Evidence map›Paper›PMID 35890979›Full record

ArticleSensors (Basel, Switzerland)2022

Leakages in District Heating Networks-Model-Based Data Set Quality Assessment and Localization.

Kai Vahldiek, Bernd Rüger, Frank Klawonn

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kai VahldiekInstitute for Information Engineering, Ostfalia University of Applied Sciences, Salzdahlumer Str. 46/48, 38302 Wolfenbuttel, Germany.ORCID 0000-0002-9713-4595
Bernd RügerSWM Services GmbH, Emmy-Noether-Str. 2, 80992 Munchen, Germany.
Frank KlawonnInstitute for Information Engineering, Ostfalia University of Applied Sciences, Salzdahlumer Str. 46/48, 38302 Wolfenbuttel, Germany.ORCID 0000-0001-9613-182X

Funding

Federal Ministry of Economic Affairs and Climate Action 03ET1624 BFederal Ministry of Economic Affairs and Climate Action 03ET1624 C
6 · The paper itself

Abstract

Large spontaneous leakages in district heating networks (DHNs) require a separation of the affected network part, as interruption of the heat supply is imminent. Measurement data of 22 real events was analyzed for localization, but suitable results were not always achieved. In this paper, the reasons are investigated and a model for data evaluation (MoFoDatEv) is developed for further insights. This contains prior knowledge and a simplified physical model for the reaction of the DHN in the case of a large spontaneous leakage. A model like this does not exist so far. It determines the time point and the duration of the pressure drop of the pressure wave which is caused by such leakages. Both parameters and the evaluation time frame are optimized for each event separately. The quality assessment leads to a categorization of the events based on several parameters, and correlations between the pressure and the refill mass flow are found. A minimum leakage size is deduced for successful evaluation. Furthermore, MoFoDatEv can also be used for leakage localization directly, combining two steps from previous publications. Therefore, more data contribute to the result. The application is conducted with artificial data to prove the model concept, and also with real measurement data.

Indexed as

HeatingHot Temperaturedata analysisdistrict heating networkleakage localizationmeasurement dataquality assessmentsensors

Identifiers

PMID35890979
PMCPMC9321529

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.