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Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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NAIADES Dynamical Treatments Suggestion Tool Modelling Dataset

Authors: Manuel, Juan; , Aida; , Rocio;

NAIADES Dynamical Treatments Suggestion Tool Modelling Dataset

Abstract

This data was generated within the European NAIADES project (grant agreement No 820985) for the development of the Dynamical Treatments Suggestion (DTS) Service. The DTS purpose is the estimation of the most efficient treatments (dosage of coagulant and chlorine) for drinking Water Treatment Plants (dWTPs) whose configuration is: coagulation/sedimentation, filtration and chlorination. The inlet water quality (pH, conductivity and turbidity) of the dWTP is used as input of the service. Then, it suggests the most efficient treatments that guarantee good drinking water quality at the outlet of the dWTP, based on WHO recommendations (turbidity below 5 NTU and chlorine concentration between 0.5 and 1 mg/L). The dataset includes data generated with Stimela, an open source water treatments processes simulation SW; and data collected in a scaled down replica of a real dWTP.

Keywords

drinking Water Treatment Plants, coagulant dosage, pH, treatments, conductivity, residual chlorine, chlorine dosage, turbidity

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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