A machine learning based approach with an augmented dataset for fatigue life prediction of additively manufactured Ti-6Al-4V samples
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00010669%3A_____%2F23%3AN0000016" target="_blank" >RIV/00010669:_____/23:N0000016 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0013794423006677?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0013794423006677?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.engfracmech.2023.109709" target="_blank" >10.1016/j.engfracmech.2023.109709</a>
Alternative languages
Result language
angličtina
Original language name
A machine learning based approach with an augmented dataset for fatigue life prediction of additively manufactured Ti-6Al-4V samples
Original language description
The article deals with the prediction of fatigue life using a machine learning (ML) approach. The original dataset is based on the parameters of defects obtained by micro-computed tomography (μ-CT) prior to fatigue tests, stress level and the fatigue life of additively manufactured (AM) Ti-6Al-4V samples. As the original dataset is considered too small to train a comprehensive ML model, the study proposed a novel approach for dataset augmentation. Dataset augmentation is done using inverse transform sampling and multivariate radial basis function (RBF) interpolation with various values of the smoothing parameter. Finally, ML model accuracy is improved up to 0.953 of coefficient of determination.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
20304 - Aerospace engineering
Result continuities
Project
—
Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Engineering Fracture Mechanics
ISSN
0013-7944
e-ISSN
1873-7315
Volume of the periodical
293
Issue of the periodical within the volume
12/2023
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
19
Pages from-to
—
UT code for WoS article
001112329800001
EID of the result in the Scopus database
2-s2.0-85176265491