Life Assessment of A Parabolic Spring Under Cyclic Stress &amp; Cyclic Strain Loading Using Finite Element Method

Karthik, J.; Chaitanya, K Lakshmi; Sasanka, C. Tara

doi:10.47893/ijmie.2013.1085

Cited by 3 publications

(5 citation statements)

References 2 publications

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“…Gerber mean stress method has predicted the fatigue life of the parabolic leaf spring with extensive high life cycles. Goodman mean stress method is more conservative than Gerber during the fatigue simulation of leaf spring [10]. Compared to Gerber and Goodman, Interpolate mean stress method is the most conservative.…”

Section: Resultsmentioning

confidence: 98%

Fatigue Life Prediction of Leaf Spring through Multi Mean S-N Approach

Kong

Omar²,

Chua

et al. 2014

AMM

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Parabolic leaf spring is a suspension component for heavy vehicles where spring itself experiences repeated cyclic loading under operating condition. Fatigue life of the parabolic leaf spring is vital since the deflection of the spring is large and continuous. To determine the fatigue life of the parabolic leaf spring, material properties input to the design is important. The objective of this study is to predict the fatigue life of a parabolic leaf spring based on two different material grades which are SAE 5160 and SAE 51B60H under constant amplitude loading through various mean stress method. SAE 51B60H is the material with slightly higher carbon, manganese and chromium content compared to material SAE 5160. Chemical composition differences between SAE 5160 and SAE 51B60H have significant effects on the mechanical properties and fatigue life. In this analysis, finite element method together with multi mean curve stress life (S-N) approach has been implemented to estimate the fatigue life of the spring. Goodman, Gerber and Interpolate mean stress correction method were adopted to correct the damage calculation for mean stress. The results show that interpolate and Goodman method predict the fatigue life of the material with higher accuracy. On the other hand, material SAE 51B60H yields higher fatigue life compared to material SAE 5160.

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Section: Resultsmentioning

confidence: 98%

Fatigue Life Prediction of Leaf Spring through Multi Mean S-N Approach

Kong

Omar²,

Chua

et al. 2014

AMM

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“…Non-constant amplitude, proportional loading within the ANSYS Fatigue module uses a "quick counting" technique to substantially reduce runtime and memory. In quick counting, alternating and mean stresses are sorted into bins before partial damage is calculated [9][10][11]. For Stress Life, another available option when conducting a variable amplitude fatigue analysis is the ability to set the value used for infinite life.…”

Section: Simulation Methodsmentioning

confidence: 99%

Implementation of a Fatigue Fracture Approach to Grinding Wheel Wear Using Numerical Simulation

Kurnenkov

Shurygin

Glebov

2022

KEM

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The paper proposes an approach to assessing the grinding wheel wear, which includes the wear of grains and pulling them out of the bond, based on fatigue failure under cyclic loads caused by cutting forces, with a period of the order of microseconds. This approach is implemented on the basis of stress life calculation in the ANSYS Fatigue module using loading data obtained from the numerical simulation of grain-workpiece interaction. The simulation results allows to obtain the grain wear area, the level of bond fatigue fracture and the possibility of self-sharpening of the grinding wheel for a given grain size and operation conditions.

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“…Figure 2 illustrates a flowchart of the research objective. SAE5160 steel (Karthik et al , 2012) was selected for mechanical properties given its high levels of carbon and chromium for spring steel, as listed in Table I. This type of material properties is used considerably in automobile suspension systems in various heavy spring applications, especially for helical coil and leaf springs.…”

Section: Methodsmentioning

confidence: 99%

“…The elastic and plastic parts of the strain life model are considerably modified using the mean stress effect ( σ m ). Therefore, Equation (1) is modified using the Morrow model, as expressed in the following equation (Karthik et al , 2012): …”

Section: Background Of the Studymentioning

confidence: 99%

“…During the design optimisation analysis, these authors reported that accuracy and reliability significantly increase in several characterisations of components, such as weight, size, shape and material properties (Lohse et al , 2015). Karthik et al (2012) reported finite element based on a durability analysis under variable amplitude loadings for a parabolic spring. The results indicated that the Morrow model is sensitive to fatigue-life prediction where the loading is tensile in nature, whereas the Goodman model confirmed that fatigue life is conservative.…”

Section: Introductionmentioning

confidence: 99%

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Reliability-based fatigue life of vehicle spring under random loading

Nya

Abdullah

Singh

2019

IJSI

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Purpose The purpose of this paper is to analyse fatigue-life prediction based on a reliability assessment for coil springs of vehicle suspension systems using different road excitations under random loading. Design/methodology/approach In this study, a reliability assessment was conducted to predict the fatigue life of an automobile coil spring during different road data surfaces. Campus, urban and highway road surfaces were considered to capture fatigue load strain histories using a data acquisition system. Random loadings are applied on top of a coil spring where coil is fixed from down. Fatigue reliability was established as a system of correlated events during the service life to predict the probability of fatigue life using Coffin–Manson, Morrow and Smith–Watson–Topper (SWT) models. Findings Fatigue-life prediction based on a reliability assessment revealed that the Morrow model can predict a safe region of a life data point for the three road surfaces. Highway road data indicated the highest rate of reliability at 0.8 for approximately 1.69 × 105 cycles for the SWT model. Originality/value Reliability assessment of the fatigue life of vehicle coil springs is vital for safe operation. The reliability analysis of a coil spring under random loading excitations can be used for fatigue-life prediction.

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Life Assessment of A Parabolic Spring Under Cyclic Stress & Cyclic Strain Loading Using Finite Element Method

Cited by 3 publications

References 2 publications

Fatigue Life Prediction of Leaf Spring through Multi Mean S-N Approach

Fatigue Life Prediction of Leaf Spring through Multi Mean S-N Approach

Implementation of a Fatigue Fracture Approach to Grinding Wheel Wear Using Numerical Simulation

Reliability-based fatigue life of vehicle spring under random loading

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