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An exploration on the social impact that access to the ressources of the city and the presence of economical, cultural, political systems generate in the urban landscape.

Team members: Andrés Gómez Mares, Pablo Goldin, Mikhail Pikman, Iktihab Ali External advisers: Sebastián Estremo

Introduction

According to a study on marginalization realized by the Elliott School of International Affairs & the World Fair Trade Organization-Asia in 2015, the term can be defined as “ a condition and a process that prevents individuals and groups from full participation in social, economic, and political life enjoyed by the wider society.” This definitions that implies the existence of physical, political, social and economical limits and borders in the city that shape the life of it’s inhabitants also suggest that this limits are not static but are also constantly evolving by the correlation of this factors who add to each others creating a virtual “hotspot” map of this multifaceted cloud that somehow generates this “deterministic storm” on the city inhabitants.

This addition phenomenon and the limits it generates can also be explained by this second definition created by the Zentrum für Entwicklungsforschung Center for Development Research University of Bonn; “Marginality is an involuntary position and condition of an individual or group at the margins of social, political, economic, ecological and biophysical systems, preventing them from access to resources, assets, services, restraining freedom of choice, preventing the development of capabilities, and eventually causing extreme poverty. The poorest themselves have described their situation as being trapped in a “complex knot which can lead to further knots if the wrong threads are pulled.”

On the other hand, the concept of “density” in the urban field represents a delicate balance in the urban discussion where its presence is simultaneously perceived as a cause and also a solution for some of the problems that are described by marginalization.

Therefore, the analysis of the city of Moscow thru this two concepts would allow us to integrate qualitative and quantitative data into a single map who can express a complex social, spatial and temporary reality of the city and provide one more answer to a larger debate on the shaping of contemporary cities.

Research question

What is the relation between the concept of “density “and the overall idea of marginalization in the city of Moscow? How marginalization is related to the city of Moscow?

Hypothesis 1: The lower the density the higher the marginalization
Hypothesis 3: Populations in proximity to the City Center are less marginal than the ones in peripheries

Research method

In order to collect the necessary data for the analysis, we used secondary data and archival from open sources to have a strong quantitative base that later on was crossed with qualitative research elements and notions.


Crime in Moscow for example is a topic that has very few geolocalized information so we researched on different medias, news papers and social medias and we found this info graphic that gave us the enough information to start making correlations.
source:
https://openpolice.ru/news/ves-kriminal-okazhetsya-v-internete/

To collect information related to the concept of density, we started by working with the physical aspects of the city such as the area of the districts that was introduced in the map as a geometric shape in .geojason that we combined with the presence of different actors collected in open street map that could work as indicators of the dimensions that where going to be analyzed for the marginality map such as:

  • Schools = Educational
  • Police Stations = Governance
  • Hospitals = Health
  • Churches = Faith and tradition
  • Metro stations = Accessibility
  • Parks = Ecology
  • Market 24h = Wealth
  • Crime / 10 000 = Violence

All the collected data we merged into one CSV file that we used to make the different graphics in QGIS

By the definition of the dimensions parameters it will that allow us to generate a map that can only expose if a level of something is achieved according to some political, social, economical and physical parameters that by being overlapped would create an image that could express a complex concept such as marginality like in the example bellow.

source: Bonn University
https://www.zef.de/fileadmin/webfiles/downloads/projects/margip/downloads/Poster-marginality-tropentag.pdf

Resultants and discussions

Density

We decided to focus our research on the concept of the density of population by district and the presence of schools, churches and health infrastructure in these areas according to the data collected in Open street map and collected in Over pass turbo.

  1. Density of population

2. Presence of schools

3. Presence of churches

4. Presence of Health infrastructure

5. Presence of Police Stations

Dashboard

Using the excel table we generated a dashboard to show the correlations between different aspects in a dynamic table. In the example bellow we made a selection of the top 10 districts with more crimes committed for every 10 000 and we analyzed how the other categories are expressed in those 10 districts to have a correlation between the committed crimes a the presence of each of the commodities.

File without macros and with macros

Marginality

In order to achieve our marginality map we created this specific dimensions that would generate the “positive and negative” layers of the heatmap according to some sensible indicators. Nevertheless, since all of these indicators are represented in identical geometries the map will show the “intensity” of the “marginality” by the number of overlappings of the defined dimensions creating a heatmap of it. All five dimensions have 20% opacity creating a scale of marginality in 5 steps.

QGIS instruments

In order to only show a certain amount of information from a table it is necessary to use the field calculator tool that allows us to select data from the attributes table according to specific instructions. In this case we used

// “fieldname” < value

Dimensions

  1. Health and distribution of public infrastructure: Density of hospitals for more than 10 000 persons < 0.35, the average of clinics per district for every 10 000 persons. This indicator helps us to measure the physical access to outpatient health care services and the position of the district compared to the others.
  2. Education: Density of schools for every 10 000 persons < 0.36, the average of schools per district for every 10 000 persons. This indicator helps us to understand the accessibility that citizens have to education in their own district and the impact that this facility can have in their daily life in terms of transportation for the involved persons but also in the independence that children can have from their parents if the distance between their houses and their schools allow them to walk or the impact on the work of the parents if they need to transport their children to school in another district and then go to their work.
  3. Security: Density of police stations for every 10 000 < 0,39, the average of police stations per district for every 10 000 persons. With this indicator we can challenge the perception that the number of crimes that occur for every 10 000 persons creates because some of the crimes might not be denounced in areas where relation with police is not common as much as the type of crime can variate between one district and another creating another layer of violence and repercussions that the number does not provide. The number of police stations therefore expose the resources that are invested in the security of a district compared to the others as much as the necessity of control in them.
  4. Faith and traditions: Density of churches for every 10 000 < 0,32, the average of churches per district for every 10 000 persons. This indicator help us to understand how the presence of the Church as an institution can be correlated to other primary aspects of life in urban environments such as health, education and security and also to understand its presence in the city.
  5. Medical commercial services: Density of pharmacies for every 10 000 < 3, the average of pharmacies facilities per district. While the number of hospitals per district express the access of the population to the health facilities provided by the government and financed on public budgets, the presence of pharmacies expose the commercial geographical strategy from the pharmaceutical sector to make profit from the ill populations. The discrepancy of presence of hospitals and pharmacies then expose the tensions between private or public strategies on infrastructure related to urban planning from hospitals and market based presence of pharmacies that can be related to the either to the proximity of hospitals, the health conditions of a populations that would be translated into consumption of medical products or the lack of hospitals that is replaced by pharmacies where persons satisfy their access to medical aid.

Conclusions and limitations

Hypothesis 1: The lower the density the major the marginalization
Observation: Some of the districts with low density are higly marginated nevertheless, the districts in the South center area of the city who have high density are also marginalized while other distircts in the west with low density are not marginalized under these parameters.
Hypothesis 2: Populations in proximity to the City Center are less marginal than the ones in peripheries.
Observation: The marginality map do not express such a clear contrast between “center and periphery” but more on cardinal references.

This kind of analysis create a dialectic that could be infinitely developed and correlated since every aspect of the city impacts on the other. Nevertheless, it is interesting for us to understand how an element can become and indicator by the position it occupies and the correlation of the information.

Moscow is a highly centralized city which could be perceived as a way of marginalization of its inhabitants depending on their proximity to the center of the city, nevertheless, the strong transportation system can be a factor that change the map of marginality as much as the quality and access to the public services described since proximity cannot be the only aspect that impacts on the experience of the users to such facilities. Other aspects which are not expressed in the graphics such as income could also transform the perception of the districts.

By further explorations and the additions of new information based not only in the shape of the districts but other geometries and other indicators the map would create a different image of the notion of marginality.

Task:

The excercise consisted in using the CNC machine to transform a 10x10x2 cm wood tile. To achieve the goal it is necessary to create a 3d model, then a G code to define how the machine will interact with the material and finally set the parameters on the CNC machine software to run the file and cut the piece.

Softwares:

  • Modelling: Rhino
  • G code generation: Art Cam
  • CNC interface: NcStudio

Tools and machines:

  • CNC
  • Manual basic tools for wood

Process:

In order to understand the possibilities of the CNC and the kind of results it could generate, I decided to make one prototype 90° angles and complex geometric intersections and another with more simple curved geometries using only boolean unions and substractions in Rhino.

For the first prototype, I subdivided a 10×10 cm rectangle in different proportional modules and created a topography by extracting them in different heights.

To make the work of the CNC more complex and understand the possibilities of it, I intersected an elliptical section volume and subtracted it from the original topography

After the volume is created, I transformed it into a mesh and uploaded into the Art Cam software whose procedure I will explain later in this blog.

In a first step it is necessary to define the size of the model and it’s position in the digital interface
In a second step we must set the size of the milling bit and the path it will follow and we exporte the G code
The CNC machine es composed by a surface where the material is placed and mechanical arm who follows numerical instructions.
The material that will be milled must be fixed to the surface. For this essay we used double side tape. The use of protective glasses is highly recommended.
We set the starting point in the software
We upload the G code into the NcStudio software from the CNC machine and we run the file.

The result was not as I expected maybe because of the reasons I will describe:

-Possibly the size of the geometries was too small for the milling bit.
-Sharp orthogonal shapes are not easily cut.
-The cutting path strategy was not proper for curved and orthogonal cuttings.

In a second attempt, I made a curved geometry thru a similar substractive process of design in Rhino.

I uploaded it to Art Cam

We must first define the scale of the object
Then introduce the final geometry in the volume that will be cut.
Define the milling strategy and the parameters according to the material and the kind of work that will be done.
In this case we fixed the tile to a piece of wood using screws.
And we programmed the CNC to go longer and in more phases to have a smoother result.

Files:

https://drive.google.com/file/d/1DHkLkrM-eU6LYXFM-FU6dyMuQvenyuCN/view?usp=sharing


https://drive.google.com/file/d/1aLFilJi7YI_s9jFpWasGxdcQ74MZcFSs/view?usp=sharing

Mijail Pikmann and Pablo Goldin

3d printers are a tool that allow to create objects with millimeter precision that can be used as tools or finished products. The only required element to use them is a 3d model that can be create in numerous softwares and must be saved as a “stl.”

For this exercise we designed some simple moduar geometries that can be interlocked in order to understand the possibilities of the machine and have some elements to make abstract models.

Rhino model

In order to use the 3d model it is necessary to transform the solids into meshes.

Mesh creation

And save it as a stl. file

Every 3d printer machine has a different software to transform the stl. file into a gcode that can processed by the machine and also uses different materials that allow specific physical achievements therefore it is recommended to choose the machine before even designing.

In a class with Nadia Kutyreva a 3d printing professional she provided us some material to help us to make the proper choose of the material and the machines according to our design. We provide the contact in case our readers want to explore more on this technique and two diagrams she gave us.
nadia.kutyreva@gmail.com instagram @nadia.k.la

Useful links:

Knowledge base from 3Dhubs.com:
https://www.3dhubs.com/knowledge-base
Design rules:
https://www.3dhubs.com/get/3d-printing-design-rules/
FDM and Supports:
https://all3dp.com/1/3d-printing-support-structures/
Design to print without supports:
https://www.youtube.com/watch?v=RPijCjz9G1w
Printing process Trouble shooting:
https://all3dp.com/1/common-3d-printing-problems-troubleshooting-3d-printer-issues/
Retraction:
http:// https://www.matterhackers.com/articles/retraction-just-say-no-to-oozing
Cleaning the model:
http:// https://makeprintable.com/


In the laboratory, the machine we chose to use is the Ultimaker 2 Go

The software the machine uses is cura It can be downloaded from the company website

address: 20 Myasnitskaya ulitsa
(metro stations ‘Lubyanka’ and ‘Kitay-Gorod’)
Moscow 101000 Russia

phone: +7(495)772-95-90 *15026

email: city@hse.ru