Application of multi-agent programming for modeling the viscosity state of mash in alcohol production

Larysa Gumeniuk

lorapost@gmail.com
Lutsk National Technical University (Ukraine)
https://orcid.org/0000-0002-7678-7060

Ludmyla Markina


Lutsk National Technical University (Ukraine)
https://orcid.org/0000-0003-0735-0743

Viktor Satsyk


Lutsk National Technical University (Ukraine)

Pavlo Humeniuk


Lutsk National Technical University (Ukraine)

Anton Lashch


Lutsk National Technical University (Ukraine)

Abstract

In alcohol production from starch-containing raw materials, it is essential to know the viscosity of the resulting solution. The main drawback of control systems in the solution preparation process is the lack of viscosity monitoring. This prevents the use of processing modes that would ensure efficient execution of the subsequent thermoenzymatic treatment of the solution. This work is dedicated to examining the qualitative impact of the timing of enzyme addition on the change in solution viscosity, aiming to improve the quality of the process control during its preparation. The study was conducted in the free multi-agent programming environment NetLogo, which is used for modeling complex systems evolving over time.


Keywords:

optimization models, NetLogo, dynamic viscosity, alcohol production

[1] Casey G. P., Ingledew W. M.: Ethanol tolerance in yeasts. Crit. Rev. in Microbiology 13(3), 1986, 219–280 [https://doi.org/10.3109/10408418609108739].
  Google Scholar

[2] Drevetskiy V. V., Vorobyuk S. P., Kutya V. M.: Control of values of solid residue using viscosity of the grainflour mixture. Bulletin of the Engineering Academy of Ukraine 1, 2012, 180–182.
  Google Scholar

[3] Folly R. et al.: control of feed load changes in alcohol fermentation. Brazilian Journal of Chemical Engineering 14(4), 1997 [https://doi.org/10.1590/S0104-66321997000400012].
  Google Scholar

[4] Galbe M. Zacchi G.: Simulation of ethanol production processes based on enzymatic hydrolysis of woody biomass. Comput. Chem. Eng, 1994 [https://doi.org/10.1016/0098-1354(94)80112-6].
  Google Scholar

[5] Jarovenko V. L.: Guide to the production of alcohol. Raw materials, technology, and chemical control. Light and Agro-Food Industry, 1981.
  Google Scholar

[6] Lee J., Singh V., Eckhoff S. R.: Effects of Processing Conditions on the Viscosity of Corn Mash During Ethanol Production. Transactions of the ASABE 58(5), 2015, 1387–1393.
  Google Scholar

[7] Lotysh V., Gumeniuk L., Humeniuk P.: Comparison of the effectiveness of time series analysis methods: SMA, WMA, EMA, EWMA, and Kalman filter for data analysis. Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 13(3), 2023, 71–74 [https://doi.org/10.35784/iapgos.3652].
  Google Scholar

[8] Marinchenko V. et al.: Technology of alcohol. Vinnytsia, 2003.
  Google Scholar

[9] Markina L. et al.: Optimization of Ethanol Production Using State-Space Modeling and Optimal Control Technology. 13th International Conference on Dependable Systems, Services and Technologies (DESSERT’2023), Greece, 2023, 1–7 [https://doi.org/10.1109/DESSERT61349.2023.10416529].
  Google Scholar

[10] Melnik Y. R. et al.: Thinning of rye batter using the enzyme preparation shearzyme 500L. Chemistry, Technology and Application of Substances 7(1), 2024, 171–176 [https://doi.org/10.23939/ctas2024.01.171].
  Google Scholar

[11] Palchevsky B., Markina L.: Intelligent control system for the process of preparation of the batch and its water-heat treatment in the production of alcohol. Scientific Notes 75/2023, 22–26 [https://doi.org/10.36910/775.24153966.2023.75.3].
  Google Scholar

[12] Palchevsky B., Markina L.: Optimization of the process of controlling the preparation of the batch in alcohol production. Perspective Technologies And Devices 20, 2022, 82–87 [https://doi.org/10.36910/6775-2313-5352-2022-20-13].
  Google Scholar

[13] Peng Z., Jin Y., Du J.: Enzymatic Properties of endo-1,4-β-xylanase from Wheat Malt. Protein and peptide letters 26(5), 2019, 332–333 [https://doi.org/10.2174/0929866526666190228144851].
  Google Scholar

[14] Rivera E. et al.: Kinetic modeling and parameter estimation in a tower bioreactor for bioethanol production. Applied Biochemistry and Biotechnology 148, 2008, 163–173.
  Google Scholar

[15] Vorobyuk S., Drevetskyi V.: Process automation of continuous quality control of mixture preparation at the distillery. Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 4(4), 2014, 59–61 [https://doi.org/10.5604/20830157.1130194].
  Google Scholar

[16] http://ccl.northwestern.edu/netlogo (available: 15.05.2024).
  Google Scholar

[17] https://drive.google.com/file/d/1M-tZZCoC3jZ8Ekfdvq7eldgwzockICfH/ view?%20pli=1 (available: 25.05.2024).
  Google Scholar

Download


Published
2025-03-31

Cited by

Gumeniuk, L., Markina, L., Satsyk, V., Humeniuk, P., & Lashch, A. (2025). Application of multi-agent programming for modeling the viscosity state of mash in alcohol production. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 15(1), 27–32. https://doi.org/10.35784/iapgos.6509

Authors

Larysa Gumeniuk 
lorapost@gmail.com
Lutsk National Technical University Ukraine
https://orcid.org/0000-0002-7678-7060

Lutsk National Technical University,
Ph.D.Eng. Associate Professor, Department of Automation and Computer – Integrated Technologies.

Research interests: Modeling of reliability and safety of the automated control systems. 


Authors

Ludmyla Markina 

Lutsk National Technical University Ukraine
https://orcid.org/0000-0003-0735-0743

Authors

Viktor Satsyk 

Lutsk National Technical University Ukraine

Authors

Pavlo Humeniuk 

Lutsk National Technical University Ukraine

Authors

Anton Lashch 

Lutsk National Technical University Ukraine

Statistics

Abstract views: 31
PDF downloads: 23


License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.