Fatigue behaviour and S-N curve prediction of additively manufactured Inconel 718 using Self-Heating and Energy-Based methods
The result's identifiers
Result code in 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>
Alternative codes found
RIV/49777513:23210/25:43975841
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Fatigue behaviour and S-N curve prediction of additively manufactured Inconel 718 using Self-Heating and Energy-Based methods
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20302 - Applied mechanics
Result continuities
Project
<a href="/en/project/LUABA22071" target="_blank" >LUABA22071: Fatigue life estimation from temperature measurements of additively manufactured specimens to decrease costs using the artificial intelligence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Engineering Failure Analysis
ISSN
1350-6307
e-ISSN
1873-1961
Volume of the periodical
174
Issue of the periodical within the volume
June
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
18
Pages from-to
1-18
UT code for WoS article
001445365600001
EID of the result in the Scopus database
2-s2.0-86000588983