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      Preface

      The various actions taken worldwide in support of sustainable development and greenhouse gas emission control have led to increasingly restrictive regulations. Manufacturers in the automotive field have thus developed innovative mechatronic systems, enabling various vehicle functions to go electric. Confronted with the globalization of exchanges that has generated stronger competition and a surge of new product performances, companies in the sector of embedded mechatronic systems are developing new products at an increasingly faster rate.

      In other domains, to achieve volume or mass reduction or curb energy dissipation, manufacturers of mechatronic systems are developing new assembly methods based on multimaterials (e.g. composite materials, hybrids) or on innovative nanomaterials (e.g. carbon nanotubes). Modeling is essential to reduce product development cost, shrink time to market, understand failure mechanisms occurring in the operating conditions and optimize design before launching production. The reliability-based design optimization (RBDO) method is a modeling approach that optimizes design, guarantees the required high level of performance and takes into account the variability in the manufacturing process as well as the climatic variability in the use conditions. The efficiency of RBDO, however, depends on a solid understanding of the failure mechanisms caused by aging.

Creating a model of a dynamic system often involves developing a simplified model of its behavior based on realistic hypotheses and on the key parameters that are required for its functioning. The dynamic behavior of this modeled system is ruled by partial differential equations (PDEs). The model is then improved by introducing elements or parameters that were not initially included and by improving the set

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