Instructor: Yannis Orfanos, Harvard GSD Research Associate
Max Enrollment: 15
Date/Time: Jan 7, 8, 9, 12, 13 and 14 /11 a.m.-1 p.m.
Location: Gund 510
The course is about integrating data from infrastructure systems in algorithmic modelling at urban scale. While our understanding of contemporary cities is powered from data and information technology tools, that data has to reflect systemic qualitative criteria. Therefore, an additional fundamental understanding of the basic urban systems is needed. This course will offer an introduction to this dialogue by providing a framework to integrate data from four urban infrastructure systems (water, energy, food, and solid waste) through the lens of sustainability.
The course is focused on data for urban algorithmic modelling in Grasshopper. Students that practice or are interested in urban algorithmic modelling will learn what kind of data can be related with spatial parameters. Participants are encouraged to expand the set of parameters that they use to model urban environments. Modelling can have various applications, like data-driven analysis, computational design, or performance simulation.
The learning process includes an introduction to the basics of each infrastructure system (based on the research findings from the Zofnass Program for Sustainable Infrastructure in GSD), identification of the quantifiable components of the system that entail urban/spatial qualities, and designation of their relations within the system. Finally, sample simulations will be exercised in order to see the performance of the data framework.
The course is comprised of 6 classes:
Day one: introduction to infrastructure systems, data frameworks, and urban algorithmic modelling with Grasshopper
Day two: integrating data from the water infrastructure system
Day three: integrating data from the energy infrastructure system
Day four: integrating data from the food infrastructure system
Day five: integrating data from the solid waste infrastructure system
Day six: synergies between infrastructure systems
1. Introduction to the basic components of the system and their quantifiable relations.
2. Establish an organizational framework for integrating data from infrastructure systems in urban algorithmic modelling.
3. Provide basic knowledge to simulate scenarios
Requirements: Basic knowledge of Grasshopper is preferred but not necessarily required. Experience on urban data quantification is expected. Laptops recommended.