|Scope details||6 Credits|
|Level of study||Syklus 2|
|Language of instruction||English|
• 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’.
Recommended prerequisite knowledge
• Mindset towards intense self-development and experimental design;
• Enthusiasm for learning, research, collaboration and innovation;
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.
• 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 in data collection and the making of weather stations;
• Skills in data-driven computational design;
• Skills in advanced visualization methods;
• 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
• Lectures on key conceptual and methodological approaches;
• Workshops focused on skill building;
• Hands-on tutorial sessions;
Core thematic foci include:
• Data-driven design;
• Associative Modeling;
• Multi-objective Optimization;
The methodological approach encompasses:
• Integration of iterative data-driven Methods, Processes, Information and Analysis;
• 90% mandatory attendance;
• Participation in 3 intense one-week workshop sessions;
Professor in chargeSøren Sørensen / Michael Hensel
Mandatory work requirements
|Work requirements||Number||Number of approved||Mandatory presence||Comment|
• 90% mandatory attendance;
|Assessment||Date||Duration||Grade scale||Oral examination|
The examination will focus on: