Generative Urban Design // MaCT 2020/21 Seminar Results

Each year the students of the Master in City & Technology are introduced to a large variety of technological tools and software that are imperative for the multi-scalar representation and understanding of the urban environment. During the program, students are trained on the latest tools for computational design, urban simulations, and spatial data science by attending seminars on programming, dynamic mapping, big data analytics and visualization, as well as parametric urban design.

Here are some of the results from the Computational Urban Design III seminar, conducted during the third term of the Master in City & Technology 2020/21 and led by Milad Showkatbakhsh, the co-founder of the evolutionary, multi-objective optimization and analytic engine for Grasshopper 3D, Wallacei.

Wallacei for Grasshopper 3D


Seminar faculty: Milad Showkatbakhsh

The seminar introduced the students to the concept of multi-objective optimization and its application in urban design. It provided them with the necessary knowledge of how computational design can draw inspiration from evolutionary principles which are found within the field of biology. The goal is to expose such parallelisms and create innovative urban planning and design methodologies, which combine the inherent abstraction and ambiguity of design with the deterministic, calculable and rule-based processes of evolutionary processes.

This course is the third part of a 3-course-long investigation on how the combination of big data & computational design not only makes it possible to explore, analyze and evaluate cities but also to generate multiple design solutions for the urban environment, thus making it easier and faster for urban designers to draw insights and thus make informed decisions at every stage of the problem-solving process.

To fully exhibit the capacities of Wallacei to manage the complexity that the local context can bring to an urban project, the students focused on 7 different cities (London, Manhattan, Venice, Yazd, Hong Kong, Barcelona and Delhi). Below you can find more information about each project:

1) London

The London Green Links project aims to optimize the city’s urban fabric by providing more green space and improving connectivity between blocks with green pedestrian links. 

This is achieved by a series of computational operations which explore many options, compare them and look for the best optimal solution. The main tools used in this optimization are Grasshopper and Wallacei X plugin for the optimization process.

You can see the full documentation here:
http://www.iaacblog.com/programs/london-links/

Project Name: London Links
Students: Leyla Saadi, Marta Galdys, Sridhar Subramani

2) Manhattan

The London Green Links project aims to optimize the city’s urban fabric by providing more green space and improving connectivity between blocks with green pedestrian links. 

This is achieved by a series of computational operations which explore many options, compare them and look for the best optimal solution. The main tools used in this optimization are Grasshopper and Wallacei X plugin for the optimization process.

You can see the full documentation here:
http://www.iaacblog.com/programs/manhattan-development-urban-tissue/

Project Name: Manhattan | Development of Urban Tissue
Students: Kshama Patil, Simone Grasso, Sinay Coskun, Stephania-Maria Kousoula

3) Venice

This project explores the potential of generative evolutionary algorithms in redesigning the city of Venice. Venice has been facing many challenges over the years due to the sea level rise and increased touristic pressure. Consisting of 118 small islands that are separated by canals and linked by over 400 bridges, the city’s urban fabric is quite unique and can easily be described by waterchanels, irregular street networks and dense urban tissue.

You can see the full documentation here:
http://www.iaacblog.com/programs/venice-2-0/

Project Name: Venice 2.0
Students: Hebah Qatanany, Laura Guimarães, Dongxuan Zhu, and Arina Novikova

4) Yazd

“Court Yadz city: A vernacular architecture” is a machine learning project to virtually generate a district of the old town of Yazd. It recreates the key elements of this old town with its narrow streets, vegetalised courtyard and wind protection orientation. The project is an urban design program based on Grasshopper, Wallacei X  and Self-Organized Map algorithm.

You can see the full documentation here:
http://www.iaacblog.com/programs/court-yadz-city-vernacular-architecture/

Project Name: Court Yadz city: A vernacular architecture
Students: Adriana Aguirre Such, Alvaro Cerezo Carrizo, Iñigo Esteban Marina, Tugdual Sarazin

5) Hong Kong

The simulation of New Hong Kong had the aim to optimize the characteristics of Hong Kong focusing on specific objectives. The heat island effect, the light pollution and the citizens’ mental health are the 3 main challenges identified. The utilization of the evolutionary multi-objective optimization engine for Grasshopper 3D Wallacei allowed not only to generate different scenarios, but also provided the detailed data to analyze the different outputs supporting any decision making process.

You can see the full documentation here:
http://www.iaacblog.com/programs/new-hong-kong/

Project Name: Simulating New Hong Kong
Students: Aishath Nadh Ha Naseer, Diana Roussi and Riccardo Palazzolo Henkes

6) Barcelona

The expected growing population in Barcelona and the lack of places to live creates a scenario of opportunity where  Plug-In Barcelona aims to add density without modifying the current urban morphology by the plan Cerdá and maintaining the quality access to environmental elements such as wind and solar radiation to the original buildings.

You can see the full documentation here:
http://www.iaacblog.com/programs/plug-in-barcelona/

Project Name: Plug-In Barcelona
Students: Sasan Baharami, Juan Pablo Pintado, Mario Gonzales & Iván Reyes

7) Delhi

The aim of the project is to explore the different possible solutions for the transformation and optimisation of the urban tissue of Delhi North East with Wallacei. The tool based on the biological principles of evolution, allows the analysis and the design of those solutions. The optimisation was based on the problems faced by the city, such as the lack of public space, the uncontrolled increase in population and the lack of basic services such as water.

You can see the full documentation here:
http://www.iaacblog.com/programs/delhi-restatement/

Project Name: Delhi Restatement
Students: Miguel Tinoco, Matteo Murat and Kevin Aragón

Written by
Alex Mademochoritis
Urban Technologist
MaCT Coordinator & Faculty | AAG Urbanism & Big Data


 

Are you interested in taking part in this research? Don’t miss out on a once-in-a-lifetime opportunity to study the future of cities in Barcelona, the birthplace of urbanism!

Find out more about the Master in City & Technology:
www.iaac.net/mact