Simulating the Spiralling Motion of a Coin on a Table

  • Context: Graduate 
  • Thread starter Thread starter sreenathb
  • Start date Start date
  • Tags Tags
    Effects
Click For Summary
SUMMARY

This discussion focuses on simulating the spiraling motion of a coin on a table using three key equations: the gyroscopic moment equation, the conservation of energy equation, and the general kinematic equation. The user is facing challenges with non-linear equations and seeks numerical methods for approximate solutions. Recommended techniques include the Runge-Kutta method for numerical integration, the Euler method for simpler integration, and gradient-based optimization algorithms like Levenberg-Marquardt and Newton's Method.

PREREQUISITES
  • Understanding of gyroscopic motion and its equations
  • Familiarity with conservation of energy principles
  • Knowledge of kinematic equations
  • Basic programming skills for numerical methods implementation
NEXT STEPS
  • Research the Runge-Kutta method for numerical integration
  • Explore the Euler method for solving differential equations
  • Learn about gradient-based optimization algorithms, specifically Levenberg-Marquardt
  • Investigate Newton's Method for finding roots of non-linear equations
USEFUL FOR

Students and researchers in physics, mathematicians, and software developers interested in simulating dynamic systems and solving non-linear equations.

sreenathb
Messages
10
Reaction score
0
i am trying to simulate the spiralling motion of a coin that is rolled on a table.i am having three equations...
1. the gyroscopic moment equation.
2. the conservation of energy equation.
3. general kinematic equation.

three unknowns...curvature radius,precession velocity and coin inclination.
the equations i am getting are non-linear.can someine suggest me any numerical methods to solve these approximately.
i want those which can be easily programmed.i tried one which uses the jacobian..bit found that the solution was not converging.

anyone please help.
 
Physics news on Phys.org
It sounds like you're trying to solve a difficult problem! Have you tried using numerical integration techniques, such as the Runge-Kutta method? This method is relatively easy to program, and can be used for non-linear equations. You could also look into the Euler method, which is a simpler numerical integration technique. Another option is to try a gradient-based optimization algorithm, such as Levenberg-Marquardt or Newton's Method. These may be able to help you find an approximate solution to your equations. Good luck!
 

Similar threads

  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 20 ·
Replies
20
Views
20K
  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 9 ·
Replies
9
Views
4K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 38 ·
2
Replies
38
Views
4K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 6 ·
Replies
6
Views
6K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K