Batch settling curve registration via image data modeling

Nicolas Derlon; Christian Thürlimann; David Dürrenmatt; Kris Villez

doi:10.1016/j.watres.2017.01.049

Batch settling curve registration via image data modeling

Nicolas Derlon, Christian Thürlimann, David Dürrenmatt, Kris Villez

Research output: Contribution to journal › Article › peer-review

20 Scopus citations

Abstract

To this day, obtaining reliable characterization of sludge settling properties remains a challenging and time-consuming task. Without such assessments however, optimal design and operation of secondary settling tanks is challenging and conservative approaches will remain necessary. With this study, we show that automated sludge blanket height registration and zone settling velocity estimation is possible thanks to analysis of images taken during batch settling experiments. The experimental setup is particularly interesting for practical applications as it consists of off-the-shelf components only, no moving parts are required, and the software is released publicly. Furthermore, the proposed multivariate shape constrained spline model for image analysis appears to be a promising method for reliable sludge blanket height profile registration.

Original language	English
Pages (from-to)	327-337
Number of pages	11
Journal	Water Research
Volume	114
DOIs	https://doi.org/10.1016/j.watres.2017.01.049
State	Published - 2017
Externally published	Yes

Funding

This work was supported by the Commission for Technology and Innovation (CTI) of the Swiss Federal Department of Economic Affairs Education and Research (EAER) (CTI project no. 14351.1 PFIW-IW). The authors thank Gustaf Olsson for sparking our interest in the topic and feedback. We thank Stefan Diehl, Ulf Jeppsson, and Eberhard Morgenroth for their comments and suggestions. All computations were executed by joint use of Matlab (The MathWorks Inc, 2014); the Functional Data Analysis software package accompanying the book (Ramsay and Silverman, 2002); and MOSEK (Andersen and Andersen, 2000; MOSEK ApS, 2012)

Funders	Funder number
EAER	14351.1 PFIW-IW
Gustaf Olsson
MOSEK
Swiss Federal Department of Economic Affairs Education and Research
Kommission für Technologie und Innovation

Keywords

Secondary clarifiers
Separation processes
Shape constrained splines
Sludge blanket height
Sludge settling
Wastewater treatment

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.watres.2017.01.049

Cite this

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title = "Batch settling curve registration via image data modeling",

abstract = "To this day, obtaining reliable characterization of sludge settling properties remains a challenging and time-consuming task. Without such assessments however, optimal design and operation of secondary settling tanks is challenging and conservative approaches will remain necessary. With this study, we show that automated sludge blanket height registration and zone settling velocity estimation is possible thanks to analysis of images taken during batch settling experiments. The experimental setup is particularly interesting for practical applications as it consists of off-the-shelf components only, no moving parts are required, and the software is released publicly. Furthermore, the proposed multivariate shape constrained spline model for image analysis appears to be a promising method for reliable sludge blanket height profile registration.",

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AU - Villez, Kris

PY - 2017

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N2 - To this day, obtaining reliable characterization of sludge settling properties remains a challenging and time-consuming task. Without such assessments however, optimal design and operation of secondary settling tanks is challenging and conservative approaches will remain necessary. With this study, we show that automated sludge blanket height registration and zone settling velocity estimation is possible thanks to analysis of images taken during batch settling experiments. The experimental setup is particularly interesting for practical applications as it consists of off-the-shelf components only, no moving parts are required, and the software is released publicly. Furthermore, the proposed multivariate shape constrained spline model for image analysis appears to be a promising method for reliable sludge blanket height profile registration.

AB - To this day, obtaining reliable characterization of sludge settling properties remains a challenging and time-consuming task. Without such assessments however, optimal design and operation of secondary settling tanks is challenging and conservative approaches will remain necessary. With this study, we show that automated sludge blanket height registration and zone settling velocity estimation is possible thanks to analysis of images taken during batch settling experiments. The experimental setup is particularly interesting for practical applications as it consists of off-the-shelf components only, no moving parts are required, and the software is released publicly. Furthermore, the proposed multivariate shape constrained spline model for image analysis appears to be a promising method for reliable sludge blanket height profile registration.

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KW - Separation processes

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ER -

Batch settling curve registration via image data modeling

Abstract

Funding

Keywords

UN SDGs

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