2022
DOI: 10.3390/met12020339
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Fatigue Life and Reliability of Steel Castings through Integrated Simulations and Experiments

Abstract: The quality and performance of steel castings is always a concern due to porosities formed during solidification of the melt. Nowadays, computational tools are playing a pivotal role in analyzing such defects, followed by their minimization through mold design optimization. Even if the castings are produced with defects in a permissible range, it is important to examine their service life and performance with those defects in a virtual domain using simulation software. This paper aims to develop a methodology … Show more

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Cited by 3 publications
(2 citation statements)
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“…It is a common research method to analyze the force on machine parts by software simulation. Some researchers compared the simulation results of fatigue analysis software or finite element software with experimental results [38,39]. It is proven that software simulation tools can quickly obtain the stress and fatigue life results of components, which have certain reference significance.…”
Section: Fatigue Failure Mode Analysis Of Gears and Fatigue Life Curv...mentioning
confidence: 99%
“…It is a common research method to analyze the force on machine parts by software simulation. Some researchers compared the simulation results of fatigue analysis software or finite element software with experimental results [38,39]. It is proven that software simulation tools can quickly obtain the stress and fatigue life results of components, which have certain reference significance.…”
Section: Fatigue Failure Mode Analysis Of Gears and Fatigue Life Curv...mentioning
confidence: 99%
“…Computational tools can play an important role in optimization problems. The paper by Khan et al [5] presents a simulation-based optimization methodology for mold design and the prediction of reliability in mechanical components with minimum level of casting defects. The reliability was computed using classical strength-stress models and probability distribution functions.…”
Section: Contributionsmentioning
confidence: 99%