94160 - AFPG -Lab-based Course OF GENERATIVE SHAPE DRAWING THROUGH PARAMETRIC ALGORITHMS

Learning outcomes

The course introduces students to the principles of algorithmic and parametric design applied to architecture.

By the end of the course, students will understand how an architectural project can be described and developed through rules, geometric relationships and numerical parameters. They will be able to construct digital systems that generate and control different design configurations and evaluate the effects produced by changing their parameters.

Students will also be able to:

• translate a design intention into a logical sequence of operations;
• establish relationships between geometry, data and numerical parameters;
• generate families of solutions rather than isolated static forms;
• control geometric variations, modular systems and complex surfaces;
• integrate three-dimensional modelling, parametric design and environmental analysis;
• critically select and evaluate generated configurations;
• clearly document and communicate the generative process and its architectural outcome.

Course contents

The 30-hour course addresses the foundations of computational and parametric design through theoretical introductions, demonstrations, guided exercises and laboratory activities.

The principal topics include:

• introduction to algorithmic thinking and parametric design;
• differences between conventional modelling and the construction of generative systems;
• representation of a design through rules, relationships and operational sequences;
• use of data and numerical parameters to control geometry;
• construction and transformation of two- and three-dimensional geometries;
• relationships between points, curves, surfaces and volumes;
• development of systems of geometric variation;
• generation of families of design solutions;
• use of mathematical functions and fields of influence;
• development of patterns, modules, panelisation systems and architectural envelopes;
• discretisation and rationalisation of complex surfaces;
• integration of different digital modelling environments;
• introduction to simulation and dynamic geometric transformation;
• use of climatic and environmental data as design parameters;
• preliminary analysis of sun paths and solar exposure;
• critical evaluation of generated alternatives;
• organisation and representation of algorithmic processes;
• development of a final parametric design project.

The final project requires students to define an architectural system controlled through numerical parameters. Students must communicate its generative rules, possible variations, selection criteria and final architectural outcome.

Readings/Bibliography

Mario Carpo, The Alphabet and the Algorithm, The MIT Press, 2011.

Mario Carpo, The Second Digital Turn: Design Beyond Intelligence, The MIT Press, 2017.

Arturo Tedeschi, AAD—Algorithms-Aided Design: Parametric Strategies Using Grasshopper, Le Penseur, 2014.

Ming Tang, Parametric Building Design Using Autodesk Maya, Routledge, 2014.

Teaching methods

The course adopts a practical, laboratory-based approach combining theoretical introductions, live demonstrations, guided exercises and design applications.

Activities follow a progressive structure, beginning with relationships between geometry, data and numerical parameters and leading to the construction of more advanced algorithmic systems.

Students develop a series of exercises and a final individual or group project, supported by regular tutorials. Particular attention is given not only to software operation, but also to understanding the underlying design logic, consciously modifying the rules of a system and critically evaluating the generated results.

Assessment methods

Learning is assessed through the presentation of a final project and an oral discussion.

The project may be developed individually or in groups, in accordance with the instructor’s guidelines. During the examination, however, each student must individually demonstrate an understanding of the project’s algorithmic logic, the role of its parameters and the consequences of the introduced variations.

Assessment considers:

• clarity of the design principle and generative rules;
• correct definition of relationships between data, parameters and geometry;
• functionality and degree of control of the algorithmic system;
• ability of the system to produce coherent variations;
• awareness in selecting parameters and generated solutions;
• consistency between concept, process and architectural outcome;
• integration of environmental or performance-based criteria, where applicable;
• quality of representation and documentation;
• autonomy and critical understanding demonstrated during the oral discussion.

A pass is awarded when the student demonstrates the ability to consciously describe, control and modify the developed parametric process.

Teaching tools

Teaching activities use three-dimensional modelling, algorithmic design and environmental-analysis software, primarily Autodesk Maya, Rhinoceros, Grasshopper and Ladybug Tools.

The instructor also provides presentations, tutorials, digital models, parametric definitions, example files and supporting materials for the exercises and final project.

Office hours

See the website of Nicolas Turchi