ALL libraries (COBIB.SI union bibliographic/catalogue database)
13.
Wear prediction of hot working tools
Terčelj, Milan ; Turk, Radomir ; Peruš, Iztok
The method of CAE neural network was used to predict the wear of hot forging tool. The data base for prediction consisted of experimental observations of the laboratory simulation of tribomechanical ...and tribotemperature conditions on the locally most loaded part of the forging tool during the application. Individual influence variables of the wear were computed by FEM. The laboratory simulation of the tool wear was performed on a module which was developed separately as appendix for the GLEEBLE 1500 simulator. The ability of CAE has shown to be vital in the prediction of wear on the basis of experimental phenomena.
It was not necessary to add the material to the shelf.
Bibliographic material was successfully added on shelf.
Adding bibliographical material on shelf was not successful.
Material is already on the shelf.
Permalink
URL:
Impact factor
Access to the JCR database is permitted only to users from Slovenia. Your current IP address is not on the list of IP addresses with access permission, and authentication with the relevant AAI accout is required.
Year
Impact factor
Edition
Category
Classification
JCR
SNIP
JCR
SNIP
JCR
SNIP
JCR
SNIP
Select the library membership card:
DRS,
in which the journal is indexed
Database name
Field
Year
Links to authors' personal bibliographies
Links to information on researchers in the SICRIS system
Subject headings in COBISS General List of Subject Headings
Select pickup location
The material from the parent unit is free. If the material is delivered to the pickup location from another unit, the library may charge you for this service.
