Hello Atlanta !

Project Description | Hello Colorful Atlanta! Data visualization on Cesium platform!

The goal of this project is to research how smart a city can be, and how we can design a city in a smart way. In this project, we use Atlanta as the research subject. Atlanta is a city which has a convenient public transportation system, MARTA. As a busy public transportation system, MARTA is able to collect massive data by installing sensors on the trains, bus and stations. The data collected can be used to develop some applications and make this city respond to people's needs more quickly, or, real-timely. Hence, this project is aimed to input MARTA data to architecture design, urban design to develop a system for Atlanta citizens. The first take we did is to visualize the MARTA data in building scale.

Fig. 00. Heat Map of ATL - Dennis R. Shelden, Diego Osorio, T.C. Kurt Hong, 2017 Spring

Fig. 01. Real Time Updating Transportation - Dennis R. Shelden, Diego Osorio, T.C. Kurt Hong, 2017 Spring

Fig. 02. Data Visualization of ATL - T.C. Kurt Hong, 2017 Spring

Fig. 03. Data Visualization of ATL - T.C. Kurt Hong, 2017 Spring

Fig. 04. Data Visualization of ATL - T.C. Kurt Hong, 2017 Spring

Fig. 05. Coloring Test of ATL - T.C. Kurt Hong, 2017 Spring

CourtSpace | Generative System of Courthouse Design

Project Description | 

CourtSpace is a generative design software  which is based on rule-based design. Rules embedded in CourtSpace are from the analysis of the federal courthouses in US, this research is conducted by Dr. Thanos Economou at Georgia Tech and PhD candidates, Heather Ligler and James Park. In CourtSpace project, the goal is to develop a series of design vocabulary and integrate this design language into Rhinoceros platform, thereby providing architects a tool for courthouse design.

Fig.01 - Composition of courthouse, T.C. Kurt Hong, 2017 Spring

Fig.02 - Composition of courthouse, T.C. Kurt Hong, 2017 Spring

Fig.03 - Composition of courthouse, T.C. Kurt Hong, 2017 Spring

Fig.04 - Composition of courthouse, T.C. Kurt Hong, 2017 Spring

Fig.05 - Composition Test, T.C. Kurt Hong, 2017 Spring

Fig.06 Rules, T.C. Kurt Hong, Spring 2017

ARGO | Generalized shape search test

Description | ARGO - Topological Shape Search

ARGO is a project which is trying to capture some data features of each shape, thereby recognizing the shape embedded in a bigger shape on Rhinoceros. This project starts with an extension of the previous project, GRAPE, which is using an open-sourced graph engine, GRGen. However, GrGen is not designed specifically for shape grammar community, so there are some limitations in the future development. Thus, Allo is initiated with an ambitious goal that we try to build up our own graph engine and expand the search power. So far, Allo can search any embedded topological shape less than 5 lines (1-line to 4-line shape are working) in a bigger shape. In the future development, we will try to push the limit further and come up with a total solution for this project.


Demo Video link:
https://www.youtube.com/watch?v=r3riMnFAgKs

Fig.01 - Topological shape search, T. C. Kurt Hong, 2017 Spring

Fig.02 - Topological shape search, T. C. Kurt Hong, 2017 Spring

Fig.03 - Topological shape search, T. C. Kurt Hong, 2017 Spring

Fig.04 - Topological shape search, T. C. Kurt Hong, 2017 Spring

Digital Building Lab | Auto-routing Test

Project Description |

In ship design and chip design, auto-routing is a common technology to deal with highly complex routing problem. However, routing can be viewed as a broader technology to help architects design circulations and deal with piping problem. This program is the first take trying to search all the possible routing solutions. The computation is very expensive, so it can work in a small region for now.

Fig.01 - Routing solution with 4 sets of points, 2 obstacles in a 6 x 6 box, T.C. Kurt Hong, 2016 Summer

Fig.02 - Routing solution with 3 sets of points, 0 obstacle  in a 6 x 6 box, T.C. Kurt Hong, 2016 Summer

Fig.03 - Routing analysis with 3 sets of points, 0 obstacle in a 6 x 6 box, T.C. Kurt Hong, 2016 Summer

Fig.04 - Routing solution with 4 sets of points, 2 obstacles in a 6 x 6 box, T.C. Kurt Hong, 2016 Summer

Fig.05 - Routing solution with 4 sets of points, 2 obstacles in a 6 x 6 box, T.C. Kurt Hong, 2016 Summer

Fig.06 - Routing solution with 4 sets of points, 2 obstacles in a 6 x 6 box, T.C. Kurt Hong, 2016 Summer

Fig.07 - Routing solution with 4 sets of points, 2 obstacles in a 6 x 6 box, T.C. Kurt Hong, 2016 Summer

Fig.08 - Routing solution with 4 sets of points, 2 obstacles in a 6 x 6 box, T.C. Kurt Hong, 2016 Summer

Fig.09 - Routing solution with 4 sets of points, 2 obstacles in a 6 x 6 box, T.C. Kurt Hong, 2016 Summer

Fig.10 - Routing solution with 4 sets of points, 2 obstacles in a 6 x 6 box, T.C. Kurt Hong, 2016 Summer

Fig.11 - Routing solution with 4 sets of points, 2 obstacles in a 6 x 6 box, T.C. Kurt Hong, 2016 Summer

Shape Computing Group | Froebel Blocks

Project Description |

For shape grammar 101, Froebel Blocks are always a good tool to help us understand shape grammar. However, Froebel Blocks are physical tools which has some limitations that students can hardly use as many blocks as they can. Also, physical Froebel Blocks limit some possible combinations because physical blocks can not overlap to each other (embedded in each other). Thus, this project is aimed to develop a digital tool which can expand the educational possibilities of Froebel Blocks. This program is developed in Rhino environment with Rhino Python.

Fig.01 - 5-rule Combination Analysis, T.C. Kurt Hong, 2016 Summer

Fig.02 - 5 rules, T.C. Kurt Hong, 2016 Summer

Fig.03 - 5-rule Combination 3, T.C. Kurt Hong, 2016 Summer

Shape Computing Group | Emergence SHAPE

Project Description |

This project is aimed to develop a graph engine which can recognize emergence shapes according to the concept of shape grammar by George Stiny in 1960's. "Shape" is a non-classical representation which provide readers multiple ways to read. For human beings, it is easy to catch a sub-shape embedded in a shape but difficult to computers. The first version of this engine is designed to find out all the quadrilaterals including convex ones and concave ones. This engine is developed in Rhino environment with Rhino Python to connect architecture designers. Users can draw any shape and this engine will report the number of all possible quadrilaterals and list them as a category.

 Fig.01 "Finding all quadrilaterals" Test 01, T.C. Kurt Hong, 2016 Summer

 Fig.02 "Finding all quadrilaterals" Test 02, T.C. Kurt Hong, 2016 Summer

 Fig.03 "Finding all quadrilaterals" Test 03, T.C. Kurt Hong, 2016 Summer

 Fig.04 "Finding all quadrilaterals" Test 04, T.C. Kurt Hong, 2016 Summer

Fig.05 "Finding all quadrilaterals" Test 05, T.C. Kurt Hong, 2016 Summer

Fig.06 "Finding all quadrilaterals" Test 06, T.C. Kurt Hong, 2016 Summer

Capstone - Folding Concrete

Folding Concrete Review - T.C. Kurt Hong, Z.J. Candice Yang, 2016 Winter

Folding Concrete Model 3 - T.C. Kurt Hong, Z.J. Candice Yang, 2016 Winter

Folding Concrete Model 3 - T.C. Kurt Hong, Z.J. Candice Yang, 2016 Winter

Molds - T.C. Kurt Hong, Z.J. Candice Yang, 2016 Winter

Molds - T.C. Kurt Hong, Z.J. Candice Yang, 2016 Winter

Casting Process - T.C. Kurt Hong, Z.J. Candice Yang, 2016 Winter