Prediction of the intramembranous tissue formation during perisprosthetic healing with uncertainties. Part 2. Global clinical healing due to combination of random sources

Ji Yang (1) , Béatrice Faverjon (2, 1) , David Dureisseix (3, 4) , Pascal Swider (5) , Steffen Marburg (6) , Herwig Peters (1) , Nicole Kessissoglou (1)

1 School of Mechanical and Manufacturing Engineering [Sydney]
2 LaMCoS - Laboratoire de Mécanique des Contacts et des Structures [Villeurbanne]
3 SMC - Systèmes Mécaniques et Contacts
4 TMI - Tribologie et Mécanique des Interfaces
5 IMFT - Institut de mécanique des fluides de Toulouse
6 Faculty of Mechanical Engineering, Institute of Vibroacoustics of Vehicles and Machines

This work proposes to examine the variability of the bone tissue healing process in the early period after the implantation surgery. The first part took into account the effect of variability of individual biochemical factors on the solid phase fraction, which is an indicator of the quality of the primary fixation and condition of its long-term behaviour. The next issue, addressed in this second part, is the effect of cumulative sources of uncertainties on the same problem of a canine implant. This paper is concerned with the ability to increase the number of random parameters to assess the coupled influence of those variabilities on the tissue healing. To avoid an excessive increase in the complexity of the numerical modelling and further, to maintain efficiency in computational cost, a collocation-based polynomial chaos expansion approach is implemented. A progressive set of simulations with an increasing number of sources of uncertainty is performed. This information is helpful for future implant design and decision process for the implantation surgical act.

Mots clés: collocation-based polynomial chaos expansion; Implant fixation; Stochastic Model; Combined uncertainties; Collocation-based polyno-mial chaos expansion; Biomechanics

Domaines: Biomécanique [physics.med-ph]; Mécanique des structures [physics.class-ph]

Ji Yang, Béatrice Faverjon, David Dureisseix, Pascal Swider, Steffen Marburg, et al.. Prediction of the intramembranous tissue formation during perisprosthetic healing with uncertainties. Part 2. Global clinical healing due to combination of random sources. Computer Methods in Biomechanics and Biomedical Engineering, 2016, 19 (13), pp.1387-1394. ⟨10.1080/10255842.2016.1143465⟩. ⟨hal-01345511⟩