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SUMMARY:Machine learning as a tool to design special concrete mixes - Dr R
 ubén-Daniel López 
DTSTART:20240524T140000Z
DTEND:20240524T150000Z
UID:TALK217054@talks.cam.ac.uk
CONTACT:Nishangani Gowrikanthan
DESCRIPTION:Special concretes refer to concrete mixtures designed with uni
 que properties to achieve specific purposes beyond those of conventional c
 oncrete\, such as increased strength\, lighter weight\, or higher permeabi
 lity\, among others. Due to their particular composition\, existing mix de
 sign methods often lack sufficient accuracy to reliably estimate their beh
 aviour. Consequently\, complementary use of laborious laboratory tests may
  be required\, thus increasing the consumption of time\, money\, and resou
 rces during structural design processes.\nIn the last decade\, the widespr
 ead use of artificial intelligence and its application in civil engineerin
 g and architecture has represented a significant step forward in gaining a
  better understanding of construction materials. By combining experimental
  data with machine learning algorithms\, it has been possible to develop m
 odels that enhance existing design methodologies for special concrete mixe
 s\, and reduce the need for extensive experimental testing. This seminar w
 ill present various examples of neural network applications in the design 
 of fibre-reinforced and pervious concrete mixes with the objective of pred
 icting their key performance properties.\n
LOCATION:CivEng Seminar Room (1-33) (Civil Engineering Building)
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