Modulating Microclimate 1

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Modulating Microclimate 1

Emnenavn på Norwegian Bokmål:

Modulating Microclimate 1

Credits:

Course code:

40 305

Level of study:

Master

Teaching semester:

2017 Spring

Language of instruction:

English

Required prerequisite knowledge

• Command of English Language (Reading, Writing, Listening, Speaking);
• Working Knowledge in Rhino;

The elective course ‘Modulating Microclimates’ is configured to provide knowledge and skills for the studio course ‘Architecture and Productive Landscapes’.

Course content

The elective course ‘Modulating Microclimates’ is configured to provide knowledge and skills for the studio course ‘Architecture and Productive Landscapes’. The focus is on learning concepts and skills related to environmental data collection and data-driven computational design.

Students will develop further their knowledge in Rhino modeling and acquire related skills in data-driven associative modeling (Grasshopper; see: http://www.grasshopper3d.com/) and in multi-objective optimization (see: https://en.wikipedia.org/wiki/Multi-objective_optimization; and Octopus; see: http://www.grasshopper3d.com/group/octopus/page/octopus-examples).

Students will also learn how to collect environmental data through purpose-configured measure-stations (Arduino; see: https://www.arduino.cc/) and how to feed the collected data into the Rhino environment for modeling purposes.

The elective course will be delivered in three one-week sessions prior to the field trip of the studio course.

Learning outcome

Knowledge
• Knowledge of architectural and computational design themes;
• Knowledge in local microclimate and architectural design;
• Knowledge in data collection and data-driven computational design.
• Knowledge in the utilization of advanced visualization methods;

Skills
• Skills in data collection and the making of weather stations;
• Skills in data-driven computational design;
• Skills in advanced visualization methods;

General competence
• The ability to set up and follow through a design process that leads to the desired result;
• The ability to develop designs based on specific performance criteria;

Working and learning activities

Teaching Activities:
• Lectures on key conceptual and methodological approaches;
• Workshops focused on skill building;
• Hands-on tutorial sessions;

Core thematic foci include:
• Data-collection;
• Data-driven design;
• Associative Modeling;
• Multi-objective Optimization;

The methodological approach encompasses:
• Integration of iterative data-driven Methods, Processes, Information and Analysis;

Work Effort
• 90% mandatory attendance;
• Participation in 3 intense one-week workshop sessions;

Mandatory coursework	Presence required	Comment
Presence required	Not required	• 90% mandatory attendance; • Participation in 3 intense one-week workshop sessions;

Form of assessment	Grouping	Grading scale	Comment
Project assignment	-	-	The examination will focus on: • Active participation in workshop sessions; • A detailed workshop log delivered at the end of the elective course; • A working system for collection of environmental data;

Form of assessment:	Project assignment
Grouping:	-
Grading scale:	-
Comment:	The examination will focus on: • Active participation in workshop sessions; • A detailed workshop log delivered at the end of the elective course; • A working system for collection of environmental data;

Mandatory coursework:	Presence required
Presence required:	Not required
Comment:	• 90% mandatory attendance; • Participation in 3 intense one-week workshop sessions;