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The study presented attempts to prove the concept that mechanical changes in the structure of a bone can be predicted for a specific exercise by a subject specific model created from CT data, MRI data, EMG data, and a physiologic FE model. Previous work generated a subject specific FE model of a femur via CT and MRI data as well as created a set of subject specific biomechanical muscle forces that are required to perform a single leg extension exercise. The FE model and muscle forces were implemented into a single leg extension FE code (ABAQUS) along with a specialized bone remodeling UMAT. The UMAT updated the mechanical properties of the femur via a damage-repair bone remodeling algorithm. The single leg extension FE code was verified by applying walking loads to the femur and allowing the system to equilibrate. The results were used to apply the appropriate walking loads to the final FE simulation for the single leg extension exercise. The final FE simulation included applying the single leg extension loads over a one year period and plotting the change in porosity at various regions of the femoral neck. Although only two regions were found to generate valid results, the data seemed counterintuitive to Wolff’s Law which states that bone adaptation is promoted when the material is stressed. The model was successful in creating a subject specific model that is capable of predicting changes in the mechanical properties of bone. However, in order to generate valid FE model results, further understanding of the bone remodeling process and application via a FE model is required.

No / Modern manufacturing involves multiple stages of complex process chains where Finite Element Analysis is frequently used as a simulation method on a discretized mesh to provide an accurate estimation of factors such as stresses, strains, and displacements. The choice of the most suitable element type and density is dependent on the individual manufacturing process or treatment applied at each stage of the process chain. To map between unalike Finite Element meshes, differing in density and/or element type, an Octree spatial index was evaluated as a solution for highly performant mapping. Compared to existing solutions, the Octree spatial index introduces parallelism within index creation and provides a strategy to perform the most complex interpolation technique, Element Shape Function, in a more computationally efficient manner.