Model-free Data-Driven viscoelasticity in the frequency domain

@article{Salahshoor2022ModelfreeDV,
  title={Model-free Data-Driven viscoelasticity in the frequency domain},
  author={Hossein Salahshoor and Magdalena Ortiz},
  journal={Computer Methods in Applied Mechanics and Engineering},
  year={2022}
}

Figures from this paper

Data-driven numerical site response

of the application of multiscale its capacity to wave propagation problems using discrete datasets, obtained via sampling grain ensembles using the discrete element method (DEM), in lieu of a

A model-free Data-Driven paradigm for in situ patient-specific prediction of human brain response to ultrasound stimulation

A new model-free Data-Driven framework that directly incorporates patient-specific data on-the-fly into calculations of wave patterns in the brain resulting from harmonic transcranial stimulation is developed.

Automated identification of linear viscoelastic constitutive laws with EUCLID

EUCLID, a computational strategy for automated material model discovery and identification, is extended to linear viscoelasticity and shown to accurately identify a linear visCOelastic model out of a library with several hundreds of terms spanning relaxation times across seven orders of magnitude.

References

SHOWING 1-10 OF 19 REFERENCES

Model-Free Data-Driven Inelasticity

Nanoindentation and the dynamic characterization of viscoelastic solids

Using a high-damping thermoplastic as a standard reference material, the purpose of this work is to compare measured values of the complex modulus as determined by dynamic nanoindentation and dynamic

Measuring the constitutive behavior of viscoelastic solids in the time and frequency domain using flat punch nanoindentation

The purpose of this work is to further develop experimental methodologies using flat punch nanoindentation to measure the constitutive behavior of viscoelastic solids in the frequency and time

Data-Driven Problems in Elasticity

We consider a new class of problems in elasticity, referred to as Data-Driven problems, defined on the space of strain-stress field pairs, or phase space. The problem consists of minimizing the

Magnetic Resonance Measurement of Transient Shear Wave Propagation in a Viscoelastic Gel Cylinder.

Improved relaxation time coverage in ramp-strain histories

A simple if (not) obvious method to extend the range of relaxation data that can be acquired from a single test at a single temperature and draws on new computational developments for inverting ill-conditioned systems of equations which allows the determination of relaxation parameters nearly routinely and trouble-free.

Learning viscoelasticity models from indirect data using deep neural networks

Data-driven computational mechanics

Material characterization of the brainstem from oscillatory shear tests.

Magnetic resonance elastography by direct visualization of propagating acoustic strain waves.

The results indicate that displacement patterns corresponding to cyclic displacements smaller than 200 nanometers can be measured and suggest the feasibility of a medical imaging technique for delineating elasticity and other mechanical properties of tissue.