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Programming P7, Study notes of Physics

Material Type: Notes; Professor: Parthasarathy; Class: Foundat Physics II; Subject: Physics; University: University of Oregon; Term: Fall 2007;

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Uploaded on 07/22/2009

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Prof. Raghuveer Parthasarathy
University of Oregon; Fall 2007
Physics 351 – Vibrations and
Waves
Programming #P7: Solution
(a) For the exact (analytic) solution:
The general solution x(t) = A sin(ωt - ϕ). The initial x(t=0) = 0, so ϕ = 0. v(t=0) = A ω cos(ωt) = v0, so A = v0/ω.
Therefore the particular solution x(t) = (v0/ω) sin(ωt).
Program listing, with “new” lines in bold:
% verletSHO_P7.m
% SOLUTION to exercise P7 -- modifying SHO model to have a variable timestep
% and also to plot the exact SHO solution
%
% Raghuveer Parthasarathy
% Oct. 5, 2007
clear all
close all
x(1) = 0.0; % initial position, meters
v(1) = 2.0; % initial velocity, m/s
Deltat = input('Enter Deltat (seconds): '); % time increment, s
x(2) = x(1) + v(1)*Deltat; %We’ll explicitly write x(1), even though
% it’s zero here, in case we ever want to change
% our initial conditions. (Otherwise, we might get
% confused!)
k = 0.1; % Newtons / meter
m = 1.0; % kilograms
% for exact solution
% General solution x = A sin(wt - phi)
% Initial x(t=0) = 0, so phi = 0. v(t=0) = Aw cos(wt)=v0, so A = v0/w
ta = 0:0.1:100; % time array, seconds
w = sqrt(k/m); % angular freqency (omega), radians / sec
xa = (v(1) / w)*sin(w*ta);
Tfinal = 100.0; % ending time, seconds
t = 0:Deltat:Tfinal; % an array of all the time values -- starts at 0
N = length(t); % “length” gives the number of elements in an array
for j=3:N;
x(j) = 2*x(j-1) - x(j-2) + Deltat*Deltat*(-1.0*k/m)*x(j-1);
v(j-1) = (x(j) - x(j-2))/ (2*Deltat);
end
v(N) = (x(N)-x(N-1))/Deltat; % Why? Because v(N)
% is not set by the above For loop
figure; plot(t, x, 'ko:'); grid on;
xlabel('Time, sec. ');
ylabel('x, meters')
hold on
plot(ta, xa, 'b-');
pf2

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Prof. Raghuveer Parthasarathy

University of Oregon; Fall 2007

Physics 351 – Vibrations and

Waves

Programming #P7: Solution

(a) For the exact (analytic) solution:

The general solution x(t) = A sin(ωt - ϕ). The initial x(t=0) = 0, so ϕ = 0. v(t=0) = A ω cos(ωt) = v 0 , so A = v 0 /ω. Therefore the particular solution x(t) = (v 0 /ω) sin(ωt).

Program listing, with “new” lines in bold:

% verletSHO_P7.m % SOLUTION to exercise P7 -- modifying SHO model to have a variable timestep % and also to plot the exact SHO solution % % Raghuveer Parthasarathy % Oct. 5, 2007

clear all close all

x(1) = 0.0; % initial position, meters v(1) = 2.0; % initial velocity, m/s Deltat = input('Enter Deltat (seconds): '); % time increment, s x(2) = x(1) + v(1)*Deltat; %We’ll explicitly write x(1), even though % it’s zero here, in case we ever want to change % our initial conditions. (Otherwise, we might get % confused!) k = 0.1; % Newtons / meter m = 1.0; % kilograms

% for exact solution % General solution x = A sin(wt - phi) % Initial x(t=0) = 0, so phi = 0. v(t=0) = Aw cos(wt)=v0, so A = v0/w ta = 0:0.1:100; % time array, seconds w = sqrt(k/m); % angular freqency (omega), radians / sec xa = (v(1) / w)sin(wta);**

Tfinal = 100.0; % ending time, seconds t = 0:Deltat:Tfinal; % an array of all the time values -- starts at 0 N = length(t); % “length” gives the number of elements in an array for j=3:N; x(j) = 2x(j-1) - x(j-2) + DeltatDeltat(-1.0k/m)x(j-1); v(j-1) = (x(j) - x(j-2))/ (2Deltat); end v(N) = (x(N)-x(N-1))/Deltat; % Why? Because v(N) % is not set by the above For loop figure; plot(t, x, 'ko:'); grid on; xlabel('Time, sec. '); ylabel('x, meters') hold on plot(ta, xa, 'b-');

Output (Δt = 0.5 s). We see that the numerical and analytic solutions are very similar.

(b) See above for the program listing with Deltat being a user-input variable.

Output (Δt =3, 6 s).

We see that for larger Δt, the numerical solution is increasingly incorrect. This is because our algorithm, based on a Taylor expansion of x(t), is an increasingly poor approximation to the true “continuous” x(t).

Mr. K. suggests Δt = 0.0001 seconds. He thinks this is a good idea because, as noted above, smaller Δt yields a better approximation to the true x(t). However, it requires lots of calculation time – to model 100 seconds with Δt = 0.0001 seconds requires 10^6 passes through our for-loop, which may be slow.