Reduced Order Granular Intrusion Modeling using RFT

The main features include:
1) Intruder shape input: Image or data points
(a) A random B/W image can be used as an input for intruder shape (use .png formate). Remember to save the images in the current directory
The size of the intruder is entered manually by defining the extreme intruder-endpoints in xand y direction.
(b) Shape discretization can be chosen from a pool of five different options (1/n,n=[1,2,3,4,8]) . The base shape discretization depends on the base image resolution (in pixels).
(c) Additional data points can be for used improving the image processing algorithms' estimate for the intruder shape eg: add [0.008,-0.0125,0.008,-0.0125,0.1,0.1,-.1,-.1] for wheel1.png
(d) In case of algorithms fails to choose the correct outward normal direction, discretize again after pressing the flip-normal button.

2) Two sets of motions can be modeled:
1) Free locomotion (Choice between Explicit & implicit time integration technique)
2) Constrained locomotion (Only Explicit time integration technique)

3) Leading edge hypothesis is set to be always on

4) Macro inertial effects = F=\alpha \rho*A*(Vn)^2 can be switched on as per requirements
wher \alpha is scaling coefficient, \rho is material density, A is subsurface area, Vn is normal velocity of subsurface

5) Animation Pane
Following set of options are available for better visualization
1) Start/Stop animation
2) Changing the force/velocity arrows: Define scaling limits before starting the animation and use the slider to change scale during animation )
3) Changing graph limits: Two modes are available- a) Automatic and 2) Manual. In manual mode only x-axis limits are defined, the y-axis limits are set automatically for maintaining the aspect ratio of the figure.

Please cite our paper: Modeling of the interaction of rigid wheels with dry granular media, Agarwal et al, Journal of Terramechanics (2019) in case you use this app for your research work.