{"id":966,"date":"2015-10-20T23:36:24","date_gmt":"2015-10-20T23:36:24","guid":{"rendered":"https:\/\/mikelberman.com\/pgraff\/?p=966"},"modified":"2015-10-20T23:45:26","modified_gmt":"2015-10-20T23:45:26","slug":"bryan-digital-flo-nation-of-guns","status":"publish","type":"post","link":"https:\/\/mikelberman.com\/pgraff\/bryan-digital-flo-nation-of-guns\/","title":{"rendered":"Bryan \/ Digital Flo$$: “Nation of Guns”"},"content":{"rendered":"

As I thought\u00a0about a data-driven procedural design project for this assignment, I realized I had already created a 3D digital gun model.<\/p>\n

I also remembered that there are a LOT of guns in the United States – 1.2 guns for every person, according to recent estimates.<\/a><\/p>\n

So I wondered – what would that look like if I used my gun model to visualize the total U.S. firearms population? What kind of impression and emotional resonance would that have? Would I have to condense down the number visualized to some representative portion of the total?<\/p>\n

PROCESS<\/strong><\/p>\n

I started by importing a 2D U.S. map into Rhino as a reference:<\/p>\n

\"USMap\"<\/a><\/p>\n

Then I traced the outlines of the map and brought those curves into Grasshopper. I used the “intersection” tool to find the points at which a series of lines intersected the contours of the US; this gave me a lattice on which I could place a scalable number of points to fill the country:<\/p>\n

\"Points\"<\/a><\/p>\n

Because the gun model was complex and required processing power to modify, I started testing the placement of multiple models with a series of simpler boxes, which I translated to each point in my lattice:<\/p>\n

\"Boxes\"<\/a><\/p>\n

Once I had this working well, and scaled to a good number (~350 points for ~350 million guns in the country), I replaced the boxes with a brep version of the gun model:<\/p>\n

\"GunsStraight\"<\/a><\/p>\n

Finally, I applied a series of random rotations to each gun model to create the final “prickly” look. I used several pseudo-random nodes in series to generate varying random seeds and outputs to get a more aggressively randomized effect. At the end of this generative process, I also did some fine tuning: I added one more gun to the tip of Florida to make the country shape more recognizable, and tweaked my random seed inputs until I found a rotation that gave the most visually intense effect:<\/p>\n

\"FinalRotatedOutline\"<\/a><\/p>\n

Here’s my full Grasshopper layout, in two parts (from left to right):<\/p>\n

\"GH1\"<\/a> \"GH2\"<\/a><\/p>\n

 <\/p>\n

Unfortunately, three attempts attempts at printing the model on a MakerBot failed. Simply exporting the complex shape was difficult, and the MakerBot couldn’t handle the irregular base or easily calculate support.<\/p>\n

\"makerError\"<\/a><\/p>\n

After 48 hours of unsuccessful 3D printing efforts, I took the procedurally-generated image in another direction. Using Rhino’s “artistic” rendering options, I exported a variety of images that captured the size, density and number of interlocking guns:<\/p>\n

\"NationOfGunsZm6\"<\/a><\/p>\n

\"GunThicket4\"<\/a><\/p>\n

\"NationOfGunsZM2\"<\/a><\/p>\n

\"MericaWBigGun\"<\/a><\/p>\n

\"NationOfGunsSide\"<\/a><\/p>\n

I pulled several of these images together into a “meme-ish” poster highlighting the message the project was created to convey:<\/p>\n

\"NationOfGuns\"<\/a><\/p>\n

…And posted it in the real world:<\/p>\n

\"PosterCap\"<\/a><\/p>\n

 <\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

As I thought\u00a0about a data-driven procedural design project for this assignment, I realized I had already created a 3D digital gun model. I also remembered that there are a LOT of guns in the United States – 1.2 guns for…<\/p>\n","protected":false},"author":5,"featured_media":1007,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-966","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/mikelberman.com\/pgraff\/wp-json\/wp\/v2\/posts\/966","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mikelberman.com\/pgraff\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mikelberman.com\/pgraff\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mikelberman.com\/pgraff\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/mikelberman.com\/pgraff\/wp-json\/wp\/v2\/comments?post=966"}],"version-history":[{"count":4,"href":"https:\/\/mikelberman.com\/pgraff\/wp-json\/wp\/v2\/posts\/966\/revisions"}],"predecessor-version":[{"id":1048,"href":"https:\/\/mikelberman.com\/pgraff\/wp-json\/wp\/v2\/posts\/966\/revisions\/1048"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mikelberman.com\/pgraff\/wp-json\/wp\/v2\/media\/1007"}],"wp:attachment":[{"href":"https:\/\/mikelberman.com\/pgraff\/wp-json\/wp\/v2\/media?parent=966"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mikelberman.com\/pgraff\/wp-json\/wp\/v2\/categories?post=966"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mikelberman.com\/pgraff\/wp-json\/wp\/v2\/tags?post=966"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}