This is the standard mass-spring-dashpot model. The general solution may be easily obtained by guessing \(x = e^{rt}\), and particular solutions found by specifying different initial conditions. These demonstrations provide graphs of the solutions for different initial conditions, and an animation showing how the solutions reflect the actual motion of the mass on the spring.
Lecture: The mass-spring-dashpot model can again be presented with little derivation, though some emphasis of the physics behind the different terms may be appropriate in this case. The demonstrations are intended to provide insight into how the solution curves reflect the actual motion of the mass on the spring. The default values for in the demonstration are \(m=1\), \(c=1\) and \(k=8\) (so that \(r = -0.5\pm i\sqrt{7.75}\)).
Outside of Lecture Consider \(m = 1\), \(c = 1\) and \(k = 8\) and solve the initial value problem with \(x(0) = 1\), \(x(0) = 2\),... \(x(0) = 5\) and \(x'(0) = 0\). Check that the solutions you obtain are consistent with the animation and solutions shown in the demonstrations.
This is the standard mass-spring model leading to a second-order linear
constant-coefficient ordinary differential equation. We consider a mass
attached to a spring, as suggested by the figure below.
Here we have labeled the spring with its Hooke's-law constant \(k\), the
mass \(m\), and the floor with a coefficient of friction, \(c\).
We shall also represent this with a circular mass with friction
suggested by a "dashpot," against which the mass assembly rubs, as shown
below.
Let \(x\) be the displacement of the mass from its equilibrium position. Then, assuming a Hooke's-law spring and that the resistance is a viscous damping force, the restoring force of the spring is \(F_s = -k x\) and damping force is \(F_R = -c x'\). Then, applying Newton's law (and assuming no external force on the system), we have \[ m\,x'' = \mbox{sum of forces} = -c\,x' - k\,x, \] or \[ m\,x'' + c\,x' + k\,x = 0. \]
We can obviously solve this easily by taking \(x = e^{rt}\).
As usual, we consider a number of Matlab demos for this:
Some questions that may be worth considering: