Dynamic Optimisation and Visualisation of Industrial Beer Fermentation with Explicit Heat Transfer Dynamics

Rodman, Alistair D.; Weaser, Megan; Griffiths, Lee; Gerogiorgis, Dimitrios I.

doi:10.1016/b978-0-12-818634-3.50244-7

Cited by 3 publications

(11 citation statements)

References 5 publications

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“…Beer fermentation is both nonlinear and complex, with its modeling and simulation described as a time-consuming task [2,[20][21][22][23][24]31,[38][39][40]. Though several mechanisms for enzyme activity exist, Michaelis-Menten and Monod kinetics are the most useful in the present effort.…”

Section: Mathematical Modeling Of Fermentationmentioning

confidence: 99%

“…The de Andrés-Toro et al model [41] is implemented in the MATLAB (R2018b) environment and integrated numerically via ode45: the code comprises 13 (11 differential and 1 algebraic) equations, one of which inputs the temperature profile to Arrhenius-type parameter definitions, Equation (23), at each time point. Initial conditions with source (or calculation method) are provided in Table 3.…”

Section: Numerical Integrationmentioning

confidence: 99%

“…Laboratory-scale CCF research has been covered in the literature since inception [8,9], but CCF dynamic modeling has not yet received interest commensurate with beverage demand, especially compared with dynamic modeling and optimization success for 'warmer' ale and lager (6-22 °C) brewing [20][21][22][23][24]. We thus aim to pave the way for robust modeling platforms and higher industrial process efficiency.…”

Section: Introduction 1low-alcohol Beer (Lab) and Alcohol-free Beer (...mentioning

confidence: 99%

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Systematic Parameter Estimation and Dynamic Simulation of Cold Contact Fermentation for Alcohol-Free Beer Production

Pilarski

Gerogiorgis

2022

Processes

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Global demand for Low-Alcohol Beer (LAB) and Alcohol-Free Beer (AFB) has surged due to flavor attributes, health benefits, and lifestyle changes, prompting efforts for process intensification. This paper aims to offer a detailed modelling basis for LAB manufacturing study and optimisation. A first-principles dynamic model for conventional beer manufacturing has been re-parameterized and used for dynamic simulation of Cold Contact Fermentation (CCF), an effective LAB and AFB production method, with concentrations tracked along plausible temperature manipulation profiles. Parameter estimation is pursued using industrial production data, with a detailed local sensitivity analysis portraying the effect of key parameter variation on sugar consumption, ethanol production, and key flavor component (ethyl acetate and diacetyl) evolution during (and final values after) CCF. Ethyl acetate (esters in general) affecting fruity flavors emerge as most sensitive to CCF conditions.

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Section: Mathematical Modeling Of Fermentationmentioning

confidence: 99%

Section: Numerical Integrationmentioning

confidence: 99%

Section: Introduction 1low-alcohol Beer (Lab) and Alcohol-free Beer (...mentioning

confidence: 99%

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Systematic Parameter Estimation and Dynamic Simulation of Cold Contact Fermentation for Alcohol-Free Beer Production

Pilarski

Gerogiorgis

2022

Processes

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“…Although the number of temperature profiles considered here is limited in comparison to the full scope of possibilities that could be implemented industrially, comparison of the effects of the theoretical Q limits the number of temperature profiles that allow one to stay within product specifications. Each Q may have multiple associated temperature profiles; the optimal manipulation may be established via dynamic optimisation attain target ethanol concentrations while also ensuring critical flavour component concentration constraints (Rodman et al, 2019).…”

Section: Course Grid Enumeration Of Hypothetical Temperature Profilesmentioning

confidence: 99%

Dynamic Modelling and Simulation of Cold Contact Fermentation (CCF)

Pilarski

Gerogiorgis

2020

Computer Aided Chemical Engineering

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The increased commercial presence and comparative health benefits of alcohol-free beer (AFB) provide a substantial impetus for research, particularly in the field of dynamic simulation whereby the development of accurate models can help reduce costs of experimentation. Cold Contact Fermentation (CCF) is an existing method of industrialscale AFB production that utilises reduced fermentor temperatures and altered contact times compared to Warm Fermentation (WF), though requiring continual attention given the production of non-optimal organoleptic compositions, which drastically affect taste. In order to better understand the differences between Warm Fermentation (WF) and CCF, a DAE system is constructed based on previous WF studies whose responses are compared vis-à-vis to simulations of the same model under industrial CCF conditions. Given the significant discrepancies between dynamic results, industrial data can be for the parametrisation of a new CCF model, in order to accurately portray plant operation. Further to these simulations, the sensitivity of final species concentrations to parameter variation and the effect of hypothetical temperature profiles are studied with the aim of evaluating model system flexibility and opportunities for improvement based on changes to fermentor temperature profiles. Overall, disparate relative ethyl acetate sensitivity and clustering of hypothetical CCF responses reflect existing challenges with flavour composition but highlight opportunities for remarkable process improvements.

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“…In the production of beer, the aim is to improve the methods to obtain a quality product, from the preparation of an established formula, to the treatment of the drink in each of the stages. Rodman [7] recognizes fermentation as the most important process when brewing beer, therefore, it is sought to improve the production times of this stage and generate a better yield [8], [9]. Specifically, through improvements in cooling, after the wort boil.…”

Section: Introductionmentioning

confidence: 99%

Numerical Study of a Helical Heat Exchanger for Wort Cooling in the Artisanal Beer Production Process

et al. 2020

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The objective of the present work is to study the behavior of a helical tube and shell heat exchanger, for the cooling of the wort in the process of making craft beer with cold water, through the methodology of computational fluid dynamics (CFD) by finite volume models for heat exchanger modeling. This by using the ANSYS Fluent software, which allows to understand the behavior of the fluid through equations that describe their movement and behavior, using numerical methods and computational techniques. In the mesh convergence, two methods were used, orthogonality and obliquity, with which it was confirmed that the meshing is ideal in the simulations that were carried out. For the simulation, the k-epsilon turbulence model and the energy model were used. Through various simulations, it was obtained that by varying the mass flow, better results are reducing the outlet temperature, with a variation of 15.16 °C, while varying the inlet temperature of the water, there is just a variation from 2.71 °C to 0.01 °C. Therefore, a significant improvement in the performance of the heat exchanger was found. In the same way, it was confirmed that the number of spikes in the heat exchanger is adequate, since the outlet temperature would not be reached with less spikes.

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Dynamic Optimisation and Visualisation of Industrial Beer Fermentation with Explicit Heat Transfer Dynamics

Cited by 3 publications

References 5 publications

Systematic Parameter Estimation and Dynamic Simulation of Cold Contact Fermentation for Alcohol-Free Beer Production

Systematic Parameter Estimation and Dynamic Simulation of Cold Contact Fermentation for Alcohol-Free Beer Production

Dynamic Modelling and Simulation of Cold Contact Fermentation (CCF)

Numerical Study of a Helical Heat Exchanger for Wort Cooling in the Artisanal Beer Production Process

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