2021
DOI: 10.1177/0954409720986667
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Fatigue life prediction for locomotive bogie frames using virtual prototype technique

Abstract: Current research papers use simulated load spectrums to assess bogie frames’ fatigue life but seldom consider traction and braking loads. Traction and braking loads play important roles in predicting fatigue life in high-speed and heavy haul operational scenarios. Hence, there is a research gap in terms of the consideration of longitudinal load spectrums while assessing bogie frames’ fatigue life. This paper presents research about this topic. A virtual prototype technique available in literature has been exte… Show more

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Cited by 11 publications
(7 citation statements)
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“…These forces result in a bending moment. Similar conclusions were drawn in other studies as well [23,24]. The experimental testing device depicted in Figure 3 was created to assess the fatigue properties of the structural material.…”
Section: Introductionsupporting
confidence: 52%
“…These forces result in a bending moment. Similar conclusions were drawn in other studies as well [23,24]. The experimental testing device depicted in Figure 3 was created to assess the fatigue properties of the structural material.…”
Section: Introductionsupporting
confidence: 52%
“…During the normal operation of the train, because the antenna baffle is fixed at one end and free at the other, it is subjected to four different forces, which are inertia force, wind resistance, gravity, and vibration force caused by an uneven roadbed [ 33 , 34 ]. Since PUR has the characteristics of high hardness, good strength, high elasticity, and high wear and tear resistance, these four forces will not affect the use of the baffle under normal circumstances.…”
Section: Comprehensive Analysismentioning
confidence: 99%
“…Therefore, scholars have carried out in-depth research on structural fatigue life prediction. Considering the load spectrum, temperature, material, defects and energy laws, a reasonable linear or nonlinear fatigue cumulative damage model is established (Liu and Ma, 2023), such as Wang H (Wang et al ., 2021), Hang L (Li et al ., 2022) and Ruixian X (Xiu et al ., 2021). They all have established a new fatigue life prediction model in combination with various influencing factors.…”
Section: Introductionmentioning
confidence: 99%