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Thermal Modeling of a Typical Room by Use of Inverse Analysis

Kazemipour Papkiadeh, Ali | 2009

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 40788 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Kazemzadeh Hannani , Siamak; Taghizadeh Manzari, Mehrdad
  7. Abstract:
  8. Building simple and effective models are essential to many applications, such as building performance diagnosis and optimal control. Detailed physical models are time consuming and often not cost-effective. Black box models require large amount of training data and may not always reflect the physical behaviors. In this study, a method is proposed to simplify the building thermal model and to identify the parameters of the simplified model. For instance, predicting the next-24-hour load in a building is essential for the optimal control of heating, ventilating and air-conditioning (HVAC) systems that use thermal or cool storage technology. In the first phase of this study, equations for transient heat transfer of walls were solved and radiation between walls, radiation through the window and storage of energy in the room is taken into consideration. For conservation equations for air, the very simple bulk (single node) model is replaced by a zonal model and thus air circulation and also temperature distribution in the room is predicted. The model showed compatible results with the experimental data and also commercial softwares, such as Carrier HAP. The second phase of the project dealt with capabilities of inverse analysis to estimate important unknowns in studying thermal performance of building. These unknowns include instantaneous heating and cooling load, understanding residents’ behavior and how to account for the effect on building simulation, solution parameters in simulation such as wall convection heat transfer coefficients, the number of people in the building, heat production from equipments within the building and many other unknowns. The assessment of the results indicated that the unknown load and heat transfer coefficients were well estimated as functions of time
  9. Keywords:
  10. Air Conditioning ; Inverse Analysis ; Air Zonal Model ; Building Thermal Modeling ; Hourly Heating Load ; Hourly Cooling Load

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