Prediction of fracture toughness transition from tensile test data applying neural network

Kód výsledku v 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>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Prediction of fracture toughness transition from tensile test data applying neural network

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Prediction of fracture toughness transition from tensile test data applying neural network

Popis výsledku anglicky

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.

Druh

O - Ostatní výsledky

CEP obor

JL - Únava materiálu a lomová mechanika

OECD FORD obor

—

Projekt

<a href="/cs/project/GAP108%2F10%2F0466" target="_blank" >GAP108/10/0466: Predikce lomového chování konstrukčních ocelí na základě kvantifikace lokální odezvy materiálu</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů