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  5. Integration of Mathematical Modeling and Artificial Intelligence to Predict Thermal Conditions and Optimize the Operation of Biogas Plants
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Integration of Mathematical Modeling and Artificial Intelligence to Predict Thermal Conditions and Optimize the Operation of Biogas Plants

Автор(ы)
Omirlan Auelbekov
Айнур Козбакова
Kairat Yessentayev
Timur Merembayev
Kuanyshbek Igibayev
Дата публикации
1 января 2025 г.
Тип
journal article
Журнал
Engineered Science
DOI
10.30919/es1603
ISSN
2576-988X
Аннотация
Modern biogas plants face a number of challenges related to precise control of thermal conditions, which significantly affect the stability of processes and the overall efficiency of energy production.The complexity lies in the nonlinear and dynamic nature of biochemical reactions occurring under anaerobic conditions, as well as in a large number of factors affecting heat transfer inside the reactor.In this regard, there is a need to develop adaptive and highly accurate models capable of predicting thermal processes and optimizing the operation of biogas systems.In this study, we propose a hybrid modeling framework that integrates physics-based mathematical models with machine learning algorithms, enabling real-time prediction and adaptive control of thermal processes.Unlike prior models focused solely on thermodynamics or empirical
Темы

biogas plants

anaerobic digestion

hybrid physics-machin...

reactor temperature c...

process optimization

heat transfer

real-time prediction

adaptive control

Области науки (FoS)

Engineering

Building and Construc...

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