Synergistic optimization framework for the process synthesis and design of biorefineries

Vollmer, Nikolaus; Al, Resul; Gernaey, Krist V.; Sin, Gürkan

doi:10.1007/s11705-021-2071-9

Cited by 11 publications

(12 citation statements)

References 103 publications

(138 reference statements)

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“…Similar to the results of (Vollmer et al, 2021a;Vollmer et al, 2021b), the DTR surrogate shows the weakest validation metrics for the test dataset, whereas the GPR surrogate overall excels with respect to the resulting metrics. The ANN surrogate equally performs overall well with slightly weaker metrics than the GPR surrogate.…”

Section: Superstructure Optimizationsupporting

confidence: 64%

“…They are implemented in the S3O framework and assessed regarding their prediction robustness through an uncertainty and sensitivity analysis. Further information regarding the models and their implementation can be found in the original manuscript describing the S3O framework (Vollmer et al, 2021a).…”

Section: Unit Operationsmentioning

confidence: 99%

“…As described by Vollmer et al (2021a), the framework consists of three sequential steps: 1) the selection of products, feedstock, and processes, 2) superstructure optimization, and 3) simulationbased optimization. The overall procedure is established with the idea of "having the end in mind."…”

Section: Process Synthesis and Design Frameworkmentioning

confidence: 99%

“…For a successful application of these surrogate models, a proper benchmark of different alternatives is vital (Vollmer et al, 2021b). After determining the reduced set of candidate process topologies, in the third step, all of these are subjected to simulation-based optimization to consolidate the process design and find a truly optimal solution (Vollmer et al, 2021a).…”

Section: Process Synthesis and Design Frameworkmentioning

confidence: 99%

“…Concerning conceptual process design, there exist several schools of thinking. In the S3O framework, a synergistic approach is followed to best integrate expert knowledge, optimization approaches, and simulation-based strategies to leverage synergies for the conceptual design of bioprocesses in three steps (Vollmer et al, 2021a). The framework is applied for the case study of designing a xylitol biorefinery with value-added co-products in this manuscript.…”

Section: Introductionmentioning

confidence: 99%

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Conceptual Process Design of an Integrated Xylitol Biorefinery With Value-Added Co-Products

2022

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This manuscript describes the conceptual process design of an integrated xylitol biorefinery with value-added co-products. Based on an existing three-step framework, the main product of a second-generation integrated biorefinery is chosen in the first stage. Based upon this, other decisions as the feedstock and value-added co-products are made. All relevant unit operations for the process are introduced. An initial superstructure with all potential process alternatives is composed of all introduced models. In the second step of the framework, a global sensitivity analysis is performed, firstly with coarse sampling to determine all viable flowsheet options and secondly with fine sampling to determine the most sensitive operational variables. As a result of the sensitivity analysis, most of the flowsheet options in the initial superstructure are not feasible. Based on these results, flowsheet sampling with the five most sensitive operational variables is performed to create surrogate models. In the scope of this work, three types of surrogate models are benchmarked against each other. Regarding the results of the superstructure optimization, firstly, it becomes apparent that the production of biokerosene does not contribute significantly to the net present value of the biorefinery. Furthermore, reducing the number of unit operations in the downstream processing leads to lower capital expenditures, but it lowers the product yield. Lastly, most flowsheets are economically feasible, indicated by a positive net present value. Based on this result, the most promising candidate process topology is subjected to the third step of the framework, including uncertainty in capital expenditure and operational expenses according to their estimations and uncertainties in the product prices. As a result, the net present value of the flowsheet turns negative, indicating that the high uncertainties for the expenditure and the expenses do not allow for an economically feasible operation. Lastly, the analysis of conceptually designed process flowsheets based on Monte Carlo sampling shows failure rates, with the NPV falling below the break-even point, of around 60% probability or higher. Based on these results, an economically feasible construction and operation of a xylitol biorefinery seems unlikely. Further ways to improve the metrics are elucidated.

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Section: Superstructure Optimizationsupporting

confidence: 64%

Section: Unit Operationsmentioning

confidence: 99%

Section: Process Synthesis and Design Frameworkmentioning

confidence: 99%

Section: Process Synthesis and Design Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Conceptual Process Design of an Integrated Xylitol Biorefinery With Value-Added Co-Products

2022

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Life cycle assessment of an integrated xylitol biorefinery with value-added co-products

Vollmer

Gargalo

Gernaey

et al. 2023

Int J Life Cycle Assess

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Purpose This manuscript comprises a detailed life cycle assessment of an integrated xylitol biorefinery with value-added co-products. The biorefinery utilizes wheat straw as lignocellulosic feedstock and employs bio-based processes to produce xylitol as the main product and succinic acid as a co-product. The biorefinery was conceptually designed in an optimization-based framework and assessed through a techno-economic analysis published in the authors’ prior publications. Methods The goal is to determine the environmental impacts of the xylitol biorefinery and to compare the effects of bio-based production in the biorefinery to the current chemical production processes of xylitol. The scope is set as cradle-to-gate to allow a direct comparison of the chemical processes. The presented life cycle assessment was performed according to the standardized ISO procedure. Results The reference unit is related to the feedstock as multiple products are produced, and an economic allocation is chosen. The life cycle inventory is based on secondary data from process simulations stemming from earlier published work. The impact assessment is performed with the ReCiPe 2016 Midpoint H V1.05 method and the IMPACT2002 + method since the available data of the life cycle assessment for the chemical processes was obtained with the latter. The characterization of the impacts shows high impacts for the terrestrial, marine, and human carcinogenic toxicity impact categories and a comparatively low impact on global warming. Conclusions The results are interpreted and assessed with an additional sensitivity analysis. Furthermore, the results are compared with the two chemical production processes. The comparison shows lower impacts of the xylitol biorefinery compared to the standard chemical production process but slightly higher impacts compared to the proprietary production process of DuPont, which employs a high level of process integration. These results are further discussed and contextualized.

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Multiscale process systems engineering—analysis and design of chemical and energy systems from molecular design up to process optimization

Zhou

Sundmacher

2021

Front. Chem. Sci. Eng.

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As indicated by Grossmann and Westerberg [1], a process system can be generally decomposed into hierarchical levels or scales at which different physical and/or chemical phenomena take place (see Fig. 1). The first step of multiscale process modeling is to connect the molecular level with the phase level, where the main task is to model and predict the properties of fluid mixtures based on the atomic-or molecular-level information. Typically, quantum chemical (QC) computation, molecular simulation, and equations of state are used to provide such predictions. Recently, due to the ever-increasing number of available data and fast development of cheminformatics and machine learning tools, data-driven descriptor models have been developed and widely used for property predictions [2]. With the properties of the system, it is then possible to derive the constitutive relations (e.g., kinetics and phase equilibria) and implement them into the mass, energy, and momentum conservations of each process unit. Taking into account the connections between different units, one can finally scale the system up toward the process level where process modeling, intensification, and optimization are performed to maximize the economic and environmental performances of the process. It is clear that domain knowledge (e.g., chemical engineering) as well as data science and systems engineering methods are essential for an adequate description or modeling of a

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Synergistic optimization framework for the process synthesis and design of biorefineries

Cited by 11 publications

References 103 publications

Conceptual Process Design of an Integrated Xylitol Biorefinery With Value-Added Co-Products

Conceptual Process Design of an Integrated Xylitol Biorefinery With Value-Added Co-Products

Life cycle assessment of an integrated xylitol biorefinery with value-added co-products

Multiscale process systems engineering—analysis and design of chemical and energy systems from molecular design up to process optimization

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