Welcome to the home for Digital Research 2013

Here you will be asked to post a screenshot as well as an approximately 400 word description of the criteria or parameters that you implemented in your use of this weeks precedent study.

Here is the schedule for the semester, including the student responsible for moderating the discussion:

Performative
8/20- Shanghai Tower- Beorkrem
8/27- Versioning- Steven Danilowicz
9/3- Adaptive Components- Dylan davis
9/10- Material Constraints- Christian Sjoberg
9/17- Programmatic Constraints- Neil Edwards

Generative
9/24- Aesthetic- Trevor Hess
10/1- Biomimicry- Ben Sullivan
10/8- NO CLASS- Fall Break

Interactive Design
10/15- Smart Objects- Lina Lee
10/22- Smart interfaces- Isabel Fee

Data Visualization
10/29- Emotive Expression- Chris Pockette
11/5- Physical Expression-
11/12- Daylighting-
11/19- Final Project begins
11/26
12/3

Friday, September 20, 2013

Seattle Public Library Scripting Exercise

9-20-13

  Using the lunchbox plugin for grasshopper is an incredibly useful tool for editing models based on data.  Simply editing the Excel Spreadsheet where the data is based changes the model and provides a fairly fluid environment for experimentation.  By allowing excel to do the heavily lifting when it comes to the functions and equations, grasshopper becomes a more drawing element based scripting tool. 
  
  In this exercise, the data from the excel sheet was used to drive the dimensions of room volumes and the distance of the volume above the ground floor.  Outside of the spreadsheet, other buttons within grasshopper drove the X and Y jitter of the room volumes at their respective Z locations in the model.  The spreadsheet was set up so that there was a fixed square footage per volume, so that the width variable was not only tied to the length variable, but also the number of floors in the particular volume.  The user can control the number of floors in the particular volume as well as the width of the volume, leaving excel to calculate the length of the volume to allow for the square footage to match the predetermined value.  Height and spacing are also controlled by the user, since the user inputs how high the floor to floor height is.  Because this has no effect on the square footage, it merely changes the overall height of the building. 

  
  I see lunchbox as a means to take different data sets and apply it to a specific model rather than one that is based off of pre-determined or grasshopper constructed forms.  Here, the data drives the model, whereas in other situations, it may be curves or boundary representations that drive the way a model works.  Not that there is anything wrong with being a numbers driven model, it’s just a different method of solving an architectural problem.



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