AbstractA static multivariate statistical process control model based on principal component analysis (PCA-MSPC) was developed for an anaerobic reactor maintained in steady-state, joining the biogas composition (CH4, CO2, H2) to the total solids (TS), volatile solids (VS), total inorganic carbon (TIC) and total ammonia nitrogen (TAN) contents of the slurry. The principal component analysis (PCA) highlighted a lack of correlation between the individual process variables (IPVs) measured in the slurry and the gas phase. The application of this model to the data set collected for an independent anaerobic reactor (fed with the same substrate) progressively led from steady-state to critical volatile fatty acids (VFA) intoxication did not allow ev...
Detergents and solvents are included in the list of compounds that can be inhibitory or toxic to ana...
One of the key success factors for optimal management of anaerobic digestion reactors is to control ...
Here, we report data of the principal component analysis (PCA) assessment and clustering analysis re...
A static multivariate statistical process control model based on principal component analysis (PCA-M...
Stable operation of high-rate thermophilic sludge anaerobic reactors is sometime hard to achieve bec...
The data presented here is the one used to build the figures and tables of the manuscript "Asse...
Monitoring in the anaerobic bioreactor system is requiring understanding the occurred situation in t...
Morphological parameters, obtained by quantitative image analysis techniques, together with physiol...
Detergents and solvents are included in the list of compounds that can be inhibitory or toxic to ana...
Abstract Morphological parameters, obtained by quantitative image analysis techniques, together with...
The Principal Component Analysis (PCA) is a method widely used to process experimental data. The PCA...
Improving the knowledge of anaerobic digestion process parameters can lead to a reduction of anaerob...
International audienceThe Anaerobic Digestion Model No. 1 (ADM1) is a complex model which is widely ...
Principal component analysis (PCA) was applied to datasets gathering morphological, physiological an...
This research analyzes the feasibility of developing a Multivariate Statistical Process Control (MSP...
Detergents and solvents are included in the list of compounds that can be inhibitory or toxic to ana...
One of the key success factors for optimal management of anaerobic digestion reactors is to control ...
Here, we report data of the principal component analysis (PCA) assessment and clustering analysis re...
A static multivariate statistical process control model based on principal component analysis (PCA-M...
Stable operation of high-rate thermophilic sludge anaerobic reactors is sometime hard to achieve bec...
The data presented here is the one used to build the figures and tables of the manuscript "Asse...
Monitoring in the anaerobic bioreactor system is requiring understanding the occurred situation in t...
Morphological parameters, obtained by quantitative image analysis techniques, together with physiol...
Detergents and solvents are included in the list of compounds that can be inhibitory or toxic to ana...
Abstract Morphological parameters, obtained by quantitative image analysis techniques, together with...
The Principal Component Analysis (PCA) is a method widely used to process experimental data. The PCA...
Improving the knowledge of anaerobic digestion process parameters can lead to a reduction of anaerob...
International audienceThe Anaerobic Digestion Model No. 1 (ADM1) is a complex model which is widely ...
Principal component analysis (PCA) was applied to datasets gathering morphological, physiological an...
This research analyzes the feasibility of developing a Multivariate Statistical Process Control (MSP...
Detergents and solvents are included in the list of compounds that can be inhibitory or toxic to ana...
One of the key success factors for optimal management of anaerobic digestion reactors is to control ...
Here, we report data of the principal component analysis (PCA) assessment and clustering analysis re...