lucci mirra pignatelli - laurea 08.06_ld

Computational morphogenesis and FabriCation

oF an aCoustiC shell For outdoor Chamber musiC

università degli studi di napoli FederiCo iidipartimento di arChitettura

gabriella luCCi

gabriele mirra

eduardo pignatelli

relatore

sergio pone

Correlatori

alberto pugnale

seraFino di rosario

soFia Colabella

bianCa parenti

tesi di laurea

1

2

IDENTIFYING

THEMATIC AREA

STATE OF THE ART

METHODOLOGICAL

HYPOTESIS

EXPERIMENTAL

APPLICATION

THE ESSENCE OF SOUND WAVES

THE PROBLEMS OF AN OPEN AIR CHAMBER MUSIC CONCERT

3DESIGNING AN ACOUSTIC CHAMBER FOR OUTDOOR

.THE SOUND WAVE

.SOUND PROPAGATION

.GEOMETRICAL ACOUSTICS

.FREE FIELD

.REVERBERANT FIELD

ACCORDING TO MUSICIANS

.ACCORDING TO AUDIENCE

.WHAT ARE GOOD ACOUSTICS

.ACTIVE ACOUSTIC SYSTEMS

.PASSIVE ACOUSTIC SYSTEMS

1

2

EXAMPLES OF SOLVED PROBLEMS

3RESONANT STRING SHELL - RES.THE RESEARCH PROJECT

.RESONANT STRING SHELL 1.0

.RESONANT STRING SHELL 2.0

.RESONANT STRING SHELL 3.0.RESEARCH STATE AND

FUTURE PURPOSES

.SOUNDFORMS

.SIEBEIN ASSOCIATES

.SUONOVIVO

.HOLLYWOOD BOWL SHELL

.SPECIALITY THEATRE

.AALBORG ACOUSTIC PAVILION

1

2

FROM DIGITAL MODEL TO REAL MODEL

STRUCTURAL DESIGN PROCESS

.HOW TO REALIZE COMPLEX FORMS

BUILDING SITE AS AUTOMATED INDUSTRY

HIGHTECH DESIGN/LOWTECH CONSTRUCTION

.PREREQUISITES

.CONCEPT

.EXPLORING SOULTIONS

TENSEGRITY SHELL

SELF BEARING SHELL

RECIPROCAL STRUCTURE

CABLE-STAYED STRUCTURE

3ENGINEERING THE STRUCTURE

.EXECUTIVE PROJECT

OPTIMIZATION OF THE CUTTING PROCESS FROM TRUSS TO BOX BEAM

KNOTS DEFINITION

4SIMPLIFYING CONSTRUCTION SITE

PROGRAMMING INSTALLATION PHASES

CONSTRUCTION MACHINERY’S DESIGN

3THE OPTIMIZATION PROCESS

1COMPUTATIONAL MORPHOGENESIS

.WHAT IS COMPUTATIONAL MORPH

.THE MORPHOGENETIC PROCESS2RES 4.0 - THE ALGORITHM

.ALGORITHM OVERVIEW

.INPUTS

.COMPLEX FORMS FROM SIMPLE ELEMENTS

.DESIGN VARIABLES (RES ANALISYS).RES 4.0 GENOME (VARIABLE AND STABLE)

.INPUT POPULATION

.MODELING THE NATURE OF SOUND

THE IMAGE SOURCE METHOD

THE RAYTRACING METHOD

.THE PROCESSING CORE

THE CODE

.USEFUL OUTPUTS

SOUND PRESSURE LEVEL

.OPTIMIZATION AS AWARENESS TOOL

FIRST DOMAIN SETTINGS

SECOND DOMAIN SETTINGS

THIRD DOMAIN SETTINGS

.ARCHITHECTURAL SETTING

PALAZZO GRAVINA

THE MUSICIANS

THE AUDIENCE

.FINAL OPTIMIZATION

.RESULTS ANALYSIS

.CILIA SYSTEM

THE EVOLUTION OF DESIGN METHODS

.FROM ANALOG DESIGN TO PARAMETRIC APPROACH

.A SIGNIFICANT EXAMPLE FROM ANALOG TO DIGITAL DESIGN

IdentyfIng thematIc areathe essence of sound Waves

the Problems of an oPen aIr concert

desIgnIng an acoustIc chamber for outdoor musIc

examPle of solved Problems

evolutIon of desIgn methods

resonant strIng shell - res

comPutatIonal morPhogenesIs

res 4.0 - the algorIthm

the oPtImIzatIon Process

from dIgItal tI real model

structural desIgn Process

engIneerIng the structure

sImPlIfyIng constructIon sIte

state of the art methodologIcal hyPotesIs exPerImental aPPlIcatIon

T H E E S S E N C E O F S O U N D W A V E S















f frequency = c / λ T cycle = 1 / fc sound speed in air = 343 m/s

λ wavelenght

x [m

]

y [m]

a















WAVE FRO

NT

SOURCE

FROM ACOUSTIC WAVE TO ACOUSTIC RAY















24 rW

SWI

π== 1120log(rLL WI )−−=SOUND INTENSITY SOUND PRESSURE LEVEL

r

a

aa

a

a

a

a

a

a

a

a a

a a

2r

3r















FFFFFF

D I R E C T R AY R E F L E C T E D R AY

SOURCE

IMAGE SOURC

E

R E F L E C T I V E S U R F A C E

ACOUSTIC REFLECTION MODEL

θ1 θ2

SNELL LAW : θ1 = θ2















Free Field















reverberant Field















the problems oF an open air

Chamber musiC ConCert















THE PROBLEMS ACCORDING TO MUSICIANS

MUSIC

PERCEPTION

ACOUSTIC

PARAMETER

MUSICIANS CANNOT HEAR EACH OTHERS ENSEMBLE STAGE SUPPORT















THE PROBLEMS ACCORDING TO MUSICIANS

MUSIC

PERCEPTION

ACOUSTIC

PARAMETER

MUSICIANS CANNOT HEAR EACH OTHERS ENSEMBLE STAGE SUPPORT

EARLY DECAY OF SOUND

FOR CHAMBER MUSICSUBJECTIVE

REVERBEARLY DECAY TIME















LOW SOUND INTENSITY NO MUSICSOUND PRESSURE

LEVEL

THE PROBLEMS ACCORDING TO AUDIENCE

MUSIC

PERCEPTION

ACOUSTIC

PARAMETER















LOW SOUND INTENSITY NO MUSICSOUND PRESSURE

LEVEL

THE PROBLEMS ACCORDING TO AUDIENCE

MUSIC

PERCEPTION

ACOUSTIC

PARAMETER

SPATIALIZATIONINTERAURAL CROSS

CORRELATIONNON-UNIFORM SOUND FIELD















What are good aCoustiCs?

[...]the Composition, the ConduCtor, the orChestra, and the hall . it is vital to distinguish among these ingredients and to understand

What eaCh Contributes to the totality.

l.l. beranek - ConCert hall and opera houses, 2004















designing an aCoustiC Chamber For outdoor

aCtive aCoustiC systems

passive aCoustiC systems















passive aCoustiC systems

designing an aCoustiC Chamber For outdoor

aCtive aCoustiC systems















examples oF solved problems















soundForms_arup

the regular siZe (21m x 14m)

-75 mq oF platForm area

-10m Wide at the Front

-8m Wide at the baCk

-7m deep

the regular is aCoustiCally optimiZed For 18 – 23 musiCians

the medium siZe (17m x 27m)

-98 mq oF platForm area


-8.5m Wide at the baCk

-9m deep

the medium is aCoustiCally optimiZed For 36 – 50 musiCians

the large siZe (20m x 33.5m)

-231 mq


-10.4m Wide at the baCk

-11.2m deep

the large is aCoustiCally optimiZed For 75 – 100 musiCians
















aCoustiCal design oF the band shell or enClosure

• Design anD shape the ceiling anD walls to proviDe natural acoustic projeCtion oF sounds From the enClosure to the audienCe

• integrate sounD system components to proviDe weather protection a Well as enhanCe aCoustiCal direCtivity For loudspeakers

• proviDe a network of wall anD ceiling panels to proviDe sounD reFleCtions so perFormers on stage Can hear eaCh other and

play in ensemble

Containment of SoundS within faCility to meet noiSe ordinanCe requirementS at faCility Perimeter

• natural barriers anD partial enclosures such as walls, berms, hills, planters, landsCape elements, etC. as part oF

arChiteCtural design oF FaCility

• location anD Directionality of louDspeakers to minimize sounD spills out oF audienCe area

• use of a greater number of smaller louDspeakers or Digitally con-trolled line array speakers With Controlled direCtional

patterns to minimiZe sound spills outside oF audienCe area

• automatic control of volume anD frequency response through Dsp (digital signal proCessing) Controllers

siebein assoCiates shell
















outdoor panels_suonovivo

the suono vivo outdoor aCoustiC Chamber Consists oF panels in lexan polyCarbonate Featuring outstanding sound reFleCtionproperties.has a modular struCture that adapts to the stage needs oF large

orChestras and also individual soloists. it is quiCkly assembled and disassembled.is WeatherprooF.
















the aCoustiC reFleCtor has aproximately the same area as the orChestra risers and is positioned roughly 9.14 m above the orChestra to provide the CritiCal 30-mseC dispersed relFeCtions; in its Final Form, the reFleCtor asumes the shape oF a longitudinally positioned ellipse, inClined about 10 degrees above oriZontal.the stage Canopy is Composed oF a tennis-Court-siZed aluminium and Fiberglass ring spanned by Folding, transluCent polyCarbonate panels.

hollyWood boWl shell

















inFlatable shell_speCiality theatre Small Shell

depth: 4 mheight: 4 mWidth: 8 mFootprint area: 32 mq

shipping Weight: 166 kg

medium Shell



large Shell



8 m

4 m

4 m

13 m

6 m

6 m

16 m

8 m

8 m















aalborg aCoustiC pavilion the aCoustiC pavilion Was designed as a stage For eleCtroniC and experimental musiC. it is Created From evolutionary algorithms that searCh the opti-mum Form and reFleCtive environment For eleCtroniC musiC Within the Context oF aalborg’s harbour Front. it enCloses the musiCal spaCe From the City and opens to the Water aiming at Creating an intimate sound based milieu Within an open publiC realm. the aCtu-al design proCess Was based on numerous experiments ConCerned With Form, materials, struCture, and aCoustiCs that aided by Com-putational algorithms generated the Final shape as Well as the pointy Wood Components.
















analog design vs parametriC approaCh















resonant string shell

a signiFiCant example oF evolution

From analog to digital design















res 1.0design methods

• totally analog proCess

aCoustiC deviCes

• main shell

• array system

• Cilia system

• reFleCtive bottom















res 1.0aCoustiC perFormanCe
















• First digital design proCess

• restriCted Form improvement proCess

• panel orientation optimiZed by COVERING AREA

aCoustiC deviCes

• main shell

• array system

• Cilia system

• reFleCtive bottom

















• digital design proCess

• restriCted Form improvement proCess

• CustomiZable aCCording to musiCians setups

• Computational improvement oF the Form by number

oF reFleCtions

aCoustiC deviCes

• main shell

• CustomiZable array system

• elongated Cilia system

• diFFusive bottom















researCh state and Future purposes















What is Computational morphogenesis?

the morphogenetiC proCess involves: the ConstruCtion, the analysis and the evaluation oF a Certain topologiCal spaCe, designed For one or

more objeCtives.it FolloWs a reCursive paths, perForming a Continous improvement oF the

Form:1. deFining the most perForming ConFiguration oF the spaCe

2. providing a landsCape oF solutions For the aWareness oF the problem















the morphogenetiC proCess

DEFINITION OF DESIGN VARIBALES

INPUT SYSTEM

INDIVIDUALSELECTION

RESULTINGINDIVIDUALS

CROSSOVER

MUTATION

NEWPOPULATION GEOMETRY

FITNESS ACOUSTIC SIMULATION

PROCESSING COREEVOLUTIONARY-BASED OPTIMIZATION

REPRESENTATION OF THE ACOUSTIC SHELL

OUTPUT SYSTEM

RANDOM GENERATION OF THE 1ST POPULATION















algorithm overvieW

input

proCessing Coreoutput















INPUT VARIABLE DESIGNRES 3.0 ANALYSIS0PHENOTYPE

LAST RES

2THE SOURCE GEOMETRY THE SHAPE

3THE SOURCE GEOMETRY

PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS

0PHENOTYPELAST RES
















LAST RES



PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS

0PHENOTYPELAST RES

1st ring1st ring1RINGS

THE SMOOTHNESS
















LAST RES



PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS

0PHENOTYPELAST RES


THE SMOOTHNESS

2nd ring2nd ring

1st ring1st ring
















LAST RES



PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS

0PHENOTYPELAST RES


THE SMOOTHNESS

2nd ring2nd ring

1st ring1st ring

3rd ring3rd ring

2nd ring2nd ring

1st ring1st ring
















LAST RES



PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS

3rd ring3rd ring

2nd ring2nd ring

1st ring1st ring
















LAST RES



PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS

3rd ring3rd ring

2nd ring2nd ring

1st ring1st ring

0PHENOTYPELAST RES


1RINGS

THE SMOOTHNESS
















LAST RES



PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS

0PHENOTYPELAST RES


1RINGS

THE SMOOTHNESS
















LAST RES



PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS

0PHENOTYPELAST RES


1RINGS

THE SMOOTHNESS


PANELIZATION

0PHENOTYPELAST RES


1RINGS

THE SMOOTHNESS
















LAST RES



PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS


PANELIZATION

0PHENOTYPELAST RES


1RINGS

THE SMOOTHNESS
















LAST RES



PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS
















LAST RES



PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS

R1

R24THE SOURCE GEOMETRY

PROPORTIONS

0PHENOTYPELAST RES


1RINGS

THE SMOOTHNESS


PANELIZATION
















LAST RES



PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS


CURVATURE

0PHENOTYPELAST RES



PANELIZATION


PROPORTIONS

1RINGS

THE SMOOTHNESS
















LAST RES



PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS

0PHENOTYPELAST RES



PANELIZATION


PROPORTIONS


CURVATURE


DEPTH

1RINGS

THE SMOOTHNESS















21DEPTH

RINGS

3RATIO

4RADIUS

5POSITION

6SCALE0

7SCALE1

8SCALE2

9SCALE3

10PANEL1

11PANEL2

INPUT VARIABLES DESIGNRES 4.0 GENOME















21DEPTH

RINGS

3RATIO

4RADIUS

5POSITION

6SCALE0

7SCALE1

8SCALE2

9SCALE3

10PANEL1

11PANEL2


1DEPTH















21DEPTH

RINGS

3RATIO

4RADIUS

5POSITION

6SCALE0

7SCALE1

8SCALE2

9SCALE3

10PANEL1

11PANEL2


21DEPTH

RINGS















21DEPTH

RINGS

3RATIO

4RADIUS

5POSITION

6SCALE0

7SCALE1

8SCALE2

9SCALE3

10PANEL1

11PANEL2


21DEPTH

RINGS

3RATIO















21DEPTH

RINGS

3RATIO

4RADIUS

5POSITION

6SCALE0

7SCALE1

8SCALE2

9SCALE3

10PANEL1

11PANEL2


21DEPTH

RINGS

3RATIO

4RADIUS

5POSITION















21DEPTH

RINGS

3RATIO

4RADIUS

5POSITION

6SCALE0

7SCALE1

8SCALE2

9SCALE3

10PANEL1

11PANEL2


21DEPTH

RINGS

3RATIO

4RADIUS

5POSITION

6SCALE0

7SCALE1

8SCALE2

9SCALE3















21DEPTH

RINGS

3RATIO

4RADIUS

5POSITION

6SCALE0

7SCALE1

8SCALE2

9SCALE3

10PANEL1

11PANEL2


21DEPTH

RINGS

3RATIO

4RADIUS

5POSITION

6SCALE0

7SCALE1

8SCALE2

9SCALE3

10PANEL1

11PANEL2















input variables designres 4.0 topologiC spaCe















modelling

the physiCal nature oF soundpropagation models

alvar aalto - aCoustiC studies For viipuri muniCipal library















S

A

B

C

R

0DEFINE N ACOUSTIC RAYS:EX N = 10

2EXTEND UNTIL IT WILL INTERSECT A SURFACE

3MIRROR THE SOURCE ON SURFACE A

4DRAW A LINE BETWEEN THE MIRRORED SOURCEAND THE INTERSECTION POINT

5INTERSECT WITH THE NEXT SURFACE

6MIRROR THE MIRRORED SOURCE ON SURFACE C


8INTERSECT WITH THE NEXT SURFACENO INTERSECTION!

9REPEAT THE PROCESS FOR EACH RAY

1CHOOSE ONE ACOUSTIC RAY

RAY TRACING METHOD















S

A

B

C

R

0DEFINE N ACOUSTIC RAYS:EX N = 100DEFINE N ACOUSTIC RAYS:EX N = 10










RAY TRACING METHOD















S

A

B

C

R












RAY TRACING METHOD















S

A

B

C

R

m_Sa












RAY TRACING METHOD















S

A

B

C

R

m_Sa

m_Sac












RAY TRACING METHOD















S

A

B

C

R

m_Sa












RAY TRACING METHOD















S

A

B

C

R












RAY TRACING METHOD















S R

A

B

C

S R

0DEFINE A BOUNCES NUMBEREX N = 2

A

B

C

5INTERSECT WITH SURFACE C

7INTERSECT WITH SURFACE A

9REPEAT THE PROCESS FOR EACH COMBINATION


1CHOOSE A BOUNCES COMBINATION EX SACR


4DRAW A LINE BETWEEN THE TARGET ANDTHE LAST MIRRORED SOURCE

6DRAW A LINE BETWEEN THE INTERSECTION POINT AND THE PREVIOUS MIRRORED SOURCE

8DRAW A POLYRAY BETWEEN THE POINTS


IMAGE SOURCE METHOD















S R

A

B

C

S

A

B

C

R


BOUNCES NUMBER: 2

POSSIBLE COMBINATIONS:SABR SACRSBAR SBCRSCAR SCBR











IMAGE SOURCE METHOD















S R

A

B

C

m_Sa












IMAGE SOURCE METHOD















S R

A

B

C

m_Sa

m_Sac












IMAGE SOURCE METHOD















S R

A

B

C

m_Sa

m_Sac

5INTERSECT WITH SURFACE C5INTERSECT WITH SURFACE C










IMAGE SOURCE METHOD















S R

A

B

C

m_Sa

m_Sac












IMAGE SOURCE METHOD















S R

A

B

C












IMAGE SOURCE METHOD















S R

A

B

C

S R

A

B

C

S

A

B

C

R

S

A

B

C

R

METHODS COMPARISON

PROCESSING CORE















#IMAGE SOURCEDEFINING TRASFORMATION MATRIX

DirectionMove_L = []SrfCenter_L = []for i in ReflectSrf:....SurfaceCenterPoint = rs.SurfaceAreaCentroid(i)[0]....SrfCenter_L.append(SurfaceCenterPoint)....SurfaceUV = rs.SurfaceClosestPoint(i,SurfaceCenterPoint)....DirectionMove_L.append(rs.SurfaceNormal(i,SurfaceUV))

MirrorMatrix_L = []for srfIN in range(len(ReflectSrf)):....MirrorMatrix_L.append(rs.XformMirror(SrfCenter_L[srfIN] ,....DirectionMove_L[srfIN]))

#DEFINING MIRRORED SORCE POINTS UNTIL INFINITE ORDER

def graftlist(List):....MainList = []....Void = []....MainList.append(Void) ....GraftList = []....for i in range (len(MainList)):........for j in List: ............Sub = []............Sub.append(j)............GraftList.append(Sub)....return (GraftList)SrcPtsGraft = graftlist(SrcPts)

ObjList = []ObjList.append(SrcPtsGraft)def RecursiveMirror(SrcPtsGraft,gens):....Macro = []....for i in range (len(SrcPts)):........List = []........for j in range (len(SrcPtsGraft[0])):............for k in range(len(ReflectSrf)):................List.append(rs.TransformObjects(SrcPtsGraft[i][j],................MirrorMatrix_L[k],True)[0])........Macro.append(List)....if gens != 0:........ObjList.append(Macro)....if gens > 0:........RecursiveMirror(Macro,gens-1)....return(ObjList)

Nmax = max(n)mSrcN_full = RecursiveMirror(SrcPtsGraft, Nmax )

#REMOVE FROM MIRRORED SOURCE POINTS LIST ALL DUPLICATES

def PointsConversion(coordinate):....Converted = []....for i in range (len(mSrcN_full)):........Csub1 = []........for j in range (len(SrcPts)):............Csub2 =[]............for k in range (len(mSrcN_full[i][j])):................Csub2.append(round(rs.PointCoordinates(mSrcN_full[i]................[j][k])[coordinate],2))............Csub1.append(Csub2)........Converted.append(Csub1)....return(Converted)

mSrcN_x = PointsConversion(0)mSrcN_y = PointsConversion(1)mSrcN_z = PointsConversion(2)

def RecursiveCull(mSrcN_full,gens,empty):....if Nmax >= 2:........mSrcN = []........for j in range (len(SrcPts)):............SubM1 = []............for k in range (len(mSrcN_full[gens][0])):................if gens >= 2:................if ((round((rs.PointCoordinates(mSrcN_full[gens]................[j][k])[0]),2) in (mSrcN_x[(gens-2)][j]))................and(round((rs.PointCoordinates(mSrcN_full[gens]................[j][k])[1]),2) in (mSrcN_y[(gens-2)][j]))

................and(round((rs.PointCoordinates(mSrcN_full[gens]

................[j][k])[2]),2) in (mSrcN_z[(gens-2)][j]))):

....................SubM1.append(None)

................else:

....................SubM1.append(mSrcN_full[gens][j][k])

............mSrcN.append(SubM1)

........empty.insert(0,mSrcN) #Ordine n

........if gens > 2:

............RecursiveCull(mSrcN_full,gens-1,empty)

........return(empty)

....elif Nmax == 1:

........empty.append(mSrcN_full[0])


........return(empty)

....else:


........return(empty)empty = []mSrcN = (RecursiveCull(mSrcN_full,Nmax,empty))if Nmax >=2:....mSrcN.insert(0,mSrcN_full[1])....mSrcN.insert(0,mSrcN_full[0])

#FINDING INTERSECTION PTS AT ORDER N

def CodeExecution (n):....#1 FAKE RAYS ORDER N....fRays = []....for i in range(len(TgtPts)):........fRay_Sub = []........for j in range(len(SrcPts)):............fRay_Sub2 = []............for k in range(len(mSrcN[n][0])):................if mSrcN[n][j][k] != None:....................fRay_Sub2.append(rs.AddLine(mSrcN[n][j][k],....................TgtPts[i]))................else:....................fRay_Sub2.append(None)............fRay_Sub.append(fRay_Sub2)........fRays.append(fRay_Sub) ....#2 INTERSECTION ORDER N ....ReflectSrf_t = []....for i in range (int(len(ReflectSrf)**(n)/len(ReflectSrf))): ........for Srf in ReflectSrf:............ReflectSrf_t.append(Srf) ....#per n = 3 appende 36 volte la lista di 6 per ramo di src ....Intersection = []....for i in range (len(TgtPts)):........sub1 = []........for j in range (len(SrcPts)):............sub2 = []............for w in range(len(ReflectSrf_t)):................if fRays[i][j][w] != None:....................Int = rs.CurveBrepIntersect(fRays[i][j][w],....................ReflectSrf_t[w])................else:....................Int = None................if Int is not None:....................sub2.append(Int[1][0])................else:....................sub2.append(None)............sub1.append(sub2)........Intersection.append(sub1)

#FINDING INTERSECTION PTS FROM ORDER N-1

RECURSION ....def RecursiveIntersection (IntPts, gens, IntList):........if n != 1 : ............fRayN = []............for i in range (len(TgtPts)):................sub1 = []................for j in range (len(SrcPts)):....................sub2 = []....................for k in range (len(mSrcN[gens-1][0])):........................h = k * int((len(Intersection[0][0]))/........................(len(mSrcN[gens-1][0])))........................for x in range(int((len(Intersection[0][0]))/........................(len(mSrcN[gens-1][0])))):............................if (IntPts [i][j][x + h]) and ............................(mSrcN[gens-1][j][k]) != None:................................sub2.append(rs.AddLine(IntPts[i][j]................................[x + h],mSrcN[gens-1][j][k]))

............................else:

................................sub2.append(None)

....................sub1.append(sub2)

................fRayN.append(sub1)

............ReflectSrf_p = []

............for i in range (((int((len(mSrcN[gens-1][0]))/

............(len(ReflectSrf)))))):

................for Srf in ReflectSrf:

....................for j in range (int((len(IntPts[0][0]))/

....................(len(mSrcN[gens-1][0])))):

........................ReflectSrf_p.append(Srf)

............Pt = []

............for i in range (len(TgtPts)):

................sub1 = []

................for j in range (len(SrcPts)):

....................sub2 = []

....................for k in range(len(ReflectSrf_p)):

........................if fRayN[i][j][k] is not None:

............................Int = rs.CurveBrepIntersect(fRayN[i]

............................[j][k],ReflectSrf_p[k])

........................else:

............................Int = None

........................if Int is not None:

............................sub2.append(Int[1][0])

........................else:

............................sub2.append(None)

....................sub1.append(sub2)

................Pt.append(sub1)

............IntList.append(Pt)

........if gens == n:

............IntList.insert(0,Intersection)

........if gens > 2:

............RecursiveIntersection (Pt, gens-1, IntList)

........return(IntList)

....

....IntList = []

....RecInt = RecursiveIntersection(Intersection, n, IntList)

#DRAW POLYRAYS ....RList = []....for i in range (len(TgtPts)):........Rsub1 = []........for j in range (len(SrcPts)):............Rsub2 = []............for k in range (len(ReflectSrf)**n):................Rsub3 = []................for w in range (len(RecInt)):....................Rsub3.append(RecInt[w][i][j][k])................Rsub2.append(Rsub3)............Rsub1.append(Rsub2)........RList.append(Rsub1) ....for i in range (len(TgtPts)):........for j in range (len(SrcPts)):............for k in range (len(RList[0][0])):................RList[i][j][k].insert(0,TgtPts[i])....................RList[i][j][k].append(SrcPts[j])....polylines = []....for i in range (len(TgtPts)):........Plsub1 = []........for j in range (len(SrcPts)):............Plsub2 = []........for k in range (len(RList[0][0])):............if (None in RList[i][j][k]) == True :................Plsub2.append(None)............else:................Plsub2.append(rs.AddPolyline(RList[i][j][k]))........Plsub1.append(Plsub2)....polylines.append(Plsub1)

#OBSTACLE CHECK ....#1 FIND SEGMENTS....SegmentsList = []....for i in range (len(TgtPts)):........SLsub1 = []........for j in range (len(SrcPts)):............SLsub2 = []............for k in range (len(polylines[0][0])):................if polylines[i][j][k] != None:....................SLsub2.append(rs.ExplodeCurves(polylines[i]....................[j][k])) ................else:....................SLsub2.append(None)

............SLsub1.append(SLsub2)

........SegmentsList.append(SLsub1) ....#2 FIND INTERSECTION COUNT LIST ....SegmentIntlist = []....for i in range (len(TgtPts)):........SILsub1 = []........for j in range (len(SrcPts)):............SILsub2 = []............for k in range (len(polylines[0][0])):................SILsub3 = []................for w in range (n+1):....................for x in range (len(ReflectSrf)):........................if SegmentsList[i][j][k] is not None:............................Int = rs.CurveBrepIntersect............................(SegmentsList[i][j][k][w],ReflectSrf[x])........................else:............................Int = None........................if Int is not None:............................SILsub3.append(Int[1][0])........................else:............................SILsub3.append(None)................SILsub2.append(len(SILsub3) - SILsub3.count(None))............SILsub1.append(SILsub2)........SegmentIntlist.append(SILsub1) ....#3 BUILD NEW POLYLINES WITH NEW CONDITION ....polyrays = []....for i in range (len(TgtPts)):........Prsub1 = []........for j in range (len(SrcPts)):............Prsub2 = []............for k in range (len(RList[0][0])):................if (SegmentIntlist[i][j][k]) > (2+2*(n-1))................or (None in RList[i][j][k]) == True:....................Prsub2.append(None)................else:....................Prsub2.append(rs.AddPolyline(RList[i][j][k]))............Prsub1.append(Prsub2)........polyrays.append(Prsub1)

#CALCULATE SPL AND TIME ....time = []....SPL = []....for i in range(len(TgtPts)):........time1 = []........SPL1 = []........for j in range(len(SrcPts)):............time2 = []............SPL2 = []............for h in range(len(RList[0][0])):................if polyrays[i][j][h] != None:....................time2.append((rs.CurveLength....................(polyrays[i][j][h]))/343)....................SPL2.append((111-(20*math.log10....................(rs.CurveLength(polyrays[i]....................[j][h])-1))-11)*(r**n))................else:....................time2.append(None)....................SPL2.append(None)............time1.append(time2)............SPL1.append(SPL2)........time.append(time1)........SPL.append(SPL1)....return (SPL,polyrays)

if Compute == True:....FINAL = []....for i in range (len(n)):........FINAL.append(CodeExecution(n[i])) ....RAYS = [] ....for i in range (len(n)):........SPL.append(FINAL[i][0])........RAYS.append(FINAL[i][1]) ....a = SPL....b = RAYS















SOURCES: 1TARGETS: 25REFLECTIVE SURFACES: 6

PROCESSING CORE - RAYS SHOOTING















BOUNCES: 0

POTENTIAL RAYS: 25TOTAL RAYS: 25min LENGHT: 6,56 m

















BOUNCES: 1


















BOUNCES: 2


















BOUNCES: 3


















d =14 mSPL[dB] = Lw - 20log10(d) - 11

PROCESSING CORE - SPL CALCULATION















SPL COMBINATION















SPL COMBINATION

DIRECT SOUND LEVELS

TOTAL SOUND LEVELS = 10^DS/10+10^RS/10

REFLECTED SOUND LEVELS















SPL COMBINATION70 75 80 85 90 95 100 [dB]

DIRECT SOUND LEVELS

TOTAL SOUND LEVELS = 10^DS/10+10^RS/10

REFLECTED SOUND LEVELS





























THE OPTIMIZATION PROCESS















the morphogenetiC proCess

DEFINITION OF DESIGN VARIBALES

INPUT SYSTEM

INDIVIDUALSELECTION

RESULTINGINDIVIDUALS

CROSSOVER

MUTATION

NEWPOPULATION GEOMETRY

FITNESS ACOUSTIC SIMULATION

PROCESSING COREEVOLUTIONARY-BASED OPTIMIZATION

REPRESENTATION OF THE ACOUSTIC SHELL

OUTPUT SYSTEM

RANDOM GENERATION OF THE 1ST POPULATION















OPTIMIZATION 1

SOURCE

TARGETS















OPTIMIZATION 1

SOURCE

TARGETS

DMIN = 1.5M















OPTIMIZATION 1

70 75 80 85 90 95 100 [dB]

GENERATIONS

SPL SUM = 11509.90 dB SPL SUM = 11623.23 dB SPL SUM = 11700.00 dB SPL SUM = 11727.82 dB SPL SUM = 11738.34 dB

51 15 30 50















OPTIMIZATION 1

70 75 80 85 90 95 100 [dB]

GENERATIONS

SPL SUM = 11738.34 dB

50

INEFFICIEN

T PAN

ELS

RED DOTS = BOUNCING POINTS















OPTIMIZATION 2

70 75 80 85 90 95 100 [dB]

GENERATIONS


51 15 30 50















OPTIMIZATION 2

70 75 80 85 90 95 100 [dB]

GENERATIONS

SPL SUM = 12022.27 dB

50















OPTIMIZATION 3

SOURCES

TARGETS















OPTIMIZATION 3

70 75 80 85 90 95 100 [dB]

GENERATIONS


51 15 30 50















OPTIMIZATION 3

70 75 80 85 90 95 100 [dB]

GENERATIONS

SPL SUM = 12626.06 dB

50

EXTENDED PANELS

3,6

11

1,6

2

0,6 0,4

ARCHITECTURAL SETTINGMETHOD APPLICATION















18,66

A = 262m2

18,82

ARCHITECTURAL SETTINGMETHOD APPLICATION















OPTIMIZATION A - FITNESS FUNCTIONRANDOM SHELL SPL MAP

1x M *100

N

iif −= ∑

=

δ

Where:

- N is the total number of targets; - xi is SPL value on the ith target;

- M is the Number of SPL Values smaller than 90dB

FITNESS FUNCTION















OPTIMIZATION A

70 75 80 85 90 95 100 [dB]

GENERATIONS

SPL SUM = 18070.97dB SPL SUM = 18297.18 dB SPL SUM = 18532.14 dB SPL SUM = 18577.21 dB SPL SUM = 18580.11 dB

51 15 30 80















OPTIMIZATION A

70 75 80 85 90 95 100 [dB]

GENERATIONS

SPL SUM = 18580.11 dB

80

8.00 m4.30 m

4.40 m















70 75 80 85 90 95 100 [dB]

SOU

ND

PRE

SSU

RE L

EVEL

[dB]

DISTANCE [m]80

82

84

86

88

90

92

94

96

98

100

102

0.5 2.4 4.3 6.2 8.1 10.0 12.0 13.9 15.8 17.7

ALL

SOU

RCES

SPL

MA

P

BACK

SOU

RCES

SPL

MA

P

MID

DLE

SOU

RCES

SPL

MA

P

FRO

NT S

OU

RCES

SPL

MA

P

ALL

OPTIMIZATION A - RESULT ANALYSIS















70 75 80 85 90 95 100 [dB]

SOU

ND

PRE

SSU

RE L

EVEL

[dB]

DISTANCE [m]80

82

84

86

88

90

92

94

96

98

100

102

0.5 2.4 4.3 6.2 8.1 10.0 12.0 13.9 15.8 17.7

ALL

SOU

RCES

SPL

MA

P

BACK

SOU

RCES

SPL

MA

P

MID

DLE

SOU

RCES

SPL

MA

P

FRO

NT S

OU

RCES

SPL

MA

P

ALL

BACK

MIDDLE

FRONT
















70 75 80 85 90 95 100 [dB]

SOU

ND

PRE

SSU

RE L

EVEL

[dB]

DISTANCE [m]80

82

84

86

88

90

92

94

96

98

100

102

0.5 2.4 4.3 6.2 8.1 10.0 12.0 13.9 15.8 17.7

ALL

SOU

RCES

SPL

MA

P

BACK

SOU

RCES

SPL

MA

P

MID

DLE

SOU

RCES

SPL

MA

P

FRO

NT S

OU

RCES

SPL

MA

P

ALL

BACK

MIDDLE

FRONT

CRITICAL DECAY






























FORM FINDING - CILIA

α 0°<α<60°

DEFINE 1m TRANSLATION VECTOR FOR EACH SEGMENT1 EXTRUDE EACH SEGMENT AND BUILD NEW SURFACES2 ROTATE EACH SURFACE BY DIFFERENT ANGLES3















FORM FINDING - CILIASO

UN

D P

RESS

URE

LEV

EL [d

B]

DISTANCE [m]80

82

84

86

88

90

92

94

96

98

100

102

0.5 2.4 4.3 6.2 8.1 10.0 12.0 13.9 15.8 17.7

FRONT SOURCES SPL MAP

NO CILIA

2

1)(1 xx

N

N

iif −= ∑

=

δ

Where:

- N is the total number of targets; - xi is SPL value on the ith target;

- x is the arithmetic mean of the xi ;

- 2)( xxis −=σ is the measure of the variance of the data structure and represents the simple spread relative to the mean value.

FITNESS FUNCTION
















UN

D P

RESS

URE

LEV

EL [d

B]

DISTANCE [m]80

82

84

86

88

90

92

94

96

98

100

102

0.5 2.4 4.3 6.2 8.1 10.0 12.0 13.9 15.8 17.7


NO CILIA

CILIA

OPTIMIZATION RESULT
















UN

D P

RESS

URE

LEV

EL [d

B]

DISTANCE [m]80

82

84

86

88

90

92

94

96

98

100

102

0.5 2.4 4.3 6.2 8.1 10.0 12.0 13.9 15.8 17.7


NO CILIA

CILIA

OPTIMIZATION RESULT

OPTIMIZATED TARGETS















DIMENSIONS ND

STAGE ND

INSTRUMENT ND

RANGE 4M

THROW 60 PEOPLE

DIMENSIONS 8 X 4 X 4 MSTAGE 20M2

INSTRUMENT 10RANGE 10M

THROW 150 PEOPLE

DIMENSIONS 8 X 4 X 4 MSTAGE 20M2


THROW 210 PEOPLE

DIMENSIONS 7 X 5 X 4STAGE 22M2


THROW 250 PEOPLE

DIMENSIONS 8 X 5 X 5STAGE 27M2


THROW 600 PEOPLE















From digital model to real model

landesgartensChau exhibition hall















hoW to realiZe Complex Form_building site as automated industry

dragon skin pavilion / emmi keskisarja, pekka tynkkynen & lead















.Computer-aided maniFaCturing methods

.reverse engineering and digital sCanning

.Computer numeriCally Controlled equipments

-tWo dimension CnC Cutting

-three dimesional CnC FabriCation


bilbao guggenheim /gehry partners, llp















the Caad sWissbau pavilion/ eth ZüriCh
















hoW to realiZe Complex Form_high teCh design / loW teCh ConstruCtion

timber seasoning shelter ConstruCtion / aa design&make experienCe















eladio diestegridshell.it

aa design&make experienCe

hoW to realiZe Complex Form_high teCh design / loW teCh ConstruCtion















struCtural design proCess

the use oF Wood

preserve shell geometry

Composition oF Flat elements

respeCt For eCologiC prinCiples

re-use materials

prerequisites















struCtural design proCess ConCept















aCoustiC shell

reCiproCal struCture

selF-bearing shell

tensegrity shellCable-stayed struCture

struCtural design proCess exploring solutions















selF bearing shell

+ pros

landesgartensChau exhibition hall

insp

irin

g

.the aCoustiC ConFiguration resulting From the projeCt isn’t resistent Form

.material eConomy

.ConstruCtion site seimpliFiCation

.strong CharaCteriZation oF the arChiteCtural objeCt- Cons

physiCalsimulation















tensegrity shell

physiCalsimulation

landesgartenshau exibition hall

. mismatCh betWeen optimal aCoustiC and struCtural perFormanCes

insp

irin

g

g30 summer pavilion 03

+ pros .material eConomy

.ConstruCtion site seimpliFiCation

.strong CharaCteriZation oF the arChiteCtural objeCt- Cons















reCiproCal struCture

leonardo’s bridge

insp

irin

g

.need to siZeable Cross-seCtion to avoid stability problems

.extremely simple to realiZe

.ChanCe to modiFy the struCture aCCording to diFFerent shell ConFigurations

physiCalsimulation

+ pros

- Cons















Cable stayed struCture

langkaWi sky bridge

insp

irin

g

physiCalsimulation

.heavier than other struCtures

.bukling problems

+ pros

- Cons

.possibility to shape struCtural Form on the aCoustiC shell

.great Flexibility oF the system















engigneering the struCture















optimiZation oF the Cutting proCessengigneering the struCture

C2b

M0

M1

M2

G0

G1

G2

M0

M1

M2

G0

G1

G2

C0a

C2a

C1a

C2a

C1b C1a

C0b C0a

Pannelli shell acustica

G2

G2

M1 M1

G0

M2G1M0

M0

G0C0b C0a

C2a

C2a

C0a C1a

C1b C2b

M2

G1

C1a

Ca cig

G cig

M cig

Ca cigG cig

M cig

Ca cig

Ca

cig

Cb

cig

Ca

cig

G c

ig

M c

ig

G c

ig

M c

ig

Pannelli shell acustica

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Arr

Pannelli Array

Elementi ricavati da pannelli dilegno truciolare grezzo 3760 x1860 x 40

PIANO DEI TAGLI















optimiZation oF the Cutting proCessengigneering the struCture















Fromtruss to box beamengigneering the struCture















knots deFinitionengigneering the struCture















simpliFying ConstruCtion site ConstruCtion maChinery design

phase 1

phase 2

phase 3

liFt up system















simpliFying ConstruCtion site ConstruCtion maChinery design

phase 1 phase 2 phase 3

liFt up system















simpliFying ConstruCtion site programming installation phases

lucci mirra pignatelli - laurea 08.06_ld

Documents