Techne W3: Structure

TECHNE: W3 – STRUCTURE workshop asks students to examine the structural behaviors inherent in 3D printing with clay and earth. Our goal for this week’s workshop was to print the tallest single and double surface structure that will be assessed against performance metrics such as toolpath length, print volume, print time, weight, collapse height, and … Read more

Techne W2: Machine

The Techne 02 machine workshop, is meant to introduced students and part of the research team into the different print methodologies of 3D clay printers. Part of the workshop explores different nozzle sizes, seam strategies, and even geometries, that can be created with a simple cylinder. The purpose is to explore height, and geometrical difference … Read more

Techne W6: Volume

In Valdaurra Labs, the design of 3D-printed earth walls needs to incorporate strategic grid/period deformations to optimize for natural light and ventilation. By adjusting the curvature and openings in these periods and grids, the structure allows for more sunlight to penetrate while improving airflow and maintaing the building cool. This strategic deformation allows for play … Read more

Polykatoikia advisor

abstract This thesis presents an experimental approach that enables architects to automatically generate and rank multiple building layouts based on specific metrics, focusing on the Polykatoikia—the prevalent multi-story residential building type in Greece. By applying graph theory, architectural spaces are conceptualized as nodes, and their relationships—such as adjacency—are represented as edges. The graph offers a … Read more

Urban Insights: Leveraging Open Data for Smart Property Rate Predictions

1.0 Concept In the evolving landscape of urban development, property rates are influenced by numerous factors, including geographical, socio-economic, and infrastructural elements. Our project, “Urban Insights: Leveraging Open Data for Smart Property Rate Predictions,” aims to create an intelligent, data-driven model to forecast property rates. This model utilizes features such as wards, property types, and … Read more

SafeNet: Network-Driven Machine Learning for Urban Safety

Abstract This study examines the pressing problem of violence against women in Mexico City, focusing specifically on strategies to prevent the escalation of violence that can lead to femicides. The persistence of gender-based violence in the city is aggravated by socioeconomic disparities, inadequate urban planning, and a deficiency of safe public spaces. The notable increase … Read more

Design as Grammar – Utilizing Graph ML for Modular determination

In a world driven by digital transformation, the realm of architecture and design faces new challenges in achieving flexibility, scalability, and efficiency. One of the most pressing issues is modular determination—how do we ensure that modular structures fit together seamlessly, across various design patterns? Design as Grammar addresses this by leveraging Graph Machine Learning (Graph … Read more

BIMConverse – GraphRAG for IFC Natural Language Queries

Introduction BIM and Cloud Adoption The construction industry is still experiencing a digital revolution led by the widespread adoption of Building Information Modeling (BIM) and cloud computing technologies. BIM has established itself as the central tool for the digital planning, construction and management of buildings, while cloud computing is transforming collaboration and data access. Studies … Read more

Democratizing Design

Abstract As we advance into the 21st century, addressing the global housing crisis becomes imperative. By 2025, approximately 1.6 billion people will lack adequate housing, necessitating the construction of 96,000 affordable homes daily to meet the demand of 3 billion people by 2030 (Masterson, 2022). Urban areas, which now host over 50% of the world’s … Read more

C.O.M.F.O.R.T

City-Oriented Modeling for Observational Radiative Thermal comfort CONCEPT The idea behind C.O.M.F.O.R.T is to provide an effective tool for architects and urban planners to design cooler and more sustainable cities, leveraging the power of machine learning and AI technologies. FACTORS OF IMPACT To create COMFORT we had to study the different factors of impact which … Read more

Pix2Daylight

Daylight autonomy is a climate-based metric that measures the percentage of occupied hours during which a given space receives a specific amount of light, typically 300 lux, through natural daylight alone. It is used to evaluate energy efficiency in building designs by evaluating how much artificial lighting can be reduced throughout the year (Lorenz et … Read more

REVITvoice

Vocal Commands for Autodesk Revit Problem Despite decades of technological advancement, the core user experience between man and computer has remained nearly unchanged. This tedious and repetitive process requires designers to spend extreme amounts of time that could be saved through updated methods. This thesis explores a potential future for computer user experience, utilizing AI … Read more

Mediación de la Paz Urbana: Ideando un Campus-Parque para la Auto-Fabricación en San José de Costa Rica, CA.

La formulación de la paz es imposible para el consenso de las masas actuales. Esta misma perspectiva es igualmente negativa en el país que inició el desarme de sus tropas después de la dolorosa II Guerra Mundial y una sangrienta Guerra Civil en 1948, esta es Costa Rica. Una utopía en las américas, una deformada … Read more

Thermal Insight: Optimizing Indoor Analysis

Thermal Insight would be a standalone app that optimizes indoor environments by predicting thermal comfort. With simulations from trained models to help enhance occupant comfort and energy efficiency, evaluating metrics like PMV, PPD, and MRT. This tool would help improve well-being and productivity while achieving efficiency goals. Abstract Methodology Use Case Data Analysis Results and … Read more

Vehicle Crash Prediction in New York City

Project Aim In this project we aim to predict the type of vehicle crash that can be foreseen in the city of New York based on the traffic volume, using Graph Neural Networks (GNNs). To develop this machine learning model we use 3 different datasets. The model could hold potential if developed further, to be … Read more

Predicting optimal layout configurations for sustainable heritage shophouses

Our project aims to determine suitable workstation arrangement for office typology in a conservation shophouse in Singapore through maximise daylight on the worksurface to achieve 300 lux (to a maximum of 3000 lux) for good lighting condition. In a conservation shophouse, where the building envelope and facade cannot be altered. There are two daylight sources … Read more