A Proof of Concept for a Digital Twin of an Ultrasonic Fermentation System
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866909993180069888 |
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| author | Pisoni, Francesco Saverio Sconocchia Vitaletti, Andrea Appolloni, Davide Ortenzi, Federico della Rocca, Blasco Morozzo Guillén, Mariano José Contaldo, Alessandro |
| author_facet | Pisoni, Francesco Saverio Sconocchia Vitaletti, Andrea Appolloni, Davide Ortenzi, Federico della Rocca, Blasco Morozzo Guillén, Mariano José Contaldo, Alessandro |
| contents | This paper presents the design and implementation of a proof of concept digital twin for an innovative ultrasonic-enhanced beer-fermentation system, developed to enable intelligent monitoring, prediction, and actuation in yeast-growth environments. A traditional fermentation tank is equipped with a piezoelectric transducer able to irradiate the tank with ultrasonic waves, providing an external abiotic stimulus to enhance the growth of yeast and accelerate the fermentation process. At its core, the digital twin incorporates a predictive model that estimates yeast's culture density over time based on the surrounding environmental conditions. To this end, we implement, tailor and extend the model proposed in Palacios et al., allowing us to effectively handle the limited number of available training samples by using temperature, ultrasonic frequency, and duty cycle as inputs. The results obtained along with the assessment of model performance demonstrate the feasibility of the proposed approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_11723 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Proof of Concept for a Digital Twin of an Ultrasonic Fermentation System Pisoni, Francesco Saverio Sconocchia Vitaletti, Andrea Appolloni, Davide Ortenzi, Federico della Rocca, Blasco Morozzo Guillén, Mariano José Contaldo, Alessandro Emerging Technologies Machine Learning This paper presents the design and implementation of a proof of concept digital twin for an innovative ultrasonic-enhanced beer-fermentation system, developed to enable intelligent monitoring, prediction, and actuation in yeast-growth environments. A traditional fermentation tank is equipped with a piezoelectric transducer able to irradiate the tank with ultrasonic waves, providing an external abiotic stimulus to enhance the growth of yeast and accelerate the fermentation process. At its core, the digital twin incorporates a predictive model that estimates yeast's culture density over time based on the surrounding environmental conditions. To this end, we implement, tailor and extend the model proposed in Palacios et al., allowing us to effectively handle the limited number of available training samples by using temperature, ultrasonic frequency, and duty cycle as inputs. The results obtained along with the assessment of model performance demonstrate the feasibility of the proposed approach. |
| title | A Proof of Concept for a Digital Twin of an Ultrasonic Fermentation System |
| topic | Emerging Technologies Machine Learning |
| url | https://arxiv.org/abs/2601.11723 |