We introduce a finite-element-model-updating-based open-source framework to identify
mechanical parameters of heterogeneous hyperelastic materials from in silico generated full …

We present a simple open-source semi-intrusive computational method to propagate
uncertainties through hyperelastic models of soft tissues. The proposed method is up to two …

Objective: To present the first a posteriori error-driven adaptive finite element approach for
real-time simulation, and to demonstrate the method on a needle insertion problem …

This contribution discusses Bayesian inference (BI) as an approach to identify parameters in
viscoelasticity. The aims are:(i) to show that the prior has a substantial influence for …

A numerical scheme is proposed for the detection of multiple cracks in three dimensional
(3D) structures. The scheme is based on a variant of the extended finite element method …

Phase-field modeling of fracture has gained popularity within the last decade due to the
flexibility of the related computational framework in simulating three-dimensional arbitrarily …

Errors in biomechanics simulations arise from modelling and discretization. Modelling errors
are due to the choice of the mathematical model whilst discretization errors measure the …

Data Science is today one of the main buzzwords, be it in business, industrial or academic
settings. Machine learning, experimental design, data-driven modelling are all, undoubtedly …

The state of materials and accordingly the properties of structures are changing over the
period of use, which may influence the reliability and quality of the structure during its life …

The identification accuracy of material model parameters is essential for accurately
predicting the deformation behavior of metallic materials (eg, metal forming) using a finite …