The pervasive use of engineering simulation during the design phase and for virtual testing, thus eliminating the need for multiple prototypes prior to product launch, is well established today.
The continuously growing availability of computing power and simultaneous algorithmic improvements now make high-fidelity numerical resolution of complex problems possible, integrating methodologies that are becoming established procedures in many fields of engineering. Clinical research has benefitted from these advances. Furthermore, the advent of technologies such as big data management, augmented reality, automated computer-aided engineering (CAE) processing in high performance computing (HPC) environments, and additive manufacturing are changing the way healthcare is delivered with implications for the skills required by the next generation of healthcare professionals and academic researchers. The use of numerical simulation to address clinical problems has been consolidated in Europe through several research activities that also involved non-medical institutions specialized in engineering technologies.
This article provides a non-exhaustive overview of some of the latest advances in the adoption of CAE technologies in the medical field by citing some ongoing EU research programs.
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The text provides an in-depth account of Stefano Odorizzi’s journey in founding and growing EnginSoft, our engineering company specializing in computer simulation and modelling. Established in 1984, EnginSoft overcame early challenges, such as the high cost of computing, to emerge as a leader in simulation services, particularly in the fields of mechanical engineering and computational fluid dynamics (CFD). The narrative highlights several key milestones in the company’s history.
cfd metal-process-simulation industry4 news mechanics optimization
CASE STUDY
This paper demonstrates how the biological growth method, studied by Mattheck in the 1990s, can be easily implemented for structural shape optimization finite element method (FEM) analyses using advanced radial basis functions (RBF) mesh morphing.
ansys biomechanics rbf-morph