The MaCAD is a unique online programme training a new generation of architects, engineers and designers ready to develop skills into the latest softwares, computational tools, BIM technologies and AI towards innovation for the Architecture, Engineering and Construction (AEC) industry.
Predicting Building Energy Performance: A Machine Learning Approach to Energy Use Intensity (EUI) In the world of sustainable architecture and building design, understanding energy consumption is crucial for creating efficient, environmentally responsible structures. Energy Use Intensity (EUI) serves as a fundamental metric that tells us how much energy a building consumes per square meter per … Read more
In the ever-evolving world of architecture, Hyper A is an exploration into the limits—and freedoms—of structural design. We, the Structure Team, consisting of Joaquin Broquedis and myself, Marco Durand, are excited to present the structural concept that supports not just a building, but a multi-neighborhood urban vision. This blog offers a deeper look into our … Read more
Introduction As the Data Team, we didn’t produce any geometry. Instead, we focused on creating a data infrastructure that enhances collaboration between all design teams. Our primary goal was to streamline information flow, validate data integrity, and provide meaningful metrics that inform the design process. The Birth of our Holistic Approach One of the tacit … Read more
Hyper-B Residential team went through design concept, technical analyses, and integrated modeling process to create a detailed architectural documentation of four residential towers. In addition, the project covers various aspects including energy consumption, occupancy, and modular unit types. We approached this project with a goal that incorporates sustainable energy practices and efficient space planning with … Read more
Introduction The Data team’s role in the Hyper A project is to calculate the performance metrics of each Design Team. Each Design Team provides the Data Team the component values for needed to calculate their metrics. These component values are cumulative for their entirety of their design. For example, the Industrial Team’s Primary Metric is … Read more
Overview PaperLink WIP – This study specifically explores Physics-Informed Neural Networks (PINNs) and Computational Fluid Dynamics (CFD) to analyze pedestrian wind comfort. It aims to integrate these neural network models into a web application using Three.js and other tools. By utilizing data from OpenWeatherMap, and OpenStreetMap, the project aims to support real-time simulations and visualizations … Read more
Research Questions: Can climate sensitive facade interventions reduce the intensity of the Urban Heat Island effect within urban blocks in arid climates?“ Research Goal: The goal is to propose simplified, climate-sensitive facade interventions in highly urbanized cities that reduce energy loads by mitigating Urban Heat Island (UHI) effects, while complying with climate-resilient regulations. These interventions … Read more
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
We embarked on a fascinating journey through the latest advancements in Image Synthesis and Language Models within the Architecture, Engineering, and Construction (AEC) industry. The course highlighted the transformative potential of generative AI, enabling architects, engineers, and designers to push the boundaries of traditional design processes, streamline workflows, and tackle complex challenges in groundbreaking ways. … Read more
Skin Sense is a project that aims to help users optimize the thermal comfort of their interior spaces by applying skin shaders. Why implement this? What can skin sense help the user with? Once the designer designs the skin for the building facade it has to be analyzed for indoor comfort. To analyze indoor comfort … Read more
Block Classification This project aims to classify urban blocks in Barcelona, focusing on the districts of Saint Martí and Eixample, based on their dominant functions. By identifying the primary uses of these urban blocks, we can gain insights into the spatial organization and functional distribution within the research area. Saint Martí and Eixample, two vibrant … Read more
DF Predictor aims to revolutionize daylight prediction in architectural design by implementing the conditional generative adversarial network (cGAN) Pix2Pix to predict daylight factors, motivated by the need to improve efficiency and accuracy in daylight analysis. Daylight factor analysis, an integral part of the early design stages and mandated by building codes, is typically lengthy due … Read more
Introduction Accurate prediction of rental prices poses a significant challenge in dynamic real estate markets such as Amsterdam. Our research project explores the use of graph-based machine learning to improve the accuracy of such predictions. This methodology could be of interest to various actors in the real estate sector, including brokers, investors, and urban planners. … Read more
Studying migration is crucial for urban planners and architects to anticipate and accommodate the influx of people into cities, ensuring the development of robust infrastructure that can support this growth. As migration patterns shape demographic changes, understanding these trends allows cities to plan for adequate housing, transportation, healthcare, and educational facilities. This foresight is essential … Read more
Who Why: For the Amenities, we selected the following due to its overall correlation with residential real estate and we anticipate that it will give a good indication of how the properties would be priced. By creating bounding boxes around the amenities, with a radius of 1km, we ensure that as much of the graph … Read more
Abstract 3D-SOLIDS Component Classification tool utilizes machine learning to optimize the placement of essential 3D components such as walls, doors, windows, floors, and railings in residential floor plans. By analyzing spatial features and architectural attributes, it automates and enhances the design process, ensuring accuracy, consistency, and compliance with building standards. This tool aids architects and … Read more
