ORF 307: Lecture 16 Linear Programming: Chapter 16: Structural Optimization Robert J. Vanderbei April 18, 2017 Slides last edited on May 3, 2018 http://www.princeton.edu/∼rvdb
ORF 307: Lecture 16
Linear Programming: Chapter 16:Structural Optimization
Robert J. Vanderbei
April 18, 2017
Slides last edited on May 3, 2018
http://www.princeton.edu/∼rvdb
Designing an “Optimal” Wall Bracket
Click here for two-phase simplex method animation tool.Click here for parametric self-dual simplex method animation tool.
Click here for affine-scaling method animation tool.
1
Structural Optimization
Forces: xij = tension in beam (aka member) {i, j}.• xij = xji.
• Compression = -Tension.
Force Balance:
Look at joint 2:
x12
[−10
]+ x23
[−0.60.8
]+ x24
[01
]= −
[b12b22
]
Notations:
~pi = position vector for joint i
~uij =~pj −~pi‖~pj −~pi‖
( Note ~uji = −~uij)
Constraints:∑j:
{i,j}∈A
~uijxij = −~bi i = 1, . . . ,m.
2
Matrix Form
Ax = −b
xT =[
x12 x13 x14 x23 x24 x34 x35 x45
]
A =
1
2
3
4
5
[10
] [01
] [.6.8
][−10
] [−.6.8
] [01
][
0−1
] [.6−.8
] [10
] [.6.8
][−.6−.8
] [0−1
] [−10
] [−.6.8
][−.6−.8
] [.6−.8
]
, b =
b11b21b12b22b13b23b14b24b15b25
.
Notes:• ‖~uij‖ = ‖~uji‖ = 1.
• ~uij = −~uji.
• Each column contains a ~uij, a ~uji, andrest are zero.
• In one dimension, exactly a node-arcincidence matrix.
3
Minimum Weight Structural Design
minimize∑{i,j}∈A
lij|xij|
subject to∑j:
{i,j}∈A
~uijxij = −~bi i = 1, 2, . . . ,m.
Not quite an LP.Our favorite trick:
xij ≤ tij−tij ≤ xij
Reformulated as an LP:
minimize∑{i,j}∈A
lijtij
subject to∑j:
{i,j}∈A
~uijxij = −~bi i = 1, 2, . . . ,m,
xij ≤ tij {i, j} ∈ A−tij ≤ xij {i, j} ∈ A
4
Another Absolute Value Trick
minimize∑{i,j}∈A
lij|xij|
subject to∑j:
{i,j}∈A
~uijxij = −~bi i = 1, 2, . . . ,m.
Not quite an LP.Use a common trick:
xij = x+ij − x−ij, x+
ij, x−ij ≥ 0
|xij| = x+ij + x−ij
Reformulated as an LP:
minimize∑{i,j}∈A
(lijx+ij + lijx
−ij)
subject to∑j:
{i,j}∈A
(~uijx+ij −~uijx
−ij) = −~bi i = 1, 2, . . . ,m
x+ij, x
−ij ≥ 0 {i, j} ∈ A.
5
Redundant Equations
Recall network flows:
number of redundant equations = number of connected components.
Row combinations:~yTi ~uij +~y
Tj~uji
Sum of “x”-component rows:
[1 0
] [ ~u(x)ij
~u(y)ij
]+[1 0
] [ ~u(x)ji
~u(y)ji
]= 0
Sum of “y”-component rows, “z”-component rows, etc. is similar.
6
Are There Others?
Yes. Put
~yi = R~pi, R =
[0 −11 0
], RT =
[0 1−1 0
]= −R.
Compute:
~yTi ~uij +~yTj~uji = ~pTi R
T~uij +~pTj R
T~uji
= (~pi −~pj)TRT~uij
= −(~pj −~pi)TRT (~pj −~pi)
‖~pj −~pi‖= 0
Last equality follows from:[ξ1 ξ2
] [ 0 1−1 0
] [ξ1ξ2
]= ξ1ξ2 − ξ1ξ2 = 0 for all ξ1, ξ2
7
Skew Symmetric Matrices
Definition.RT = −R
For d = 1: no nonzero ones.
For d = 2: [0 −11 0
]
For d = 3: 0 −1 01 0 00 0 0
, 0 0 −10 0 01 0 0
, 0 0 00 0 −10 1 0
Structure is stable if the redundancies just identified represent the only redundancies.
8
Conservation Laws
Suppose a combination of rows of A vanishes.Then the same combination of elements of b must vanish.
Force Balance: ∑i
b(x)i = 0 and
∑i
b(y)i = 0
What is meaning of the other redundancies?∑i
(R~pi)T~bi = 0
Answer...
9
Torque Balance
Consider two-dimensional case:
R =
[0 −11 0
].
Physically, this matrix rotates vectors 90◦ counterclockwise.
Let ~vi =~pi/‖~pi‖ be a unit vector pointing in the direction of ~pi:
~pi = ‖~pi‖~vi.
Then,
(R~pi)T~bi = ‖~pi‖(R~vi)T~bi
= (length of moment arm)(component of force perp to moment arm)
In three dimensions, three independent torques: roll, pitch, yaw.
They correspond to the three basis matrices given before.
Note: torque balance is invariant under parallel translation of axis.
10
Trusses (analog of a Tree in Network Flows)
Definition.
• Stable (analog of connected)
• Has md− d(d + 1)/2 beams, d is dimension (analog of acyclic)
Anchors
No force balance equation at anchored joints.Earth provides counterbalancing force.
If enough (d(d + 1)/2) independent constraints are dropped (due to anchoring), then noforce balance or torque balance limitations remain.
11
The Michell Bracket (1904)
Constraints: 5,396Variables: 193,310Time: 270 seconds
Click here for parametric self-dual simplex method anima-tion tool.Click here for affine-scaling method animation tool.
12
The Michell Bracket (1904)
Constraints: 14,996Variables: 536,972Time: 1994 seconds
Click here for parametric self-dual simplex method anima-tion tool.Click here for affine-scaling method animation tool.
13