PSI - Issue 17

C P Okeke et al. / Procedia Structural Integrity 17 (2019) 589–595

594

C P Okeke et al / Structural Integrity Procedia 00 (2019) 000 – 000

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The experimental fatigue lives of twelve tested specimens obtained are given in table 1. It can be seen that the fatigue life varies from a minimum of 164seconds to a maximum of 548 seconds, with an average of 298 seconds and a standard deviation (StDev) of 105. The scatter in the fatigue life of materials is a known phenomenon – polymers are known to exhibit inter-sample variations due to manufacturing process. This means different specimens of the same material batch will give different stiffness and in turn different fatigue life. The specimen surface condition is also attributed to the variation in fatigue life.

Table 1: Experimental fatigue life

Experimental Fatigue Life

Specimen

1

2

3

4

5

6

7

8

9

10

11

12

Average

StDev

Fatigue Life (s)

318

548

164

276

333

316

350

192

172

308

237

364

298

105

5.2. Simulation results

The numerical fatigue life was predicted using ANSYS software. The S-N curve properties used to calculate fatigue damage is derived from S-N curve shown in fig 5. Table 2 shows results based on initial elastic modulus and tensile modulus for three fatigue life formulations, Steinberg, Narrow band and Wirsching. For initial elastic modulus, the fatigue life predicted by Steinberg method is 38% of the averaged experimental fatigue life, while Narrow band and Wirsching methods give 40% and 52% of the experimental fatigue life. The secant modulus based results are more accurate, the life predicted by Steinberg, Narrow band and Wirsching formulations are 71%, 75% and 99% of the average experimentally measured fatigue life. The significant error in the results of initial elastic modulus clearly reflects the evidence of material non-linearity. It has been shown that the stiffness of PMMA material varies across the stress due to nonlinearity in the stress-strain response. The use of linear elastic model in the material response and fatigue analysis assumes that the material stiffness is constant across the stress or strain. This assumption ultimately leads to error in the out-put results and the magnitude of error can be large depending on the level of stress or strain the material is subjected to.

Figure 5: S-N curve of PMMA - Okeke et al (2018)

Table 2: Numerical fatigue life

Numerical fatigue life

Fatigue life (s) - Initial Elastic Modulus

Fatigue life (s) - Secant Modulus

Method

Steinberg

112 118 155

212 223 294

Narrow Band

Wirsching