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ARUP; ISBN: 978-0-9562121-5-3 - CMBBE 2012 - Cardiff University

ARUP; ISBN: 978-0-9562121-5-3 - CMBBE 2012 - Cardiff University

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6. THE DETERMINISTIC STRESS ANALYSIS<br />

The validation of the model needs to be done by comparing the stress results from the<br />

deterministic stress analysis with that in the literature since there is not any study in the<br />

literature, to our knowledge, regarding the probabilistic analysis of the knee implant in<br />

which the material properties and loads applied were considered as random variables.<br />

Therefore, a static structural analysis was carried out, and the results have been<br />

compared with the previous studies.<br />

As seen from Fig. 7, the contact area on the UHMWPE is larger compared to that in the<br />

literature, thus the contact stress is less than given in the similar studies. However, the<br />

stress patterns given in Fig. 7 are similar, which can be yielded that the model<br />

developed in this study is valid.<br />

7. THE PROBABILISTIC ANALYSIS<br />

The inherent variability in both material properties and loading affect the performance<br />

of the knee implant. Therefore, the design variables having variations are considered as<br />

random variables. Their statistical properties are determined using statistical methods<br />

based on the experiments. For femur and tibia cortical, the statistical values obtained<br />

from the literature, which are assumed to be lognormal distributed with GPa<br />

and GPa. For trabecular bone, HU values from the CT images were grouped in<br />

30. Then, the Lognormal distribution and statistical values for the rabecular bones of<br />

both the femur and tibia were obtained using MATLAB (Mathworks Inc., Natrick,<br />

USA) statistical toolbox as given in Fig. 8, which results in MPa and<br />

MPa for the femur trabecular bone, and MPa and MPa for the tibia<br />

trabecular bone.<br />

Probabilistic analyses, which utilize simulation methods such as the Monte Carlo or<br />

Importance Sampling, take considerable time. Therefore, some limitations such as<br />

reducing the random variables affecting the model or simplifying the FE models are<br />

common practices in such analyses.<br />

(a) (b)<br />

Figure 8. Distribution of Young’s Modulus of the femur trabecular (a) and tibia<br />

trabecular (b).<br />

7

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