Abstract
The flocculation process is an important step towards product purification in downstream bio-manufacturing, and for removal of organics, biomass and cell debris in wastewater treatment. Despite a broad application in various industries, the process mechanism is not well understood. Flocculation is a process that can be represented across scales, from nano-scale and all the way beyond the microscale. Due to the current lack of knowledge for modeling flocculation across the length scales, industry often resorts to manual control or no control at all of flocculation processes. In this work, it is intended to develop a hybrid systematic model-based framework, which integrates computational chemistry and stochastic modeling approaches for monitoring and control of the flocculation process above micro-scale. The intention is to reduce the time required for manual control, and to avoid potential product losses in addition to unwanted process variations during operation.
Original language | English |
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Publication date | 2020 |
Number of pages | 7 |
Publication status | Published - 2020 |
Event | The 11th International Chemical Engineering Congress & Exhibition (IChEC 2020) - Fouman, Iran, Islamic Republic of Duration: 15 Apr 2020 → 17 Apr 2020 |
Conference
Conference | The 11th International Chemical Engineering Congress & Exhibition (IChEC 2020) |
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Country/Territory | Iran, Islamic Republic of |
City | Fouman |
Period | 15/04/2020 → 17/04/2020 |
Keywords
- Flocculation
- Process Modeling
- Computational Chemistry
- Artificial Intelligence