ilyasst / processes-modelling

processes-modelling

This repository contains all the codes written to model processes developped at the LIPEC.

In the file requirements.txt, all the required python packages are listed.

Rotary Jet-Spinning

Concept of the process

This process consists in extruding a melt polymer through the orifices of a rotating spinneret due to the centrifugal force. The extruded polymer transforms into a fiber to be collected.

Predict the critical rotational velocity for jet ejection

 

: Critical rotational velocity for jet ejection (RPS)

: Surface tension ()

a : Radius of the orifice (m)

: Radius of the reservoir (m)

: Density ()

Explanation of where this equation comes from

Predict the final radius of the fiber

 

r : Final radius of the fiber (m)

a : Radius of the orifice (m)

U : Initial axial velocity (m/s)

: kinematic viscosity ()

Rc : Radius of the collector (m)

: Angular velocity (RPS)

Explanation of where this equation comes from

Prediction of the effect of several parameters on the final radius.

The following parameters were studied : angular velocity, collector distance, orifice radius, reservoir radius, density, surface tension, viscosity.

Predict the radius of the jet in steady state as a function of the axial coordinate x

 

: Surface tension ()

x : Axial coordinate (m)

: Initial radius of the jet = orifice radius a (m)

U : Initial axial velocity (m/s)

: Density ()

: Viscosity (Pa.s)

: Angular velocity (RPS)

How this code works ?

Classes

• Deck : get the value in deck.yaml
• Polymer : stock the values of deck concerning the polymer in variables that will be reuse
• RJSMachine : stock the values of deck concerning the machine in variables that will be reuse
• RJSModel : contain all equations
• Data : compute the datas for which we want to draw graphics
• Organization : organize the previous data in order to draw graphics
• PointGraph : draw the graphic with the organized data and save it in the folder Graphics

What the user have to do ?

• Adapt the values of the polymer and machine in the file deck.yaml :

Polymers:
  Name: 'Polypropylene'
  Viscosity: 0.63
  Density: 900
  Surface Tension: 0.0436

Machines:
  Name: 'Super Floss Maxx'
  Orifice Radius: 0.001512
  Collector Radius: 0.3302
  Reservoir Radius: 0.06985
  Angular Velocity : 57.5

Discretisation: 20

The Discretisation number is the number of points on the graphics.

• Install all required python packages listed in requirements.txt:

pip install -r requirements.txt

• The only file which need to be run is the main.py. This script brings together all classes.

python main.py

Viscosity

Compute the viscosity as a function of the temperature and the shear stress

 

: Melt viscosity (Pa.s)

: Shear stress

: activation energy of viscous-elastic flow under condition of = constant

R : gas constant in J/(mol.K)

T : temperature of experiment in K

B, b, s : Constants of the material (in this case : s=1/2)

How this code works ?

Classes

• Deck : get the value in viscosity.yaml
• Polymer : stock the values of deck concerning the polymer in variables that will be reuse
• Model : contain the equation to predict the viscosity
• Graph : calculate the data with the model, draw the graphic and save it in the folder Graphics

What the user have to do ?

• Adapt the values in the file viscosity.yaml :

Polymers:
  Name: 'PP Shell'
  Constant B: 1.5
  Constant b: 0.0043
  Activation Energy: 45522

Constants:
  Gas Constant: 8.314

Discretisation: 20

The Discretisation number is the number of points on the graphics.

• Install all required python packages listed in requirements.txt:

pip install -r requirements.txt

• The only file which need to be run is the main_viscosity.py. This script brings together all classes.

python main_viscosity.py