ADVANCED STEREOTOMIC   
Computational descriptive geometries

“Stereotomy” is the art and science of cutting three-dimensional solids into particular shapes. Formulated in the 16th–17th century, stereotomy is valuable in contemporary architecture, and research about it continues today in various centers around the world. The reason for this is a sense of constructive rationalisation inherent to the discipline of stereotomy which permits the optimization of structural form through the knowledge of geometry and cutting techniques and to simplify it using advanced technologies and techniques for design and production of building elements.  

The course will focus on the design of shell structures with discretised building blocks for 3d printing technology. With the help of computational design workflows and optimization processes, we will deal with form finding exploration with live physics simulations, FEM analysis and stereotomic subdivision for the production of rationalised interlocking structural elements that can self-support structural loads. 

Learning objectives

• Understand fundamentals of computational design
• Be introduced to logical algorithm thinking 
• Have knowledge of basic concepts of generative design
• Be capable of generating parameterised processes
• Learn how to create dynamic modelling and fabrication workflows
• Learn basic concepts of funicular structures and basic structural analysis methods
• Learn about  Stereotomic subdivision and voussoirs generation

FACULTY: Rodrigo Aguirre // IAAC Computational Design Expert
FACULTY ASSISTANT: Ashkan Foroughi // IAAC Computational Designer

Full Syllabus & Schedule 

DESIGN FOR ROBOTICS 
Fabrication through remote controlled robots

Although reusing reclaimed material can significantly reduce the environmental impact in building construction, current design processes are not set up for this shift in thinking. Contrary to conventional practices, designing within the constraints of available material means that geometry and topology cannot be fully pre-determined. What if an industrial robotic arm had to perform different tasks in unknown environments? 

In order to challenge the conventional conceptual framework posed by notational systems, this workshop will focus on the design and fabrication of 2D no-standardised elements, offering the opportunity to develop experience on working with robotic sensor data and integrate the data into the computational design. The students will explore different design intentions through the definition of performance criteria parameters, which are constantly evaluated and adjusted in real-time.  The application generated at the end of the workshop will be the assembly of a mosaic using recycled leftover pieces where the closed-loop system will guide the robotic arm to choose the right piece in each step of the process. Participants will have the unique opportunity to remote control robots in IAAC and will learn about the necessary technology to execute the project while having the possibility to design and make their own assembly processes.

Learning objectives

• Be introduced to integrated computational design and robotic fabrication
• Be introduced to robotic fabrication
• Learn the concepts of sensor feedback and machine vision
• Learn how to perform online robotic control methods

FACULTY: Soroush Garivani // IAAC Robotic Fabrication Expert
FACULTY: Seyed Mobin Moussavi // TWE and EDEK Robotic Fabrication Expert

Full Syllabus & Schedule 

URBAN ANALYTICS
Understanding cities through big data mapping

Data is everything, and is everywhere. From our social interactions to the way we work, there is not a single moment of our days that isn’t propelled nor generating some sort of data. These bits of information have saturated our cities radically transforming their productive sectors, and are now food for training models and AI, which are promising to drastically alter our perception of society. It became clear that quantity does not stand quality and data ownership, interoperability, scalability, and – more important – objectivity are key topics around which the future is currently being debated. 

These challenges call for designers and creative thinkers to reconsider our interactions with data. They demand innovative solutions that hack the current status quo and switch the paradigm from a mere bits-to-product extraction to a real citizen empowerment. Participants will be introduced to geospatial data analytics with a specific focus on the understanding and representation of urban patterns, following the question of what is the nature of the city through the lens of its services and urban fabric. 

Main tools: Rhinoceros, Grasshopper 3D.

Learning objectives

• Manipulate and combine data from different data source and data typologies
• Set up a flexible protocol to analyse different urban contexts in the world
• Learn the fundamentals of APIs
• Learn how to creatively represent geospatial data and how to create a web map

FACULTY: Iacopo Neri // IAAC Computational Urban Design Expert
FACULTY: Eugenio Bettucchi // IAAC Engineer & Computational Design Expert

Full Syllabus & Schedule

ENVIRONMENTAL DESIGN   
Computational modelling and simulations

Over the last years, sustainability has become a key topic in the architecture, engineering, and construction industry. Professionals involved in AEC have the opportunity to impact change within the environment, and thus the responsibility to do so from a standpoint of knowledge and diligent evaluation. Aligned with the necessity for performance-aware design, a growing suite of environmental analysis and simulation tools are developed and readily available within mainstream CAD frameworks. Literacy around environmental data analysis and the ability to use environmental simulation as drivers of the design process is key to the toolset of the emergent architects, urban planners, and decision-makers. This workshop aims to take students through the complete workflow of evidence-based environmental design supported by a generative optimization framework to enable the exploration of vast design spaces.

Starting from the analysis of an existing unused plot or a site selected for rehabilitation, students will formulate the design problem, develop an optimization hypothesis, parametrically explore the wide solution space and propose an optimal solution supported by data. This hands-on investigation will enable students to apply state of the art analytical techniques to complex problems in real context.

Learning objectives

• Learn key concepts of environmental analysis using parametric tools
• Understand concepts of multi-objective optimization
• Understand how to define sustainability goals as measurable design parameters
• Learn to setup a generative optimization process
• Be capable to perform multi objective optimization on a parametric model
• Be able to set out an optimization strategy on a given problem

FACULY: Oana Taut // IAAC Computational Design Expert
FACULY ASSISTANT: Ivan Marchuk // IAAC Computational Designer

Full Syllabus & Schedule