Surrogate-model prediction of mechanical response in architected Ti6Al4V cylindrical TPMS metamaterials
author
Rezapourianghahfarokhi, Mansoureh
Khoshbin, Mohammadreza
Schmauder, S.
Hussainova, Irina
statement of authorship
Mansoureh Rezapourian, Ali Cheloee Darabi, Mohammadreza Khoshbin, Siegfried Schmauder, Irina Hussainova
source
Metals
special issue
Application of Machine Learning in Metallic Materials
publisher
MDPI
journal volume number month
vol. 15, 12
year of publication
2025
pages
art. 1372, 24 p. : ill
url
https://doi.org/10.3390/met15121372
subject term
mehaanilised omadused
modelleerimine (teadus)
tehisõpe
nanomaterjalid
lasertehnoloogia
implantaadid
keyword
ANN-based mechanical property prediction
computational modeling
cylindrical Ti6Al4V-based lattice implants
quasi-static compression
surrogate-based approach
triply periodic minimal surface (TPMS)
ISSN
2075-4701
notes
Bibliogr.: 76 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
https://www.scopus.com/sourceid/21100399731
https://www.scopus.com/pages/publications/105025968949?origin=resultslist
WOS
https://jcr.clarivate.com/jcr-jp/journal-profile?journal=METALS-BASEL&year=2024
https://www.webofscience.com/wos/woscc/full-record/WOS:001647074700001
category (general)
Materials science
Materjaliteadus
category (sub)
Materials science. Metals and alloys
Materjaliteadus. Metallid ja sulamid
Materials science. General materials science
Materjaliteadus. Üldine materjaliteadus
TalTech department
mehaanika ja tööstustehnika instituut
Department of Mechanical and Industrial Engineering
language
English
Inglise