Home > Search Results: Šmida, T.
Search:
Search Tips :: Advanced Search
Search collections:
Sort by: Display results: Output format:
National Repository of Grey Literature 3 records found  Search took 0.00 seconds. 
Prediction of Fracture Toughness Transition from Tensile Test Parameters Applying Artificial Neural Networks
 Dlouhý, Ivo ; Hadraba, Hynek ; Chlup, Zdeněk ; Kozák, Vladislav ; Šmida, T.
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.
Detailed record
Prediction of Fracture Toughness Temperature Diagram from Tensile Test Parmaeters
 Dlouhý, Ivo ; Hadraba, Hynek ; Šmida, T. ; Babjak, J.
Reference temperature of fracture toughness temperature diagram has been predicted based on tensile test data. Neuron analysis was applied to solve these properties correlation. For fracture toughness determination three-point bend specimens have been applied, the reference temperature being calculated applying multi-temperature method. Different strength and deformation properties have been evaluated from standard tensile specimens focusing on data from localised deformation during specimen necking. Totally 29 data sets from low alloy steels have been generated for the analysis. Good correlation of predicted and experimentally determined values has been found. Further analysis with higher number of data sets is needed to increase the accuracy of predicted values and decrease the number of input data.
Detailed record
Reference temperature prediction from tensile test parameters
 Šmida, T. ; Babjak, J. ; Dlouhý, Ivo
Reference temperature of fracture toughness temperature diagram has been predicted based on tensile test data. Neuron analysis was applied to solve these properties correlation. For fracture toughness determination three-point bend specimens have been applied, the reference temperature being calculated applying multi-temperature method. Different strength and deformation properties have been evaluated from standard tensile specimens focusing on data from localised deformation during specimen necking. Totally 29 data sets from low alloy steels have been generated for the analysis. Good correlation of predicted and experimentally determined values has been found. Further analysis with higher number of data sets is needed to increase the accuracy of predicted values and decrease the number of input data.
Detailed record

Interested in being notified about new results for this query?
Subscribe to the RSS feed.
Digital Repository :: Search :: Submit :: Personalize :: Help
Powered by Invenio v1.1.2
Maintained by admin.invenio@techlib.cz
This site is also available in the following languages:
Česky  English