3.2.1. Thompson et al. (2001) “Investigation of Rigid-Roll Coating”¶
Thompson, H.M., Kapur, N., Gaskell, P.H., Summers, J.L. and Abbott, S.J. “A theoretical and experimental investigation of reservoir-fed rigid-roll coating”, Chemical Engineering Science, vol 56, 2001.
3.2.1.1. Abstract¶
A variant of reverse roll coating is studied via:
Experimental
Analytical (lubrication)
Computational (finite element)
Experimental results:
Flow rate and wetting line position over range of roll speed ratios and capillary numbers
Provided the wetting line is sufficiently far from the nib, the flow rate depends linearly on reservoir level
What is unique about this study:
Variation of dynamic contact angle with metering roll speed has been accounted for
Lubrication model boundary conditions:
Free surface
Surface tension
Wetting line effects
Physics:
The effect of gravity is influential
Flow in the reservoir is recirculating in nature
The size and number of recirculations depends on reservoir geometry
Good agreement between models and experimental data
3.2.1.2. Introduction¶
Rigid-roll coating systems operating in reverse mode are used for applying thin liquid films, in the production of:
Magnetic media
Adhesive tapes
Films
Foils
Types of rigid-roll coating systems:
Pan-fed
Direct-fed
Physics:
Flow in the positive metering gap between the co-rotating applicator and metering rolls plays a crucial role in determining the final wet film thickness transferred to the substrate
Discrepancy between FE model and experiment:
Neglect of gravity
Absence of dynamic wetting line
Discrepancy between lubrication model and experiment:
At high speed ratio and capillary number
Importance of the position of the dynamic wetting line relative to the nip - w.r.t onset of cascade instability
Other effects:
Effect of feed condition on the flow structure
Direct-fed reverse roll coating is investigated. The web thickness is determined by:
Competition between metering action of the reverse roll configuration
Influence of gravity in the form of hydrostatic head provided by the reservoir
3.2.1.2.1. Aim of this paper¶
Quantify the effect of the reservoir on:
The coated film thickness
Dynamic wetting line position
3.2.1.3. Experimental Method¶
A rig was designed to:
Retain the important features of the industrial model
Be flexible in operation
Allow optical access
Conditions:
Large bank of liquid ensured that ambient temperature changes did not affect liquid properties
0.5kg weight was applied to the hosing of the tank to seat it on the rolls
Doctor blade used to remove any residue
Fluid:
Newtonian mineral oil
Surface tension measured with a torsion balance
Viscosity measured with a viscometer
Density measured by measuring the mass of a known volume of fluid
Visualisation:
Liquid illuminated
Illumination of nip region achieved using a mirror
Flow patterns recorded on a video system via a microscope and CCD camera
3.2.1.3.1. Flux and wetting line location measurements¶
Non-contacting methods for measuring film thickness:
Infra-red absorption
Microwave absorption
X-ray fluorescence
Capacitance probes
Problem with non-contacting methods:
Not possible to deduce an exact flux due to variations in velocity through the film
Solution:
Web was scraped clean of liquid using a twin scraper blade
A mass of liquid was collected over a known time interval, hence flux determined
Wetting line:
Position of wetting line measured using microscope fitted with a cross hair graticule
3.2.1.3.2. Flow visualisation¶
Purpose:
Highlight flow patterns near dynamic wetting line
Show how the flow patterns depend on operating parameters
Hydrogen bubble technique impractical due to:
buoyancy effects
long residence times
difficulty of constraining a bubble stream to a narrow planar section
Used dye injection method instead (a laser was not needed)
Flow in reservoir was visualised by:
discharging dye continuously by traversing flow field at stagnation points
dye was not confined to a single streamline
Flow in nip region was visualised by:
releasing a pulse of tracer liquid onto metering roll just upstream of dynamic wetting line
3.2.1.4. Mathematical Models¶
Assumptions:
Isothermal
2D
Newtonian
Incompressible
Governed by the Navier Stokes Equations
Two approaches:
Lubrication model:
A new approach - where variation of contact angle will roll speed is predicted rather than prescribed
Numerical model:
Finite element method for full non-linear problem
Algebraic mesh generation algorithm
3.2.1.4.1. Lubrication Analysis¶
Assumptions:
Uni-directional
Away from free surface
One-dimensional
Physics:
Used non-dimensional scaling
In the past the influence of wetting lines has been ignored in previous free surface models
Lubrication theory is inapplicable in the vicinity of the downstream free surface and the solution domain is terminated by introducing appropriate boundary conditions
3.2.1.4.1.1. Boundary Conditions¶
At the free surface, the pressure is equal to the capillary pressure due to surface tension
We assume that the free surface forms an arc of a circle, so it is a function of the dynamic wetting line angle
Previous studies didn’t model the idea that the dynamic wetting line angle varies with metered roll speed, however the nature of the flow near the dynamic wetting line is still a matter of debate
The variation is accounted for using a hydrodynamic asymptotic model for wetting
The asymptotic model is based on the assumption that the free surface is planar near the wetting line and requires the velocity of the fluid in the liquid-gas interface to be a function of the dynamic wetting line angle
A calibration procedure is adopted in order to estimate the variables in the above in terms of a single adjustable parameter - the interfacial thickness. Further experimental data is needed to verify the accuracy of the estimates for the parameters
The calibration results in two equations in terms of Bond Number (which measures the relative importance of gravitational to surface tension force) and Capillary Number
A third equation is derived to relate the flux to the radius of curvature of the meniscus at the wetting line
Newtonian iteration is used to solve the three equations
Limitation:
Lubrication theory is inapplicable near the meniscus where the flow is 2D and often recirculating
This requires fully non-linear 2D finite element simulation
3.2.1.4.2. Finite Element Solutions¶
Flow in the reservoir is solved using FE method (due to it’s topological flexibility)
Models:
Extends from top of the reservoir into the nip region
Extends from the nip region to the downstream free surface
Solution method:
The governing equations are non-dimensionalised w.r.t. velocity, length and pressure
Solved using Bubnov-Galerkin weighted residual FE formulation
Problems:
Obtaining FE solutions in the reservoir region is straightforward since the geometry is fixed.
Flow in the downstream region is more complex because of the existence of the meniscus and the associated wetting line
Downstream Model
Solution to boundary conditions for downstream model:
Boundary conforming mesh based on spine approach
Conditions at the wetting line are controversial
Solution:
Dynamic wetting angle is predicted and fluid is allowed to slip on the roll surface for those nodes adjacent to the wetting line
Reservoir Model
Velocity profile at nip is the same as that specified in the downstream model
Reservoir surface set to atmospheric pressure
Parabolic velocity profile set at the surface to ensure mass conservation
Solution
Frontal Method
Newton iteration
Leading to second order convergence
Grid refinement was also completed
3.2.1.5. Results¶
Variables of interest:
Flow rate
Wetting line position is useful w.r.t cascade instability when it migrates upstream of the nip
Two experiments:
Peripheral speed of the applicator fixed and metering roll speed varied. Three different reservoir levels. Capillary number fixed, speed ratio varied
Peripheral speed of metering roll fixed and applicator roll speed varied. Capillary number varied and speed ratio varied
In both sets of experiments Bond Number is fixed
Experiment 1
Shows q decreasing as S increases until a critical value is reached, beyond which q increases. This is caused by the wetting line moving upstream of the nip, which increases the effective gap at the meniscus.
Effect of reservoir level depends on position of wetting line w.r.t. nip - i.e. whether it’s upstream or downstream of the nip
Experiment 2
Shows q increases as Ca increases
Wetting line is located downstream of the nip for Ca > 0.2
Validation of model:
q and wetting line position are validated with good agreement
Results also show the sensitivity of the wetting line position to dynamic wetting line angle
Problem we are unable to predict wetting line positions at the higher Ca numbers - possibly due to Bretherton condition Suggesting flow rate insensitive to this condition, whereas wetting line position is more sensitive. Reasoning Circle assumption is not a good representation of the free surface shape for higher Ca numbers - it’s probably more parabolic
Effect of head:
linear dependence between q and head - where wetting line is safely downstream of the nip
Flow inside the reservoir:
Recirculations can cause difficulties for the lubrication model because the rectilinear assumption is violated in such regions
3.2.1.6. Conclusions¶
This is a study of the equilibrium flow in a variant of reverse roll coating, where the metering gap sits beneath a large reservoir
Experimental data shows:
If wetting line is sufficiently far downstream of the nip: flow rate increases linearly with reservoir level
If wetting line is close to the nip: effect of level on flow rate is non-linear and influences the onset of the cascade instability
Hydrodynamic model:
Dynamic contact angle with metering roll speed is incorporated using a hydrodynamic model for wetting.
However, data is lacking for the hydrodynamic model, so a calibration method is proposed, in terms of the interfacial layer thickness.
This interfacial layer thickness is calibrated by matching the prediction against theory for one data point only.
FE solutions can predict accurately:
Flow rate
Wetting line positions (even at high Capillary Numbers)
Lubrication model predicts the flow rate over a range of Capillary Numbers, however:
Wetting line prediction is sensitive to the way the free surface is represented
Free surface profile should be represented by a parabolic rather than a circular arc
But the lubrication prediction demonstrates the benefit of incorporating the effects of free surface, surface tension and the wetting line - especially the ability to predict the flow rate minimum caused by wetting line migration through the nip
Experimental results vs FE solutions show good comparison
Flow in reservoir should not be overlooked - given the possibility of recirculations there