Rick Schutte Portfolio 2024 by rick.schutte

ARCHITECTURE PORTFOLIO Rick Schutte

GENERATIVE SOLAR ATRIUM Fall 2021 | Academic | ARC1011: Design Studio 1 | Instructors: Maria Denegri | Individual Project

HA/F SEMINAR: ENVIRONMENTAL SCIENCES AND CHEMISTRY BUILDING UTSC WHOLE LIFE CARBON ASSESSMENT + BIM MODEL Fall 2023 | Academic | ARC3402: Ha/f Research Seminar | Instructors: Kelly Doran, Alstan Jakubiec | Climate Studio Groupmate David Yan (Revit Model: Individual Project) Fall 2023 | Academic | ARC3200: Adv. Topics in Computer Applications: BIM | Instructors: Salman Khalili | Individual Project

ARTIFICIAL RESPIRATION: AI KINETIC SOLAR-POWERED PAVILION Fall 2020 | Academic | ARC480: Adv. Topics in the Technology of Architecture: Re-integrating Design | Instructor: Salman Khalili-Araghi | Individual Project

AIR QUALITY INDEX PAVILION Summer 2020 | Personal | Velux Competition Winning Submission | Advisor: JP King | Groupmate Mina Onay*

HIGH SPEED RAIL EQUITABLE PLANNING OPTIMIZATION: CONNECTING THE LAURENTIAN CORRIDOR Winter 2022 | Extra-Curricular | Groupmates: John Shen, Zyra Joseph

PARKVIEW TOWERS AMENITY FLOOR VISUALIZATION Summer 2020 | Professional | Visualization and design work for QuadReal Property Group | Individual Project

UNCANNY DENSITY: AI GAN PLAN REGENERATION Summer 2020 | Academic | ARC480: Adv. Topics in the Technology of Architecture: Lazy Computing | Instructor: Andrew Bako | Groupmates: Zhenxiao Yang, Lauren Ngo*

DOWNSVIEW FOREST Fall 2023 | Academic | ARC2013: Design Studio 3 | Instructors: Christos Marcopolous | Groupmates: Lhanzi Gyaltsan, Khadija Waheed

GENERATIVE SOLAR ATRIUM

31st Floor Amenity Level The pre-construction shared space was visualized through several realtime animations in Unreal Engine

Teaching AI to generate Architecture - then exploring it

GENERATIVE SOLAR ATRIUM

HA/F SEMINAR: ENVIRONMENTAL SCIENCES GENERATIVE SOLAR ATRIUM INFILL DESIGN AND CHEMISTRY BUILDING UTSC WHOLE LIFE CARBON ASSESSMENT

3 % K = (! 8 " 3 3 :

31st Floor Amenity Level The pre-construction shared space was visualized through several realtime animations in Unreal Engine

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Teaching AI AI to to generate generate Architecture Architecture -- then then exploring exploring itit Teaching . 9

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10/17/22

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Rick Schutte

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LEVEL 2 - Presentation 1 : 50

SHEET ISSUE DATE

10/17/22

1 A402

MECH PH ROOF 28150

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PROJECT

UTSC ESCB

DSA

TITLE

EAST ELEVATION T.O. BASEMENT SLAB -4900

NUMBER ELEVATOR PIT -6625

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STUDENT NAME

East

Rick Schutte

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10/17/22

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NUMBER

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STUDENT NAME

Rick Schutte

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10/17/22

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Section 2 - Callout 2 1 : 20

PROJECT

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TITLE

DETAIL CALLOUTS NUMBER

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STUDENT NAME

Rick Schutte

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1 : 10 SHEET ISSUE DATE

11/14/22

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ARTIFICIAL RESPIRATION: AI KINETIC SOLAR-POWERED PAVILION

AI-generated pavilion form continually changes to optimize its environmental comfort

ARTIFICIAL RESPIRATION: AI KINETIC SOLAR POWERED PAVILION

A I C I R C U L AT I O N P R E D I CT I O N

A I PA V I L I O N F O R M G E N E R A T I O N

AI Learns and Predicts Human Movement

Environmental Input Becomes 3D Surface Environmental Input Map + Circulation

+ Te m p e r a t u r e

Input

A G e n e ra tive Adver s ar ial Net work (GA N) is a type of A I . I t has a G e n e ra t o r and a Dis cr iminat or that both lear n from a set of i n p u t i m a ges . Th e G e n e rat o r cr eat es new images (like an Artist), and the D isc r i m a t o r a t t empt s t o dis t ing uis h the new images from the or igin a l i n p u t imag es (like an Ar t Cr itic). Th e g e n e ra t ed imag es o n t he r ight represent w here the G enerato r w a s a b le t o fo o l t he Dis cr iminator and create images indisti n g u i sh a ble fr o m t he input ima ges. I n t h i s p ro ject , a GA N was us ed to lear n from circulation paths th rou g h a s it e and g ener at e it s ow n predicted human paths.

+ Wind

Desired Output

Precipitation

AI Output

A C GA Non i sdai timo rel aGden v aera ncetidvfo f N erura N e t w orrkk as i t N) i s a A C on a e rm Ad voersa i a l l Netwo ( C GA ca n m b eore traaidne n ce rtaei nof CAoInd p reorjaec v adnoc ed typ . I ittiaol ns so . hIn a s thi a Gs en t ot r, an a n do baj ec Ditsicve ri3 D fo rm i s cre a te d i n K a ng a ro o 3 D fo r a ny g i v e n s i t e b as ed o n t h m a tor th a t a re tra i n ed f rom i n p u t i m a ges, h o we ve r t h e Ge n e r ea E nv tor i ro nme co ndtw i tioo ns a nd a ths l ea rnta n s lf rom sets of dienspi uret pi m a geso fath n datt rsiiet se. t o t r a n s l a t e on e i n to th e oth er. A ho t cl i ma te w o ul d b e ne fi t fro m mo re s ha d i ng an d ven t i l at i o n , tra ns i nto a ta r,en mo retor o pleea n rfo A ico lim I tl ai sti ang s th ou gh thlel eG era n srm. En gl shl da er n d cFr e nat che , waonudl dt h e b e neDfii sc t fro m a s he l te re d fo rm tha t re d uce s v e nti l at i o n . r i m i n a tor i s i ts L a n gu a ge tea ch er. Af ter h a vi n g l e a r n e d t h e tw o l a n gu a ges, th e G en era tor c a n n ow tra n s l a t e o n e i m a g e s e t T he i ni np i ncl udies sthdee soth i re er. p a New ths a und a n Ri G to ut w hdaattai ts eptred i c ts n seen mBa gbeac s ckagr n onuonwd b e tha ttra i nd i ca te s e nv i ro nme nta l i nfo rma ti o n, the C o n d i t i o n al d es i r ed n sl a ted i n to a n ew p red i c ted i m a ge. o utp ut i ma g e re p re s e nts the g o a l he i g ht o f the p avi l i o n . I n th i s p roj ec t, a C GA N w a s u sed to tra n s l a t e e n vi r o n m e n t a l T he i nApI uot utp ut th reep 3reds esunts a v ial i opna vfo i n to rf aac ep of i l irm on .a b l e t o p r ed i c t an o p ti ma l fo rm fo r up co mi ng e nv i ro nme nta l co nd i t i o n s .

ARTIFICIAL RESPIRATION: AI KINETIC SOLAR POWERED PAVILION

AI Environmental Optimization

Solar Powered Kinetic Pavilion

AI learns to optimize environmental comfort of pavilion

Solar-Powered mechanisms move the pavilion according to AI to optimize its form

Environmental Input Map + Circulation

+ Te m p e r a t u r e

Environmetal Input

P r e d i c t e d E nv i ro n m e nt a l I n p u t

Morning

Afternoon

+ Wind

Precipitation

M e d Te m p

H i g h Te m p

High Wind

Low Wind

Low Precipitation

L Output for Morning Conditions

Output for Afternoon Conditions

In th hii s pro p ro ject j e ct , I h have ave cr eat ed two t wo lang la ng uag ua g e s for a C GAN to tra nslate nsla te b et e twe ween. e n . The i np ut l ang a ng uag ua g e con co nssii sts s ts of o f the Ci C i rcul atio a ti o n, Te mpe mp e ra ture, ture , Win Wi nd a nd Pre cipi ci p i ta tion ti o n o f a si s i t e at a spec s p ec if i f ic i c t im i me c o m m-d,, and bin ha t is o a uto ma tic bi nee d in i n t o a sin gle colou r f u l im ag agee . The output lang la ng ua g e is a he ightmap ig htma p image ima ge ttha is u ussee d tto ti caall ly l y g en e neerat ra tee the 3 d fo r m o f the pavi p av i l ion. i o n. The re d b ackg a ck g rou ro u n d is i s i gn o r ed by b y t h e par p ar am et r ic ic so a re , an a nd black die pav thapta ths l o caatind o n.the d ,tigca el n, axp nda nd l ue rrow s rects p rebse saesnt ere d de ddeidcte mfo oo p i zt at i coonnfdor oirt iso soonlar lsar softw ware, d t he b laalgor ck t oitwhit e g rara dient re pre se pa ntsv ilion the heforms ig ht of that loca on. The d, relen, b lue pre codmfort This hm gene tent s org a nic bathe se d pavilion on ilio a s interro ’sooodf easti re n kre i ne y eand s o ar rrows co ntra e d eomb n ped e nvrti r optim n tmi m eniz al ion . h eat gai n , pav ilion for ms are produ ce d to m axim iz e co mfo rt in di ffe re nt env iro nme nta l co nd i ti on s usi ng the pavili o n’s ki n et ic S MA m ech an ism r a iinwat nw a teerr run ru n of f , an d ven t ilat ion control. D iffere iffe re ntFurthe a re produce ma xi mi ze i n d i e nv i ro o ns us i p av i l i k i i c M A i s m s. s. r re se a rch wa s cond ucte d to e xp l o re the us e o f Sha p e Me mo ry A l l o ys to co ntro l the fo rm.

ARTIFICIAL RESPIRATION: AI KINETIC SOLAR POWERED PAVILION

Further description words here

Morning Experiential Control: Extended Extended Panels mimic forest canopy conditions while producing shade

Afternoon Experiential Control: Retracted Retracted Panels generate an intimate, comfortable environment

Th e A I m oves b eyon d envir on me nta l optimiza tion into e xpe r ie ntia l optimi za ti o n. The A I w i l l re co rd the v i s i to rs ’ ti me s p e nt i n d i ffe re nt l o ca ti o ns a cco rd i ng to d i f f er en t envi r o n m en t al c o n d i t i o n s t o o p t i m i z e t he pavilion ’ s ex per ie ntia l qua litie s a ccording to wha t it ha s l e a r ne d . The A I i s no l o ng e r a d e s i g n to o l b ut a co nti no us co l l a b o ra to r i n the e v o l ut i o n ar y d es i gn p r o c es s o f ar ch i t ec t u r e.

AIR QUALITY INDEX PAVILION: VELUX COMPETITION WINNING SUBMISSION

Pollution Levels Translated Into Colours The source of city pollution is mapped into a range of colours representing healthy and hazardous conditions

Air Quality Index Pavilion Tinted glass walls represent city pollution levels

The tragedy of climate change is that it alters our environment so slowly that w wee b ecome comfortable he proposed with it. We fail to recognize that the whole earth shares a single breath. Upon enter ing tthe ation of natural light as Air Quality Index Pavilion (AQI P), visitors witness an immediate transfor m mation ayers of opt ically sim uit is filtered through vertical layers of tinted curvilinear glass. Immersed in llayers optically simuhenomenon of hazard lated air pollution, visitors are invited to explore and contemplate a globa globall p phenomenon hazard-ous atmospheres, indexed by the colourful language of light.

Pavilion design, concept, and renderings created with Mina Onay, drawing in bottom right completed by Mina Onay

HIGH SPEED RAIL EQUITABLE PLANNING OPTIMIZATION: CONNECTING THE LAURENTIAN CORRIDOR

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NP K Teaching AI to generate Architecture - then exploring it

Produce a web of possible routes based on GIS data and reasonably open paths found from satellite images

Assign each path type a bias for optimization

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Group paths in network to produce four lists of options to combine into a final path to test against fitness goals

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PARKVIEW TOWERS AMENITY FLOOR AND FACADE VISUALIZATION

PARKVIEW TOWERS AMENITY FLOOR AND FACADE DESIGN VISUALIZATION

31st Floor Amenity Level The pre-construction shared space was visualized through several realtime animations in Unreal Engine

Parametric Condo Design Grasshopper building code wascode usedwas to generate used to generate condo design condooptions designand options modelling and allow for Unreal VirtualEngine RealityVisualization exploration

Teaching AI to generate Architecture - then exploring it

PARKVIEW TOWERS AMENITY FLOOR AND FACADE DESIGN VISUALIZATION

Parametric Iteration 1

Parametric Iteration 2

Parametric Iteration 3

Parametric Iteration 4 Selected Iteration

UNCANNY DENSITY: AI GAN PLAN REGENERATION

Teaching AI to generate Architecture - then exploring it

UNCANNY DENSITY: AI PLAN REGENERATION

AI House Generation

Convert generated plans into 3d models

Uncanny Density

Investigate strange architecture in realtime

The G A N AI i s tr ai n ed o n c o l o u r e d h o u s e p l a n s l a b e l l e d a cco r d i n g t o t h e i r r o o m fu n ctio n , the A I then gen er ates tho u s an d s o f n ew p lan s that have the em b ed d ed l og i c of t h e or i g i na l p l a ns . Th e w a ll s of t he gen er ated i m ages are a u t o m a t i ca l l y e x t r u d e d a n d f u r n i t u r e m o d els ar e p ar am etr ically ad d ed acco r d in g to the r o o m fu n ctio n co lo u r. The A I can o n ly g e ne ra t e wh a t i t ’ s l e a r ne d f rom t h e input , i n t h i s c ase i t r ec y c l es ar ch i t e ct u ra l d e s i g n l o g i c a n d e x p o s e s h i d d e n ten d en cies w ithin the field o f A r chitetu r e.

Groupmates assisted in collection and labelling of input images

DOWNSVIEW FOREST

Teaching AI to generate Architecture - then exploring it

Rick Schutte, 2024