Prediction of fracture toughness transition from tensile test data applying neural network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081723%3A_____%2F11%3A00361265" target="_blank" >RIV/68081723:_____/11:00361265 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Prediction of fracture toughness transition from tensile test data applying neural network
Original language description
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, nstrumented ball indentation test etc. have been applied. A very promising correlation of predicted and experimentally determined values of reference temperature was found.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
JL - Fatigue and fracture mechanics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GAP108%2F10%2F0466" target="_blank" >GAP108/10/0466: Fracture behaviour prediction based on kvantification of local material response</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů