modeling for latent cities

8/7/2019 modeling for latent cities

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Novi - Pontrella


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Introduction

The Problem

As with any data-production technique, TINs have a limit to the data they can pro-

duce. Additionally, when it comes to producing geo-censual TINs (unlike traditional

TINs in that they utilize social data rather than terrain data to dictate Z factors),

they also often have a fatal aw of being illegible by those without specic skills,turning a wide range of audiences away.

Our Questions: How can new neighborhoods be identied (apart from GIS) through

the translation of digital data in to the physical? How can digital data be made leg-

ible to a larger, transdisciplinary audience through physical modelling without losing

the complexity of the computer system?

The Science

Geographical Information Systems (GIS) can take a vide variety of information andproject it in to 3D space. Through the utilization ofTriangulated Irregular Networks

(TINs), which are 2.5D data-surfaces, will be exported to Rhino for further manipula-

tion. The digital model produced by Rhino can then be exported to STL--a program

that communicates data between a CNC Mill and the computer. Once the model is

imported, the program generates a tool path based on a series of factors: tool bit

size, interval length, mill speed, surface roughing, material type, and data-surface

complexity. Once generated, the CNC Mill can begin milling according to this tool

path.

The Experiment

To mill a model and, through manually selecting data points based on the milling, to

construct an analog form of a TIN in order to reveal neighborhoods.

-Geo-censual TINs will be produced by Heather Roger and Mary DeLaurentis

-A physical model will be produced by Ryan Novi and Caitlin Pontrella based on their

resultant TINs

-An attempt to elicit a new set of data from the intersection of digital and physical

data.

GIS, Rhino, STL, CNC Mill, Projector, Wood, Brads, Twine, Gesso

Materials and Programs

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Step 1: Heather and Mary produce a 2-Generation TIN based on land value and popu-

lation data. Several areas of greatest volatility are noted.

Step 2: The le is exported in to Rhino. The model is reduced to a single area of

volatility. The length and width are dictated by the constraints of the Mill Bed and

the height is restricted by the Mill-Bit Depth

Method/Process

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Tool Bit Size 1/4

Interval Length 0.25

Mill Speed 2160 RPM

Surface Roughing No Finish

Material Type Hard Wood

Step 3: The surface is manually regenerated (10 hours). This is different from previ-

ous experiments where the surfaces were taken in their original state and sent to the

mill. From there the model was split in to four sections, dictated by the size restric-

tions of the mill and our material of choice.

Step 4: The le is exported to STL and the following settings were used:

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Step 5: A tool path is generated off the previous settings and a digital projection is

generated with a visual of the eventual produced surface contouring. We are pre-

dicting however that this will not match the resulting product, post mill, based on

past experiments

Step 6: The wood is clamped down to the mill bed. The STL le is then sent to the

mill machine. Each piece is milled separately at varying lengths of time due to com-

plexity.

Block 1

Block 2

Block 3

Block 4

2.0 hr

2.2 hr

2.3 hr

2.2 hr

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Step 7: The milled model is set up in front of a projector. The map-model of the

city, as generated in Rhino, is re-projected down on to the milled surface. This al-

lows for the lines of the streets and rail to be manually transferred on to the surface

to be analyzed further. This type of data stretching and contorting is a result unable

to be achieved via the computer.

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Step 9: The physical model is cut along the rail line, which has become the focus of

the third generation of TINs being produced by H&M. The major road crossing the

railway serves as

Step 6: A 3GEN-Tin is produced based off the triangulation of the data between

points where roads cross the rail line and pedestrian activity.

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Step 10: From these points two analog TINs were generated, revealing areas of

greatest pedestrian activity in relationship to the topography of population and land

value.

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Conclusions

The analogue TINs that were generated through the connecting of points on the phys-

ical terrain model produced areas of overlap that have the greatest potential for tak-

ing advantage of pedestrian activity (in respect to population and land value). They

are the spaces that connect the routes across the railway.

Variables

There is a lot of room for variation and continued exploration.

Bit-size, mill speed, information selection for TINs, information extracted from tins,

material selection, surface roughing, mill intervals, representation decisions, twine

length.

Considerations + Conclusions

Documents

modeling for latent cities