| dc.description.abstract | High energy demand and the use of greenhouse gases are issues of today’s world. The world has a higher energy consumption now than ever before, and it is estimated to increase further. With the rise of renewable energy, we can help decrease the greenhouse gases on the planet.[10] However, by just building renewable infrastructure, which has a lower energy outcome than fossil fuels, we will not fight the energy demands[13].
The energy demand vs. production can be more stable by not wasting energy by working in other ways. This thesis will present a dynamic heating model made with discretized formulas of mass and energy balances. The model will simulate the indoor temperature with scenarios and environments on a small and more significant scale.
The thesis’ hypothesis will be to check if a physical model can help learn more about the environment of a building and how it responds to different scenarios. Testing both the hypothesis and the model itself, scenarios of both average and extreme standards will be used in the simulations. The model will also implement different buildings with different criteria to test how the physical model will react when given other parameters.
The simulations show results in which the model behaves as intended. The results show how the temperature of the building reacts when introducing different parameters, such as outdoor temperature or sunlight, and how parameters such as airflow can help reduce the temperature. This model can help make improvements on how to keep the energy at a minimum. | |
