International, Volume: 82-01.
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506 $a This item must not be sold to any third party vendors.
520 $a Industrial processes have to be competitive and thus efficient. Products have to be produced with a high reproducibility and quality. At the same time, the scale of these processes reaches up to several 100 m3 and was even increasing in recent years. This is challenging since the power input is limited in large-scale processes. Therefore, mixing times are increasing in parallel to the volume, whereas heat and mass transfer rates are decreasing. This leads to spatial gradient formation, e.g. for the pH-value, dissolved oxygen (DO), dissolved carbon dioxide (DCO2), temperature or cell concentration. Hence, substrate consumption and metabolite synthesis rates are often altered during scale-up. Since the available sensor technology, which is usually located at an arbitrarily chosen spot in large-scale reactors, is not designed for the consideration of heterogeneities, the knowledge about gradients and their magnitude is rather low. Off-line or on-line data obtained with devices installed at one single position of the tank are not representative for the major part of the liquid phase. Computational fluid dynamics do not necessarily contribute to a better process understanding, if uncoupled from kinetic models, which consider consumption and synthesis rates. In addition, cellular synthesis rates can be affected by the gradient formation, which would also lead to false assumptions in the models. In this thesis, mobile, multi-parameter sensor tools have been developed for in-situ and on-line measurements of various process parameters in order to improve process monitoring in industrial bioreactors. Sensors for the pH-, DO-, DCO2-value, redox potential, conductivity, temperature, and pressure were integrated into sensor units. These monitoring tools were applied in various brewing tanks of different geometries and scales and frequently moved along the height of the liquid phase in the 3 m3, 24 m3, and 170/199 m3 scale. The time-dependent and spatial parameter distribution was correlated to data from off-line metabolite analysis (carbohydrates, main carbon metabolites, sterols). The long-term application of miniaturized sensors with a small membrane diameter and electrolyte volume is challenging in complex brewing media due to the risk of clogging or toxification of the electrolyte by chemical compounds, e.g. DCO2. This negatively affects the measurement stability and sensor drift. With larger sensors, however, the pH-value, redox potential, temperature, and DO-value were measured in brewing fermentations of up to 220 h with a pressure of up to 1.9 bar without significant losses in the measurement stability and with a negligible increase in the sensor drift. In the brewing processes, only a few spatial gradients were detected along the tank height, e.g. for the redox potential with a maximum of 66 mV during the onset of the fermentation and for the pH-value with a maximum of 0.17 pH-units during the main fermentation in the 170/199 m3 scale. During the filling process, even larger gradients of up to 110 mV for the redox potential and 0.2 pH-units were determined. In the 3 m3 scale, the gradients were maximum 23 mV and 0.04 pH-units during the onset of the fermentation. Monitoring of gradients during this operation step allows for real-time adaption of the filling process, reducing time and energy losses. Correlation analyses of on-line sensor data with off-line data from metabolite analysis showed that the carbohydrate concentrations, especially for glucose and fructose, correlated best with the on-line data (pH-, DO-value, redox potential, temperature) (R2 > 0.9), followed by the total sterol content. The mobile multi-parameter measurement devices developed and applied in this thesis allow for a fast detection of gradients in large-scale processes. By the correlation of the sensor data from multi-position measurements with the data from metabolite analysis, the impact of gradients on the bioprocess performance can be described. Hence, critical reactor zones and process phases can be identified rapidly and the filling process as well as tank geometries in combination with filling levels can be optimized for anaerobic fermentation processes.
520 $a Industrielle, grosskalige Prozesse mussen wettbewerbsfahig und daher effizient sein. Produkte mussen mit hoher Reproduzierbarkeit und Qualitat hergestellt werden. Gleichzeitig werden in diesen Prozessen Masstabe von mehreren 100 m³ erreicht, die in den letzten Jahren sogar weiter gestiegen sind. Das bringt Herausforderungen mit sich, da der Energieeintrag in diesen grosskaligen Prozessen limitiert ist. Dadurch verlangern sich mit steigendem Volumen Mischzeiten, wogegen Warme- und Stoffubertragungsraten sinken. Das fuhrt zu raumlichen Gradienten, z.B. beim pH-Wert, Gelostsauerstoff (DO), gelostem Kohlenstoffdioxid (DCO2), bei der Temperatur oder Zellkonzentration. Somit verandern sich Substratverbrauch und metabolische Syntheseraten wahrend der Masstabsvergroserung haufig. Da die verfugbare Sensortechnik, die oft an einem zufallig gewahlten Ort in grosskaligen Reaktoren installiert ist, nicht fur die Betrachtung von Heterogenitaten ausgelegt ist, ist das Wissen uber Gradienten und ihr Ausmas sehr gering. Offline oder online gewonnene Daten, die mittels Mess- oder Probenahmetechniken gewonnen werden, die nur an einem einzigen Punkt im Tank installiert sind, sind nicht reprasentativ fur den Grosteil der Flussigphase. Computer-basierte Fluiddynamik (CFD) tragt nicht notwendigerweise zu einem verbesserten Prozessverstandnis bei, wenn sie losgelost von kinetischen Modellen angewandt wird, die Verbrauchs- und Syntheseraten mit einbeziehen. Zusatzlich konnen zellulare Syntheseraten von Gradienten beeinflusst sein, was wiederum zu verfalschten Annahmen in den Modellen fuhren wurde. In dieser Dissertation wurden mobile Multiparameter Sensor-Tools fur eine in-situ und online Messung verschiedenster Prozessparameter entwickelt, um die Prozessuberwachung in industriellen Bioreaktoren zu verbessern. Sensoren fur die Messung des pH-, DO-, und DCO2-Wertes, dem Redoxpotential, der Leitfahigkeit, der Temperatur und dem Druck wurden in Sensoreinheiten integriert. Diese Sensoreinheiten wurden in unterschiedlichen Brautanks mit verschiedenen Geometrien und Masstaben eingesetzt und im 3 m3, 24 m3 und 170/199 m3 Masstab regelmasig entlang der Flussigkeitshohe bewegt. Die zeit- und ortsabhangige Parameterverteilung wurde mit den Daten aus den offline-Analysen der Metabolite (Kohlenhydrate, Haupt-Kohlenstoff-Metabolite, Sterole) korreliert. Die Langzeitnutzung von miniaturisierten Sensoren mit kleinem Membrandurchmesser und geringem Elektrolytvolumen in komplexen Braumedien ist herausfordernd, da das Risiko besteht, dass sich die Membranen zusetzen oder der Elektrolyt durch chemische Substanzen, wie z.B. DCO2, "vergiftet" wird. Dies beeinflusst die Messstabilitat und das Driftverhalten der Sensoren negativ. Mit den groseren Sensoren wurden dagegen der pH-Wert, das Redoxpotential, die Temperatur und der DO-Wert ohne signifikante Verluste in der Messstabilitat und mit einer vernachlassigbar geringen Sensordrift in Braufermentationen von bis zu 220 h und mit einem Druck von bis zu 1,9 bar gemessen. In den Brauprozessen wurden nur wenige ortsabhangige Gradienten entlang der Tankhohe ermittelt, z.B. fur das Redoxpotential mit maximal 66 mV wahrend der Angarphase und fur den pH-Wert mit einem Maximum von 0,17 pH-Einheiten wahrend der Hauptgarphase im 170/199 m3 Masstab. Wahrend des Befullvorgangs wurden sogar grosere Gradienten von bis zu 110 mV und 0,2 pH-Einheiten gemessen. Die Gradienten im 3 m3 Masstab waren maximal 23 mV und 0,04 pH-Einheiten gros (wahrend der Angarphase). Eine Gradientenuberwachung wahrend dieses Prozessschrittes erlaubt eine Echtzeitanpassung des Befullvorgangs, was Zeit und Energie einspart. Die Korrelationsanalysen der online Sensordaten mit den Daten der offline Metaboliten-Analyse zeigten, dass die Kohlenhydrate, darunter vor allem Glukose und Fruktose, am besten mit den Sensordaten (pH-, DO-Wert, Redoxpotential, Temperatur) korrelieren (R2 > 0,9), gefolgt vom totalen Sterolgehalt. Die mobile Multiparameter-Messtechnik, die in dieser Arbeit entwickelt und angewandt wurde, ermoglicht eine schnelle Bestimmung von Gradienten in grosskaligen Prozessen. Mit Hilfe der Korrelation der Sensordaten aus den Multipositionsmessungen mit den Daten der Metabolitenanalyse kann der Einfluss von Gradienten auf die Bioprozessleistung beschrieben werden. Somit konnen kritische Reaktorzonen und Prozessphasen schnell identifiziert und der Befullvorgang sowie Tankgeometrien in Verbindung mit dem Fullstand fur anaerobe Prozesse optimiert werden.
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