Development of pavement temperature predictive models using thermophysical properties to assess urban climates in the built environment
| Autor: | Krishna Prapoorna Biligiri, Shashwath Sreedhar |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Renewable Energy
Sustainability and the Environment 020209 energy Geography Planning and Development 0211 other engineering and technologies Transportation 02 engineering and technology Heat capacity Wind speed Moment (mathematics) Thermal conductivity Asphalt Urban climate 021105 building & construction 0202 electrical engineering electronic engineering information engineering Environmental science Relative humidity Geotechnical engineering Urban heat island Civil and Structural Engineering |
| Zdroj: | Sustainable Cities and Society. 22:78-85 |
| ISSN: | 2210-6707 |
| DOI: | 10.1016/j.scs.2016.01.012 |
| Popis: | This study developed pavement temperature predictive models based on the characterized thermophysical properties of different pavements to assess urban climates in the built environment. A database comprising of six pavement types including conventional and modified asphalt, and cement concrete mixtures was available with their thermophysical properties: specific heat capacity, thermal conductivity and material density. Models were developed to predict temperature at the surface, and at 40 mm depth using the measured thermophysical properties, and recorded climatological parameters: air temperature, wind speed, and relative humidity. The two predictive models were robust and rational depicted by low bias and high precision. An increase in heat capacity increased pavement surface temperature indicating that higher energy is required to raise the pavement temperature, and also be able to release as much energy as stored, which would be best suitable at different times of the day to counter urban heat island (UHI) effects. An increase in thermal conductivity decreased pavement temperature illustrating that the pavement would store more heat within the system for a longer duration, and may release this heat at a particular timeframe changing the urban climate at that moment. An increase in wind speed by about 1 m/s increased pavement temperature by 1 °C, and this may increase UHI if there is already higher temperature in the environment. Overall, based on rational correlations between model predictions and actual field measurements it is recommended that the pavement temperatures of the systems be comfortably predicted for pavements using the developed models. |
| Databáze: | OpenAIRE |
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