A multispecies1D concentration distribution model for coarse‐particle slurries

Abstract Coarse‐particle (settling) slurry pipelines are key process units in many industries. In Canada's oil sands operations, such pipelines represent hundreds of millions of dollars of infrastructure investment and transport thousands of tonnes of solids every hour. The ability to determine key design/operating parameters of a settling slurry, such as frictional pressure gradient and deposition velocity, is dependent on the accuracy of the concentration distribution model used to determine the local concentration of coarse solids as a function of vertical position within the pipe. Accurate predictions of the concentration profile are also required for physics‐based models of particle‐impact erosion in slurry pipelines. In this study, an improved concentration distribution model was developed. The classic Schmidt‐Rouse turbulent diffusion equation forms the basis for the model. The improvements made here include the use of a more suitable, high‐concentration hindered settling velocity correlation, and a simple semi‐empirical correlation for the particle diffusivity, which is shown to be dependent only upon the terminal particle settling velocity and the Kolmogorov turbulent velocity scale. The model is applicable to slurries with broad size distributions and/or species with different densities. The performance of the model is tested against numerous slurry flow conditions, including particles from 70 μm to 8 mm in diameter, pipe diameters of 76 mm ≤  D ≤ 500 mm, and in situ solids volume concentrations from 0.10 to 0.45. The concentration distribution predictions are shown to be in excellent agreement with the measurements..

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:100

Enthalten in:

The Canadian Journal of Chemical Engineering - 100(2022), 9, Seite 2245-2258

Beteiligte Personen:

Spelay, Ryan B. [VerfasserIn]
Hashemi, Seyed A. [VerfasserIn]
Gillies, Randall G. [VerfasserIn]
Sanders, R. Sean [VerfasserIn]

Anmerkungen:

© 2022 Canadian Society for Chemical Engineering

Umfang:

14

doi:

10.1002/cjce.24504

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

WLY00359016X