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<p>To better understand the anaerobic digestion process, models can be made based on already performed fermentations, however, these models are limited in the literature. In this contribution, a model was developed based on the modified Hill model, which can predict the production of volatile fatty acids. The model used eight differential equations reported by Haugen who is based on the modified Hill model and four state variables, using MATLAB. This model can predict the production of volatile fatty acids in both semi-continuous and batch processes, using substrates digested sludge and primary sludge from a Wastewater Treatment Plant under different conditions such as organic load, temperature, pH, and hydraulic retention time. The deviation between the experiments performed and the model developed was less than ± 9.1%, demonstrating this model’s accuracy and robustness. Furthermore, the statistical analysis showed that there were no significant differences between the fermentations and the simulation, verifying the null hypothesis. The developed model identified a stable and optimal VFA-generating loading rate from experimental data.</p> Graphical Abstract <p></p>

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Predictive Modelling of Volatile Fatty Acid Production in Anaerobic Digestion: A Modified Hill Approach for Enhanced Accuracy

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月10日

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  • Jeniffer Paola Gracia Rojas,
  • Carlos Enrique Montenegro-Marin,
  • Iván Cabeza

摘要

To better understand the anaerobic digestion process, models can be made based on already performed fermentations, however, these models are limited in the literature. In this contribution, a model was developed based on the modified Hill model, which can predict the production of volatile fatty acids. The model used eight differential equations reported by Haugen who is based on the modified Hill model and four state variables, using MATLAB. This model can predict the production of volatile fatty acids in both semi-continuous and batch processes, using substrates digested sludge and primary sludge from a Wastewater Treatment Plant under different conditions such as organic load, temperature, pH, and hydraulic retention time. The deviation between the experiments performed and the model developed was less than ± 9.1%, demonstrating this model’s accuracy and robustness. Furthermore, the statistical analysis showed that there were no significant differences between the fermentations and the simulation, verifying the null hypothesis. The developed model identified a stable and optimal VFA-generating loading rate from experimental data.

Graphical Abstract