A Mathematical Model for Simultaneous Saccharification and Co-fermentation （SSCF） of C6 and C5 Sugars

Reliable production of biofuels and specifically bioethanol has attracted a significant amount of re-search recently.Within this context,this study deals with dynamic simulation of bioethanol production processes and in particular aims at developing a mathematical model for describing simultaneous saccharification and co-fermentation （SSCF） of C6 and C5 sugars.The model is constructed by combining existing mathematical mod-els for enzymatic hydrolysis and co-fermentation.An inhibition of ethanol on cellulose conversion is introduced in order to increase the reliability.The mathematical model for the SSCF is verified by comparing the model predic-tions with experimental data obtained from the ethanol production based on kraft paper mill sludge.When fitting the model to the data,only the yield coefficients for glucose and xylose metabolism were fine-tuned,which were found to be 0.43 g·g-1 （ethanol/glucose） and 0.35 g·g-1 （ethanol/xylose） respectively.These promising validation results encourage further model application to evaluate different process configurations for lignocellulosic bioetha-nol technology.

Synergistic optimization framework for the process synthesis and design of biorefineries

The conceptual process design of novel bioprocesses in biorefinery setups is an important task,which remains yet challenging due to several limitations.We propose a novel framework incorporating superstructure optimization and simulation-based optimization synergistically.In this context,several approaches for superstructure optimization based on different surrogate models can be deployed.By means of a case study,the framework is introduced and validated,and the different superstructure optimization approaches are benchmarked.The results indicate that even though surrogate-based optimization approaches alleviate the underlying computational issues,there remains a potential issue regarding their validation.The development of appropriate surrogate models,comprising the selection of surrogate type,sampling type,and size for training and cross-validation sets,are essential factors.Regarding this aspect,satisfactory validation metrics do not ensure a successful outcome from its embedded use in an optimization problem.Furthermore,the framework’s synergistic effects by sequentially performing superstructure optimization to determine candidate process topologies and simulationbased optimization to consolidate the process design under uncertainty offer an alternative and promising approach.These findings invite for a critical assessment of surrogatebased optimization approaches and point out the necessity of benchmarking to ensure consistency and quality of optimized solutions.

Digital Twin in biomanufacturing:challenges and opportunities towards its implementation

The domain of industrial biomanufacturing is enthusiastically embracing the concept of Digital Twin,owing to its promises of increased process efficiency and resource utilisation.However,Digital Twin in biomanufacturing is not yet clearly defined and this sector of the industry is falling behind the others in terms of its implementation.On the other hand,some of the benefits of Digital Twin seem to overlap with the more established practices of process control and optimization,and the term is vaguely used in different scenarios.In an attempt to clarify this issue,we investigate this overlap for the specific case of fermentation operation,a central step in many biomanufacturing processes.Based on this investigation,a framework built upon a five-step pathway starting from a basic steady-state process model is proposed to develop a fully-fledged Digital Twin.For demonstration purposes,the framework is applied to a bench-scale second-generation ethanol fermentation process as a case study.It is proposed that the success or failure of a fully-fledged Digital Twin implementation is determined by key factors that comprise the role of modelling,human operator actions,and other propositions of economic value.