National Repository of Grey Literature 4 records found  Search took 0.01 seconds. 
The influence of microstructure on the KV values of microalloyed steel 694F60
Abaidullin, Ilgiz ; Pacal, Bohumil (referee) ; Foret, Rudolf (advisor)
The subject of this master’s thesis was to find the causes of impact toughness scattering of forgings of the test disk with dimension range of 540 – 170 mm. The experimental samples were developed from steel A694 F60. To reach the main aim light microscopy, electron microscopy, EBSD technique, fractographic analysis and hardness measurement HV10 were utilized.
Hodnocení kvality pomocí nedestruktivních technologií
Šarocký, Robert
This diploma thesis is focused on evaluating quality of materials which are manufactured by additive method of production. The thesis describes methods of additive production and their materials. Furthermore, the thesis deals with the methodology of investigation of mechanical properties of products of additive production. The following part of the thesis describes production of samples from two different types of material. Subsequently, these samples were tested by acoustic emission in the impact bending test and the tensile strength test.
The influence of microstructure on the KV values of microalloyed steel 694F60
Abaidullin, Ilgiz ; Pacal, Bohumil (referee) ; Foret, Rudolf (advisor)
The subject of this master’s thesis was to find the causes of impact toughness scattering of forgings of the test disk with dimension range of 540 – 170 mm. The experimental samples were developed from steel A694 F60. To reach the main aim light microscopy, electron microscopy, EBSD technique, fractographic analysis and hardness measurement HV10 were utilized.
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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