Final Project

Team Name: Lost Vikings

Team Members: Brooke Beesley, Jon Janikowski, Riley Larcher, Lenina Pascua

Design Objectives

What performance objectives you set (temperature, price, etc.)

The goal of this project is to design a cardboard box that contains the basic energy goals of a human home. Homes usually want to maintain a mild indoor temperature, let in natural sunlight and fresh air, and use as litttle energy as possible. For this box, instead of having an energy source, we are going to use thermal mass and not let in fresh air, so our main goal is to keep a cardboard box at a comfortable temperature for humans to live in. We aimed to keep the maximum temperature of the box at 75 degrees F and the minimum temperature of the box at 65 degreees F.

Design Strategy

What was your overall strategy?

Our overall contruction of the box included a double layer of R-1.93 foam for insulation and a 12inch-by-8inch south-facing window made of clear plastic. As our source of thermal mass, we used eight 16.9oz water bottles, which is about 1.06 gallons of water. For our second run, we focused on the window. We chose to patch up half of our 96 sq.inch window horizontally, making it a 12inch-by-4inch window or 48 sq.inches.

Insert a photo of your model.

Estimation of Performance

Prove to yourself and your reader how you went about estimating your design needs

How did you determine the amount of insulation needed?

We used a double layer of the foam insulation because our biggest worry was the amount of energy that would exit the box throughout the night, and we did not think that a single layer was going to be sufficient.

How did you determine the amount of window needed?

We thought that our biggest problem was going to be heat loss during the nighttime, so to combat a high thermal loss, we decided to make a 96 sq.inch window to allow a high amount of solar energy to enter the box.

How did you determine the type and amount of thermal mass you used?

We decided to use water as our thermal mass because water has a high specific heat capacity (4.186 J/gK) and is a relatively cheap option for this project. The higher specific heat capacity helps keep the solar energy gained during the day from leaving the box during the night. We also decided to use eight 16.9oz water bottles because that was the amount of bottles that fit as a bottom layer for our box and that roughly amounted to 1.06 gallons of water.

How did you estimate the highest and lowest temperature you would observe?

Assuming that humans are going to live in this house, we tried to keep the box at temperatures between 65 and 75 degrees Fehrenheit, which is the range of temperatures that humans are most comfortable living in.

Clearly show the basic details of your calculations.

KNOWN

  • Box Dimensions: 12inch x 12inch x 16 inch
  • R-Value Cardboard:
  • Thickness of Cardboard: 0.125 inch
  • R-Value Foam Insulation: 1.93 ft^2 degree_F hr/ BTU , Double Layer: 3.86 ft^2 degree_F hr/ BTU
  • Thermal Mass: 1.06 gal of water

FORMULAS

  • Surface Area of Box: 2(LW) + 2(WH) + 2(LH)
  • U-Value: 1/ (R-Value)
  • Heat transfer coefficient: q=UAdelta_T

Clearly summarize the outputs of your calculations.

- UA product
- Expected solar gain
In [1]:
from pint import UnitRegistry
u = UnitRegistry()
area = 10 * u.feet**2
u.define('R_US = foot**2 * delta_degF * hour / BTU')
wall_r_value = (0.17 + 0.5 + 0.68) * u.R_US
UA_product = area / wall_r_value
print('Our UA product estimate is', UA_product.to(u.BTU/u.hour/u.delta_degF))
print('Our UA product estimate is', UA_product.to(u.watt/u.delta_degC))

Our UA product estimate is 7.4074074074074066 btu / delta_degF / hour
Our UA product estimate is 3.9076142689629627 watt / delta_degC

Results

  • Include a graph of your temperature performance inside and the temperature outside
  • Include a graph of the temperature difference over time
  • Are the results what you expect?
  • What design improvements would you make?
In [2]:
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd

data = pd.read_csv('my_run.csv', parse_dates=True, index_col=0)
data['t_diff'] = data['t_in_C'] - data['t_out_C']
data[['t_in_C', 't_out_C', 't_diff']].plot()
plt.title('My Title')
plt.ylabel('Temperature (C)')
plt.show()

Contributions

Each team member writes what their contributions to the project are.
You can also comment on how you facilitated teamwork during your project.

In [ ]: