1
|
Experimental Analysis of Mixing-Processes in Biogas Plants. Chem Eng Sci 2022. [DOI: 10.1016/j.ces.2022.117767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
|
2
|
Ho P, Täuber S, Stute B, Grünberger A, von Lieres E. Microfluidic Reproduction of Dynamic Bioreactor Environment Based on Computational Lifelines. FRONTIERS IN CHEMICAL ENGINEERING 2022. [DOI: 10.3389/fceng.2022.826485] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The biotechnological production of fine chemicals, proteins and pharmaceuticals is usually hampered by loss of microbial performance during scale-up. This challenge is mainly caused by discrepancies between homogeneous environmental conditions at laboratory scale, where bioprocesses are optimized, and inhomogeneous conditions in large-scale bioreactors, where production takes place. Therefore, to improve strain selection and process development, it is of great interest to characterize these fluctuating conditions at large-scale and to study their effects on microbial cells. In this paper, we demonstrate the potential of computational fluid dynamics (CFD) simulation of large-scale bioreactors combined with dynamic microfluidic single-cell cultivation (dMSCC). Environmental conditions in a 200 L bioreactor were characterized with CFD simulations. Computational lifelines were determined by combining simulated turbulent multiphase flow, mass transport and particle tracing. Glucose availability for Corynebacterium glutamicum cells was determined. The reactor was simulated with average glucose concentrations of 6 g m−3, 10 g m−3 and 16 g m−3. The resulting computational lifelines, discretized into starvation and abundance regimes, were used as feed profiles for the dMSCC to investigate how varying glucose concentration affects cell physiology and growth rate. In this study, each colony in the dMSCC device represents a single cell as it travels through the reactor. Under oscillating conditions reproduced in the dMSCC device, a decrease in growth rate of about 40% was observed compared to continuous supply with the same average glucose availability. The presented approach provides insights into environmental conditions observed by microorganisms in large-scale bioreactors. It also paves the way for an improved understanding of how inhomogeneous environmental conditions influence cellular physiology, growth and production.
Collapse
|
3
|
Characterization of mixing performance in bioreactors using flow-following sensor devices. Chem Eng Res Des 2021. [DOI: 10.1016/j.cherd.2021.08.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
|
4
|
Automated Compartment Model Development Based on Data from Flow-Following Sensor Devices. Processes (Basel) 2021. [DOI: 10.3390/pr9091651] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Due to the heterogeneous nature of large-scale fermentation processes they cannot be modelled as ideally mixed reactors, and therefore flow models are necessary to accurately represent the processes. Computational fluid dynamics (CFD) is used more and more to derive flow fields for the modelling of bioprocesses, but the computational demands associated with simulation of multiphase systems with biokinetics still limits their wide applicability. Hence, a demand for simpler flow models persists. In this study, an approach to develop data-based flow models in the form of compartment models is presented, which utilizes axial-flow rates obtained from flow-following sensor devices in combination with a proposed procedure for automatic zoning of volume. The approach requires little experimental effort and eliminates the necessity for computational determination of inter-compartmental flow rates and manual zoning. The concept has been demonstrated in a 580 L stirred vessel, of which models have been developed for two types of impellers with varying agitation intensities. The sensor device measurements were corroborated by CFD simulations, and the performance of the developed compartment models was evaluated by comparing predicted mixing times with experimentally determined mixing times. The data-based compartment models predicted the mixing times for all examined conditions with relative errors in the range of 3–27%. The deviations were ascribed to limitations in the flow-following behavior of the sensor devices, whose sizes were relatively large compared to the examined system. The approach provides a versatile and automated flow modelling platform which can be applied to large-scale bioreactors.
Collapse
|
5
|
Understanding gradients in industrial bioreactors. Biotechnol Adv 2020; 46:107660. [PMID: 33221379 DOI: 10.1016/j.biotechadv.2020.107660] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 10/22/2020] [Accepted: 11/14/2020] [Indexed: 01/07/2023]
Abstract
Gradients in industrial bioreactors have attracted substantial research attention since exposure to fluctuating environmental conditions has been shown to lead to changes in the metabolome, transcriptome as well as population heterogeneity in industrially relevant microorganisms. Such changes have also been found to impact key process parameters like the yield on substrate and the productivity. Hence, understanding gradients is important from both the academic and industrial perspectives. In this review the causes of gradients are outlined, along with their impact on microbial physiology. Quantifying the impact of gradients requires a detailed understanding of both fluid flow inside industrial equipment and microbial physiology. This review critically examines approaches used to investigate gradients including large-scale experimental work, computational methods and scale-down approaches. Avenues for future work have been highlighted, particularly the need for further coordinated development of both in silico and experimental tools which can be used to further the current understanding of gradients in industrial equipment.
Collapse
|
6
|
Bisgaard J, Muldbak M, Cornelissen S, Tajsoleiman T, Huusom JK, Rasmussen T, Gernaey KV. Flow-following sensor devices: A tool for bridging data and model predictions in large-scale fermentations. Comput Struct Biotechnol J 2020; 18:2908-2919. [PMID: 33163151 PMCID: PMC7595931 DOI: 10.1016/j.csbj.2020.10.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 09/27/2020] [Accepted: 10/02/2020] [Indexed: 12/11/2022] Open
Abstract
Production-scale fermentation processes in industrial biotechnology experience gradients in process variables, such as dissolved gases, pH and substrate concentrations, which can potentially affect the production organism and therefore the yield and profitability of the processes. However, the extent of the heterogeneity is unclear, as it is currently a challenge at large scale to obtain representative measurements from different zones of the reactor volume. Computational fluid dynamics (CFD) models have proven to be a valuable tool for better understanding the environment inside bioreactors. Without detailed measurements to support the CFD predictions, the validity of CFD models is debatable. A promising technology to obtain such measurements from different zones in the bioreactors are flow-following sensor devices, whose development has recently benefitted from advancements in microelectronics and sensor technology. This paper presents the state of the art within flow-following sensor device technology and addresses how the technology can be used in large-scale bioreactors to improve the understanding of the process itself and to test the validity of detailed computational models of the bioreactors in the future.
Collapse
Affiliation(s)
- Jonas Bisgaard
- Freesense ApS, Copenhagen, Denmark.,Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 228A, 2800 Kgs. Lyngby, Denmark
| | - Monica Muldbak
- Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 228A, 2800 Kgs. Lyngby, Denmark
| | | | - Tannaz Tajsoleiman
- Freesense ApS, Copenhagen, Denmark.,Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 228A, 2800 Kgs. Lyngby, Denmark
| | - Jakob K Huusom
- Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 228A, 2800 Kgs. Lyngby, Denmark
| | | | - Krist V Gernaey
- Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 228A, 2800 Kgs. Lyngby, Denmark
| |
Collapse
|
7
|
Annas S, Elfering M, Volbert N, Jantzen H, Scholz J, Janoske U. Einfluss der Rührwerksposition auf den Mischprozess in Biogasanlagen anhand eines Paddelrührwerks. CHEM-ING-TECH 2019. [DOI: 10.1002/cite.201800116] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Sven Annas
- FH MünsterFachbereich Maschinenbau Stegerwaldstraße 39 48565 Steinfurt Deutschland
- Bergische Universität WuppertalFakultät für Maschinenbau und Sicherheitstechnik Gaußstraße 20 42119 Wuppertal Deutschland
| | - Michael Elfering
- FH MünsterFachbereich Maschinenbau Stegerwaldstraße 39 48565 Steinfurt Deutschland
| | - Nico Volbert
- FH MünsterFachbereich Maschinenbau Stegerwaldstraße 39 48565 Steinfurt Deutschland
| | - Hans‐Arno Jantzen
- FH MünsterFachbereich Maschinenbau Stegerwaldstraße 39 48565 Steinfurt Deutschland
| | - Jürgen Scholz
- FH MünsterFachbereich Maschinenbau Stegerwaldstraße 39 48565 Steinfurt Deutschland
| | - Uwe Janoske
- Bergische Universität WuppertalFakultät für Maschinenbau und Sicherheitstechnik Gaußstraße 20 42119 Wuppertal Deutschland
| |
Collapse
|
8
|
Kress P, Nägele HJ, Oechsner H, Ruile S. Effect of agitation time on nutrient distribution in full-scale CSTR biogas digesters. BIORESOURCE TECHNOLOGY 2018; 247:1-6. [PMID: 28942207 DOI: 10.1016/j.biortech.2017.09.054] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2017] [Revised: 09/05/2017] [Accepted: 09/06/2017] [Indexed: 06/07/2023]
Abstract
The aim of this work was to study the impact of reduced mixing time in a full-scale CSTR biogas reactor from 10 to 5 and to 2min in half an hour on the distribution of DM, acetic acid and FOS/TAC as a measure to cut electricity consumption. The parameters in the digestate were unevenly distributed with the highest concentration measured at the point of feeding. By reducing mixing time, the FOS/TAC value increases by 16.6%. A reduced mixing time of 2min lead to an accumulation of 15% biogas in the digestate.
Collapse
Affiliation(s)
- Philipp Kress
- University of Hohenheim, State Institute of Agricultural Engineering and Bioenergy, Garbenstraße 9, Stuttgart 70599, Germany.
| | - Hans-Joachim Nägele
- University of Hohenheim, State Institute of Agricultural Engineering and Bioenergy, Garbenstraße 9, Stuttgart 70599, Germany
| | - Hans Oechsner
- University of Hohenheim, State Institute of Agricultural Engineering and Bioenergy, Garbenstraße 9, Stuttgart 70599, Germany
| | - Stephan Ruile
- University of Hohenheim, State Institute of Agricultural Engineering and Bioenergy, Garbenstraße 9, Stuttgart 70599, Germany
| |
Collapse
|
9
|
Reinecke SF, Jobst K, Hampel U. Untersuchung der Hydrodynamik von ovalen Biogasreaktoren mit instrumentierten Strömungsfolgern. CHEM-ING-TECH 2017. [DOI: 10.1002/cite.201600153] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
| | - Karin Jobst
- Fraunhofer-Institut für Keramische Technologien und Systeme (IKTS); Arbeitsgruppe Mischprozesse und Reaktoroptimierung; Winterbergstraße 28 01277 Dresden Deutschland
| | - Uwe Hampel
- Helmholtz-Zentrum Dresden-Rossendorf (HZDR); Bautzner Landstraße 400 01328 Dresden Deutschland
- Technische Universität Dresden; Institut für Energietechnik; 01062 Dresden Deutschland
| |
Collapse
|
10
|
Reinecke SF, Deutschmann A, Jobst K, Hampel U. Macro-mixing characterisation of a stirred model fermenter of non-Newtonian liquid by flow following sensor particles and ERT. Chem Eng Res Des 2017. [DOI: 10.1016/j.cherd.2016.12.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
|
11
|
McClure DD, Kavanagh JM, Fletcher DF, Barton GW. Characterizing bubble column bioreactor performance using computational fluid dynamics. Chem Eng Sci 2016. [DOI: 10.1016/j.ces.2016.01.016] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
|
12
|
Montante G, Paglianti A. Fluid dynamics characterization of a stirred model bio-methanation digester. Chem Eng Res Des 2015. [DOI: 10.1016/j.cherd.2014.05.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
|
13
|
Naegele HJ, Mönch-Tegeder M, Haag NL, Oechsner H. Effect of substrate pretreatment on particle size distribution in a full-scale research biogas plant. BIORESOURCE TECHNOLOGY 2014; 172:396-402. [PMID: 25308908 DOI: 10.1016/j.biortech.2014.09.037] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2014] [Revised: 09/03/2014] [Accepted: 09/06/2014] [Indexed: 06/04/2023]
Abstract
The objective of this study was to investigate the pretreatment effects of high-fibre substrate on particle size distribution in a full-scale agricultural biogas plant (BGP). Two digesters, one fed with pretreated material and one with untreated material, were investigated for a period of 90days. Samples from different positions and heights were taken with a special probe sampling system and put through a wet sieve. The results show that on average 58.0±8.6% of the particles in both digesters are fine fraction (<0.063mm). A higher amount of particles (13.1%) with a length >4mm was measured in the untreated digester. However, the volume distribution over all positions and heights did not show a clear and uniform distribution of particles. These results reveal that substrate pretreatment has an effect on particle size in the fermenting substrate, but due to the uneven distribution mixing, is not homogeneous within the digester.
Collapse
Affiliation(s)
- Hans-Joachim Naegele
- University of Hohenheim, State Institute of Agricultural Engineering and Bioenergy, Garbenstrasse 9, Stuttgart 70599, Germany.
| | - Matthias Mönch-Tegeder
- University of Hohenheim, State Institute of Agricultural Engineering and Bioenergy, Garbenstrasse 9, Stuttgart 70599, Germany.
| | - Nicola Leonard Haag
- University of Hohenheim, State Institute of Agricultural Engineering and Bioenergy, Garbenstrasse 9, Stuttgart 70599, Germany.
| | - Hans Oechsner
- University of Hohenheim, State Institute of Agricultural Engineering and Bioenergy, Garbenstrasse 9, Stuttgart 70599, Germany.
| |
Collapse
|
14
|
How Efficient are Agitators in Biogas Digesters? Determination of the Efficiency of Submersible Motor Mixers and Incline Agitators by Measuring Nutrient Distribution in Full-Scale Agricultural Biogas Digesters. ENERGIES 2013. [DOI: 10.3390/en6126255] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
|
15
|
Delvigne F, Goffin P. Microbial heterogeneity affects bioprocess robustness: Dynamic single-cell analysis contributes to understanding of microbial populations. Biotechnol J 2013; 9:61-72. [DOI: 10.1002/biot.201300119] [Citation(s) in RCA: 100] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2013] [Revised: 08/23/2013] [Accepted: 09/12/2013] [Indexed: 12/27/2022]
|