Modelling and Simulation of Soft Robotic Human Tongue with Improved Motion

There is a huge demand for electronic tongues in the food and pharmaceutical industries for chemical detection and flavor analysis. The lack of availability of robots with electronic tongues has motivated us to investigate, design and simulate a human tongue's complex motions. Human anatomy was studied in detail to modify the standard design of the human tongue, with the addition of embedded chambers at strategic locations, to replicate various 3D motions (rolling, groove, twist, and elongation) of the human tongue necessary for improving the bio-chemical sensing capabilities. The FEM (Finite element method) simulations showed the relation between pressure and deformation range for various kinds of motions in a human tongue, including the mechanical properties from the stress versus strain response.

Floating Wind Turbine Model Test to Verify a MoorDyn Modification for Nonlinear Elastic Materials

As the Floating Offshore Wind industry matures it has become increasingly important for researchers to determine the next generation materials and processes that will allow platforms to be deployed in intermediate (50-85 m) water depths which challenge the efficiency of traditional catenary chain mooring systems and fixed-bottom jacket structures. One such technology, synthetic ropes, have in recent years come to the forefront of this effort. The challenge of designing synthetic rope moorings is the complex nonlinear tension-strain response inherent of some rope material choices. Currently, many numerical tools for modeling the dynamic behavior of FOWTs are limited to mooring materials that have a linear tension- strain response. In this paper an open source FOWT design and analysis program, OpenFAST, was modified to capture the more complex tension-strain responses of synthetic ropes. Simulations from the modified OpenFAST tool were then compared with 1:52-scale test data for a 6MW FOWT Semi- submersible platform in 55m of water subjected to representative design load cases. A strong correlation between the simulations and test data was observed.

Development and Validation of Subject-Specific 3D Human Head Models Based on a Nonlinear Visco-Hyperelastic Constitutive Framework

Computational models of the human head are promising tools for the study and prediction of traumatic brain injuries (TBIs). Most available head models are developed using inputs (i.e., head geometry, material properties, and boundary conditions) derived from ex-vivo experiments on cadavers or animals and employ linear viscoelasticity (LVE)-based constitutive models, which leads to high uncertainty and poor accuracy in capturing the nonlinear response of brain tissue under impulsive loading conditions. To resolve these issues, a framework for the development of fully subject-specific 3D human head models is proposed, in which model inputs are derived from the same living human subject using a comprehensive in-vivo brain imaging protocol, and the viscous dissipation-based visco-hyperelastic constitutive modeling framework is employed. Specifically, brain tissue material properties are derived from in-vivo magnetic resonance elastography (MRE), and full-field strain-response of brain under rapid rotational acceleration is obtained from tagged MRI, which is used for model validation. The constitutive model comprises the Ogden hyperelastic strain energy density and the Upadhyay-Subhash-Spearot viscous dissipation potential. The simulated strain-response is compared with experimental data and with predictions from subject-specific models employing two commonly used LVE-based constitutive models, using a rigorous validation procedure that evaluates agreement in spatial strain distribution, temporal strain evolution, and differences in maximum values of peak and average strain. Results show that the head model developed in this work reasonably captures 3D brain dynamics, and when compared to LVE-based models, provides improvements in the prediction of peak strains and temporal strain evolution.