Understanding the rheology of kaolinite clay suspensions using Bayesian inference

Mud is a suspension of fine-grained particles (sand, silt, and clay) in water. The interaction clay minerals mud gives rise to complex rheological behaviors, such as yield stress, thixotropy, viscoelasticity. Here, we experimentally examine the flow behaviors kaolinite suspensions, model mud, using steady shear rheometry. curves exhibit both stress hysteresis for various volume fractions ([Formula: see text]). Further understanding these requires fitting existing constitutive models, which challenging due numerous parameters. To this end, employ Bayesian inference method, Markov chain Monte Carlo, fit experimental microstructural viscoelastic model. method allows us estimate properties viscosity, relaxation time scales. comparison inherent scales suggests that suspensions are strongly weakly thixotropic at relatively low [Formula: text], while being almost inelastic purely high text]. Overall, our results provide framework predictive elucidate natural materials other structured fluids.