Operator training simulators for biorefineries: current position and future directions

Isimite, Joseph; Baganz, Frank; Hass, Volker C.

doi:10.1002/jctb.5583

Cited by 7 publications

(9 citation statements)

References 42 publications

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“…Process simulators also train senior engineers and field operators. [50][51][52] Commercial software simulate mostly reactions, separations, and design heat integration, and offer a variety of ideal reactors. [53,54] Depending on the field of application, the software is integrated in the design of a new process, in the simulation of an existing plant, or both.…”

Section: Applicationsmentioning

confidence: 99%

Experimental methods in chemical engineering: Process simulation

et al. 2020

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Process simulation software designs equipment, simulates operations, optimizes a plant's configuration (heat exchangers network, for example), estimates operating and capital expenses, and serves as an educational tool. However, mastering the theoretical background minimizes common mistakes such as applying an incorrect thermodynamic method, selecting improper algorithms in the case of tear systems, and setting irrational system specifications. Engineers and researchers will exploit this tool more often in the future as constant advancements in simulation science as well as new models are released continually. Process simulators make it easier to build digital twins and thus will facilitate the implementation of the industry 4.0 guidelines. We highlight the mathematical and technical features of process simulators, as well as the capabilities and the fields of application. A bibliometric map of keywords from articles citing Aspen+, Aspen plus, Hysys, and Pro/II indexed by Web of Science between 2017 and 2020 identified the main research clusters, such as design, optimization, energy or exergy, biomass; H 2 and CO 2 capture, thermodynamics; and separations and techno-economic analysis.

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Section: Applicationsmentioning

confidence: 99%

Experimental methods in chemical engineering: Process simulation

et al. 2020

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“…Twin is parameterised based on real process data to represent the behaviour of the physical process [10]. Another possibility to keep Digital Twin and the real process as identical as possible is an online and at-line data connection between the "twins".…”

Section: General Approachmentioning

confidence: 99%

“…According to Hass [11], desirable characteristics of a functionally useful Digital Twin include realistic simulation of the biological, physical and chemical processes, accurate representation of automation and control actions and a GUI with a similar 'look and feel' to that of the real plant [11]. Mathematical models used in Digital Twin development are classified broadly as mechanistic, non-mechanistic or hybrid models [9,10,12]. In this context, a model refers to a mathematical representation of certain aspects of a real-world object or phenomenon.…”

Section: Design Of Digital Twins As Control Strategy Development Toolsmentioning

confidence: 99%

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Digital Twins for Bioprocess Control Strategy Development and Realisation

Appl

Moser

Baganz

et al. 2020

Advances in Biochemical Engineering/Biotechnology

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New innovative Digital Twins can represent complex bioprocesses, including the biological, physico-chemical, and chemical reaction kinetics, as well as the mechanical and physical characteristics of the reactors and the involved peripherals. Digital Twins are an ideal tool for the rapid and cost-effective development, realisation and optimisation of control and automation strategies. They may be utilised for the development and implementation of conventional controllers (e.g. temperature, dissolved oxygen…), as well as for advanced control strategies (e.g. control of substrate or metabolite concentrations, multivariable controls), and the development of complete bioprocess control. This chapter describes the requirements Digital Twins must fulfil to be used for bioprocess control strategy development, and implementation and gives an overview of research projects where Digital Twins or "earlystage" Digital Twins were used in this context. Furthermore, applications of Digital Twins for the academic education of future control and bioprocess engineers as well as for the training of future bioreactor operators will be described. Finally, a case study is presented, in which an "early-stage" Digital Twin was applied for the development of control strategies of the fedbatch cultivation of Saccharomyces cerevisiae.

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“…Subsequently, the developed mathematical model for the combined starch hydrolysis and proteolysis was integrated into an existing DT developed by our group [3,[16][17][18][19][20][21][22]. This DT has been shown to simulate the cultivation of S. cerevisiae and the whole-cell biocatalysis of ethyl-3-hydroxy-butyrate (E3HB) from the substrate ethyl acetoacetate in a 20 L STR under aerobic and anaerobic conditions [23].…”

Section: Introductionmentioning

confidence: 99%

Development of a Digital Twin for Enzymatic Hydrolysis Processes

2021

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Enzymatic hydrolysis processes can be used to produce organic nutrient media from renewable raw materials. However, many of these processes are not optimally designed, so expensive enzymes and substrates are wasted. Mathematical models and Digital Twins (DTs) are powerful tools, which can be used to optimize bioprocesses and, thus, increase the yield of the desired products. Individual enzymatic hydrolysis processes have already been modeled, but models for the combined starch hydrolysis and proteolysis, or DTs, are not available yet. Therefore, an easily adaptable, dynamic, and mechanistic mathematical model representing the kinetics of the enzymatic hydrolysis process of the combined starch hydrolysis and proteolysis was developed and parameterized using experimental data. The model can simulate the starch hydrolysis process with an agreement of over 90% and the proteolysis process with an agreement of over 85%. Subsequently, this model was implemented into an existing DT of a 20 L stirred tank reactor (STR). Since the DT cannot only map the kinetics of the enzymatic process, but also the STR with the associated periphery (pumps, heating jacket, etc.), it is ideally suited for future process control strategy development and thus for the optimization of enzymatic hydrolysis processes.

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Operator training simulators for biorefineries: current position and future directions

Cited by 7 publications

References 42 publications

Experimental methods in chemical engineering: Process simulation

Experimental methods in chemical engineering: Process simulation

Digital Twins for Bioprocess Control Strategy Development and Realisation

Development of a Digital Twin for Enzymatic Hydrolysis Processes

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