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Research Papers: Gas Turbines: Structures and Dynamics

Prediction of Nonlinear Evolution of Fatigue Damage Accumulation From an Energy-Based Model

[+] Author and Article Information
M.-H. Herman Shen

Professor
Fellow ASME
Department of Mechanical and
Aerospace Engineering,
The Ohio State University,
201 W. 19th Avenue,
Columbus, OH 43210
e-mail: shen.1@osu.edu

Sajedur R. Akanda

Department of Mechanical and
Aerospace Engineering,
The Ohio State University,
201 W. 19th Avenue,
Columbus, OH 43210
e-mail: akanda.2@buckeyemail.osu.edu

1Corresponding author.

Contributed by the Structures and Dynamics Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received August 29, 2016; final manuscript received October 8, 2016; published online February 14, 2017. Editor: David Wisler.

J. Eng. Gas Turbines Power 139(7), 072501 (Feb 14, 2017) (8 pages) Paper No: GTP-16-1426; doi: 10.1115/1.4035401 History: Received August 29, 2016; Revised October 08, 2016

An energy-based framework is developed for welded steel and AL6061-T6 for assessment of nonlinear evolution of fatigue damage accumulation along fatigue life. The framework involves interrogation at continuum using a newly developed experimental procedure to determine the cyclic damaging energy to reveal that the accumulated fatigue damage evolves nonlinearly along cycle in case of low cycle fatigue but has somewhat linear relationship with cycle in case of high cycle fatigue. The accumulated fatigue damage is defined as the ratio of the accumulated cyclic damaging energy to the fatigue toughness, a material property and hence remains the same at all applied stress ranges. Based on the experimental data, a model is developed in order to predict cyclic damaging energy history at any applied stress range. The predicted fatigue damage evolution from the energy-based model are found to agree well with the experimental data.

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References

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Figures

Grahic Jump Location
Fig. 1

Cyclic plastic strain-energy dissipation or fatigue damaging energy in a stress control LCF test of (a) welded steel (stress rang is 877.5 MPa) and (b) AL6061-T6 (stress range is 468 MPa). Region 1 indicates initial cyclic softening in (a) and hardening in (b), region 2 indicates fatigue microcrack growthand region 3 indicates macrocrack propagation to final fracture [23].

Grahic Jump Location
Fig. 2

Variation of fatigue strength coefficient KN′ in a stress-control LCF test of (a) welded steel (stress range is 877.5 MPa) and (b) AL6061-T6 (stress range is 468 MPa) along loading cycle N. In case of welded steel, the variation is best approximated by a power-fit in regions 1 and 2, while in case of AL6061-T6 by a linear-fit in region 2 only.

Grahic Jump Location
Fig. 3

(a) Life, Nf in log scale (b) fatigue toughness, Wf (c) average fatigue strain-hardening exponent, n¯′ and (d)averagefatigue strength coefficient, K¯′ as a function of stress range, Δσ for welded steel

Grahic Jump Location
Fig. 4

Functional values of Eq. (12) for different values of β. In each stress range, two solutions of β exist as can be seen in the figure. Among the two solutions, we take the one that is negative. At Δσ  = 719.5 MPa, β has no solution.

Grahic Jump Location
Fig. 5

Experimental and predicted evolution of (a) fatigue damage accumulation and (b) accumulation rate along cycle for welded steel at different applied stress ranges. At stress range 719.5 MPa, no prediction is made.

Grahic Jump Location
Fig. 6

Functional values of Eq. (15) for different values of β (Δσ = 442 MPa). Two solutions of β exist as can be seen in the figure. Among the two solutions, we take the one that is greater than K¯′. In this particular case, K¯′  = 1955.99 MPa, therefore, β = 2148.2 MPa.

Grahic Jump Location
Fig. 7

Experimental and predicted evolution of fatigue damage accumulation along cycle for AL6061-T6 at different applied stress ranges

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