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Národní úložiště šedé literatury Nalezeno 2 záznamů.  Hledání trvalo 0.02 vteřin. 
PREDICTION OF FRACTURE TOUGHNESS TRANSITION FROM TENSILE TEST DATA APPLYING NEURAL NETWORKS
 Dlouhý, I. ; Hadraba, Hynek ; Chlup, Zdeněk ; Válka, Libor ; Žák, L.
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.
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NEW APPROACH TO STRESS-STRAIN CURVE PREDICTION USING BALL INDENTATION TEST
 Brumek, J. ; Strnadel, B. ; Dlouhý, Ivo
This work is concerned with the method for predicting stress-strain behavior of material using instrumented indentation technique. High strength low alloy steel with different thermal treatment was taken into the analysis. Heat treatment for the steel was performed to obtain different mechanical properties. Assessment of mechanical properties was done by using inverse technique of the finite element analysis. The results were confronted with conventional test parameters and prediction procedure defined such Automated Ball Indentation Technique (ABIT). Comparison of the material curves shows good agreement with tensile test properties which makes this non-destructive method suitable for industrial application.
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