Exploiting machine learning to radically change the way hydrodynamic simulations support planning and operation of smart liveable cities

M. Grum, R. Palmitessa, F. Bauer, R. Engels, M. Ringelkamp, M. Siekmann, P. S. Mikkelsen, R. Löwe

Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

Abstract

While planning and operation of smart liveable cities require a solid appreciation of the impacts of hydrodynamic phenomena, classical numerical simulation methods are slow and ill-suited both to today’s challenges and goals, and to tomorrow’s agile and stakeholder-inclusive approaches. Exploiting latest developments in machine learning, we present a new simulation approach that radically changes the way hydrodynamic modelling supports planning and operation. The approach builds on recent developments in neural networks suitable for incorporating physical network characteristics. The marked shorter turnaround time fosters better co-creation, string stakeholder involvement, comprehensive exploration of the solution space and associated impacts, and ultimately better investments towards more liveable cities.
Original languageEnglish
Publication date2022
Number of pages4
Publication statusPublished - 2022
EventIWA World Water Congress & Exhibition 2022 - Bella Center, Copenhagen, Denmark
Duration: 11 Sept 202215 Sept 2022
https://worldwatercongress.org/

Conference

ConferenceIWA World Water Congress & Exhibition 2022
LocationBella Center
Country/TerritoryDenmark
CityCopenhagen
Period11/09/202215/09/2022
Internet address

Bibliographical note

Danish Eco-Innovation Program (MUDP) (grant number 2020-15748).

Keywords

  • Hydrodynamic modelling
  • Machine learning
  • Urban planning

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