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Architecture Portfolio - Brayden Tang Jia Jun

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BRAYDEN TANG

SELECTED WORKS 2021-2023

PORTFOLIO

ABOUT ME

BRAYDEN TANG JIA JUN

B.Sc Architecture and Sustainable Design

Singapore University of Technology and Design

Mobile +65 96424630

Email brayden.tang@gmail.com

Linkedin www.linkedin.com/in/braydentangjj

I’ve always been fascinated by the design of the built environment, as it has the power to shape our behaviour and influence our perception of spaces. However, this is not an easy task, given the demands and requirements from different stakeholders, be it the client, future users of even our natural environment.

Through computational means, I hope to develop efficient and streamlined systems to aid decisions through data driven designs, building an environment for all to thrive.

EDUCATION

SEP 2021 - MAY 2025

JAN 2024 - JUN 2024

JUN 2022 - AUG 2022

SINGAPORE UNIVERSITY OF TECHNOLOGY AND DESIGN Architecture & Sustainable Design Bachelors of Science

AALTO UNIVERSITY

School of Arts, Design and Architecture Global Exchange Programme

UNIVERSITY OF LOS ANGELES

School of Architecture and Urban Design Summer Programme

JAN 2017- NOV 2018

RAFFLES INSTITUTION

H2 Physics, Chemistry, Math and Art

GCE Singapore-Cambridge ‘A’ Levels

WORK EXPERIENCE

AUG 2023 - DEC 2023

HKS ASIA PACIFIC DESIGN CONSULTING PTE. LTD.

Architectural Intern

Assisted with Building Design, Renderings and Presentation Decks

CO-CURRICULAR ACTIVITIES

FEB 2024 - MAY 2025

MAR 2023 - FEB 2024

MAY 2022 - FEB 2023

MAY 2022 - FEB 2023

ARCHITECTURE AND SUSTAINABLE DESIGN PILLAR Senior Pillar Representative

ARCHITECTURE AND SUSTAINABLE DESIGN PILLAR Sophomore/Junior Pillar Representative

SUTD MOUNTAINEERING CLUB President

SUTDIO (ARCHITECTURE AND CRAFTS CLUB) Secretary

ACHIEVEMENTS

STUDENT SERVICE AWARD (INDIVIDUAL)

TOP STUDENT FOR 02.003 SOCIAL SCIENCE

SUTD HONOURS LIST 2021/22

SUTD UNDERGRADUATE MERIT SCHOLARSHIP

SKILLS

MODELLING RENDERING

DESIGN

OTHERS

LANGUAGES

RHINO 7, GRASSHOPPER, SKETCHUP, BLENDER

VRAY, UNREAL ENGINE 5, ENSCAPE, D5

PHOTOSHOP, ILLUSTRATOR, INDESIGN, PREMIERE PRO WORD, POWERPOINT, EXCEL, PYTHON ENGLISH, MANDARIN CHINESE

2023
2022 2021 2024
THE PROTO-CEMETERY: LIFECYCLE THE PROTO-CEMETERY: LIFECYCLE // FINAL ARCHITECTURAL MASSING 28 29 CONTENTS LIFECYCLE TAPESTRY HELIX GRAFFITUM 01 03 02 04 PADDYBUDDIES 09 ORGANISCAPE SKYLIGHT UNDULATE DUNES 05 07 06 08

LIFECYCLE is cemetery which sits in the context of a speculative dystopian future.

Presently, the global trash problem is a pressing issue, with over 2 billion metric tons of municipal solid waste being generated every year, and it is expected to rise to 3.4 billion by 2060, a number that would greatly strain ecosystems and pollute waterways.

As such, this future is in a state where trash has overwhelmed the surface of Earth, making the polluted grounds uninhabitable for life. The sole option that allows mankind to persist is to live upwards.

In this reality, this is achieved through harnessing trash itself, compacted into blocks and stacked to form towering mounts suitable for dwelling. The cemetery is designed to be built within the trash mounts and meant to serve as a facility for the deceeased to be processed.

This project challenges traditional ideas about building materials, as well as an understanding of how architecture responds to human behaviour and interactions accommodated with the digital realm.

01
THE PROTO-CEMETERY 20.102 ARCHITECTURE CORE STUDIO 2 > SUMMER 2023 > EVA CASTRO, HO JIN TECK DARYL > INDIVIDUAL WORK
LIFECYCLE
Mourning Chamber Worker Quarters Morgue Storage Tanks Disinfectant Tanks VR Control Room Treatment Rooms Machine Rooms Operations Room Viewing Deck Launch Zone Recovery Area Entrance Medical Reception THE PROTO-CEMETERY: LIFECYCLE // FINAL ARCHITECTURAL MASSING // 28 29
THE PROTO-CEMETERY: LIFECYCLE

THE PROTO-CEMETERY: LIFECYCLE // SITE MASSING//

PICTURE COLLAGES

WORLD BUILDING AND NARRATIVE

SITE DEVELOPMENT

DIGITAL MODEL ITERATIONS

SITE DEVELOPMENT PHYSICAL MODEL

FLOOR PLAN SKETCHES
26
27
Inserting programs within void, position is based on space required and adjacency to other related programs SUB-LEVEL 3 SUB-LEVEL 2 SUB-LEVEL 1 ALLOCATION
BUBBLE DIAGRAMS
THE PROTO-CEMETERY: LIFECYCLE // ARCHITECTURAL MASSING//
DEAD ENTRANCE VIEWING DECK VISITORS STAFF DEAD INJURED MATERIALS MACHINE 1 STERILIZATION 2 MECHANICAL DISASSEMBLY 3 SEPARATION OF ORGANS 4 EXTRACTION OF FLUIDS 5 RECOVERY OF BONES FLUID STORAGE BONE STORAGE GRAND HALLWAY INJURED ENTRANCE VISITOR ENTRANCE MOURNING CHAMBER SEND-OFF ZONE TREATMENT ROOM 1 OPERATIONS ROOM STAFF QUARTERS VR LAB VISITOR EXIT MACHINE MACHINE MACHINE MACHINE INFORMATION ROOM TREATMENT ROOM TREATMENT ROOM ORGAN STORAGE
ARRANGEMENT OF PROGRAMS Using the negative space between instead as trash towers should mainly re main uncarved for stability reasons REVISED APPROACH

THE PROTO-CEMETERY: LIFECYCLE

THE PROTO-CEMETERY: LIFECYCLE

Mourning Chamber Worker Quarters Morgue Storage Tanks Disinfectant Tanks VR Control Room Treatment Rooms Machine Rooms Operations Room Viewing Deck Launch Zone Recovery Area Entrance Medical Reception 29
Mourning Chamber Worker Quarters Morgue Storage Tanks Disinfectant Tanks VR Control Room Treatment Rooms Machine Rooms Operations Room Viewing Deck Launch Zone Recovery Area Entrance Medical Reception 29 RENDERINGS UNREAL ENGINE SCREENSHOT EXPLODED AXONOMETRIC

HELIX is an investigation on unconventional truss designs. The focus is on utilizing parametric design principles to optimize specific parameters, constrained by limited materials.

Drawing inspiration from the Helix Bridge found in Marina Bay, Singapore, we referenced the intriguing design that breaks free from conventional truss structures.

3 approaches were used to develop the design, each with varying degrees of freedom for the position of the beams. The outcome of this study is a truss design that incorporates nonplanar joints and introduces undulating truss patterns, deviating from the typical triangulation-based arrangements found in conventional designs.

CANTILEVER TERM PROJECT 20.202 ARCHITECTURE STRUCTURE AND DESIGN 20.212 DIGITAL DESIGN AND FABRICATION > SUMMER 2023 > STYLIANOS DRITSAS, SAM CONRAD JOYCE > GROUP WORK 02
HELIX

APPROACH 1 GRASSHOPPER CODE

Approach 2 optimizes the position of points randomly placed within a bounding connections

Initially, all points box space However, find a solution sections, enabling faster.

APPROACH 2 GRASSHOPPER CODE

Approach 1optimizes the positions of vertical beams connecting the top and bottom horizontal beams

generate a design that is skewed in either aspect

The top and bottom beams were first determined through the marking of the endpoints.

However, the code does not account for utilization Hence, certain results produced are not feasible Additionally, the code is too restrictive, with results often being in the shape of already existing trusses

Therefore, a new approach that allows for more freedom for the points to break its form is required Approach 1: Along Beams Lengthwise – Results

The position of the connecting bems are based on a parameterised position along the top and bottom. These beams are placed into the model analyser, with the cost being directed into the Galapagos Optimizer.

It is successful in achieving optimised forms that reduce both material usage and strength, however, it does not account for utilization, hence certain results produced are not feasible. The code is also too restrictive, with results often being in the shape of existing trusses.

APPROACH 1 RESULTS OF VARIOUS COST FUNCTIONS

APPROACH 2 INTERESTING RESULTS

From

Approach 2 optimizes the positions of points randomly placed within a bounding box to form the nodes for the beam connections.

Hence,

Approach 2 is successful in achieving irregular forms, however, many of them are not constructable or too challenging to build From the 3 variations, all exceed the utilization value of >2000%

It is successful in achieving irregular forms, however, many of them are not constructable or too challenging to construct (as seen in the 3 variations, all exceed the utilization value of >2000%)

From Graph 1 there is no linear correlation between the total material used and the performance of the cantilever As such, there is no clear relationship that can be inferred to achieve a strong design

Hence, an approach that achieves the distortion of the cantilever shape and still strong would be ideal Therefore, an algorithm that has more control over the position of the points is required

As seen in graph 1, there is no linear correlation between the total material used and the performance of the cantilever, hence there is no clear relationship that can be inferred to achieve an ideal design.

Approach 1: Along Beams Lengthwise – Overall Code
optimizes the positions of vertical beams connecting the top and bottom horizontal beams 1. FIXED TOP AND BOTTOM HORIZONTAL BEAMS 2. CONNECTION POINT POSITIONS 3. MODEL COMPONENTS 5. OPTIMIZATION 4. MODEL ANALYSIS PARAMETERS: - TOTAL MATERIAL CONSUMPTION (TMC) - MAX DEFLECTION (MD) 01
Approach 1
Approach
successful in achieving optimised forms that reduce both material usage and strength
1 is
Greater weightage can be placed on either criterion in the cost function, giving us the flexibility to
COST: 100*MD + TMC MD: 0 83cm TMC: 11 9m MD: 1 34cm TMC: 9.8m COST: MD + TMC COST: MD + 100*TMC MD: 8 90cm TMC: 8 5m UTIL: -306 8% to 309 1% UTIL: -58.6% to 114.5% UTIL: -157.5% to 90.1% 01 2.NODE GENERATION 1.ASSIGNING FIXED POINTS 3.CONNECTIONS 4.MODEL COMPONENTS 5.MODEL ANALYSIS 6.OPTIMZATION Full Random Points
PARAMETERS: - TOTAL MATERIAL CONSUMPTION (TMC) - MAX DEFLECTION (MD) 01 Captions 01 Approach 2 Grasshopper code 01 Approach 2: Full Random Points – Results
04 05 02 01 03 GRAPH 1: MAX DEFLECTION (MD) VS TOTAL MATERIAL CONSUMED (TMC) MD: 95 3cm TMC: 53.6m UTIL: -2851 5% to 2829 9% MD: 158.9cm TMC: 50 9m UTIL: -4060 3% to 4154 8% Captions 01 Approach 2 results (full random points) MD: 111 4cm TMC: 52.5m UTIL: -2311 5% to 4154 8% v 01 Approach 2: Full Random Points – Results
2 is successful in achieving irregular forms, however, many of them are not constructable or too challenging to build From the 3 variations, all exceed the utilization value of >2000%
Approach
Graph 1, there is no linear correlation between the total material used and the performance of the cantilever As such, there is no clear relationship that can be inferred to achieve a strong design
an
that achieves the distortion of the cantilever shape and still strong would be ideal Therefore, an algorithm that has more control over the position
the points is required 04 05 02 01 03 GRAPH 1: MAX DEFLECTION (MD) VS TOTAL MATERIAL CONSUMED (TMC) MD: 95 3cm TMC: 53.6m UTIL: -2851 5% to 2829 9% MD: 158 9cm TMC: 50 9m UTIL: -4060 3% to 4154 8% Captions 01 Approach 2 results (full random points) MD: 111 4cm TMC: 52 5m UTIL: -2311.5% to 4154.8%
approach
of

Approach 3 optimizes the position of 4 points placed within a bounding box, after which, the

Ultimately, the final design was chosen based on a balance between detail and overall form, taking into consideration that excessive complexity could complicate construction.

To deviate configurations, triangular

and back surfaces of

points

coordinate

0.56m.

Approach 3 optimizes the positions of 4 points placed within a fixed region, which determines the connection points for the beams, after which, the points are mirrored lengthwise.

To deviate from the conventional truss configuration, a triangular shape was used for both the front and back surfaces of the cantilever structure.

From the graphs, it was found that a greater total amount of material used leads to a smaller deflection. Interestingly, the greater the length of the longest beam, the smaller the value of the maximum deflection.

Top Side Final Model Captions 01 Digital modelling of structure 01 2. NODE GENERATION 1. ASSIGNING FIXED POINTS 6. MODEL ANALYSIS 7. OPTIMIZATION 4. SUPPORT POINTS 5. MODEL COMPONENTS 3. FINDING CLOSEST POINT
points are mirrored lengthwise
front
Approach 3: Mirrored Points PARAMETERS: - TOTAL MATERIAL CONSUMPTION (TMC) - MAX DEFLECTION (MD) - LONGEST BEAM (LB) - UTILIZATION (UTIL) points is connected the primary from one truss corresponding beams balance Horizontal address shear 01 Approach 3: Mirrored Points From the 3 parameters are to be more desirable From Graph length the longest discernible curve illustrating Notably, a attain modest deflection beams Interestingly, limitation arises due to the configuration comprising a total of five points on each cantilever side hence, connectivity ceases when the longest beam From Graph amount material utilized positioning deflection GRAPH 1: MAX DEFLECTION (MD) VS LONGEST BEAM (LB) GRAPH 2: MAX DEFLECTION (MD) VS TOTAL MATERIAL CONSUMPTION (TMC) GRAPH 3: MD VS TMC VS LB Approach 3: Mirrored Points all origin only manages m arises due to the configuration comprising a total on each cantilever side; hence, connectivity ceases when the greater deflection maximum GRAPH 1: MAX DEFLECTION (MD) VS LONGEST BEAM (LB) GRAPH 2: MAX DEFLECTION (MD) VS TOTAL MATERIAL CONSUMPTION (TMC) GRAPH 3: MD VS TMC VS LB Octopus diagrams 01 Approach 3: Mirrored Points From the 3D graph generated by Octopus, as all 3 parameters are to be minimized, points closer to the origin are more desirable From Graph 1 it was found that comparing only the length of the longest beam and the max deflection led to a discernible curve illustrating an inverse relationship Notably, a substantial subset of designs manages to attain modest deflection levels despite employing shorter beams Interestingly, the curvature culminates at 0 6m This limitation arises due to the configuration comprising a total of five points on each cantilever side hence, connectivity ceases when the longest beam falls below 0 6m From Graph 2 it can be observed that a greater total amount of material utilized leads to a smaller deflection However, the positioning of the beams also influence the maximum deflection GRAPH 1: MAX DEFLECTION (MD) VS LONGEST BEAM (LB) GRAPH 2: MAX DEFLECTION (MD) VS TOTAL MATERIAL CONSUMPTION (TMC) GRAPH 3: MD VS TMC VS LB Captions 01 Octopus Output diagrams 01 APPROACH 3 MIRRORED POINTS APPROACH 3 ITERATIONS AND FINAL DESIGN TOP SIDE More designs were generated following the same method Each meets the criteria under 26m of material, less than 5cm max deflection, and no beam over 2m Attention remains on staying under 80% utilization as nearing 100% strains in terms of compression or tension on the beams might risk fractures Lastly, design choice balances detail and overall form, taking note that excessive complexity could complicate construction Final Design Approach 3: Mirrored Points MD: 52cm TMC: 25 8 UTIL -70 9% to 67 % LB: 65m MD: 1 58cm TMC: 23 7m UTIL: -87 0 to 77 1% LB: 1 73m MD: 48cm TMC: 22 9 UTIL -75 3% to 59 % LB: 60m Captions Approach 3 (mirrored Approach 3: Mirrored Points - Results MD: 2 78cm MD: 43cm MD: 65cm TMC: 21 3m UTIL: -82 2 to 88 % LB: 1 76m MD: 1 17cm TMC: 26 m UTIL: -73 1% to 76 0 LB: 1 75 Captions Approach results (mirrored points) 01 Approach 3: Mirrored Points - Results MD: 2 78cm TMC: 21 9m UTIL: -43 3% to 45 9 LB: 1 97m MD: 43cm TMC: 25 7m UTIL -81 0 to 77 % LB: 68m MD: 65cm TMC: 21 3m UTIL: -82 2 to 88 % LB: 1 76m MD: 1 17cm TMC: 26 m UTIL: -73 1% to 76 0 LB: 1 75 Captions Approach (mirrored points) 01
These
boundaries
coordinate ranges from 0 to from 0 to
More designs were generated following the same method Each meets the criteria under 26m of material, less than 5cm max deflection, and no beam over 2m Attention remains on staying under 80% utilization as nearing 100% strains in terms of compression or tension on the beams might risk fractures Lastly, design choice balances detail and overall form, taking note that excessive complexity could complicate construction Final Design MD: 1 48cm TMC: 22 9m UTIL: -75 3% to 59 6% LB: 1 60m Captions 01 Approach 3 results (mirrored points) 01
Assignment Cantilever Term Project Context ASD Term 5 Course ASED x DDF 2023 Student Group 1: Aceson Han Chang Chou (1006342) Brayden Tang Jia Jun (1005897) James Leo Wei Shaun (1005997) Law Zhenwen (1005933) Li Junyi (1006081) Instructors Stylianos Dritsas Associate Professor Sam Conrad Overview This project investigates unconventional truss designs as a departure from traditional methodologies. The focus is on utilizing parametric design principles to optimize specific The outcome of this study is a final truss design characterized by its unique employment of parametric design techniques The truss system incorporates non-

TAPESTRY is a canopy for an outdoor plaza that explores the modulation of light.

Light is a key element in architectural design, and its effects are aesthetic, perceptual and functional.

Too much light may cause glare and generate heat, and too little light may restrict certain programs from being held. As such, light is a crucial consideration for architects and it can be explored through computational means.

The vision for this canopy is to create a space that promotes intergenerational bonding, with the programs beneath it complemeted by the awe-inspiring intricacy of the canopy’s form and pattern, serving as a conversation starter. The amount of light that passes through a particular region would influence the type of activities that are held below.

PHOTO-PHILIA | PHOTO-PHOBIA 20.211 INTRODUCTION TO DESIGN COMPUTATION > SUMMER 2023 > JASON LIM > INDIVIDUAL WORK 03
TAPESTRY

TILES/PILLARS

A base surface was first created through a grid of points, in which they are randomly displaced. The surface is then created through the aggregation of these points.

<Introduction to Design Computation> <Photo-philia/Photo-phobia>

<Step 2b - Creation of Pillars>

The pillars are formed by creating lines from the points, where each pillar unit consists of 4 diagonal beams and 1 vertical beam.

<Introduction to Design Computation>

<Step 2b - Creation of Pillars>

I aimed to make the canopy appear like a piece of fabric and use its curvature to influence the shape of the tessalted module.

The center tile where the pillars are located below are predetermined, after which the index of 4 connection tiles are obtained through calculation.

The pillars are formed by creating lines from the points, where each pillar unit consists of 4 diagonal beams and 1 vertical beam.

<Photo-philia/Photo-phobia>

PARAMETER CALCULATION

The surface is then reparameterized, and then subdivided into smaller square grids.

This grid serves as a reference point for the modules which will be populated on the canopy.

The center tile where the pillars are located below are predetermined, after which the index of 4 connection tiles are obtained through calculation.

For each tile, as it is stored as a list of 4 points, I referenced the 3rd index in the list, which correlates to the middle point. The x and y values of the vert_base_pt and diag_base_pt coordinates are constructed referencing the middle point, while the z values are set to 0 and 1 respectively.

The lines are connected to the Grasshopper ‘Pipe’ block to generated the beams with a radius of 0.2, completing the pillar.

I settled with a variation that managed to achieve a good balance of curvature and flatness, as well as giving a cloth-like appearance.

Python code (2b)

For each tile, as it is stored as a list of 4 points, I referenced the 3rd index in the list, which correlates to the middle point. The x and y values of the vert_base_pt and diag_base_pt coordinates are constructed referencing the middle point, while the z values are set to 0 and 1 respectively.

The lines are connected to the Grasshopper ‘Pipe’ block to generated the beams with a radius of 0.2, completing the pillar.

<Grasshopper Explanation

Each pillar consists of 4 diagonal beams and 1 vertical beam.

The position of the pillars, with respect to the canopy, are predetermined. Hence, the index of the 4 tiles that the diagonal beams connect to the vertical beam are calculated.

There are 4 primary components in the code. First, the base surface is created, which establishes the basic form of the canopy. Next, lists of points necessary to define the modules and pillars are generated. The modules are then drawn out by outlining its shape, making a surface and giving them thickness. Finally, the shape of the module is dependent on the parameter calculator, which takes into account the angle of the surface at that point.

Lines are drawn and then piped to form the final pillars.

Overview of Grasshopper 01
OVERALL CODE
3A:
1:CREATING BASE SURFACE 3A/B: MODULE GENERATION 3A/B: PARAMETER CALCULATION OVERALL ALGORITHM 1 CREATING BASE SURFACE 2A/B TILE/PILLAR CREATION 3A MODULE GENERATION 3B PARAMETER CALCULATION 1 CREATING BASE SURFACE 2A TILE CREATION 2B PILLAR CREATION 1 2A/B 3A 3B <Photo-philia/Photo-phobia> P4 res = 8 rd = 0 h = 7 sm = 4 res = 8 rd = 3.5 sd = 1 h = 7 sm = 4 res = 8 rd = 3.5 sd = 15 h = 7 sm = 4 <Introduction to Design Computation> <Photo-philia/Photo-phobia> 03 Captions 01 Grasshopper Chunk (2a) 02 Surface subdivision 03 Python code (2a) <Step 2a – Creation of Tiles> The surface is then re-parameterized, and then subdivided into smaller square grids. Iso-curves are drawn in the and V directions across the surface (u_isocrv/v_isocrv), which are then subdivided equally to obtain a list of values that correspond to the coordinate of that point in the respective axis (u_vals/v_vals). I used this method as I wanted to create an even grid, where I can further define points (details in subsequent slides) to create my module. This also ensures that the modules are in contact with each other, making the shelter practical for construction. 01 02 P# nu = 30, nv = 30 <Introduction to Design Computation> <Photo-philia/Photo-phobia> 03 Captions 01 Grasshopper Chunk (2a) 02 Point Grid Generation Diagram 03 Python code (2a) <Step 2a - Creation of Tiles cont.> To create the list of points, I used a nested loop to iterate through the ‘u_vals/v_vals’ Points are created using the srf.PointAt method, where they are appended to the list ‘pts’. Next, during the creation of points, a subset of points are defined (topR,botR,botL,topL,top bot,mid). These points are essential for the creation of the module (details in subsequent slides). 01 02 P# topR idx -1) topL idx -1-nv) U-direction Vdirection botR idx -2) botL idx -2-nv) botR Close-up view botL mid bot top topR topL Triangle 1 – Blue Triangle 2 - Green
1: CREATING BASE SURFACE TRIANGLE 1
MODULE GENERATION TRIANGLE 2 2A/B: CREATING
3B:
03 Captions
Grasshopper Chunk (2b) 02 Pillar Diagram (Section/Plan) 03
code
01
Python
(2b)
02 P# 01
03 Captions 01
Chunk
02 Pillar
(Section/Plan) 03
Grasshopper
(2b)
Diagram
02 P# 01

make the modules respond to the intrinsic attributes of the surface.

The base module consists of a triangle, where its shape can be adjusted based on a parameter.

To make the canopy comfortable for users below it, I explored the idea of minimizing the size of the gaps at regions that face directly upwards, and maximizing gaps at regions that are angled away. This not only reduces direct sunlight shining in downwards, but the larger side facing openings still allows for ventilation into the canopy, and it also makes the structure appear light and seemingly “float” in air like a piece of cloth.

Reference points are created for the adjustment of the shape of the module.

To achieve this, I decided to calculate the tangent of each module with respect to the zaxis, and parameterizing the value which can be used to input and adjust the size of my module.

Curves are drawn along each of the 3 sides of the triangle using 3 points, with the 2 end points dictating as anchors, while the center point serves as a controlling point that governs the degree of curvature in the curve.

that I wanted the

to

Considering the size of the gaps in the modules above, I demarcated

3B PARAMETER CALCULATION

To make the modules respond to the intrinsic attributes of the surface, I explored the idea of minimizing the size of gaps at regiions that face directly upwards, and maximising gaps at regions that are angled away.

This was done through the calculation of the tangent of each module with respect to the z-axis.

<Photo-philia/Photo-phobia> P# These the line_left ptop pleft pmid pright line_right pt_right line_bot line_perpbot pt_bot2 pt_left pt_left2 pt_right2 pt_bot pt_perpleft pt_perpright pt_perpbot line_perpleft line_perpright <Photo-philia/Photo-phobia> P# line_left ptop pleft pmid pright line_right pt_right line_bot line_perpbot pt_bot2 pt_left pt_left2 pt_right2 pt_bot pt_perpleft pt_perpright pt_perpbot line_perpleft line_perpright 3A MODULE GENERATION
CANOPY SHADOWS SHADOWS PRODUCED AT DIFFERENT TIMES OF DAY
t = 0.0 t = 0.1 t = 0.2 t = 0.3 t = 0.4 <Introduction to Design Computation> <Photo-philia/Photo-phobia> 03 Captions 01 Grasshopper Chunk (3b) 02 Overview of surface with module variation 03 Python code (3b) P# <Step 3b – Parameter Calculation>
to
<Photo-philia/Photo-phobia> P#
I wanted
01 02 Smallest opening (Parallel to sky -> large t value) Largest opening (Perpendicular
sky -> small t value) <Introduction to Design Computation> <Photo-philia/Photo-phobia> Captions 01 Programs P# <Step 3 overall – Canopy Programming> As
key
the space as such: The communal Garden stretching diagonally across, as it consists of zones with the largest gaps, allowing sunlight to reach in more easily. The Seating/Rest Area and the Arts and Craft Area are then allocated to the other 2 corners. 01 Communal Garden Seating/Rest Area Arts and Craft Area <Introduction to Design Computation> <Photo-philia/Photo-phobia> Captions 01 Shadow analysis 01 <Shadow Analysis> I felt that I was able to achieve the intended effect of the discrete tiles appearing as cloth P# MORNING NOON AFTERNOON PERSPECTIVE
to
mentioned in Step 1, I defined the
programs
canopy
host.
SHADOW

GRAFFITUM

GRAFFITUM is a proposed design for a Singapore MoMA (Museum of Modern Art) Satellite, located in Esplanade Park.

Presently, Singapore has a many different art museums, such as the National Gallery and Singapore Art Museum, which showcases various collections ranging from historical to contemporary modern artworks.

However, an artform shunned and often clamped down on is Street Art. It is an artform practised by many Singaporean artists, yet they do not have a safe space for them to showcase their work.

Hence, this proposal aims to provide the safe space for them to do so. The building is designed in a manner that it maximises its walls, turning them into canvases to display artworks.

SINGAPORE MOMA SATELLITE 20.101 ARCHITECTURE CORE STUDIO 1 > SPRING 2023 > CHRISTINE YOGIAMAN, CARLOS BANON > INDIVIDUAL WORK 04

ORGANISCAPE

ORGANISCAPE is an investigation into generative algorithms.

Generative design approaches involve creating outcomes from algorithms. In the architecture domain, these outcomes are often material in nature and exhibit traces of their algorithmic lineage through their physical characteristics.

In this project, our group wanted to explore on the growth of modules, which is dependent on its shape, its connecting face and the scalar field.

THE COMPUTATIONAL ARTEFACT 20.111 INTRODUCTION TO DESIGN COMPUTATION
SPRING 2023
LIM
GROUP WORK 05
>
> JASON
>

1 CREATING 4 CURVES

2A GENERATING MODULE

2B GENERATING SCALAR FIELD

3 COMBINING MODULES

1) CREATING 4 CURVES

3) COMBINING MODULES

GENERATING MODULE

GENERATING SCALAR FIELD

The grasshopper code contains 4 parts in total. Firstly, the creation of the curves, followed by the generation of the module and scalar field. Lastly, the module combination algorithm is applied.

<Introduction to Design Computation> <The Computational Artefact> OVERALL CODE
2A)
2B)
1 2A 2B 3
OVERALL
2B GENERATING SCALAR FIELD 2A GENERATING MODULE 1 CREATING 4 CURVES <Introduction to Design Computation> <The Computational Artefact>
CREATING 4
First, 4 lines are formed using 4 3D points and the origin. These lines form the skeleton of the module. (x1,y1,z1) (0,0,0) (x2,y2,z2) (x3,y3,z3) (x4,y4,z4) 4 points 4 lines <Introduction to Design Computation> <The Computational Artefact> Next, the 4 lines generated are placed into the MultiPipe Grasshopper Component to form the module. 2A) GENERATING MODULE MultiPipe (x1,y1,z1) (0,0,0) (x2,y2,z2) (x3,y3,z3) <Introduction to Design Computation> <The Computational Artefact> The module is then converted into a Brep object. It is also converted to a mesh to extract the surfaces and plane of its 4 ends. a a 2A) GENERATING MODULE Brep Surfaces Planes <Introduction to Design Computation> <The Computational Artefact> A 3D point grid is formed using a start point as the bottom corner point. The points are generated through a nested list, with equal horizontal and vertical spacing. 2B) GENERATING SCALAR FIELD row col z Point grid generation <Introduction to Design Computation> <The Computational Artefact> 2B) GENERATING SCALAR FIELD Attractor Point The value of each point in the grid is based on its distance from the Attractor Point. The values are then remapped using min-max normalization. A line/curve may be used as an attractor to create a greater area of influence. Point Values
ALGORITHM
1)
CURVES

<Introduction to Design Computation> <The Computational Artefact>

3) COMBINING MODULES

mod = Brep of module

mod_faces = List of module surfaces

mod_planes = List of module planes

start_faces = List of starting geometry surfaces

start_planes = List of starting geometry planes

N = Number of modules to be added

from_face = Index of face to join field_ptlist = List of points in field field_ptval = List of values of points in field

The Grasshopper Python Block takes in surface and plane data from 2A, as well as the list of points and a list of the point values from 2B.

object
Conversion of BoundingBox
to Brep object to use its methods and attributes
through each module in the list of combined modules
checking if the BoundingBox intersects
each other (with tolerance of 0.001) Checking if the list containing intersection curves is not empty If list is not empty, collision is True. Else, collision is False 3) COMBINING MODULES
Initializing lists to store aggregated blocks, available faces and planes. Iterating
and
with
<Introduction to Design Computation> <The Computational Artefact> Rule (Faces) 3) COMBINING MODULES <Introduction to Design Computation> <The Computational Artefact> Rule (Faces) 3) COMBINING MODULES FACE A > FACE A FACE A > FACE B FACE A > FACE C FACE A > FACE D <Introduction to Design Computation> <The Computational Artefact> Rule (Attractor Point) 3)
STARTING POINT LOGIC 3 PLANE TO PLANE MATCHING LOGIC 2 ATTRACTOR POINT LOGIC 1 FACES ATTRACTOR POINT <Introduction to Design Computation> <The Computational Artefact> While loop to iterate
the corresponding value for each point in the list of near points identified Iterating through list of available faces and checking through the entire list of points in the field to find the closest point for each face Getting highest value in list and getting index of corresponding face Using pre-determined face on starting module to connect to the combined structure 3) COMBINING MODULES <Introduction to Design Computation> <The Computational Artefact> Identifying the sides to form the connection. Transformation of geometry using PlaneToPlane matching Checking for collision after transforming geometry and placing it at possible location If there is no collision, the new module is appended to the list of aggregated block Applying transformation to all planes and faces, which are then stored in the list of available planes and faces respectively. The planes and faces used for the connection are removed. N is reduced by 1 only if there is a collision to ensure that the final module has exactly N modules 3) COMBINING MODULES <Introduction to Design Computation> <The Computational Artefact> Basic Rule – PlaneToPlane Matching 3) COMBINING MODULES <Introduction to Design Computation> <The Computational Artefact> Basic Rule – PlaneToPlane Matching 3) COMBINING MODULES 3 MODULE COMBINATION AGGREGATION LOGIC 3 MODULE COMBINATION GRASSHOPPER PYTHON BLOCK 3 MODULE COMBINATION GRASSHOPPER ALGORITHM
Offsetting BoundingBox inwards to prevent over selection
COMBINING MODULES
Find
<Introduction to Design Computation> (2, -4, 2) (-6, 5, 3) (3, 6, 4) (2, 2, -5) Position Face[0] Face[1] VARIATION
ATTRACTOR POSITION VS FACE SELECTED INTERESTING RESULTS Linear/ Straight (4, 4, 4) (-4,-4, -4) (-4, 4, -4) (4, -4, 4) (3, 2, 5) (-4, -5, 1) (-6, 5, 4)
MAPPING LINEAR/STRAIGHT <Introduction
Design Computation> <The
INTERESTING RESULTS INTERESTING RESULTS VARIATION
ATTRACTOR
FACE
VARIATION
STRAIGHT
BENT TOP LEFT FACE [0] FACE [1] FACE [2] FACE [3] TOP RIGHT BOTTOM RIGHT BOTTOM LEFT
MATRIX
VARIATION
to
Computational Artefact>
MATRIX
POSITION VS
SELECTED
MAPPING
VS

UNDULATE is an exploration of the use of width and height to achieve a sense of movement and dynamism in the space within the building.

3 Shapes were provided: Circle, Square and Triangle.

Firstly, I used the circle to subtract away the regions formed by the addition of the triangle and the square, forming narrow and wide spaces that imply functional spaces and spaces that are meant as transitions to one another. As a result of these operations, 3 “nodes” were defined with 2 “links” between them.

Inspired by the Farnsworth house, full glass walls were used, with furniture surrounding the centre supporting wall in the room. As the building curves towards itself, residents can see across the cottage, making it seem spacious, yet the rooms are placed far apart, creating a sense of privacy. This forms a unique and engaging architectural experience, with its spatial elements dictating the purpose of the spaces within it.

UNDULATE

THE AUTONOMY OF FORM 20.101 ARCHITECTURE CORE STUDIO 1 > SPRING 2023
CHRISTINE
> INDIVIDUAL WORK 06
>
YOGIAMAN, CARLOS BANON

Testing out different configurations and measuring the narrowest and widest space produced

B - BEDROOM

T - TOILET

K - KITCHEN

D - DINING AREA

L - LIVING ROOM

GEOMETRIC OPERATION ITERATIONS

T D L K B T D L K B T D L K B D T L K B D T L K B D T L K B 0.79-6.72 0.42-8.10 1.03-7.09
1.01-7.01 0.84-6.85 0 5 1:100
0.79-6.72
PERSPECTIVE SECTION
FLOOR PLAN

SKYLIGHT investigates the nature of intersections, producing voids or surfaces depending on the proximity between 2 tapered trapezoidal unit spaces. These trapezoidal units are carefully positioned, with the entire mass treated as a continuous field that connects different areas, creating a sense of fluidity and continuity throughout the space.

Several units extend upwards, producing skylights depending on the connectivity of that area, establishing its function as a public or private area. The public areas are designed to be open and welcoming, with plenty of natural light and communal spaces for gathering and socializing. The private spaces, on the other hand, are more enclosed, providing a sense of privacy and intimacy.

SUBTRACTIVE DESIGN 20.101 ARCHITECTURE CORE STUDIO 1
07
SKYLIGHT
> SPRING 2023 > CHRISTINE YOGIAMAN, CARLOS BANON > INDIVIDUAL WORK
4.6m² 10.4m² 4.5m² 13.0m² 12.8m² 18.5m² 16.5m² 15.5m² 15.7m² 23.0m² 15.2m² 20.0m² 11.2m² 5.1m² 13.0m² 13.2m² 4.6m² 10.4m² 4.5m² 13.0m² 12.8m² 18.5m² 16.5m² 15.5m² 15.7m² 23.0m² 15.2m² 20.0m² 11.2m² 5.1m² 13.0m² 13.2m² POSTIVE SPACE OPERATIONS SHEAR AND MERGE RENDERED VIEW FINAL AGGREGATION OF BLOCKS

DUNES

ARTICULATED GROUNDS 20.101 ARCHITECTURE CORE STUDIO 1 > SPRING 2023 > CHRISTINE YOGIAMAN, CARLOS BANON > INDIVIDUAL WORK

DUNES was formed as a product of the combination of 4 operations: folding, bending, cutting and twisting. This articulated surface performs as a field of transitions between various types of spaces.

The undulating surface, reminiscent of desert dunes, forms a permeable aggregation that burrows and floats through the earth. Vertical extrusions that appear to emerge from the ground create continuity, creating a continuous fabric, yet it delaminates the surface and articulates pockets of space.

With a mix of open and closed spaces, a variety of uses can be accommodated, from public gathering spaces to intimate personal spaces. Pedestrian circulation routes run along the openings to facilitate passage across, or up and down the slopes for vantage points and views of the surface. The diversity of forms and textures creates a fun and interactive environment for the young and old.

08

Exploration using 2 methods, namely cutting and bending, in an attempt to hide the edges of the paper

Physical Model

Digital Model

Re-attempted idea of hiding the edges of the paper, but only using 1 method (bending).

Combined “cavities” of different sizes to create irregularity

Further explored possibilities of forming such curves and cavities, using small slits along the edge

Looping of edges and connecting them to the main structure, twisting them in various ways to avoid symmetry

Merging of model to a surface of the ground to study its relationship and observe possible

DESIGN PROCESS

Created a frame for the model to be partially submerged into the ground, forming a more continuous surface

Creation of base unit

Initially used revolve, however this method was limited as it only allowed for the creation of an uniform cavity

Method: drawing out 3-4 curves, which form the cavity, followed by lofting them together Revolve

Changing angle of starting curve relative to direction of loft and altering of base curve to create more diverse looking cavities

DUNES

Construction of more elaborate cavities but still using the same method of drawing curves and lofting

Piecing together individual unit pieces, understanding the geometry of the form

Exploring ways of enclosing spaces that may be more challenging to do on the physical paper. One such area was the gaps in the interior of the model

Usage of MatchSrf and Sweep2 to form smooth transitions

Finalised integration of model into surface, tucking in rough edges and creating a seamless landscape

TANG JIA JUN (1005897) 20.101 CORE STUDIO 1

EX 1: ARTICULATED GROUNDS

Itr. 4 Itr. 5 Itr. 6 Itr. 7 E d i ts
Top View Top View Perspective Perspective Perspective Perspective DUNES EX
BRAYDEN
JUN (1005897) 20.101
1
Itr. 2 Itr. 1 Itr. 3 E d i ts
1: ARTICULATED GROUNDS
TANG JIA
CORE STUDIO
Loft
Top
Perspective
View
BRAYDEN
SECTIONS
AXONOMETRIC DRAWING FOLDING PROCESS

PADDYBUDDIES

PADDYBUDDIES is a vertical community garden designed to address food security challenges aligned with Singapore’s 2030 goals and contribute to mitigating mental health problems.

The project’s ethos is to engage the community, engage users in assembly process, and cultivate their garden. These structures shall be conceived as rapidly deployable farming modules that can be installed on HDB’s unprogrammed common spaces.

The design was influenced by the forms of paddy fields and Golden Mile Shopping Centre, where we wanted to create staggered tiered surfaces for the plants, so as to maximise the use of the floor space as well as maximise the sunlight received by the plants.

My team identified 2 key narratives which informed us on the shape of our structure as well as its placement in the plan view. Following which, with the application of Ladybug, which is a Grasshopper Plugin that allows for the application of environmental data, we were able to simulate sunlight, allowing us to determine the areas which experience the most sunlight and which areas have the least. From this data, we oriented the structure in a manner to optimise the amount of sunlight received.

For this project, I worked on the form generation using Grasshopper and the physical model .

09
DESIGNING ADAPTIVE PRODUCTIVE GARDENS 10.024 SPATIAL DESIGN WORLD 10.022 MODELLING UNCERTAINTY > FALL 2022 > ANNA TOH, JACKSON TAN > GROUP WORK

BLK413SAUJANAROAD SITE

Our design was our geometric exploration of wireframe models was influenced by stepped silhouettes and organic curves. We extracted the curved geometry and iterated it to generate the surfaces and define spaces.

1.5 PLANT ANALYSIS

1.5 PLANT ANALYSIS

1.5 PLANT ANALYSIS

SUNLIGHT EXPOSURE ANALYSIS

Based on the structural analysis of sunlight exposure and the evaluation of the growing conditions for different types of plants, our team decided that the following plants were the most desirable to be grown in the garden, which are split into 3 to determine the arrangement of the plants, ranging from the areas with greatest to the least sunlight:

We did a sunlight analysis for 2 days, 21 June 2022 and 21 December 2022, where the sun was the strongest and the weakest respectively. In our plant analysis, we noted 3 plants with different growing conditions in terms of sunlight. We evaluated the amount of sunlight exposure at various areas of the model, and concluded that our model was effective in evening out the distribution of the plants, whereby there would not be a case where there is a cluster of the same plant, as shown in the figure above.

ALLOWING FOR VARIATION IN PLANT DISTRIBUTION KALE

>6 HOURS OF SUNLIGHT

Based on the structural analysis of sunlight evaluation of the growing conditions for different types of plants, our team decided that most desirable to be grown in the garden, which are split into 3 to determine the ranging from the areas with greatest to the least sunlight:

1

Index 1 >6 hours of direct sunlight

Index 2 4‐6 hours of semi‐direct sunlight

Based on the structural analysis of sunlight exposure and the evaluation of the growing conditions for different types of plants, our team decided that the following plants were the most desirable to be grown in the garden, which are split into 3 to determine the arrangement of the plants, ranging from the areas with greatest to the least sunlight:

Index 3 ~4 hours of minimal direct sunlight

OKINAWA SPINACH 4-6 HOURS OF SUNLIGHT

Throughout the year, the areas that are colour‐coded yellow and orange will be populated with the greatest amount of sunlight exposure, which are Kale. This would then be followed by Okinawa purple areas, and Cincau at the blue areas with minimal sunlight exposure. All the plants chosen are of low maintenance, requiring only moderate amounts of water (2 times per week) so that the gardeners do not need to worry the plants frequently. We can then maximize the number grown alleviates the problem of food security.

CINCAU

~4 HOURS OF SUNLIGHT

GENERATING OVERALL GEOMETRY

STANDARDIZED VALUES

NUMBER OF SECTIONS (5), SUPPORT WIDTH (0.05), SUPPORT HEIGHT (0.6), CELL HEIGHT (0.3), PERCENTAGE OVERLAP (30%), PATH AMPLITUDE (2)

The drawings above were done using Grasshopper, where we first defined the diagonal and boundary paths for the site, which is our design requirement based on the user narratives. The diagonal path is 1.2m wide, and it has a "Path Amplitude" slider to adjust its curvature, while the boundary path is a 1.0m path which is fixed around the perimeter of the site.

Index 1 >6 hours of direct sunlight

Throughout the year, the areas that are will be populated with plants that require the greatest amount of sunlight exposure, then be followed by Okinawa Spinach at the purple areas, and Cincau at the blue exposure. All the plants chosen are of low maintenance, requiring only moderate amounts of water (2 times per week) so that the gardeners do not need to worry about making time to water the plants frequently. We can then maximize the number of plants that can be grown at any period, which alleviates the problem of food security.

PLANTS INDEX 3 CATEGORIES OF SUNLIGHT REQUIREMENT

Index 2 4‐6 hours of semi‐direct sunlight

Index 3 ~4 hours of minimal direct sunlight

B1: 0.384 B2: 0.483 B3: 1.000 T1: 0.048 T2: 0.879 T3: 0.282 B1: 0.186 B2: 0.290 B3: 1.00 T1: 0.160 T2: 0.704 T3: 1.000 B1: 0.275 B2: 0.356 B3: 1.000 T1: 0.327 T2: 0.467 T3: 0.827 B1: 0.384 B2: 0.483 B3: 1.00 Standardized values: No. of Sections (5), Support Width (0.050), Support Height (0.6), Cell Height (0.3), Percentage Overlap (30%), Path Amplitude (2)
T1: 0.327 T2: 0.467 T3: 0.827
PLANTER MODULE UNITS 3 TIERED STACKABLE PLANTERS
reachability planters top, reachability levels,
SUNLIGHT
Summer Solstice – 21 June Winter Solstice – 21 December
or wheelchair users, can still access the planters at the bottom. 1.6.2
EXPOSURE
‐ Index 1  ‐ Index 2  ‐ Index 3 SUMMER SOLSTICE - 21 JUNE - INDEX 2 - INDEX 1 - INDEX 3 WINTER SOLSTICE - 21 DECEMBER
Index 1 Index 2 Index 3
Kale Okinawa Spinach Cincau
1.6 IMPLEMENTATION (TASK 2C) 1.6.1 REACHABILITY Index sunlight Index sunlight Index direct sunlight
Index
Index
Index
Kale Okinawa Spinach Cincau
2
3
1.6 1.6.1
Kale
Index
Index
Index
Throughout the year, the areas that are colour‐coded yellow
will be populated with plants that require the greatest amount of sunlight exposure, which are Kale. This would then be followed by Okinawa Spinach at the purple and Cincau the blue with minimal sunlight All the plants chosen of low
Okinawa Spinach Cincau
1
2
3
and orange

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