Choo Ee Pin Portfolio 22-24

Portfolio 2024

Selected works

Choo Ee Pin

Research Assistant, CITA Master of Arts (MA) in architecture

BUILDINGS OF THESEUS

A cyclical assembly and disassembly of non-standard timber structures with timber joints 2021- 2022

Choo Ee Pin

Master thesis

Denmark : KADK : CITA

This research explores a novel computational design method for the multiple reconfigurations of timber structures and components to extend its material life cycle.

Objectives: (1) explore the use of computer vision to track, evaluate and machine timber elements (2) explore timber joints that are reconfigurable and multi-functional.

Prototype 4. Using computer vision to detect and identify joints and its orientation in real time.

[1]: Prototype 2. [2,3,4]: Prototype 1. [5]Prototype 4. Markings that informs dis/assembly of parts. [6] Computer vision identifying key features and matching it on another image of the same part.

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[1]: Prototype 3. Old parts are re-machined and combined to form more complex joints [2]: Render. [3,4]: Joints hold information of where it came from. [5]: Complexity and modularity of joints allow these parts to stay relevant, extending its potential life cycle.

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[6, 7]: Rendering. As the site changes, so does the building by reconfiguring, re-machining existing parts. By allowing elements to evolve, we can change their function, extending its life span. [8] Prototype 1.

Timberstructurebuiltwithfiberorientedgluelaminatedtimber.Structurewasbuiltwithtimbertimberjointsthat couldbedisassembled.Thisstructurewasusedtostudytheeffectsofweatheringonjointsandfiberorientedtimber.

[1,4]:Newelementsaddedtothestructureusing3Dscanningmethodstoobtainfabricationdataofthejoint.[2]: Simpleassemblywithonlytimberconnections.[3,5]Openendedjointstoanticipatestructureextension.

Planningandcuttingof timberboardsforlamellausedintheFiberorientedgluelaminatedtimber.

PlanningfiberorientationwithintheGLT basedonsimulationsandstructuralrequirements.

FeaturedetectionusingComputervisionandmachinelearning.Segmentationwasperformedtoidentifyregionsof interest.Theseareasaremaskedandsendtoamodeltobeidentified,valuesshownabovearethemachines'confidence inthatfeature.