June 29, 2020 Report Open Access

Blocher, Caroline; Pecci, Filippo; Jara Arriagada, Carlos; Stoianov, Ivan

Dublin Core Export

<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Blocher, Caroline</dc:creator>
  <dc:creator>Pecci, Filippo</dc:creator>
  <dc:creator>Jara Arriagada, Carlos</dc:creator>
  <dc:creator>Stoianov, Ivan</dc:creator>
  <dc:date>2020-06-29</dc:date>
  <dc:description>The application of a model-based leak localization method on the data set provided for the Battle of Leakage Detection and Isolation Methods 2020 is investigated. First, an analysis of flow residuals is used to detect a possible leak event which is then confirmed or rejected by the model-based leak localization. A prior clustering of daily flow profiles results in the identification of possible leak days, and leak-free days, in the entire data set.</dc:description>
  <dc:description>The project was co-funded by Cla-Val UK Ltd</dc:description>
  <dc:identifier>https://zenodo.org/record/3921800</dc:identifier>
  <dc:identifier>10.5281/zenodo.3921800</dc:identifier>
  <dc:identifier>oai:zenodo.org:3921800</dc:identifier>
  <dc:relation>info:eu-repo/grantAgreement/RCUK/EPSRC/EP%2FP004229%2F1/</dc:relation>
  <dc:relation>info:eu-repo/grantAgreement/RCUK/EPSRC/EP%2FL016826%2F1/</dc:relation>
  <dc:relation>doi:10.5281/zenodo.3921799</dc:relation>
  <dc:relation>url:https://zenodo.org/communities/battledim2020</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Battle of Leak Detection and Isolation 2020</dc:subject>
  <dc:subject>Water distribution networks</dc:subject>
  <dc:title>Detecting and Localizing Leakage Hotspots in Water Distribution Networks via Regularization of an Inverse Problem: An Application to the Battle of Leakage Detection and Isolation Methods 2020 Competition</dc:title>
  <dc:type>info:eu-repo/semantics/report</dc:type>
  <dc:type>publication-report</dc:type>
</oai_dc:dc>