AI WORKFLOW AND EXPLORATION

Introduction

For the redesign process, AI was used as a design-support tool rather than a replacement for architectural thinking. The purpose of using AI was to re-evaluate the original Solar Flare project, identify weaknesses, explore alternative strategies, and improve the design through faster testing, visualisation, and critical reflection.

The AI workflow focused on four main areas: environmental performance, spatial planning, user experience, and presentation clarity.

AI TOOLS USED - PURPOSE

Prompt 1: Original Design Critique
“Analyse my student clubhouse project called Solar Flare. The building uses a hexagonal glass façade, solar-responsive form, and student-focused spaces. Identify the strengths, weaknesses, and possible improvements in site response, façade performance, spatial planning, sustainability, and user experience.”

AI OUTPUT

Strengths

Strong solar concept.
Unique hexagonal glass façade.
Good daylight and student-friendly spaces.

Weaknesses

Too much glass can cause heat and glare.
May need more air-conditioning.
Quiet and active spaces need better separation.

Improvements

Add shading, fins, or screens.
Use Low-E/tinted glass.
Improve natural ventilation.
Make the façade useful, not only decorative.

Prompt Examples Used

Prompt 2: Façade Improvement

“Suggest ways to improve a hexagonal glass façade for a tropical university campus. The façade must reduce west sun glare, control heat gain, allow filtered daylight, and maintain a strong architectural identity.”

AI OUTPUT
- Use deeper hexagonal frames to block west sun.

Add vertical/angled shading fins on the west façade.

Use Low-E or tinted glass to reduce heat gain.
Mix glass, solid, and perforated hexagon panels.
Make the west side more solid and shaded.

Use perforated hexagonal screens for filtered daylight.
Add operable panels for natural ventilation.
Use a double-skin façade with an air gap.
Add internal blinds or louvers for glare control.
Keep the hexagonal pattern as the main architectural identity.

Prompt 3: User Experience
“Create a user journey for architecture students using a clubhouse with lobby, exhibition, café, design studio, model room, printing room, reading area, ARCA space, and multi-purpose hall. Identify possible conflicts and improvements.”

AI OUTPUT

User Journey

Enter through lobby
View work in exhibition area
Relax/socialize in café
Work in design studio
Build models in model room
Print work in printing room
Study in reading area
Meet in ARCA space
Attend events in multi-purpose hall

Conflicts

Noise from café and MPH
Crowding at printing room
Dust/noise from model room
Exhibition may block circulation

Improvements

Separate quiet and active zones
Place café/MPH near public area
Keep reading area quiet
Provide wider corridors
Add storage and better ventilation
Use acoustic treatment

Prompt 4: Sustainability Strategy
“Improve the sustainability strategy of a student clubhouse that currently uses daylight, solar orientation, aluminium framing, laminated glass, and a façade air cavity. Suggest passive cooling, material, energy, and landscape strategies.”

AI OUTPUT

Add cross ventilation.

Use deep shading on hot façades.
Improve double-skin façade air cavity.
Use low-E laminated glass.
Use recycled aluminium and local materials.
Add roof insulation / green roof.
Install solar panels.
Use LED lights and sensors.
Collect rainwater.
Add trees and tropical plants for shade.

AI WORKFLOW DIAGRAM

COMPARITIVE EXPLORATION OF AI TOOLS USED

Why AI Tools Were Selected

AI tools were selected to make the redesign process more critical, organised, and reflective. They helped review the Solar Flare project beyond visual judgement by considering environmental performance, user experience, technical issues, and professional responsibility.

ChatGPT supported design analysis and writing, image-based AI helped explore façade and atmosphere options, and diagramming tools helped communicate the redesign process clearly. Overall, AI was used as a support tool to improve design thinking, not to replace human judgement.

How AI Influenced Decision-Making

AI influenced the redesign by shifting the project from a mainly visual façade concept into a more performance-based proposal. It helped question how the hexagonal façade could improve daylight control, heat reduction, ventilation, and user comfort.

AI also helped connect the design more clearly to different user groups, including students, faculty, alumni, firms, and sponsors. However, not every AI suggestion was accepted. Unrealistic, expensive, or unsuitable ideas were rejected, so the final design decisions remained human-led.

How Outputs Evolved Through Refinement

The first AI outputs were broad and general. They suggested many possible improvements, but not all were suitable. The prompts were then refined to become more specific to the project site, tropical climate, student clubhouse function, west sun exposure, and hexagonal façade language.

Through refinement, the redesign became more focused. The final direction was not to completely replace the original project, but to improve it. The revised proposal keeps the identity of Solar Flare, but improves the façade, spatial planning, sustainability strategy, and user experience.

Iterative Design Refinement

The redesign process involved three main versions. Each version improved the Solar Flare student clubhouse by making it more climate-responsive, user-centred, and performance-based.

Version 1: Original Proposal

Characteristics:

▪ Light-responsive student clubhouse concept.
▪ Strong hexagonal glass façade as the main architectural identity.
▪ Curved roof form inspired by solar movement.
▪ Spaces included lobby, exhibition area, café, dining, ARCA spaces, design studios, model-making room, printing room, and multi-purpose hall.
▪ Sustainability focused mainly on daylight, solar orientation, and reduced artificial lighting.

Limitations:

▪ West sun exposure was still a major issue.
▪ Façade performance was not fully tested for glare, heat gain, and ventilation.
▪ Passive cooling strategies were limited.
▪ User journey and zoning needed clearer explanation.

Version 2: AI-Supported Improvements

Changes Introduced:

▪ The hexagonal façade was rethought as a performance system, not only a visual feature.
▪ Varied transparency and denser façade treatment were explored for stronger sun-exposed areas.
▪ Deeper shading was added to reduce glare and heat gain.
▪ The 400 mm air cavity was improved as a ventilated thermal buffer.
▪ Cross ventilation, clearer entrance hierarchy, and better user movement were considered.
▪ Ground-floor spaces were improved for exhibition, café, discussion, and informal gathering.

AI Feedback Used:

▪ AI helped identify missing design layers such as thermal comfort, maintenance, accessibility, and user experience.
▪ AI supported comparison between the original proposal and revised options.
▪ AI helped refine prompts for façade studies, student activity, campus atmosphere, and presentation.

Version 3: Final Improved Design

Final Enhancements:

▪ The final design keeps the Solar Flare identity while improving performance.
▪ The façade becomes a daylight-filtering system with varied transparency, aluminium framing, and ventilated air cavity.
▪ The west façade is improved with stronger shading and denser fritted glass.
▪ The roof can support solar photovoltaic panels and rainwater collection.
▪ Interior spaces are organised more clearly: public social spaces on the ground floor, collaborative learning on the first floor, and focused studio work on the upper level.
▪ Sustainability is expanded through passive shading, ventilation, daylight control, solar energy, rainwater harvesting, and landscape cooling.

Final Refinement Outcome

Through iterative refinement, the project developed from a visually expressive clubhouse into a more complete architectural proposal. AI feedback helped improve façade performance, user experience, sustainability, and design communication while keeping the original Solar Flare concept.

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