Tim Donohue - Tunra Bulk Solids Handling Research Associates

Dust Control Strategies for Transfer Chute Design

(STREAM: New Developments and Equipment for Dust Prevention & Management)

Dr Tim DonohueEngineering ManagerTUNRA Bulk Solidsin association with

The Centre for Bulk Solids & Particulate TechnologiesThe University of Newcastle

[email protected](02) 4033 9031

mailto:[email protected]

Agenda 2

• Characterisation techniques for evaluating the dustiness of the product • Design strategies for optimal chute design • Analysis techniques for dust evaluation of transfer chutes • Case Studies

About TUNRA Bulk SolidsA University of Newcastle fully owned not-for-profit organisation

• Largest independent bulk materials handling research and consultancy organisation in Australia

• Facilitator of industry consultancy and research since 1975

• Areas of specialist expertise include• Bulk Materials Handling Characterisation• Conceptual Design of Storage and Transfer Equipment• Materials Handling Troubleshooting• Physical and Computational Modeling• Belt Conveying• Hydraulic & Pneumatic Conveying

• > 250 projects per year are completed across all mining commodities

Introduction

• Controlling dust is important from both a health and safety point of view as well as environmental• In Newcastle, dust from the coal terminal and rail corridor is always contentious due to proximity to the city (http://www.chiefscientist.nsw.gov.au/__data/assets/pdf_file/0008/89864/160805-FINAL-Coal-Dust-Report.pdf)• Dust control measures can be classed as active or passive controls

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http://www.chiefscientist.nsw.gov.au/__data/assets/pdf_file/0008/89864/160805-FINAL-Coal-Dust-Report.pdf

Introduction

• To control dust, active measures are normally taken• Active measures are classed as those requiring external energy sources such as water for dust suppression or energy costs for extraction fans• Passive systems are those in which dust is minimised (or eliminated) in the design stage• The focus of recent research at TUNRA has been focussed on passive dust control measures

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Characterisation Techniques

• Particle Size Distribution (PSD)• Dust Extinction Moisture (DEM) – recently revised AS4156.6• Wind Tunnel Testing – Flow over stockpiles or rail wagons• Wind Tunnel Testing – measurement of induced air velocity profiles

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Particle Size Distribution

• Can reveal valuable information about dust generation• Generally a material with more fines will be more susceptible to dust generation

• Measurement Techniques;1. Mechanical sieving can be used with sieve sizes

in the range of 100mm to 45µm2. Laser diffraction can be used for smaller powder

like materials (0.1-1000µm)

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Particle Size Distribution 8

CD = drag resistance factorv = particle velocityn = drag index (normally taken as 2)Cd = drag coefficientA = frontal areaρa = air densityd = diameter

• Terminal velocity can be approximated – useful in determining minimum pick-up velocities of particles (in most applications the surrounding velocity is high enough to pick-up small particles)

Dustiness Tester

• Dustiness test covered by AS4156.6-2000• Sample used at predefined moisture content• Drum is rotated at set speed for a set time with a prescribed flow rate draw through

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Dustiness Tester• This test is repeated at a number of different moisture contents, with the Dust Extinction Moisture being defined as the moisture content as having a dust number of 10• This method is most commonly used for stockpiles• The test was recently revised as part of ACARP project C23054 – findings in reference below

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Ilic D, Planner J, Biswas S, Reid S. Revision of AS4156.6 – Coal Preparation – Part 6: Determination of Dust/Moisture Relationship for Coal The 12th International Conference on Bulk Materials Storage, Handling and Transportation (ICBMH 2016), Darwin, NT, Australia, 11 Jul 2016 -14 Jul 2016.

https://nuro.newcastle.edu.au/viewobject.html?id=289214&cid=1

Wind Tunnel Testing

• Used to simulate flow of air across a material surface (conveyor belts, stockpiles)• Generally testing is only performed on -6.3mm particles (targeting particles most likely to lift off)• The sample is weighed before and after the wind tunnel testing to determine mass lost (moisture content is measured again to determine drying out of sample)

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Wind Tunnel Testing

• In these tests, conditions are matched to those on site (moisture content, wind speed, angle of repose)• Different surface veneer treatments can also be studied to evaluate effectiveness

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Wind Tunnel Testing

• Air velocity is induced into a falling material stream – the bulk material reduces it’s bulk density as it falls and more cross-sectional area is taken by air• Upon impact, all of the excess air is exhausted from the bulk material, taking with it dust particles• Velocity profiles are typically difficult to measure –wind tunnels can assist by keeping the bulk material stationary and moving the air stream (reversal of induced air)

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Wind Tunnel Testing 14

Hot wire anemometer

Bed of material

Design Strategies for Optimal Chute Design

• As the following slides illustrate, our transfer chute design can be summarised by two key points;

1. Maintain fast, accelerated flow through the chute that keeps the material stream compact

2. Minimise impact angles and changes in momentum of the flowing material stream

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Analysis Techniques 16

Transfer Chute Dust Control Analysis

Continuum Modelling

DEM Modelling

CFD Modelling

Single Phase

Multi-Phase

Combined CFD-DEM Modelling

Direct Coupling

Indirect Coupling

Modelling dust in handling applications is challenging!

Discrete Element Modelling (DEM)

• Discrete Element Modelling takes place in a ‘vacuum’ –no air flow is present

• Small particles, or ‘dust’, cannot be modelled anyway due to resulting large number of particles

• However, for a first evaluation of the dust emission it is often sufficient to analyse material flow in general

• Generally, it can be said that dust is generated when there is an abrupt change in particle velocity or direction

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Discrete Element Modelling

• An example below shows the application of these principles

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Computational Fluid Dynamics

• CFD is a branch of fluid mechanics that uses numerical methods to solve and analyse problems involving fluid flow

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Picture courtesy STAR CCM+ and Desktop Engineering

Flow Analysis – Indirect CFD-DEM coupling 20

• Very simple approach to consider active dust suppression• 750 tph, 2m head height, 1100mm belt width• Two 400mm vents were used in the study – dust extraction fans


• Granular flow in DEM (left) gives an approximation of the velocity profile (right)• This porosity profile is then used in a single phase porous medium simulation


• Induced air was calculated via simple model –boundary condition imposed in CFD• Large exhaustion of air at the impact zone


• Material stream was simulated first

• Boundary conditions were then imported into secondary simulation for enclosure

• Comparisons for mass flow rates and vent positions can be made


M1 – zero relative pressure opening – dependent on other boundary conditions

M2 – flow induced by falling stream (imposed)

M3 – flow exhausted at impact

M4 – zero relative pressure opening – dependent on other boundary conditions

M5, M6 – specified relative pressure opening, representing an exhaust vent

Flow Analysis – Indirect CFD-DEM coupling

• Results for the airflow when vent 1 has a negative pressure of 50 Pa

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Vent 1 extracting some airflow 1.12 kg/s (mostly from inlet)

Air discharging from enclosure 0.98 kg/s (air from impact zone including dust)

Flow Analysis – Indirect CFD-DEM coupling

• Results for the airflow when vent 2 has a negative pressure of 100 Pa

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Vent 2 extracting all air flow 1.56 kg/s –0.26 kg/s is coming IN the discharge opening


Condition M1 (kg/s) M2 (kg/s) M3 (kg/s) M4 (kg/s) M5 (kg/s) M6 (kg/s)

Vent 1 (no pressure) +0.8 -0.87 +0.95 -0.98 +0.1 N/A

Vent 1 (-50 Pa) +2.03 -0.87 +0.95 -0.98 -1.12 N/A

Vent 2 (no pressure) +0.97 -0.87 +0.95 -0.85 N/A -0.2

Vent 2 (-50 Pa) +1.13 -0.87 +0.95 -0.11 N/A -1.09

Vent 2 (-100 Pa) +1.23 -0.87 +0.95 +0.26 N/A -1.56

Flow Analysis – Direct CFD-DEM Coupling

• Computationally expensive• Fluidisation and pneumatic conveying two main areas of application (Not a lot on transfer chutes)

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C. Goniva, C. Kloss, X. Chen, T.J. Donohue, A. Katterfeld, “Transfer chutes: Predicting dust emissions by multiphase CFD and coupled DEM-CFD simulations”, Bulk Solids Handling, 2014.

Case Study 1 – Iron Ore

• A particularly dusty chute was analysed to reduce its dust generation (sample was -11.2mm Iron Ore)• Scale modelling was undertaken in the lab as well as CFD modelling• Six transfer chute configurations were considered• Dust was monitored in the transfer chute enclosure for each configuration

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Chen XL, Wheeler CA, Donohue TJ, McLean R, Roberts AW. Evaluation of dust emissions from conveyor transfer chutes using experimental and CFD simulation International Journal of Mineral Processing 110-111:101-108 2012 (Journal article)

https://nuro.newcastle.edu.au/viewobject.html?id=21671&cid=1

Case Study – Iron Ore 30

Case Study – Iron Ore

• Dust measurement was done via a plastic drop sheet – all of the dust was collected for each test on one side of the enclosure• For each of the six configurations, 3 tests were carried out for each to get an average result• Particle size distributions were recorded after each test of the dust collected

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• A pitot tube was also used to measure air velocities in the discharge regions of the chutes• Multiple locations were measured for with and without the stilling chamber

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• Chutes A, B and C were similar• D and E are similar and improve on the baseline case• Chute F reduces dust by approximately 95%

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• If we consider only C and D• Chute D had approximately 70% less dust than Chute C• The only difference in these chutes is the streamlining of the material stream• This reduces impact angle and encapsulates the dust into the material stream

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• Illustrating the effect of the impact angle and the tendency of the air surrounding the stream to be induced into the granular flow stream

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• Good comparison between air velocities• Chutes A and B showed the largest discrepancy –due to the flow being more turbulent

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Particle Image Velocimetry (PIV) 37

PIV relies on a planar beam of light - a light sheet -usually from a laser. The laser light sheet illuminates particles entrained in a flow. Pairs of images are captured using a high-speed digital camera. Software then computes how far the particles moved between the two images and a velocity map is generated. Ref: www.dantecdynamics.com


Laser

Enclosure

Transfer Chute

Conveyor Belt

High-Speed Camera

Top View of Enclosure


Laser Camera


PIV Results – Chute A

Air Velocity (m/s)


PIV Results – Chute A CFD Results – Chute A


Chute A

Chute D


Biomass handling facility – heat generation 44

As-built

• Impact velocity of approx. 13 m/s• concentrated impact due to the design/orientation of the chute• impact with 6mm mild steel

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As-built

• impact contour – this shows impact intensity (units of J/s)• calculation based on impact velocities and impact forces• analogous to energy losses

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Converging chute option

• Only change in geometry is chute 14 is replaced with converging chute section

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• Only change in geometry is chute 14 (orange) is replaced with converging chute section• Disperses the material –increases impact zone with chute• Impact velocity range 8-12 m/s• Some material buffering is shown• Questions on more dust or more pellet breakage?

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• Only change in geometry is chute 14 (orange) is replaced with converging chute section• Disperses the material –increases impact zone with chute• Impact velocity range 8-12 m/s• Some material buffering is shown• Questions on more dust or more pellet breakage?

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Comparison – before and after 50

~13m/s ~8-12m/s

QUESTIONS?

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Tim Donohue - Tunra Bulk Solids Handling Research Associates