Optimizing the specific energy consumption of vacuum filtration
Huttunen, Manu (2019-12-13)
Väitöskirja
13.12.2019
Lappeenranta-Lahti University of Technology LUT
Acta Universitatis Lappeenrantaensis
School of Energy Systems
School of Energy Systems, Sähkötekniikka
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Julkaisun pysyvä osoite on
https://urn.fi/URN:ISBN:978-952-335-459-3
https://urn.fi/URN:ISBN:978-952-335-459-3
Tiivistelmä
Vacuum filtration is applied in solid-liquid separation in a wide variety of industrial processes for instance in the mining, chemical, and paper industries. The main contributor to the considerable energy consumption of vacuum filtration is the high requirement of pumping air to maintain the pressure difference driving the filtration.
In this doctoral dissertation, the specific energy consumption of vacuum filtration and subsequent thermal drying to achieve a zero moisture content of the filtration product is investigated. The objective of the study is to identify vacuum filtration process variables, which can be manipulated to enhance efficiency and to optimize the energy consumption of the filtration and drying process. The investigation is carried out by analysing the results obtained in experiments with a laboratory-scale Büchner apparatus and a pilotscale horizontal belt vacuum filter. The analysis of thermal drying is included by calculation. The applicability of a data-driven soft sensor method to estimate the filter cake solid content after vacuum dewatering is studied.
The study shows that it is key to evaluate the specific energy consumption as a function of the solid content of the cake in order to determine the optimal ending criteria for dewatering. It is found that there is an optimal combination of the slurry solid content, the pressure difference, and the slurry loading that results in the minimum specific energy consumption of vacuum filtration and subsequent thermal drying.
Exploiting the thermodynamic nature of vacuum dewatering proved to be highly beneficial to the estimation of the solid content of the filter cake. The developed datadriven soft sensor estimator was able to explain 80 %of the variance in the target variable with a mean absolute error of 0.42 percentage points.
The evaluation of the specific energy consumption of a vacuum filtration process with respect to the solid content of the filter cake and the application of the soft sensor estimator could provide the means to control and optimize the energy consumption of vacuum filtration and subsequent drying.
In this doctoral dissertation, the specific energy consumption of vacuum filtration and subsequent thermal drying to achieve a zero moisture content of the filtration product is investigated. The objective of the study is to identify vacuum filtration process variables, which can be manipulated to enhance efficiency and to optimize the energy consumption of the filtration and drying process. The investigation is carried out by analysing the results obtained in experiments with a laboratory-scale Büchner apparatus and a pilotscale horizontal belt vacuum filter. The analysis of thermal drying is included by calculation. The applicability of a data-driven soft sensor method to estimate the filter cake solid content after vacuum dewatering is studied.
The study shows that it is key to evaluate the specific energy consumption as a function of the solid content of the cake in order to determine the optimal ending criteria for dewatering. It is found that there is an optimal combination of the slurry solid content, the pressure difference, and the slurry loading that results in the minimum specific energy consumption of vacuum filtration and subsequent thermal drying.
Exploiting the thermodynamic nature of vacuum dewatering proved to be highly beneficial to the estimation of the solid content of the filter cake. The developed datadriven soft sensor estimator was able to explain 80 %of the variance in the target variable with a mean absolute error of 0.42 percentage points.
The evaluation of the specific energy consumption of a vacuum filtration process with respect to the solid content of the filter cake and the application of the soft sensor estimator could provide the means to control and optimize the energy consumption of vacuum filtration and subsequent drying.
Kokoelmat
- Väitöskirjat [1112]