1 citations · 2 across the 3 of their papers we have counts for
3 papers
Direct inference of viscoelastic memory from chirp rheometry via physics-informed Gaussian processes
Isaac Y. Miranda-Valdez, Juha Koivisto, Mikko J. Alava
Soft materials remember their deformation history, and identifying that memory from experiments is essential for predicting how these materials behave under real-world loading cond…
Bayesian optimization to infer parameters in viscoelasticity
Isaac Y. Miranda-Valdez, Tero Mäkinen, Juha Koivisto +1
Inferring viscoelasticity parameters is a key challenge that often leads to non-unique solutions when fitting rheological data. In this context, we propose a machine learning appro…
pyRheo: An open-source Python package for complex rheology
Isaac Y. Miranda-Valdez, Aaro Niinistö, Tero Mäkinen +3
Mathematical modeling is a powerful tool in rheology, and we present pyRheo, an open-source package for Python designed to streamline the analysis of creep, stress relaxation, osci…