Download Optimization And Applicability Of Bioprocesses full books in PDF, epub, and Kindle. Read online Optimization And Applicability Of Bioprocesses ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
This book argues that the sustainable management of resources requires a systematic approach that primarily involves the integration of green innovative biotechnological strategies and eco-engineering. It discusses how microbial community intelligence can be used for waste management and bio-remediation and explains how biological processes can be optimized by integrating genomics tools to provide perspectives on sustainable development. The book describes the application of modern molecular techniques such as fluorescence in situ hybridization (FISH), highly sensitive catalyzed reporter deposition (CARD)-FISH, in situ DNA-hybridization chain reaction (HCR) and methods for detecting mRNA and/or functional genes to optimize bioprocessess. These techniques, supplemented with metagenomic analysis, reveal that a large proportion of micro-organisms still remain to be identified and also that they play a vital role in establishing bioprocesses.
Book Synopsis Optimization and Applicability of Bioprocesses by : Hemant J. Purohit
Download or read book Optimization and Applicability of Bioprocesses written by Hemant J. Purohit and published by Springer. This book was released on 2018-01-02 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book argues that the sustainable management of resources requires a systematic approach that primarily involves the integration of green innovative biotechnological strategies and eco-engineering. It discusses how microbial community intelligence can be used for waste management and bio-remediation and explains how biological processes can be optimized by integrating genomics tools to provide perspectives on sustainable development. The book describes the application of modern molecular techniques such as fluorescence in situ hybridization (FISH), highly sensitive catalyzed reporter deposition (CARD)-FISH, in situ DNA-hybridization chain reaction (HCR) and methods for detecting mRNA and/or functional genes to optimize bioprocessess. These techniques, supplemented with metagenomic analysis, reveal that a large proportion of micro-organisms still remain to be identified and also that they play a vital role in establishing bioprocesses.
This is the second of two volumes that together provide an overview of the latest advances in the generation and application of digital twins in bioprocess design and optimization. Both processes have undergone significant changes over the past few decades, moving from data-driven approaches into the 21st-century digitalization of the bioprocess industry. Moreover, the high demand for biotechnological products calls for efficient methods during research and development, as well as during tech transfer and routine manufacturing. In this regard, one promising tool is the use of digital twins, which offer a virtual representation of the bioprocess. They reflect the mechanistics of the biological system and the interactions between process parameters, key performance indicators and product quality attributes in the form of a mathematical process model. Furthermore, digital twins allow us to use computer-aided methods to gain an improved process understanding, to test and plan novel bioprocesses, and to efficiently monitor them. This book focuses on the application of digital twins in various contexts, e.g. computer-aided experimental design, seed train prediction, and lifeline analysis. Covering fundamentals as well as applications, the two volumes offers the ideal introduction to the topic for researchers in academy and industry alike.
Book Synopsis Digital Twins by : Christoph Herwig
Download or read book Digital Twins written by Christoph Herwig and published by Springer Nature. This book was released on 2021-04-25 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the second of two volumes that together provide an overview of the latest advances in the generation and application of digital twins in bioprocess design and optimization. Both processes have undergone significant changes over the past few decades, moving from data-driven approaches into the 21st-century digitalization of the bioprocess industry. Moreover, the high demand for biotechnological products calls for efficient methods during research and development, as well as during tech transfer and routine manufacturing. In this regard, one promising tool is the use of digital twins, which offer a virtual representation of the bioprocess. They reflect the mechanistics of the biological system and the interactions between process parameters, key performance indicators and product quality attributes in the form of a mathematical process model. Furthermore, digital twins allow us to use computer-aided methods to gain an improved process understanding, to test and plan novel bioprocesses, and to efficiently monitor them. This book focuses on the application of digital twins in various contexts, e.g. computer-aided experimental design, seed train prediction, and lifeline analysis. Covering fundamentals as well as applications, the two volumes offers the ideal introduction to the topic for researchers in academy and industry alike.
Closes the gap between bioscience and mathematics-based process engineering This book presents the most commonly employed approaches in the control of bioprocesses. It discusses the role that control theory plays in understanding the mechanisms of cellular and metabolic processes, and presents key results in various fields such as dynamic modeling, dynamic properties of bioprocess models, software sensors designed for the online estimation of parameters and state variables, and control and supervision of bioprocesses Control in Bioengineering and Bioprocessing: Modeling, Estimation and the Use of Sensors is divided into three sections. Part I, Mathematical preliminaries and overview of the control and monitoring of bioprocess, provides a general overview of the control and monitoring of bioprocesses, and introduces the mathematical framework necessary for the analysis and characterization of bioprocess dynamics. Part II, Observability and control concepts, presents the observability concepts which form the basis of design online estimation algorithms (software sensor) for bioprocesses, and reviews controllability of these concepts, including automatic feedback control systems. Part III, Software sensors and observer-based control schemes for bioprocesses, features six application cases including dynamic behavior of 3-dimensional continuous bioreactors; observability analysis applied to 2D and 3D bioreactors with inhibitory and non-inhibitory models; and regulation of a continuously stirred bioreactor via modeling error compensation. Applicable across all areas of bioprocess engineering, including food and beverages, biofuels and renewable energy, pharmaceuticals and nutraceuticals, fermentation systems, product separation technologies, wastewater and solid-waste treatment technology, and bioremediation Provides a clear explanation of the mass-balance–based mathematical modelling of bioprocesses and the main tools for its dynamic analysis Offers industry-based applications on: myco-diesel for implementing "quality" of observability; developing a virtual sensor based on the Just-In-Time Model to monitor biological control systems; and virtual sensor design for state estimation in a photocatalytic bioreactor for hydrogen production Control in Bioengineering and Bioprocessing is intended as a foundational text for graduate level students in bioengineering, as well as a reference text for researchers, engineers, and other practitioners interested in the field of estimation and control of bioprocesses.
Book Synopsis Control in Bioprocessing by : Pablo A. López Pérez
Download or read book Control in Bioprocessing written by Pablo A. López Pérez and published by John Wiley & Sons. This book was released on 2020-03-10 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Closes the gap between bioscience and mathematics-based process engineering This book presents the most commonly employed approaches in the control of bioprocesses. It discusses the role that control theory plays in understanding the mechanisms of cellular and metabolic processes, and presents key results in various fields such as dynamic modeling, dynamic properties of bioprocess models, software sensors designed for the online estimation of parameters and state variables, and control and supervision of bioprocesses Control in Bioengineering and Bioprocessing: Modeling, Estimation and the Use of Sensors is divided into three sections. Part I, Mathematical preliminaries and overview of the control and monitoring of bioprocess, provides a general overview of the control and monitoring of bioprocesses, and introduces the mathematical framework necessary for the analysis and characterization of bioprocess dynamics. Part II, Observability and control concepts, presents the observability concepts which form the basis of design online estimation algorithms (software sensor) for bioprocesses, and reviews controllability of these concepts, including automatic feedback control systems. Part III, Software sensors and observer-based control schemes for bioprocesses, features six application cases including dynamic behavior of 3-dimensional continuous bioreactors; observability analysis applied to 2D and 3D bioreactors with inhibitory and non-inhibitory models; and regulation of a continuously stirred bioreactor via modeling error compensation. Applicable across all areas of bioprocess engineering, including food and beverages, biofuels and renewable energy, pharmaceuticals and nutraceuticals, fermentation systems, product separation technologies, wastewater and solid-waste treatment technology, and bioremediation Provides a clear explanation of the mass-balance–based mathematical modelling of bioprocesses and the main tools for its dynamic analysis Offers industry-based applications on: myco-diesel for implementing "quality" of observability; developing a virtual sensor based on the Just-In-Time Model to monitor biological control systems; and virtual sensor design for state estimation in a photocatalytic bioreactor for hydrogen production Control in Bioengineering and Bioprocessing is intended as a foundational text for graduate level students in bioengineering, as well as a reference text for researchers, engineers, and other practitioners interested in the field of estimation and control of bioprocesses.
Optimal Control: New Trends in Applications to Bioprocesses aims to bridge the gap between mathematical optimization methods to solve problems in dynamical systems and bioprocess modeling which involves various techniques to build mathematical models for applications in the bio-production of chemical and pharmaceutical products, covering different length and time scales, from single cells, to cell population, to bioreactors. The two fields are natural partners, however there is a disconnect and literature gap between the mathematical theory of optimal control and the optimization of systems arising in the field of bioprocesses engineering. Provides optimal control techniques applicable to bioprocessing and biotechnology Includes application to waste water treatment, bio-gas optimization and bioremediation problems Presents case studies from real-world examples
Book Synopsis Optimal Control by : Terence Bayen
Download or read book Optimal Control written by Terence Bayen and published by Academic Press. This book was released on 2020-11-01 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal Control: New Trends in Applications to Bioprocesses aims to bridge the gap between mathematical optimization methods to solve problems in dynamical systems and bioprocess modeling which involves various techniques to build mathematical models for applications in the bio-production of chemical and pharmaceutical products, covering different length and time scales, from single cells, to cell population, to bioreactors. The two fields are natural partners, however there is a disconnect and literature gap between the mathematical theory of optimal control and the optimization of systems arising in the field of bioprocesses engineering. Provides optimal control techniques applicable to bioprocessing and biotechnology Includes application to waste water treatment, bio-gas optimization and bioremediation problems Presents case studies from real-world examples
This is the first of two volumes that together provide an overview of the latest advances in the generation and application of digital twins in bioprocess design and optimization. Both processes have undergone significant changes over the past few decades, moving from data-driven approaches into the 21st-century digitalization of the bioprocess industry. Moreover, the high demand for biotechnological products calls for efficient methods during research and development, as well as during tech transfer and routine manufacturing. In this regard, one promising tool is the use of digital twins, which offer a virtual representation of the bioprocess. They reflect the mechanistics of the biological system and the interactions between process parameters, key performance indicators and product quality attributes in the form of a mathematical process model. Furthermore, digital twins allow us to use computer-aided methods to gain an improved process understanding, to test and plan novel bioprocesses, and to efficiently monitor them. This book explains the mathematical structure of digital twins, their development and the model’s respective parts, as well as concepts for the knowledge-driven generation and structural variability of digital twins. Covering fundamentals as well as applications, the two volumes offer the ideal introduction to the topic for researchers in academy and industry alike.
Book Synopsis Digital Twins by : Christoph Herwig
Download or read book Digital Twins written by Christoph Herwig and published by Springer Nature. This book was released on 2021-05-27 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first of two volumes that together provide an overview of the latest advances in the generation and application of digital twins in bioprocess design and optimization. Both processes have undergone significant changes over the past few decades, moving from data-driven approaches into the 21st-century digitalization of the bioprocess industry. Moreover, the high demand for biotechnological products calls for efficient methods during research and development, as well as during tech transfer and routine manufacturing. In this regard, one promising tool is the use of digital twins, which offer a virtual representation of the bioprocess. They reflect the mechanistics of the biological system and the interactions between process parameters, key performance indicators and product quality attributes in the form of a mathematical process model. Furthermore, digital twins allow us to use computer-aided methods to gain an improved process understanding, to test and plan novel bioprocesses, and to efficiently monitor them. This book explains the mathematical structure of digital twins, their development and the model’s respective parts, as well as concepts for the knowledge-driven generation and structural variability of digital twins. Covering fundamentals as well as applications, the two volumes offer the ideal introduction to the topic for researchers in academy and industry alike.
Microbial communities are a critical component of natural ecosystems and industrial bioprocesses. In natural ecosystems, these communities can present abrupt and surprising responses to perturbations, which can have important consequences. For example, climate change can influence drastically the composition of microbial communities in the oceans, which in turn affects the entirety of the food chain, and changes in diet can affect drastically the composition of the human gut microbiome, making it stronger or more vulnerable to infection by pathogens. In industrial bioprocesses, engineers work with these communities to obtain desirable products such as biofuels, pharmaceuticals, and alcoholic beverages, or to achieve relevant environmental objectives such as wastewater treatment or carbon capture. Mathematical models of microbial communities are critical for the study of natural ecosystems and for the design and control of bioprocesses. Good mathematical models of microbial communities allow scientists to predict how robust an ecosystem is, how perturbed ecosystems can be remediated, how sensitive an ecosystem is with respect to specific perturbations, and in what ways and how fast it would react to environmental changes. Good mathematical models allow engineers to design better bioprocesses and control them to produce high-quality products that meet tight specifications. Despite the importance of microbial communities, mathematical models describing their behavior remain simplistic and only applicable to very simple and controlled bioprocesses. Therefore, the study of natural ecosystems and the design of complex bioprocesses is very challenging. As a result, the design of bioprocesses remains experiment-based, which is slow, expensive, and labor-intensive. With high throughput experiments large datasets are generated, but without reliable mathematical models critical links between the species in the community are often missed. The design of novel bioprocesses rely on informed guesses by scientists that can only be tested experimentally. The expenses incurred by these experiments can be difficult to justify. Predictive mathematical models of microbial communities can provide insights about the possible outcomes of novel bioprocesses and guide the experimental design, resulting in cheaper and faster bioprocess development. Most mathematical models describing microbial communities do not take into account the internal structure of the microorganisms. In recent years, new knowledge of the internal structures of these microorganisms has been generated using highthroughput DNA sequencing. Flux balance analysis (FBA) is a modeling framework that incorporates this new information into mathematical models of microbial communities. With FBA, growth and exchange flux predictions are made by solving linear programs (LPs) that are constructed based on the metabolic networks of the microorganisms. FBA can be combined with the mathematical models of dynamical biosystems, resulting in dynamic FBA (DFBA) models. DFBA models are difficult to simulate, sensitivity information is challenging to obtain, and reliable strategies to solve optimization problems with DFBA models embedded are lacking. Therefore, the use of DFBA models in science and industry remains very limited. This thesis makes DFBA simulation more accessible to scientists and engineers with DFBAlab, a fast, reliable, and efficient Matlab-based DFBA simulator. This simulator is used by more than a 100 academic users to simulate various processes such as chronic wound biofilms, gas fermentation in bubble column bioreactors, and beta-carotene production in microalgae. Also, novel combinations of microbial communities in raceway ponds have been studied. The performance of algal-yeast cocultures and more complex communities for biolipids production has been evaluated, gaining relevant insights that will soon be tested experimentally. These combinations could enable the production of lipids-rich biomass in locations far away from power plants and other concentrated CO 2 sources by utilizing lignocellulosic waste instead. Following reliable DFBA simulation, the mathematical theory required for sensitivity analysis of DFBA models, which happen to be nonsmooth, was developed. Methods to compute generalized derivative information for special compositions of functions, hierarchical LPs, and DFBA models were generated. Significant numerical challenges appeared during the sensitivity computation of DFBA models, some of which were resolved. Despite the challenges, sensitivity information for DFBA models was used to solve for the steady-state of a high-fidelity model of a bubble column bioreactor using nonsmooth equation-solving algorithms. Finally, local optimization strategies for different classes of problems with DFBA models embedded were generated. The classes of problems considered include parameter estimation and optimal batch, continuous steady-state, and continuous cyclic steady-state process design. These strategies were illustrated using toy metabolic networks as well as genome-scale metabolic networks. These optimization problems demonstrate the superior performance of optimizers when reliable sensitivity information is used, as opposed to approximate information obtained from finite differences. Future work includes the development of global optimization strategies, as well as increasing the robustness of the computation of sensitivities of DFBA models. Nevertheless, the application of DFBA models of microbial communities for the study of natural ecosystems and bioprocess design and control is closer to reality.
Book Synopsis Simulation, Sensitivity Analysis, and Optimization of Bioprocesses Using Dynamic Flux Balance Analysis by : Jose Alberto Gomez (Ph. D.)
Download or read book Simulation, Sensitivity Analysis, and Optimization of Bioprocesses Using Dynamic Flux Balance Analysis written by Jose Alberto Gomez (Ph. D.) and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Microbial communities are a critical component of natural ecosystems and industrial bioprocesses. In natural ecosystems, these communities can present abrupt and surprising responses to perturbations, which can have important consequences. For example, climate change can influence drastically the composition of microbial communities in the oceans, which in turn affects the entirety of the food chain, and changes in diet can affect drastically the composition of the human gut microbiome, making it stronger or more vulnerable to infection by pathogens. In industrial bioprocesses, engineers work with these communities to obtain desirable products such as biofuels, pharmaceuticals, and alcoholic beverages, or to achieve relevant environmental objectives such as wastewater treatment or carbon capture. Mathematical models of microbial communities are critical for the study of natural ecosystems and for the design and control of bioprocesses. Good mathematical models of microbial communities allow scientists to predict how robust an ecosystem is, how perturbed ecosystems can be remediated, how sensitive an ecosystem is with respect to specific perturbations, and in what ways and how fast it would react to environmental changes. Good mathematical models allow engineers to design better bioprocesses and control them to produce high-quality products that meet tight specifications. Despite the importance of microbial communities, mathematical models describing their behavior remain simplistic and only applicable to very simple and controlled bioprocesses. Therefore, the study of natural ecosystems and the design of complex bioprocesses is very challenging. As a result, the design of bioprocesses remains experiment-based, which is slow, expensive, and labor-intensive. With high throughput experiments large datasets are generated, but without reliable mathematical models critical links between the species in the community are often missed. The design of novel bioprocesses rely on informed guesses by scientists that can only be tested experimentally. The expenses incurred by these experiments can be difficult to justify. Predictive mathematical models of microbial communities can provide insights about the possible outcomes of novel bioprocesses and guide the experimental design, resulting in cheaper and faster bioprocess development. Most mathematical models describing microbial communities do not take into account the internal structure of the microorganisms. In recent years, new knowledge of the internal structures of these microorganisms has been generated using highthroughput DNA sequencing. Flux balance analysis (FBA) is a modeling framework that incorporates this new information into mathematical models of microbial communities. With FBA, growth and exchange flux predictions are made by solving linear programs (LPs) that are constructed based on the metabolic networks of the microorganisms. FBA can be combined with the mathematical models of dynamical biosystems, resulting in dynamic FBA (DFBA) models. DFBA models are difficult to simulate, sensitivity information is challenging to obtain, and reliable strategies to solve optimization problems with DFBA models embedded are lacking. Therefore, the use of DFBA models in science and industry remains very limited. This thesis makes DFBA simulation more accessible to scientists and engineers with DFBAlab, a fast, reliable, and efficient Matlab-based DFBA simulator. This simulator is used by more than a 100 academic users to simulate various processes such as chronic wound biofilms, gas fermentation in bubble column bioreactors, and beta-carotene production in microalgae. Also, novel combinations of microbial communities in raceway ponds have been studied. The performance of algal-yeast cocultures and more complex communities for biolipids production has been evaluated, gaining relevant insights that will soon be tested experimentally. These combinations could enable the production of lipids-rich biomass in locations far away from power plants and other concentrated CO 2 sources by utilizing lignocellulosic waste instead. Following reliable DFBA simulation, the mathematical theory required for sensitivity analysis of DFBA models, which happen to be nonsmooth, was developed. Methods to compute generalized derivative information for special compositions of functions, hierarchical LPs, and DFBA models were generated. Significant numerical challenges appeared during the sensitivity computation of DFBA models, some of which were resolved. Despite the challenges, sensitivity information for DFBA models was used to solve for the steady-state of a high-fidelity model of a bubble column bioreactor using nonsmooth equation-solving algorithms. Finally, local optimization strategies for different classes of problems with DFBA models embedded were generated. The classes of problems considered include parameter estimation and optimal batch, continuous steady-state, and continuous cyclic steady-state process design. These strategies were illustrated using toy metabolic networks as well as genome-scale metabolic networks. These optimization problems demonstrate the superior performance of optimizers when reliable sensitivity information is used, as opposed to approximate information obtained from finite differences. Future work includes the development of global optimization strategies, as well as increasing the robustness of the computation of sensitivities of DFBA models. Nevertheless, the application of DFBA models of microbial communities for the study of natural ecosystems and bioprocess design and control is closer to reality.
Bioprocess technology involves the combination of living matter (whole organism or enzymes ) with nutrients under laboratory conditions to make a desired product within the pharmaceutical, food, cosmetics, biotechnology, fine chemicals and bulk chemicals sectors. Industry is under increasing pressure to develop new processes that are both environmentally friendly and cost-effective, and this can be achieved by taking a fresh look at process development; - namely by combining modern process modeling techniques with sustainability assessment methods. Development of Sustainable Bioprocesses: Modeling and Assessment describes methodologies and supporting case studies for the evolution and implementation of sustainable bioprocesses. Practical and industry-focused, the book begins with an introduction to the bioprocess industries and development procedures. Bioprocesses and bioproducts are then introduced, together with a description of the unit operations involved. Modeling procedures, a key feature of the book, are covered in chapter 3 prior to an overview of the key sustainability assessment methods in use (environmental, economic and societal). The second part of the book is devoted to case studies, which cover the development of bioprocesses in the pharmaceutical, food, fine chemicals, cosmetics and bulk chemicals industries. Some selected case studies include: citric acid, biopolymers, antibiotics, biopharmaceuticals. Supplementary material provides hands-on materials so that the techniques can be put into practice. These materials include a demo version of SuperPro Designer software (used in process engineering) and models of all featured case studies, excel sheets of assessment methods, Monte Carlo simulations and exercises. Previously available on CD-ROM, the supplementary material can now be accessed via http://booksupport.wiley.com by entering the author name, book title or isbn and clicking on the desired entry. This will then give a listing of all the content available for download. Please read any text files before downloading material.
Book Synopsis Development of Sustainable Bioprocesses by : Elmar Heinzle
Download or read book Development of Sustainable Bioprocesses written by Elmar Heinzle and published by John Wiley & Sons. This book was released on 2007-01-11 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bioprocess technology involves the combination of living matter (whole organism or enzymes ) with nutrients under laboratory conditions to make a desired product within the pharmaceutical, food, cosmetics, biotechnology, fine chemicals and bulk chemicals sectors. Industry is under increasing pressure to develop new processes that are both environmentally friendly and cost-effective, and this can be achieved by taking a fresh look at process development; - namely by combining modern process modeling techniques with sustainability assessment methods. Development of Sustainable Bioprocesses: Modeling and Assessment describes methodologies and supporting case studies for the evolution and implementation of sustainable bioprocesses. Practical and industry-focused, the book begins with an introduction to the bioprocess industries and development procedures. Bioprocesses and bioproducts are then introduced, together with a description of the unit operations involved. Modeling procedures, a key feature of the book, are covered in chapter 3 prior to an overview of the key sustainability assessment methods in use (environmental, economic and societal). The second part of the book is devoted to case studies, which cover the development of bioprocesses in the pharmaceutical, food, fine chemicals, cosmetics and bulk chemicals industries. Some selected case studies include: citric acid, biopolymers, antibiotics, biopharmaceuticals. Supplementary material provides hands-on materials so that the techniques can be put into practice. These materials include a demo version of SuperPro Designer software (used in process engineering) and models of all featured case studies, excel sheets of assessment methods, Monte Carlo simulations and exercises. Previously available on CD-ROM, the supplementary material can now be accessed via http://booksupport.wiley.com by entering the author name, book title or isbn and clicking on the desired entry. This will then give a listing of all the content available for download. Please read any text files before downloading material.
Optimal Control: New Trends in Applications to Bioprocesses aims to bridge the gap between mathematical optimization methods to solve problems in dynamical systems and bioprocess modeling which involves various techniques to build mathematical models for applications in the bio-production of chemical and pharmaceutical products, covering different length and time scales, from single cells, to cell population, to bioreactors. The two fields are natural partners, however there is a disconnect and literature gap between the mathematical theory of optimal control and the optimization of systems arising in the field of bioprocesses engineering. Provides optimal control techniques applicable to bioprocessing and biotechnology Includes application to waste water treatment, bio-gas optimization and bioremediation problems Presents case studies from real-world examples
Book Synopsis Optimal Control by : Terence Bayen
Download or read book Optimal Control written by Terence Bayen and published by Academic Press. This book was released on 2020-01-15 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal Control: New Trends in Applications to Bioprocesses aims to bridge the gap between mathematical optimization methods to solve problems in dynamical systems and bioprocess modeling which involves various techniques to build mathematical models for applications in the bio-production of chemical and pharmaceutical products, covering different length and time scales, from single cells, to cell population, to bioreactors. The two fields are natural partners, however there is a disconnect and literature gap between the mathematical theory of optimal control and the optimization of systems arising in the field of bioprocesses engineering. Provides optimal control techniques applicable to bioprocessing and biotechnology Includes application to waste water treatment, bio-gas optimization and bioremediation problems Presents case studies from real-world examples
Bioprocess engineering employs microorganisms to produce biological products for medical and industrial applications. The book covers engineering tasks around- the cultivation process in bioreactors including media design, feeding strategies, or cell harvesting. All aspects are described from the conceptual considerations to technical realization and provide insight by detailed explanations, drawings, formulas, and example processes.
Book Synopsis Integrated Bioprocess Engineering by : Clemens Posten
Download or read book Integrated Bioprocess Engineering written by Clemens Posten and published by Walter de Gruyter GmbH & Co KG. This book was released on 2024-07-01 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bioprocess engineering employs microorganisms to produce biological products for medical and industrial applications. The book covers engineering tasks around- the cultivation process in bioreactors including media design, feeding strategies, or cell harvesting. All aspects are described from the conceptual considerations to technical realization and provide insight by detailed explanations, drawings, formulas, and example processes.
The use of environmental and nutritional factors to optimize fermentation conditions, are important for application of bioprocesses. To optimize these processes using conventional techniques, for example the one factor at a time method, is time consuming and laborious. Statistical design of experiments has become popular for medium optimization in industry since this allows the investigator to assess more than one factor at a time. This method is a time saving and effective method for the screening significant factors of a multivariable system. This book reviews the latest research on statistical optimization of total biogas produced by Clostridium beijerinkii and Clostridium paraputrificum utilizing N-acetylglucosamine as the main carbon source. Individual chapters cover different stages in the optimization design. The Plackett and burman screening design was used to identify significant medium constituents. The information gathered from each stage of an optimization process was used for the next stage of optimization. In addition to presenting recent research in this area, this book also contains important discussions on the potential benefits of using statistical optimization design over the traditional one factor at a time optimization method.
Book Synopsis Statistical Optimisation of Medium Variables for Biogas Production by : Barnabas Owoh
Download or read book Statistical Optimisation of Medium Variables for Biogas Production written by Barnabas Owoh and published by CreateSpace. This book was released on 2015-05-02 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of environmental and nutritional factors to optimize fermentation conditions, are important for application of bioprocesses. To optimize these processes using conventional techniques, for example the one factor at a time method, is time consuming and laborious. Statistical design of experiments has become popular for medium optimization in industry since this allows the investigator to assess more than one factor at a time. This method is a time saving and effective method for the screening significant factors of a multivariable system. This book reviews the latest research on statistical optimization of total biogas produced by Clostridium beijerinkii and Clostridium paraputrificum utilizing N-acetylglucosamine as the main carbon source. Individual chapters cover different stages in the optimization design. The Plackett and burman screening design was used to identify significant medium constituents. The information gathered from each stage of an optimization process was used for the next stage of optimization. In addition to presenting recent research in this area, this book also contains important discussions on the potential benefits of using statistical optimization design over the traditional one factor at a time optimization method.
