Probabilistic finite element analysis of the uncemented total hip replacement

There are many interacting factors affecting the performance of a total hip replacement(THR), such as prosthesis design and material properties, applied loads, surgical approach, femur size and quality, interface conditions etc. All these factors are subject to variation and therefore uncertainties have to be taken into account when designing and analysing the performance of these systems. To address this problem, probabilistic design methods have been developed.A computational probabilistic tool to analyse the performance of an uncemented THR has been developed. Monte Carlo Simulation (MCS) was applied to various models with increasing complexity. In the pilot models, MCS was applied to a simplified finite element model (FE) of an uncemented total hip replacement (UTHR). The implant and bone stiffness, load magnitude and geometry, and implant version angle were included as random variables and a reliable strain-based performance indicator was adopted. The sensitivity results highlighted the bone stiffness, implant version and load magnitude as the most sensitive parameters.The FE model was developed further to include the main muscle forces, and to consider fully bonded and frictional interface conditions. Three proximal femurs and two implants (one with a short and another with a long stem) were analysed. Different boundary conditions were compared, and convergence was improved when the distal portion of the implant was constrained and a frictional interface was employed. This was particularly true when looking at the maximum nodal micromotion. The micromotion results compared well with previous studies, confirming the reliability and accuracy of the probabilistic finite element model (PFEM). Results were often influenced by the bone, suggesting that variability in bone features should be included in any probabilistic analysis of the implanted construct.This study achieved the aim of developing a probabilistic finite element tool for the analysis of finite element models of uncemented hip replacements and forms a good basis for probabilistic models of constructs subject to implant position-related variability

Risk and reliability modelling for multi-vehicle marine domains

It is well-known that autonomous underwater vehicle (AUV) missions are a challenging, high-risk robotics application. With many parallels to Mars rovers, AUV missions involve operating a vehicle in an inherently uncertain environment of which our prior knowledge is often sparse or low-resolution. The lack of an accurate prior, coupled with poor situational awareness and potentially significant sensor noise, presents substantial engineering challenges in navigation, localisation, state estimation and control. When constructing missions and operating AUVs, it is important to consider the risks involved. Stakeholders need to be reassured that risks of vehicle loss or damage have been minimised where possible, and scientists need to be confident that the mission is likely to produce sufficient high-quality data to meet the aims of the deployment. In this paper, we consider the challenges associated with risk analysis methods and representations for multi-vehicle missions, reviewing the relevant literature and proposing a methodology

Risk and reliability modelling for multi-vehicle marine domains

It is well-known that autonomous underwater vehicle (AUV) missions are a challenging, high-risk robotics application. With many parallels to Mars rovers, AUV missions involve operating a vehicle in an inherently uncertain environment of which our prior knowledge is often sparse or low-resolution. The lack of an accurate prior, coupled with poor situational awareness and potentially significant sensor noise, presents substantial engineering challenges in navigation, localisation, state estimation and control. When constructing missions and operating AUVs, it is important to consider the risks involved. Stakeholders need to be reassured that risks of vehicle loss or damage have been minimised where possible, and scientists need to be confident that the mission is likely to produce sufficient high-quality data to meet the aims of the deployment. In this paper, we consider the challenges associated with risk analysis methods and representations for multi-vehicle missions, reviewing the relevant literature and proposing a methodology

Probabilistic analysis of an uncemented total hip replacement

This paper describes the application of probabilistic design methods to the analysis of the behaviour of an uncemented total hip replacement femoral component implanted in a proximal femur. Probabilistic methods allow variations in factors which control the behaviour of the implanted femur (the input parameters) to be taken into account in determining the performance of the construct. Monte Carlo sampling techniques were applied and the performance indicator was the maximum strain in the bone. The random input parameters were the joint load, the angle of the applied load and the material properties of the bone and the implant. Two Monte Carlo based simulations were applied, direct sampling and latin hypercube sampling. The results showed that the convergence of the mean value of the maximum strain improved gradually as a function of the number of simulations and it stabilised around a value of 0.008 after 6,200 simulations. A similar trend was observed for the cumulative distribution function of the output. The strain output was most sensitive to the bone stiffness, followed very closely by the magnitude of the applied load. The application of latin hypercube sampling with 1,000 simulations gave similar results to direct sampling with 10,000 simulations in a much reduced time. The results suggested that the number of simulations and the selection of parameters and models are important for the reliability of both the probability values and the sensitivity analyses

Probabilistic finite element analysis of the uncemented hip replacement-effect of femur characteristics and implant design geometry

In the present study, a probabilistic finite element tool was assessed using an uncemented total hip replacement model. Fully bonded and frictional interfaces were investigated for combinations of three proximal femurs and two implant designs, the Proxima short stem and the IPS hip stem prostheses. The Monte Carlo method was used with two performance indicators: the percentage of bone volume that exceeded specified strain limits and the maximum nodal micromotion. The six degrees of freedom of bone-implant relative position, magnitude of the hip contact force (L), and spatial direction of L were the random variables. The distal portion of the proximal femurs was completely constrained, and some of the main muscle forces acting in the hip were applied. The coefficients of the linear approximation between the random variables and the output were used as the sensitivity values. In all cases, bone-implant position related parameters were the most sensitive parameters. The results varied depending on the femur, the implant design and the interface conditions. Values of maximum nodal micromotion agreed with results from previous studies, confirming the robustness of the implemented computational tool. It was demonstrated that results from a single model study should not be generalised to the entire population of femurs, and that bone variability is an important factor that should be investigated in such analyses