@ARTICLE{10.21494/ISTE.OP.2019.0437, TITLE={Analyse probabiliste de la tige améliorée Austin-Moore utilisée dans l’arthroplastie totale de la hanche sans ciment compte tenu de l’incertitude de chargement}, AUTHOR={Ghais Kharmanda, }, JOURNAL={Incertitudes et fiabilité des systèmes multiphysiques}, VOLUME={3}, NUMBER={Numéro 2}, YEAR={2020}, URL={https://www.openscience.fr/Analyse-probabiliste-de-la-tige-amelioree-Austin-Moore-utilisee-dans-l}, DOI={10.21494/ISTE.OP.2019.0437}, ISSN={2514-569X}, ABSTRACT={Austin-Moore hemiarthroplasty had been critically utilized for aged patients with femoral neck fractures. However, this implant became no longer favorable when increasing life activity. A multiobjective shape optimization has been integrated to improve its performance. The resulting configuration is called Improved Austin-Moore (IAM) model. Probabilistic analysis is very important when the input data are random, that leads to stochastic results. In this paper, a probabilistic analysis is applied to solid and IAM stems implanted in a proximal femur in order to show their advantages. This way it is possible to control the biomechanical effects of the implanted femur to determine its performance. The applied loads are generated randomly using Monte Carlo Simulations (MCS). MSC sampling technique is applied and the different von-Mises stresses of the layers (bone and metal) are selected as performance indicators. Two simple 2D implant-bone models of the solid and IAM designs are studied with a target reliability index equals to  3 t , which corresponds to a high level of confidence (reliability) 99.87%. The major finding of this article is that the skewness values of all output parameters of the IAM stem are positive which means that the majority of the maximum von-Mises stress values are closer to their minimum values than those associated with the solid stem. In addition, the sensitivity analysis shows that the input parameters for the IAM stem are more effective on the output parameters relative to those associated with the solid stem. The IAM stem shows a high interdependence (correlation) between the input and output parameters when comparing with the solid stem. Since this study is carried out considering loading uncertainty, the geometry can affect the load transfer. Therefore, a correlation study between the input parameters is carried out and showed significant coefficient values for the IAM stem relative to the solid one. The results show that the IAM stem is much more advantageous than the solid stem.}}