AIMC Topic: Bioreactors

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A Machine Vision Approach for Bioreactor Foam Sensing.

SLAS technology
Machine vision is a powerful technology that has become increasingly popular and accurate during the last decade due to rapid advances in the field of machine learning. The majority of machine vision applications are currently found in consumer elect...

Machine learning applied for metabolic flux-based control of micro-aerated fermentations in bioreactors.

Biotechnology and bioengineering
Various bio-based processes depend on controlled micro-aerobic conditions to achieve a satisfactory product yield. However, the limiting oxygen concentration varies according to the micro-organism employed, while for industrial applications, there is...

An osmotic membrane bioreactor-clarifier system with a deep learning model for simultaneous reduction of salt accumulation and membrane fouling.

Chemosphere
This study investigates a novel hybrid configuration of an osmotic membrane bioreactor-clarifier (OMBRC) to achieve the simultaneous reduction of salt accumulation and membrane fouling. Compared with the conventional OMBR, the OMBRC demonstrated 14 t...

Integrated Model for Understanding NO Emissions from Wastewater Treatment Plants: A Deep Learning Approach.

Environmental science & technology
This study aims to demonstrate the application of deep learning to quantitatively describe long-term full-scale data observed from wastewater treatment plants (WWTPs) from the perspectives of process modeling, process analysis, and forecasting modeli...

Combined effects of volume ratio and nitrate recycling ratio on nutrient removal, sludge characteristic and microbial evolution for DPR optimization.

Journal of environmental sciences (China)
The optimization of volume ratio (V/V/V) and nitrate recycling ratio (R) in a two-sludge denitrifying phosphorus removal (DPR) process of Anaerobic Anoxic Oxic-Moving Bed Biofilm Reactor (A/O-MBBR) was investigated. The results showed that prolonged ...

A robust soft sensor to monitor 1,3-propanediol fermentation process by Clostridium butyricum based on artificial neural network.

Biotechnology and bioengineering
With the aggravation of environmental pollution and energy crisis, the sustainable microbial fermentation process of converting glycerol to 1,3-propanediol (1,3-PDO) has become an attractive alternative. However, the difficulty in the online measurem...

Modeling water flux in osmotic membrane bioreactor by adaptive network-based fuzzy inference system and artificial neural network.

Bioresource technology
Osmotic Membrane Bioreactor (OMBR) is an emerging technology for wastewater treatment with membrane fouling as a major challenge. This study aims to develop Adaptive Network-based Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) mod...

Machine learning-aided analyses of thousands of draft genomes reveal specific features of activated sludge processes.

Microbiome
BACKGROUND: Microorganisms in activated sludge (AS) play key roles in the wastewater treatment processes. However, their ecological behaviors and differences from microorganisms in other environments have mainly been studied using the 16S rRNA gene t...

Quantification of interfacial energies associated with membrane fouling in a membrane bioreactor by using BP and GRNN artificial neural networks.

Journal of colloid and interface science
Interfacial energy between sludge foulants and rough membrane surface critically determines adhesive fouling in membrane bioreactors (MBRs). As a current available method, the advanced extensive Derjaguin-Landau-Verwey-Overbeek (XDLVO) approach canno...

Gas-phase trichloroethylene removal by Rhodococcus opacus using an airlift bioreactor and its modeling by artificial neural network.

Chemosphere
This study evaluated the biological removal of trichloroethylene (TCE) by Rhodococcus opacus using airlift bioreactor under continuous operation mode. The effect of inlet TCE concentration in the range 0.12-2.34 g m on TCE removal has studied for 55 ...