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#7: Spring Equilibrium: Fall 2020

The document outlines a method for finding equilibrium points of free objects connected by springs, assuming the initial length of each spring is zero. It details the derivation of linear equations for each free object based on their connections to other free and fixed objects, leading to a system of linear equations. The process includes constructing the equations from the x and y directions and utilizing Gaussian elimination to solve for the positions of the free objects in equilibrium.

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0% found this document useful (0 votes)
4 views8 pages

#7: Spring Equilibrium: Fall 2020

The document outlines a method for finding equilibrium points of free objects connected by springs, assuming the initial length of each spring is zero. It details the derivation of linear equations for each free object based on their connections to other free and fixed objects, leading to a system of linear equations. The process includes constructing the equations from the x and y directions and utilizing Gaussian elimination to solve for the positions of the free objects in equilibrium.

Uploaded by

macoyou1
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as PDF, TXT or read online on Scribd
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#7: Spring Equilibrium

Fall 2020
Problem
Given
free objects P1 , P2 , · · · , Pn
fixed objects F1 , F2 , · · · , F`
springs S1 , · · · , Sm with elastic coefficients(탄성계수) w1 , · · · , wm
I each spring connect free/free objects or free/fixed objects
find equilibrium points of each free objects
Simplifying Assumption

Assumption: Initial length of each spring is 0

Then, the forces Fx and Fy are represented simply:


F = w ·∆` (since the initial length is 0)
Fx = F ·cos θ = w ·∆`·cos θ = w ·∆x
Fy = F ·sin θ = w ·∆`·sin θ = w ·∆y
Observations

Let (xi , yi ) be the position of free object Pi in equilibrium


I Thus, there are 2n variables x1 , · · · , xn , y1 , · · · , yn
A pair of linear equations can be derived for each Pi
I x-direction: w4 ·(x1 −x3 ) + w5 ·(x2 −x3 ) + w7 ·(x4 −x3 ) = 0
I y-direction: w4 ·(y1 −y3 ) + w5 ·(y2 −y3 ) + w7 ·(y4 −y3 ) = 0

With these 2n linear equations, we can find the value of 2n


variables x1 , · · · , xn , y1 , · · · , yn
Deriving a pair of equations of each free object

For each free object Pi , let


Ai = the set of indices of adjacent free objects (A1 = {2, 3})
Bi = the set of indices of adjacent fixed objects (B1 = {1})
wik = elastic coefficient of the spring that connects Pi and Pk
wik0 = elastic coefficient of the spring that connects Pi and Fk
Linear equations for each Pi
P 0
wik ·(xk0 −xi ) = 0
P
wik ·(xk −xi ) + (xk0 : x-coord of Fk )
k∈A i k∈B
P 0i
wik ·(yk0 −yi ) = 0
P
wik ·(yk −yi ) + (yk0 : y-coord of Fk )
k∈Ai k∈Bi
Collecting into a system of linear equations
By symmetry, it suffices to consider equations from x-direction only
P 0
wik ·(xk0 −xi ) = 0
P
wik ·(xk −xi ) +
k∈Ai k∈Bi

With some manipulation,


!
P P 0 P P 0 0
wik + wik ·xi + −wik · xk = wik ·xk
k∈Ai k∈Bi k∈Ai k∈Bi

a11 x1 + a12 x2 + . . . + a1n xn = b1 ···


··· ai1 x1 + . . . + aii xi + . . . + ain xn = bi
an1 x1 + an2 x2 + . . . + ann xn = bn ···

What are the coefficients of the above system of linear equation?


P
0
P
 k∈Ai wik + k∈Bi wik if i = j

aij = −wij elif Pi and Pj are connected

0 else

0 0
P
bi = k∈Bi wik ·xk (= 0 if Pi is not adjacent to a fixed object)
How to efficiently construct the system of linear equations
P
0
P
 k∈Ai wik + k∈Bi wik
 if i = j
aij = −wij elif Pi and Pj are connected

0 else

0 0
P
bi = k∈Bi wik ·xk (= 0 if Pi is not adjacent to a fixed object)

Input is given as a list of informations of each spring


I elastic coefficient, free object ID, free object ID or
I elastic coefficient, free object ID, x/y-coord of fixed object

Initially, set all aij and bi to 0


For each spring that connects Pi /Pj , accumulate aii , ajj , aij , aji
I aii += wij , ajj += wij , aij -= wij , aji -= wij
For each spring that connects Pi /Fj , accumulate aii , bi
I aii += wij0 , bi += wij0 ·xj0

Do similarly for a system of equations from y-direction


Finally, run Gaussian Elimination twice to obtain (xi , yi )’s!
The system of linear equations for the example input
wij = wji
0 (x 0 −x ) = 0
P1 : w12 (x2 −x1 ) + w13 (x3 −x1 ) + w11 1 1
0 0 0
I (w
12 +w13 +w11 )x1 −w12 x2 −w13 x3 = w11 x1
0 (x 0 −x ) + w 0 (x 0 −x ) = 0
P2 : w21 (x1 −x2 ) + w23 (x3 −x2 ) + w22 2 2 23 3 2
I −w 0 0 0 0 0 0
21 x1 + (w21+w23+w22+w23 )x2 −w23 x3 = w22 x2 + w23 x3
P3 : w31 (x1 −x3 ) + w32 (x2 −x3 ) + w34 (x4 −x3 ) = 0
I −w
31 x1 −w32 x2 + (w31 +w32 +w34 )x3 −w34 x4 = 0
0 (x 0 −x ) + w 0 (x 0 −x ) = 0
P4 : w43 (x3 −x4 ) + w44 4 4 45 5 4
I −w 0 0 0 0 0 0
43 x3 + (w43 +w44 +w45 )x4 = w44 x4 + w45 x5

0 0 0
   
w12 +w13 +w11 −w12 −w13 0 w11 x1
0 0 0 0 0 0

 −w21 w21 +w23 +w22 +w23 −w23 0 
x =
w22 x2 +w23
 x3 
 −w31 −w32 w31 +w32 +w34 −w34   0 
0 0 0 0 0 0
0 0 −w43 w43 +w44 +w45 w44 x4 +w45 x5

To which aij ’s does w13 (= w31 ) contribute?

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