Terminal Silhouettes: Updated CLT with Concourse A Expansion

CLT

CLT.svg

Charlotte (CLT) had been building an expansion onto terminal A for a while. Nonetheless, I was pretty surprised when I flew through CLT on 18 July that I’d managed to unintentionally book a flight on the day that it opened.

The new concourse forks off from the existing Concourse A where the long moving sidewalk hallway used to be:

CLT-a-extension.png
Existing airport terminal in gray, new concourse A expansion in magenta

Unfortunately, adding the new expansion has made CLT look slightly less “like a reindeer,” as one of my friends noted about the original silhouette.

https://www.pbogard.com/projects/terminal-silhouettes

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Terminal Silhouettes: LBB

LBB

LBB.svg

Lubbock was an interesting airport; it appears to be curved, but it’s actually just a bunch of straight lines with shallow angles. The main curve features fifteen segments (separated by concrete ribs) over ninety degrees, so each one occupied only a six-degree slice of the curve.

Additionally, while I normally leave out awnings, LBB’s awning was really part of the structure, and connected by the concrete ribs, giving the terminal such a signature look that I really had to include it.

https://www.pbogard.com/projects/terminal-silhouettes

 

State Abbreviations Graph

In a recent chat that I participated in, we were discussing US two-letter state abbreviations that were one letter off of each other (e.g., NY and NJ).

After that discussion, I was curious about whether it would be possible to step from any state abbreviation to any other by changing one letter at a time, using only valid states along the way. My first step was to determine if there were any state abbreviations which didn’t share a first or last letter with any other states, so I wrote a simple Ruby script to test that.

Matching StatesSo every state had at least one other state it could go to. Texas (TX) had the fewest, with only Tennessee (TN); Massachusetts (MA) had the most, as quite a few state codes start with M or end with A.

Now I needed to find out if all the states would connect to each other, or if there would be several distinct “neighborhoods” of states. I decided to do this visually by creating a graph, using the output of my script to draw the connections:

State One Letter Changes
Graph with US state abbreviations as the vertices, green lines connecting state abbreviations with the same first letter, and blue lines connecting state abbreviations with the same second letter

Based on this graph, it is possible for any state abbreviation to change to any other state abbreviation!

I was also curious about the number of steps needed to go between any pair of state abbreviations, so I wrote a path distance algorithm based on Dijkstra’s algorithm (but with each path having equal weight) to find the shortest number of hops between any pair:

State to StateBased on the results, the highest number of hops is 6 – so every state abbreviation can be changed into any other state abbreviation in at most six steps!

Terminal Silhouettes: AKL

AKL

AKL.svg

AKL’s international terminal (on the left) was deceptively complex to draw. Though it was mostly straight lines, which are easier than curves, the majority of lines were not right angles or parallel. This effectively prevented me from rotating the drawing and using the rectangle tool, which added a lot of extra time.

Likewise, only one of the parts that appears curved is actually curved; the rest are a bunch of straight walls at slight angles to each other. This meant I couldn’t even use the ellipse or curve tools, and instead had to draw half a dozen or so guides each time just to get the angles consistent.

All in all, then, the international side took me quite a while to draw for what’s a relatively small terminal. At least the domestic terminal (right) was pretty quick to draw.

https://www.pbogard.com/projects/terminal-silhouettes