Multi-variable implicit viscosity model for shear-thinning fluids

Accurately modeling the viscosity of shear-thinning elastomer compounds is crucial for optimizing their performance in industrial applications. Classical models (Power Law, Carreau, Cross) cannot directly account for temperature, and when coupled with temperature models (Arrhenius, WLF, VTF), they become mathematically complex and computationally costly for simulations. This study introduces the Multi-Variable Implicit (MVI) viscosity model, derived using machine learning-based symbolic regressi