Fatigue behaviour and S-N curve prediction of additively manufactured Inconel 718 using Self-Heating and Energy-Based methods

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F25%3A00382306" target="_blank" >RIV/68407700:21220/25:00382306 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/49777513:23210/25:43975841

Výsledek na webu

<a href="https://doi.org/10.1016/j.engfailanal.2025.109507" target="_blank" >https://doi.org/10.1016/j.engfailanal.2025.109507</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.engfailanal.2025.109507" target="_blank" >10.1016/j.engfailanal.2025.109507</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Fatigue behaviour and S-N curve prediction of additively manufactured Inconel 718 using Self-Heating and Energy-Based methods

Popis výsledku v původním jazyce

Inconel 718, a nickel-based superalloy, is extensively used in high-performance applications such as gas turbines, aerospace, and the nuclear and oil industries due to its exceptional fatigue resistance, corrosion resistance, and mechanical stability across a broad temperature range (-252 °C to over 700 °C). Its weldability and high-strength properties make it suitable for additive manufacturing (AM), particularly laser powder bed fusion (L-PBF). However, the dynamic properties of AM Inconel 718, influenced by surface roughness and microstructural variations, require thorough investigation. This study evaluates the mechanical properties of AM Inconel 718 in two build orientations produced using an EOS M290 printer. Static tests and hardness measurements were conducted to establish baseline properties. The fatigue behaviour was analysed using traditional S-N curve testing alongside a self-heating (S-H) methodology adapted from previous studies on AMed AlSi10Mg. The S-H method, focusing on temperature evolution during cyclic loading, was used to estimate the fatigue limit (FL) and S-N curve predictions. The LinExp method provided slightly conservative FL estimates, which served as lower thresholds for Fargione’s energy-based S-N curve model. Only two specimens per orientation were used, demonstrating its efficiency and resource-saving potential. This work underscores the viability of integrating innovative fatigue analysis techniques with traditional methods to optimize the design and evaluation of additively manufactured components.

Název v anglickém jazyce

Fatigue behaviour and S-N curve prediction of additively manufactured Inconel 718 using Self-Heating and Energy-Based methods

Popis výsledku anglicky

Inconel 718, a nickel-based superalloy, is extensively used in high-performance applications such as gas turbines, aerospace, and the nuclear and oil industries due to its exceptional fatigue resistance, corrosion resistance, and mechanical stability across a broad temperature range (-252 °C to over 700 °C). Its weldability and high-strength properties make it suitable for additive manufacturing (AM), particularly laser powder bed fusion (L-PBF). However, the dynamic properties of AM Inconel 718, influenced by surface roughness and microstructural variations, require thorough investigation. This study evaluates the mechanical properties of AM Inconel 718 in two build orientations produced using an EOS M290 printer. Static tests and hardness measurements were conducted to establish baseline properties. The fatigue behaviour was analysed using traditional S-N curve testing alongside a self-heating (S-H) methodology adapted from previous studies on AMed AlSi10Mg. The S-H method, focusing on temperature evolution during cyclic loading, was used to estimate the fatigue limit (FL) and S-N curve predictions. The LinExp method provided slightly conservative FL estimates, which served as lower thresholds for Fargione’s energy-based S-N curve model. Only two specimens per orientation were used, demonstrating its efficiency and resource-saving potential. This work underscores the viability of integrating innovative fatigue analysis techniques with traditional methods to optimize the design and evaluation of additively manufactured components.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20302 - Applied mechanics

Projekt

<a href="/cs/project/LUABA22071" target="_blank" >LUABA22071: Odhad únavové životnosti z teplotního měření aditivně vyrobených vzorků s použitím umělé inteligence za účelem snížení nákladů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Engineering Failure Analysis

ISSN

1350-6307

e-ISSN

1873-1961

Svazek periodika

174

Číslo periodika v rámci svazku

June

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

18

Strana od-do

1-18

Kód UT WoS článku

001445365600001

EID výsledku v databázi Scopus

2-s2.0-86000588983