emily whiting john ochsendorf frédo durand massachusetts institute of technology, usa
DESCRIPTION
Procedural Modeling of Structurally-Sound Masonry Buildings. Emily Whiting John Ochsendorf Frédo Durand Massachusetts Institute Of Technology, USA. architectural models. virtual environments models require visual realism important to interact physically with surroundings - PowerPoint PPT PresentationTRANSCRIPT
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Emily Whiting John Ochsendorf Frédo DurandMassachusetts Institute Of Technology, USA
Procedural Modeling ofStructurally-Sound Masonry Buildings
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virtual environments• models require visual realism• important to interact physically
with surroundings
state of the art• simple models• or react in scripted ways
architectural models
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structurally stable• will look more realistic• suitable for physical simulations
– react to external forces
architectural models
our result
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structurally stable• will look more realistic• suitable for physical simulations
– react to external forces
earthquake simulation
architectural models
our result
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Generate models that are structurally sound
• Inverse Statics
• Procedural modelingquickly generates complex architectural models
• Masonry material
goal
unstable input stable output
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Focus is on visual realism, mainly for detail in façades
our contribution: introduce physical constraints
related work procedural modeling
Parish et al. [2001] Wonka et al. [2003] Müller et al. [2006] Müller et al. [2007] Lipp et al. [2008]
[Muller et al. 2006]
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8 [http://www.csiberkeley.com/]
related work structural analysis
Elastic Finite Element analysis
wrong physical model for masonrynot deformable
elastic material
stress profileoutput is visualizationsolves forward problem not inverse
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related work structural analysis
geometric configuration
rigid block assemblage [Heyman 1995]
linear constraint formulation[Livesley 1978, 1992; RING software]
elastic material
masonry
vs.
analyze material stress
wrong physical model for masonrynot deformable
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Non-Structural• Architectural free-form surfaces
[Pottmann et al. 2008]• Variational surface modeling
[Welch and Witkin 1992]• Layout design [Harada et al. 1995]
Structural• Structure optimization
[Smith et al. 2002; Block et al. 2006]• Tree modeling [Hart et al. 2003]
• Posing characters [Shi et al. 2007]
related work design by optimization
[Smith et al. 2002]
[Pottmannet al. 2008]
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procedural building generation
analysis method for masonry
inverse problem
overview
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procedural modeling
[Muller et al. 2006]
production ruleinput shape production type (parameters) {output shapes}
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procedural modeling
input shape production type (parameters) {output shapes}
library of primitives
production rule
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procedural modeling
input shape production type (parameters) {output shapes}
library of primitives
production rule
production• subdivision, scale, translation, …
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procedural modeling
input shape production type (parameters) {output shapes}
library of primitives
production rule
typical parameters• height• thickness of columns, walls, arches• window size• angle of flying buttresses
production• subdivision, scale, translation, …
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procedural modeling
A Repeat(“x”,0.2){B} B Subdiv(“y”){“wall”|C|”wall”}
C Subdiv(“y”){D|”arch”}
A
D Subdiv(“x”){E} E S(0.2,1,1){“wall”}
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• blocks: mass• interfaces: contact
surfaces between blocks
Output
procedural modeling
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procedural building generation
analysis method for masonry
inverse problem
overview
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conditions for stability
• static equilibrium
• masonry compression-only
analysis overview
0
0
torques
forcesfor eachblock
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conditions for stability
• static equilibrium
• masonry compression-only
analysis overview
requires tension
feasible
0
0
torques
forcesfor eachblock
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linear system of equations
static equilibrium
weights,torques
geometrycoefficients
forces
each block0
0
torques
forces
Aeq· f + w = 0
weight, wj
f if i+1
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masonry
0inf
compression-onlypositive normal forces
inf
no “glue” holding blocks together
normal force
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linearized as pyramid
friction cone
in
it
it fff 21 ,
inf i
tf 1
itf 2
normal forcefriction force
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summary model of feasibility
Stable solution existsUnstable no solution exists
unknownforces, f
Aeq· f + w = 0 static equilibrium
fni ≥ 0 compression
Afr· f ≤ 0 friction
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summary model of feasibility
Stable solution existsUnstable no solution exists
unknownforces, f
Aeq· f + w = 0 static equilibrium
fni ≥ 0 compression
Afr· f ≤ 0 friction
Problembinary,solution f exists yes/no
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Problembinary,solution f exists yes/no
tension required to stand
how much “glue”
Our Solutionmeasure infeasibility
summary model of feasibility
Aeq· f + w = 0 static equilibrium
fni ≥ 0 compression
Afr· f ≤ 0 friction
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tension required to stand
how much “glue”
Our Solutionmeasure infeasibility
measure of infeasibility
Aeq· f + w = 0 static equilibrium
fni ≥ 0 compression
Afr· f ≤ 0 friction
tension
relax constraint
minf
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fni = fn
i+ – fni- where fn
i+ ≥ 0 fni- ≥ 0
tension
split into positive, negative components
normal force variable transformation
compression
inf
e.g. for compression forces fni+ > 0
fni- = 0
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measure of infeasibility
2)( inf
s.t.
minf
Aeq· f +w = 0 static equilibrium
fni+ ≥ 0, fn
i-≥ 0 allow tension
Afr· f ≤ 0 friction
Quadratic program
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measure of infeasibility
2)( inf
Aeq· f +w = 0 static equilibrium
fni+ ≥ 0, fn
i-≥ 0 allow tension
Afr· f ≤ 0 friction
s.t.
minf
Quadratic program
scalar output y
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measure of infeasibility
2)( inf
Aeq· f +w = 0 static equilibrium
fni+ ≥ 0, fn
i-≥ 0 allow tension
Afr· f ≤ 0 friction
s.t.
minf
Quadratic program
y = 0 feasibley > 0 measure of infeasibility
scalar output y
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measure of infeasibility
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procedural building generation
analysis method for masonry
inverse problem
overview
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ProceduralModel
feasible?Analysis
parameters
optimization loop
Update Parameters
model fromoutput
parameters
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ProceduralModel
feasible?
parameters
nested optimizations
Update Parameters
model fromoutput
parameters
quadratic program
minimum tension at parameters
pi
pi+1
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nested optimizations
quadratic program
minimum tension at parameters
pi
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pi+1 update parameters
y(pi)
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update parameters
nested optimizations
quadratic program
minimum tension at parameters
pi
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pi+1
y(pi)
find parameters for feasible structure, want y(p*) = 0
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update parameters
find parameters for feasible structure, want y(p*) = 0
nested optimizations
quadratic program
minimum tension at parameters
pi
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pi+1
y(pi)
nonlinear programarg minp y(p)
MATLAB active-set algorithm, gradients with finite differencing
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p0
arch example
column widtharch thickness
columnwidth
archthickness
feasible regionzero tension
2)( tension
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Results
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typical parameters
• building height• thickness of columns,
walls, arches• window size• angle of flying buttresses
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results sainte chapelle
tension forcesunstable model frominput parameters
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results sainte chapelle 486 blocks, 17 sec/iter
4 parameter optimizationunstable model frominput parameters
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results sainte chapelle 486 blocks40 sec/iter
10 parameter optimizationunstable model frominput parameters
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results Bezier curves
6 parameter optimizationunstable model frominput parameters
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results tower
32 parameter optimization
96 blocks,12 sec/iter
unstable model frominput parameters
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results tower
with safety factorunstable model from
input parameters 32 parameter optimization
96 blocks,12 sec/iter
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• manually modify fixed parameters• re-optimize free parameters to retain stability
usage scenarios exploration
Exampleuser changes roof span
automatically update angle of flying buttress
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Load models into dynamic simulation
Bullet Physics Engine[http://www.bulletphysics.com/]
usage scenarios dynamics
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ground shake
Bullet Physics Engine [http://www.bulletphysics.com/]
usage scenarios dynamics
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51Bullet Physics Engine [http://www.bulletphysics.com/]
usage scenarios dynamicsprojectile
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blocksremoved
Bullet Physics Engine [http://www.bulletphysics.com/]
usage scenarios dynamics
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• Inverse analysis method• Procedural modeling to specify design parameters• Measure of infeasibility• Optimization scheme to generate stable models
summary stable buildings
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Singapore-MIT Gambit Game LabNSERC Canada
Phillippe SiclaitSylvain Paris
Yeuhi AbeJovan PopovicEugene Hsu
thanks...
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• Inverse analysis method• Procedural modeling to specify design parameters• Measure of infeasibility• Optimization scheme to generate stable models
summary stable buildings
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extra slides
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ground shake
∆ ground velocity = 4 m/stime step = 1/60 smodel width ~ 10 m
Bullet settings:restitution (bounce) = 0.0friction coefficient =
0.895
Bullet Physics Engine [http://www.bulletphysics.com/]
usage scenarios dynamics
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model #blocks #params #iters time/iter
Cluny 986
4579
10549
45.7 s57.3 s70.0 s106.6 s
arch 10 2 6 0.1 s
SainteChapelle 486
35710
4968
12.5 s26.5 s29.3 s40.1 s
tower 96 32 6 12.5 s
barrel vault 140 1 8 0.6 s
performance
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