Sentence examples for multimodal viscosity model from inspiring English sources

When concerning the shear rate results, multimodal viscosity model i.e. Farris model, has steep changing near the wall but smooth changing at the center region.

It was found that the multimodal viscosity model representing concrete as a three-phase suspension consisting of cement paste, sand and gravel can accurately simulate the lubrication layer.

In case of multimodal viscosity model, the modified intrinsic viscosity for sand and gravel should be determined for the shear-induced particle migration analysis.

Therefore, in case of multimodal viscosity model, the effects of individual particle shape should be carefully determined in calculating the viscosity.

Thus, through these numerical calculations, it could be noted that among four viscosity models, the multimodal viscosity model can simulate more exactly the lubrication layer, which means that multimodal viscosity model is more suitable to predict the pipe flow of pumped concrete.

Open image in new window Fig. 11 Comparison of the flow rates between the multimodal viscosity model (i.e. Farris model) without considering the particle shape effects and experimental data using a 170 m full scale pumping test.

Basically, Farris (1968) proposed the multimodal suspension viscosity model using a constant intrinsic viscosity value, i.e. 2.5, for representing the spherical particles case.

Open image in new window Fig. 8 Comparison of the normalized velocity profile along the radius between numerical simulation results using the multimodal suspension viscosity model (i.e. Farris model) and experimentally measured velocity profile using UVP.

The first unimodal viscosity model is Liu model (Liu 2000).

(a) Low viscosity model in the lower crust.

However, for higher producing rates, the constant viscosity model generally estimates higher temperatures than does the rigorous (variable viscosity) model.