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A time-integration scheme is said to be stable if there exists an integration time-step > so that for any (,], a finite variation of the state vector at time induces only a non-increasing variation of the state-vector + calculated at a subsequent time +. Assume the time-integration scheme is
In a simulation this may be implemented by using small time steps for the simulation, using a fixed number of constraint-solving steps per time step, or solving constraints until they are met by a specific deviation. When approximating the constraints locally to first order, this is the same as the Gauss–Seidel method.
Snap, [6] or jounce, [2] is the fourth derivative of the position vector with respect to time, or the rate of change of the jerk with respect to time. [4] Equivalently, it is the second derivative of acceleration or the third derivative of velocity, and is defined by any of the following equivalent expressions: = ȷ = = =.
Instantaneous acceleration, meanwhile, is the limit of the average acceleration over an infinitesimal interval of time. In the terms of calculus , instantaneous acceleration is the derivative of the velocity vector with respect to time: a = lim Δ t → 0 Δ v Δ t = d v d t . {\displaystyle \mathbf {a} =\lim _{{\Delta t}\to 0}{\frac {\Delta ...
where is position at step , + / is the velocity, or first derivative of , at step + /, = is the acceleration, or second derivative of , at step , and is the size of each time step. These equations can be expressed in a form that gives velocity at integer steps as well: [ 2 ]
Equation [3] involves the average velocity v + v 0 / 2 . Intuitively, the velocity increases linearly, so the average velocity multiplied by time is the distance traveled while increasing the velocity from v 0 to v, as can be illustrated graphically by plotting velocity against time as a straight line graph. Algebraically, it follows ...
Segment four's time period (constant velocity) varies with distance between the two positions. If this distance is so small that omitting segment four would not suffice, then segments two and six (constant acceleration) could be equally reduced, and the constant velocity limit would not be reached.
Let us now apply Euler's method again with a different step size to generate a second approximation to y(t n+1). We get a second solution, which we label with a (). Take the new step size to be one half of the original step size, and apply two steps of Euler's method. This second solution is presumably more accurate.