Donatien Delmon

Link to Design Journal

Journal Entry For

Module 7 - Study Your Options

ACC Folder Link

https://acc.autodesk.com/docs/files/projects/7a6d9404-5c50-4d49-acbd-cf67d7302936?folderUrn=urn%3Aadsk.wipprod%3Afs.folder%3Aco.NZ6tx17ETzmnCVEyiQqMzA&viewModel=detail&moduleId=folders

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Step 1 - Generative Design Framework

A very brief description of the design decisions from Step 1 following the Generative Design Framework.

Design Decision 1: Public light in cities

Design Variables

Time with lights turned on during the night
big streets vs small streets with lights on

Evaluators

Energy consumption/Cost for public lighting
Saftey hazards
Light pollution

Most Important Tradeoffs to Consider

The tradeoff here would be to reduce as much as possible the energy consumption and the light pollution without having too much safety hazards by turning off all the lights in the city. Saftey problems could be car crash, more aggressions in the streets. All of that can be a consequence of having streets in the dark. In the same time, reducing the light in cities would reduce light pollution which has an impact on birds directions for instance.

Design Decision 2

Design Variables

Radius where people are allowed to get out
Time during which people can be outside everyday

Evaluators

Happiness of people
Wildlife protection
CO2 emissions

Most Important Tradeoffs to Consider

The problem here appeared during the covid lockdowns we had in France. Everyone who could afford it left the big cities to stay in their secondary house usually in smaller towns or next to the beach. The only reason we could go outside of the house for would be groceries and one hour a day for workout but limited to 1km around the place you were staying in.
It appeared that the wildlife took back its right and was everywhere. Eagles were spotted fighting in the middle of a city, whales were seen meters away from the sure. All of that was possible especially because noise pollution was not as high as usual, people were not outside disturbing animals.
CO2 emissions were also very much reduced.
But, in the same period of time, depression was through the roof, people drank more alcohol than usual and we all felt the impact of lockdowns on our lives.

Design Decision 3

Design Variables

Number of points in the U and V directions on the facade
U value for the glass

Evaluators

CO2 emissions for the facade
Weight of the building
Energy lost through the glass
Cost of the facade
Area allowed for visibility

Most Important Tradeoffs to Consider

The most important tradeoff would be between the building weight and the visibility. The larger the panels, the better the visibility but the bigger the frame and the heavier the building.
There is also a tradeoff bewteen cost and energy lost through the glass. The lower the U value for the glass, the lower the heat loss but the higher the cost for the facade.

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Step 2 - Generative Design Study

The design decision i have chosen from Step 1 is the third one. I based my studies on the same buildings we used during the last two weeks. However all my outputs are focused on the facade. The facade is made out of glass panels each of which are sourrounded by a steel frame. The steel frame radius is proportionate to the glass area it is surrounding to be able to bear the whole weight of the glass.

By taking all the areas corresponding to the panels, i’m taking the maximum area of the panels and dividing it by an arbitrarly chosen value of 400. (400 made sense in term of magnitude).

Visibility:

The visibility is estimated by taking the area of glass surface not blocked by any frame. This area is obtained by taking the total surface of the panels and substracting the sum of the section of all the frames.
Since the area of the frames is 2*Pi*Radius*Length. The area of the section being Diameter*Length, we just divide the area of the frames by Pi.

Total cost facade:

The cost of the facade is calculated by adding the price of the steel to the price of the glass.
The price of the steel is just obtained by multiplying the mass of steel to its cost per kg.
I estimated the price of the glass by considering that glass with the lowest U value (0.1) was the most expensive (1350$ per square meter) and the one with the highest U value (1) was the least expensive (750$ per square meter).
The cost of the steel is calculated by taking 0.4$/kg of steel and multiplying it to the mass of steel needed for the frame.

Heat loss in W/°C:

The heat loss is estimated by taking the formula Q=U*A*(T_int-T_ext). U is the U value for the glass and A the area of glass. We give the result in W/°C and only calculate U*A to have a more general idea whatever the temperature difference is.

Building weight:

I chose this parameter because the weight of the building has a huge impact on the foundation work which will itself impact the carbon footprint, the price and the duration of the project.
The exterior area of the frame is 2*Pi*Radius*Length. The volume beeing Pi*Radius^2*Length, the volume is obtained with: Area*Radius/2. The volumic mass of steel being 7900kg/m^3, the mass of steel is obtained very quickly.

The mass of glass is obtained by multiplying the area by the usual thickness (3mm). And then I multiplied that volume by the volumic mass of glass (2579kg/m^3).

I then add both these weights to obtain the weight of the facade.

CO2 emissions:

Once we have th mass, we just multiply it by the quantity of CO2 emited for each kg of product (glass or steel) produced.

These five outputs are the one I am basing my generative design on.
I have managed to find only three valuable inputs to be able to compare the different designs. I wanted to keep the same building for all the study to be able to really compare the differend options. So the inputs are the following:

U and V numbers of segmentation of the surface for the panels
The U value of th glass.

I could have chosen to put the radius of the frames as an input but it would not have made much sense structurally.

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Step 3 - Generative Design Study Results

Maximizing visibility:

Inputs:

U = 49
V = 40
U_glass = 0.902 (not useful here)

Output:

Output 1 = 26 089 square meter
Output 2 = $19 371 000
Output 3 = 26 898 W/°C
Output 4 = 1 059 800 kg
Output 5 = 1 839 500 kg of CO2

Minimizing the cost of the facade:

Inputs:

U = 20
V = 35
U_glass = 1.031

Output:

Output 1 = 25 026 square meters
Output 2 = $19 873 000
Output 3 = 25 802 W/°C
Output 4 = 4 218 800 kg
Output 5 = 7 688 600 kg of CO2

Minimizing the heat loss:

Inputs:

U = 2
V = 3
U_glass = 0.496

Outputs:

Output 1 = -2 702 square meters
Output 2 = $1 691 000 000
Output 3 = -1340 W/°C
Output 4 = 4 235 000 000 kg
Output 5 = 7 834 000 000 kg of CO2

There is a glitch here. The frames are so big that the surface of the frame is higher than the glass area. Which means minimizing the heat loss means taking the highest U_glass since it is a negative value.

Minimizing the building’s weight:

Inputs:

U = 49
V = 50
U_glass = 1.059

Outputs:

Output 1 = 26 325 square meters
Output 2 = $18 952 000
Output 3 = 27 879 W/°C
Output 4 = 810 713 kg
Output 5 = 1 377 000 kg of CO2

Minimizing the CO2 emissions for the facade construction:

Inputs:

U = 50
V = 50
U_glass = 1.059

Outputs:

Output 1 = 26 337 square meters
Output 2 = $18 953 000
Output 3 = 27 891 W/°C
Output 4 = 793 153 kg
Output 5 = 1 345 000 kg of CO2

First, we can see that the solutions are not always optimal. The number of simlations might not be high enough as well as the population. But it still gives us a pretty good idea on what direction to choose.
All these simulations show different tradeoffs between the input parameters. While most outputs are optimal for the highest number of panels possible, the cost is actually reduced when using only u = 20 and v = 35.
The biggest tradeoff is between price and heat loss. Having windows with the lowest U Value doubles the price even when keeping u and v constant.
However, with these values for U and V, the weight and the carbon foot print are multiplied by 5. So there is a real tradoff between all these outputs and it depends what the focus is on.
We also musn’t forget that the model is very simplified, the structure is not taken into account and the carbon footprint could vary a lot if we added all the other elements to the building.
I also did not find a clear relationship between the U value and the carbon emissions for producing the glass or the weight of the glass. That could also have an impact on the optimization of the different outputs.