Modelling granular and fluid

flows in equipment design

Paul Cleary

Computational Modelling Group

CSIRO Mathematics, Informatics and Statistics

Motivation for modelling

• Particulate flows, particularly in large scale processing equipment, are difficult to measure:

• Opaque and enclosed

• Hostile to instruments and observers

• Hard to see and understand the detailed physical processes occurring.

• This limits and slows the improvement of these processes.

• DEM+SPH are computational tools that allow detailed particle level • DEM+SPH are computational tools that allow detailed particle level prediction of physical processes in these systems

• It is a rapidly developing technology

• Offers powerful insight into the nature of the particulate flows

• Our aim is to develop DEM/SPH to be a principle design and optimisation tool for equipment and processes, giving:

• Significantly faster development

• Cheaper development

• Continuous and step changes in performance

Bond abrasion mill

• Abrasion mill, 300 mm x 300 mm; 4 lifters 10 mm x 10 mm

• 3000 g AG charge, 17 specific size particles

• It is supposed to measure abrasion (damage due to sliding) but actually comminutes particles by direct impact (incremental damage

53 rpm

Collapse of a cube of water in a box

SPH predicts realistic surface wave motion and surface breakup

DEM predictions: information from data

• Transient flow visualisation understanding of flow fundamentals

• Torque and power consumption

• Breakage rates, mill throughput and charge composition

• Collisional and cohesion force distributions

• Energy loss spectra / spatial and frequency distributions (for input

DEM is a tool with which to gain insight into particulate flow processes

• Energy loss spectra / spatial and frequency distributions (for input into population balance models)

• Wear rates and distributions and the interaction of evolving boundary geometry (eg mill liners) and the particle flows

• Dynamic boundary stresses (eg. on lifters and liner plates)

• Segregation and / or mixing rates

• Axial flows rates and residence time distributions

• Sampling statistics and flow rates

Dragline Excavator – large boulder

• Significant lateral movement and disturbance of the bucket from impact with its side and from collisions leading to the rock entering the bucket

Coarse rock: medium distribution + 2 m boulder

Coal Shearer

• Digging of wet cohesive coal from a 4.5 m high coal seam wall

• Fracture of the initial coal

• Flow of sticky coal over the cutting wheel and on the conveyor system for transport from the mine

• Coal particles are 40-80 mm; 200 N breaking force;

• The drum rotates at 29 rpm and translates at 0.267 m/s along the tracks. The conveyer chains carry broken particles away at 1.9 m/s.

Limit 400 N

Two deck banana screen (6g)

• Top deck bed is dense and coherent (not dilated with little saltation)• Clear reduction in finer (blue) material along the top deck• Good flow through to bottom deck and lower chute

Storage and transfer

• Prediction of flow pattern depends on including shape of particles and cohesion

• Predict discharge rates, rat-holing, bridging for hoppers, silos and bins. Scale is the biggest issue

• Transfers: can model down to 5 mm at 5000 tph(14 million particles), predict wear, adhesive growth, flow rate and dynamic blockage

Coal Discharge from a Rail Wagon

• Sloping end walls provide strong resistance to flow. End compartments slower to fully discharge than inner compartments

• Considerable flow between compartments around and through the baffles. Preferential central flow through each door with coal mass retarded at walls.

• In the inner compartments, active regions of rapid coal flow are observed to extend from discharging door up to the coal surface

Double Roller Crusher

97% of the progeny mass resolved

Charge motion in a real worn SAG mill

• 32’ SAG

• Balls 45-125 mm

• Rocks:

• SG 2.7

• 15-140 mm

• Fill

• 16% media

• 12% rock

• Speed 78% critical

• 1.95 million particles

• Laser scanned liner with 800,000 elements in the mill mesh

Effect of particle shape on fluidisation behaviour

Spherical Cuboidal Prolate spheroid Oblate spheroid SQ mix

All cases have equal volume particles, except SQ mix which are doubled

Equivalent spherical diameter = 4 mm

Mixing

• Multiple ways of quantifying mixing rate and degree of mixing

• Identify dead regions• Identify dead regions

• Optimise agitator design and feed/discharge

Mixing of viscous liquids

Mixing of viscous liquids

• Re = 37

• 1 mm resolution

• 1.5 million particles

Screw elements are good for transport but not for mixing

Kneading elements are good at mixing

Mixing of particulates in fluid

Impeller speed 200 rpm

Solids loading 1.5 kg

Tank diameter 1 m

Particulate diameter = 16 mm

Particulate length = 25 mm

SPH fluid fully coupled

At high speed the recirculatory flow in the mixing tank is able to suck down the highly buoyant pellets

Very good agreement with experiment in distribution of solids, submersion critical speed and rate of submergence

SPH fluid fully coupled to particulates

Material Forming Processes

Casting Extrusion

Forging

RTM

Oil rig – 30o oblique rogue wave

• TLP oil platform impacted at 30 degrees by a 34 m rogue wave

• Complex motion including significant pitch (up to 7 degrees, strong surge and some yaw)

3D prediction of ship interacting with waves

USS Cruiser Valley Forge• Length: 173 m• Beam: 16 m• Displacement: 7400 tonnes• Speed: 10 m/s (36 km/h)

Two periodic wave components:

• wavelength 210 m, amplitude 3.4 m and wave speed 15 m/s

• wavelength 140 m, amplitude 2.0 m and wave speed of 14 m/s

Dust pickup from air flow over a heap

• Periodic boundary conditions in gas flow direction

• Dustiness parameter κ = 15%

• Simulation domain dimensions 0.5 x 0.1 x 0.1 m

Open pit collapse

• Slope failure in an open pit can lead to a disastrous landside

• The effects of different failure scenarios can be investigated

St. Francis dam collapse

Fluid nodes = 1.7 million Resolution of topography = 8 m

Total nodes = 2.4 million CPU time = 3 weeks

Fluid resolution = 4 m Distance covered = 8 km

Perth CBD Inundation – SPH

Water is coloured by velocity:

blue 0 m/s and red 15 m/s

A wave of water from the dam break flows along the Swan river and floods the outskirts of the CBD

blue 0 m/s and red 15 m/s

Tsunami inundation of the port of Fremantle

Domain is 2.5 km and the incoming wave is 3 m high and based on a 50 km scale SWE solution