Category Archives: Architecture

Introduction to Complexity

I recently learned about a free online course in Complex Systems. The concepts covered in this course are very pertinent to visualizing and making sense of complex social data sets. The course was created and is hosted by the Santa Fe Institute.

You can find more information about this course at www.complexityexplorer.org

In this course you’ll learn about the tools used by scientists to understand complex systems. The topics you’ll learn about include dynamics, chaos, fractals, information theory, self-organization, agent-based modeling, and networks. You’ll also get a sense of how these topics fit together to help explain how complexity arises and evolves in nature, society, and technology. There are no prerequisites. You don’t need a science or math background to take this introductory course; it simply requires an interest in the field and the willingness to participate in a hands-on approach to the subject.

About the Instructor:

Melanie Mitchell is Professor of Computer Science at Portland State University,  and External Professor and Member of the Science Board at the Santa Fe Institute. She is the author or editor of five books and over 70 scholarly papers in the fields of artificial intelligence, cognitive science, and complex systems. Her most recent book, Complexity: A Guided Tour, published in 2009 by Oxford University Press, won the 2010 Phi Beta Kappa Science Book Award. It was also named by Amazon.com as one of the ten best science books of 2009, and was longlisted for the Royal Society’s 2010 book prize.

Course Team:

John Balwit (Teaching Assistant) is a Ph.D. student in the Systems Science program at Portland State University. He has a background in biology education and current research interests in theoretical biology, evolvability and natural selection. John is also interested in the use of agent based modeling and machine learning techniques to explore questions in the evolution of cooperation, the nature of social dilemmas and the patterns in human decision-making under extreme conditions. His current emphasis is on the use of computer models and computational exercises to effectively teach general audiences about the constellation of topics called Complexity Science.

John Driscoll (Teaching Assistant) has a background in architecture and is a Ph.D. student in Systems Science at Portland State University. He has worked with, and credits as mentors, Dean Bryant Vollendorf, Professor Emeritus, UNCC, and George Hascup, AAP, Cornell University. John is primarily interested in the rationalization of city planning and the emerging field of the science of cities, the goal being to apply theory and methods from complex systems science to the research, analysis and design of urban environments.
Erin Kenzie (Program Assistant) is a Ph.D. student in Systems Science at Portland State University. Her interests are in the fields of urban sustainability and behavioral and social science research methods.

Visualizing Social Data using Grasshopper and Google Earth

Below is a case study on using Grasshopper and several other plugins to generate visual representations of (social) data on a map. This method along with some additions to query and pull social data automatically and possibly the functionality of tying directly back into Google Earth to update the imagery will provide very useful to inform us of how social systems shift on local and macro levels.

From Metaball Diagrams with Google Earth and gHowl

“Google Earth presents an intuitive, dynamic platform for understanding spatial context. Combined with a parametric modeler likeGrasshopper, Google Earth presents complex datasets relative to geo-positioning in a way that is understandable. Facilitated by GH plugin gHowl, GH meshes and lines can be exported in Google Earth’s .kml format to be viewed by Google Earth or an enabled web browser.

Creating legible geometry for Google Earth is challenging, but one type of geometry I’ve experimented with is GH’s metaballs, which are about as old school as it gets for 3D curvature. Metaballs, as described by Yoda (Greg Lynn), are “defined as a single surface whose contours result from the intersection and assemblage of the multiple internal fields that define it.” (Lynn, Blobs, Journal of Philosophy and the Visual Arts 1995). This aggregation of internal fields can provide an intuitive understanding of various contextual forces relative to the spatial context of a site. While GH metaballs are only curves and not meshes / surfaces you can easily use a delaunay mesh to begin to create a mesh.

This tutorial will walk through the process of creating metaballs from Geo coordinates. I’m using a map I created with Elk that is based off of Open Street Maps info, if you’re interested in doing something similar look here.

Just click on the images below if you’d like to see them in more detail.

Start by positioning your Geo coordinates in GH space through gHowl’s Geo To XYZ module.”

Read More…

Fabricating a Parametric Model with Pepakura

For this project I helped my friend Ben Ortega, a MARC student at UNM, build a model he developed with Grasshopper and Millipede. I used Pepakura to design the unfolded parts and lay them out. He and I then built the model using the paper parts and some tacky glue.

Here is the model next to the unfolded parts in Pepakura.

Parametric Pepakura unfold

Here are some photos of us building the model. In some of the photos you can see a smaller 3D printed model we were using for reference.

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Here is a flyover of the finished model.