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SUMMARY:ENAC Seminar Series by Dr D. Valero
DTSTART:20190718T090000
DTEND:20190718T100000
DTSTAMP:20260916T050608Z
UID:749e05e9f5205c31cb994697e9c76316c5a85a37254fbab99ed3ef27
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr Daniel Valero\n09:00 – 10:00 – Dr Daniel Valero\nLectur
 er\, IHE Delft Institute for Water Education\, The Netherlands\n\nAdvancin
 g hydraulic infrastructures\, from tradition to innovation : The times the
 y are a-changin'\n\nThe development of water systems has encompassed the e
 volution of the civilization through the past centuries. Water storage and
  conveyance has led to the largely advanced society by providing resources
 \, sanitation and reducing risks. Today\, hydraulic infrastructures seem t
 oo rigid for a world of emerging technologies and escalating stresses. Pri
 orities have shifted across the globe\, the statistic presented by United 
 Nations being a revealing example: more people have mobile phones than toi
 lets. Nevertheless\, as time goes by\, climate change is showing off more 
 intensely and mitigation seems to come in an untimely and insufficient man
 ner. Thus\, adaptation arises as a natural measure\, and it can only be ac
 hieved through the reengineering of our hydraulic infrastructures. Reduced
  water resources will harm hydropower – renewable – energy production 
 potential\, and increasing peak discharges will challenge dams and downstr
 eam environments.\n \nFurthermore\, our already-built dams are ageing\, a
 nd some are now older than the time series originally used to obtain their
  associated hydrology. New dams will also have to incorporate this new sou
 rce of uncertainty in a realisable form. The uprising numerical modelling 
 techniques are changing the way we deal with fluid phenomena and the capac
 ity to extract information from them. Nonetheless\, the point is on robust
 ness and accuracy\, which is not yet fully assessed. In parallel\, artific
 ial intelligence has allowed disruptive experimental predictions beyond wh
 at we thought were the instrumentation limits and\, recently\, a study in 
 Journal of Fluid Mechanics suggested that deep learning would promptly out
 smart any state-of-the-art turbulence model. All things considered\, clima
 te change evolving at a temporal scale smaller than the lifetime of our ag
 eing structures\, the already thriving numerical modelling capabilities\, 
 and the seemingly unlimited potential of artificial intelligence can be ex
 pected to shape the imminent advances related to hydraulic infrastructures
  and water systems.\n 
LOCATION:CM 1 4 https://plan.epfl.ch/?room==CM%201%204
STATUS:CONFIRMED
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