A literature review points out a large discrepancy in the results of the mechanical tests on dentin that can be explained by stress and strain assessment during the tests. Errors in these assessments during mechanical tests can lead to inaccurate estimation of the mechanical properties of the tested material. On top of that, using the beam theory to analyze the bending test for thick specimens will increase these experimental errors. After summarizing the results of mechanical tests on dentin in the literature, we focus on bending tests and compare the stress assessment obtained by finite element analysis (FEA) and by beam theory application. We show that the difference between the two methods can be quite large in some cases, leading us to prefer the use of FEA to assess stresses. We then propose a new method based on coupling finite element analysis and digital image correlation (DIC) to more accurately evaluate stress distributions, strain distributions and elastic modulus in the case of a three-point bending test. To illustrate and prove the feasibility of the method, it is applied on a dentinal sample so that mean elastic modulus and maximum tensile stress are obtained (11.9 GPa and 143.9 MPa). Note that the main purpose of this study is to focus on the method itself, and not to provide new mechanical values for dentin. When used in standard mechanical testing of dentin, this kind of method should help to narrow the range of obtained mechanical properties values.

This paper deals with the numerical simulation of combined cycle fatigue, which is characterised by two periodic loads, whose frequencies are very different one from the other. Rather than using classical fatigue life estimations, a time transient evolution model is solved using a periodic time-homogenisation method. This latter is based on the assumption that the time scales associated with the two periodic loads are decoupled. Different results on academic as well as industrial examples are presented. An extension of the proposed method up to three time scales is eventually proposed in order to speed up the numerical simulations.

It is well known that the solution of an inverse problem is unstable and not unique. In order to avoid these difficulties when solving such a problem, a Tikhonov’s regularization term is usually added to the norm quantifying the discrepancy between the model’s predictions and experimental data. However, this regularization term is often insufficient to deal with the identification of a spatially variable field of material properties. Here is discussed a general strategy using classical adaptive meshing methods in order to improve the regularization of the inverse problem in such cases. The first step consists in using two distinct meshes: one associated with the discretization of the sought spatial field, and one associated with the resolution of the mere mechanical problems. Then the introduction of usual local error estimators in a second step can drive the refinement of the coarse mesh associated with the sought parameters. This general strategy is then applied to a practical case of study: the detection of subterranean cavities using experimental data obtained by an interferometric device on a satellite.