研究目的
To investigate numerically the impact of tungsten (W) doped vanadium dioxide (VO2) application as a smart outdoor wall layer on building energy consumption in the Mediterranean climate, specifically for the Moroccan city of Meknes.
研究成果
W doped VO2 application reduces indoor surface temperature by 2-3°C in summer, with 70% cooling energy savings and minimal heating energy loss. It offers real-time dynamic control of solar absorptivity, making smart walls feasible for energy-efficient buildings in Mediterranean climates, with a payback period of about 4 years.
研究不足
The study is numerical and not experimental; it assumes specific material properties and climate data. The W doping reduces optical modulation by 20%, limiting winter performance. The model is 1D and may not capture all real-world complexities.
1:Experimental Design and Method Selection:
A numerical simulation using finite difference method implemented in Matlab to solve the 1D heat transfer equation, considering conductive, convective, and radiative heat transfer modes. The model includes dynamic variations of W doped VO2 absorptivity based on outdoor temperature.
2:Sample Selection and Data Sources:
Meteorological data (solar radiation and outdoor air temperature) for Meknes city in 2016 from Meteonorm, covering summer (July 16-23) and winter (December 24-31) weeks.
3:List of Experimental Equipment and Materials:
Wall configurations with materials including cement plaster, brick, glass substrate, and W doped VO2 thin film; properties such as thickness, thermal conductivity, density, and specific heat are specified.
4:Experimental Procedures and Operational Workflow:
Temperature distributions are calculated for four orientations (south, north, east, west) with and without W doped VO2. Absorptivity is modeled using hysteresis functions based on sol-air temperature. Decrement factor, time lag, and energy loads are computed.
5:Absorptivity is modeled using hysteresis functions based on sol-air temperature. Decrement factor, time lag, and energy loads are computed.
Data Analysis Methods:
5. Data Analysis Methods: Analysis includes temperature profiles, energy savings, cost analysis using present worth factor, and payback period calculation.
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