Using physics-informed neural networks to predict the lifetime of laser powder bed fusion processed 316L stainless steel under multiaxial low-cycle fatigue loading

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F26316919%3A_____%2F24%3AN0000010" target="_blank" >RIV/26316919:_____/24:N0000010 - isvavai.cz</a>

Výsledek na webu

<a href="https://www-sciencedirect-com.ezproxy.techlib.cz/science/article/pii/S0142112324004675?via%3Dihub" target="_blank" >https://www-sciencedirect-com.ezproxy.techlib.cz/science/article/pii/S0142112324004675?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ijfatigue.2024.108608" target="_blank" >10.1016/j.ijfatigue.2024.108608</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Using physics-informed neural networks to predict the lifetime of laser powder bed fusion processed 316L stainless steel under multiaxial low-cycle fatigue loading

Popis výsledku v původním jazyce

Axial-torsional Low-Cycle Fatigue (LCF) tests were conducted under strain control on Additively Manufactured (AM) 316L stainless steel using laser powder bed fusion. The tests covered various strain amplitudes tension-compression, proportional, and pure shear loading paths. The AM 316L stainless steel exhibited softening and transgranular cracking under all the investigated loading conditions. The presence of deposition defects, predominantly the lack of fusion type, was identified as the main factor influencing the crack initiation and propagation, as well as the scatter in the fatigue lifetime. Therefore, to account for the damaging of these deposition related defects on fatigue lifetime, a novel physics-informed neural network was proposed. Subsequently, this neural network was combined with the critical plane approach, based on the tensile of failure, in order to predict the lifetime of AM 316L stainless steel. The predicted data exhibited correlation with the experimental results.

Název v anglickém jazyce

Using physics-informed neural networks to predict the lifetime of laser powder bed fusion processed 316L stainless steel under multiaxial low-cycle fatigue loading

Popis výsledku anglicky

Axial-torsional Low-Cycle Fatigue (LCF) tests were conducted under strain control on Additively Manufactured (AM) 316L stainless steel using laser powder bed fusion. The tests covered various strain amplitudes tension-compression, proportional, and pure shear loading paths. The AM 316L stainless steel exhibited softening and transgranular cracking under all the investigated loading conditions. The presence of deposition defects, predominantly the lack of fusion type, was identified as the main factor influencing the crack initiation and propagation, as well as the scatter in the fatigue lifetime. Therefore, to account for the damaging of these deposition related defects on fatigue lifetime, a novel physics-informed neural network was proposed. Subsequently, this neural network was combined with the critical plane approach, based on the tensile of failure, in order to predict the lifetime of AM 316L stainless steel. The predicted data exhibited correlation with the experimental results.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20501 - Materials engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

INTERNATIONAL JOURNAL OF FATIGUE

ISSN

0142-1123

e-ISSN

1879-3452

Svazek periodika

190

Číslo periodika v rámci svazku

JAN 2025

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

14

Strana od-do

nestránkováno

Kód UT WoS článku

001322093600001

EID výsledku v databázi Scopus

2-s2.0-85204448639