About: Prediction of Fracture Toughness Transition from Tensile Test Parameters Applying Artificial Neural Networks     Goto   Sponge   NotDistinct   Permalink

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  • Reference temperature localizing the fracture toughness temperature diagram on temperature axis was predicted based on tensile test data. Regularization artificial neural network (ANN) was adjusted to solve the interrelation of these properties. For analyses, 29 data sets from low-alloy steels were applied. The fracture toughness transition dependence was quantified by means of master curve concept enabling to represent it using one parameter - reference temperature. Different strength and deformation characteristics from standard tensile specimens and notched specimens, instrumented ball indentation test etc. have been applied. A very promising correlation of predicted and experimentally determined values of reference temperature was found.
  • Reference temperature localizing the fracture toughness temperature diagram on temperature axis was predicted based on tensile test data. Regularization artificial neural network (ANN) was adjusted to solve the interrelation of these properties. For analyses, 29 data sets from low-alloy steels were applied. The fracture toughness transition dependence was quantified by means of master curve concept enabling to represent it using one parameter - reference temperature. Different strength and deformation characteristics from standard tensile specimens and notched specimens, instrumented ball indentation test etc. have been applied. A very promising correlation of predicted and experimentally determined values of reference temperature was found. (en)
Title
  • Prediction of Fracture Toughness Transition from Tensile Test Parameters Applying Artificial Neural Networks
  • Prediction of Fracture Toughness Transition from Tensile Test Parameters Applying Artificial Neural Networks (en)
skos:prefLabel
  • Prediction of Fracture Toughness Transition from Tensile Test Parameters Applying Artificial Neural Networks
  • Prediction of Fracture Toughness Transition from Tensile Test Parameters Applying Artificial Neural Networks (en)
skos:notation
  • RIV/68081723:_____/10:00354571!RIV11-GA0-68081723
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GAP108/10/0466), Z(AV0Z20410507)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 281069
http://linked.open...ai/riv/idVysledku
  • RIV/68081723:_____/10:00354571
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • thermal ageing; brittleness; fracture (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [94CB83743306]
http://linked.open...v/mistoKonaniAkce
  • Ostrava
http://linked.open...i/riv/mistoVydani
  • Ostrava
http://linked.open...i/riv/nazevZdroje
  • New Methods of Damage and Failure Analysis of Structural Parts
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Chlup, Zdeněk
  • Dlouhý, Ivo
  • Hadraba, Hynek
  • Kozák, Vladislav
  • Šmida, T.
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Vysoká škola báňská - Technická univerzita Ostrava
https://schema.org/isbn
  • 978-80-248-2265-5
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