Mechanical Characterization of the Elastoplastic Response of a C11000-H2 Copper Sheet.

This work presents an elastoplastic characterization of a rolled C11000-H2 99.90% pure copper sheet considering the orthotropic non-associated Hill-48 criterion together with a modified Voce hardening law. One of the main features of this material is the necking formation at small strains levels causing the early development of non-homogeneous stress and strain patterns in the tested samples. Due to this fact, a robust inverse calibration approach, based on an experimental-analytical-numerical iterative predictor-corrector methodology, is proposed to obtain the constitutive material parameters. This fitting procedure, which uses tensile test measurements where the strains are obtained via digital image correlation (DIC), consists of three steps aimed at, respectively, determining (a) the parameters of the hardening model, (b) a first prediction of the Hill-48 parameters based on the Lankford coefficients and, (c) corrected parameters of the yield and flow potential functions that minimize the experimental-numerical error of the material response. Finally, this study shows that the mechanical characterization carried out in this context is capable of adequately predicting the behavior of the material in the bulge test.

Effect of orthopedic implants on canine long bone compression stiffness: a combined experimental and computational approach.

Osteosynthesis for canine long bones is a complex process requiring knowledge of biology, surgical techniques and (bio)mechanical principles. Subject-specific finite element analysis constitutes a promising tool to evaluate the effect of surgical intervention on the global properties of a bone-implant construct, but suffers from a lack of validation. In this study, the biomechanical behavior of 10 canine humeri was compared before and after creation of a 10 mm bone defect stabilized with an eight-hole locking compression plate (Synthes®) and two locking screws on each fragment. The response under compression of both intact and plated samples was measured experimentally and reproduced with a finite element model. The experimental stiffness ratio between plated and intact bone was equal to 0.39 ± 0.06. A subject-specific finite element analysis including density-dependent elasto-plastic material properties for canine bone and automatic generation of orthopedic implants was then conducted to recover these experimental results. The stiffness of intact and plated samples could be predicted, with no significant differences with experimental data. The simulated stiffness ratio between plated and intact canine bone was equal to 0.43 ± 0.03. This study constitutes a first step toward the building of a virtual database of pre-computed cases, aiming at helping the veterinary surgeons to make decisions regarding the most suited orthopedic solution for a given dog and a given fracture.

Prediction of the mechanical response of canine humerus to three-point bending using subject-specific finite element modelling.

Subject-specific finite element models could improve decision making in canine long-bone fracture repair. However, it preliminary requires that finite element models predicting the mechanical response of canine long bone are proposed and validated. We present here a combined experimental-numerical approach to test the ability of subject-specific finite element models to predict the bending response of seven pairs of canine humeri directly from medical images. Our results show that bending stiffness and yield load are predicted with a mean absolute error of 10.1% (±5.2%) for the 14 samples. This study constitutes a basis for the forthcoming optimization of canine long-bone fracture repair.

Generating smooth surface meshes from multi-region medical images.

Thanks to advances in medical imaging technologies and numerical methods, patient-specific modelling is more and more used to improve diagnosis and to estimate the outcome of surgical interventions. It requires the extraction of the domain of interest from the medical scans of the patient, as well as the discretisation of this geometry. However, extracting smooth multi-material meshes that conform to the tissue boundaries described in the segmented image is still an active field of research. We propose to solve this issue by combining an implicit surface reconstruction method with a multi-region mesh extraction scheme. The surface reconstruction algorithm is based on multi-level partition of unity implicit surfaces, which we extended to the multi-material case. The mesh generation algorithm consists in a novel multi-domain version of the marching tetrahedra. It generates multi-region meshes as a set of triangular surface patches consistently joining each other at material junctions. This paper presents this original meshing strategy, starting from boundary points extraction from the segmented data to heterogeneous implicit surface definition, multi-region surface triangulation and mesh adaptation. Results indicate that the proposed approach produces smooth and high-quality triangular meshes with a reasonable geometric accuracy. Hence, the proposed method is well suited for subsequent volume mesh generation and finite element simulations.