Development of pavement temperature predictive models using thermophysical properties to assess urban climates in the built environment

Sreedhar, Shashwath; Biligiri, Krishna Prapoorna

doi:10.1016/j.scs.2016.01.012

Cited by 27 publications

(4 citation statements)

References 8 publications

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“…Solar radiation consists of scattered radiation and direct solar radiation, and the daily variation of solar radiation q s can be calculated following Equation (5) [ 44 ]:

where q 0 is the maximum solar radiation at noon, q 0 = 0.131 m Q ; Q is the total daily solar radiation (J/m 2 ); c is the daily effective sunshine hours (h); m is the distribution coefficient for solar radiation, m = 12/ c ; ω is the angular frequency, ω = 2π/24 (rad).…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Stone Mastic Asphalt Containing Ceramic Waste Aggregate for Cooling Asphalt Pavement

Huang

Qian

et al. 2020

Materials

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Construction and demolition waste material is of great potential for use in pavement engineering. This paper aims to investigate the feasibility of ceramic waste aggregate (CA) used in cooling asphalt pavement through a series of test methods and simulation techniques. Stone mastic asphalt (SMA) containing 10%, 20%, 30%, 40%, and 50% coarse ceramic waste aggregate (CASMAs) was first designed using the Marshall method. Afterward, the road performance and thermal insulation performance of the five different CASMAs were assessed by a comprehensive lab test, including a wheel rutting test, moisture susceptibility test, bending beam test, fatigue beam test, and indoor thermal insulation test. Finally, a 2D finite-element (FE) model was developed to investigate the transient thermal field and rutting deformation response of the cooling asphalt pavement with CASMAs. Results show that CASMAs experienced degradation of rutting resistance, moisture susceptibility, and anti-cracking performance while still meeting technical requirements with CA content of up to 40%. On the other hand, CASMAs can cool the pavement’s temperature by 11.5 °C at the bottom of asphalt layers. The permanent rutting deformation of cooling asphalt pavement was 45.36% smaller than that of conventional asphalt pavement without CASMAs. Based on the test results and numerical simulation results, the optimum content of ceramic waste aggregate in stone mastic asphalt was recommended as 40%.

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“…Solar radiation consists of scattered radiation and direct solar radiation, and the daily variation of solar radiation q s can be calculated following Equation (5) [ 44 ]:

Section: Methodsmentioning

confidence: 99%

Evaluation of Stone Mastic Asphalt Containing Ceramic Waste Aggregate for Cooling Asphalt Pavement

Huang

Qian

et al. 2020

Materials

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“…K −1 . At the interface between the wall and the outside air, convective, short and long wave radiation heat transfer occur [36]. Thus, the boundary conditions is formulated as:…”

Section: Heat Transfermentioning

confidence: 99%

Assessing the wall energy efficiency design under climate change using POD reduced order model

Berger,

Allery,

Machard

2022

Preprint

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Within the environmental context, numerical modeling is a promising approach to assess the energy efficiency of building. Resilient buildings need to be designed, capable of adapting to future extreme heat. Simulations are required assuming a one-dimensional heat transfer problem through walls and a simulation horizon of several years (nearly 30). The computational cost associated with such modeling is quite significant and model reduction methods are worth investigating. The objective is to propose a reliable reduced-order model for such long-term simulations. For this, an alternative model reduction approach is investigated, assuming a known Proper Orthogonal Decomposition reduced basis for time, and not for space as usually. The model enables computing parametric solutions using basis interpolation on the tangent space of the Grassmann manifold. Three study cases are considered to verify the efficiency of the reduced-order model. Results highlight that the model has a satisfying accuracy of 10 −3 compared to reference solutions. The last case study focuses on the wall energy efficiency design under climate change according to a four-dimensional parameter space. The latter is composed of the load material emissivity, heat capacity, thermal conductivity and thickness insulation layer. Simulations are carried over 30 years considering climate change. The solution minimizing the wall work rate is determined with a computational ratio of 0.1% compared to standard approaches.

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“…Luo et al [27] reported that wind speed, daily maximum and minimum temperature, cloud cover, radiation, road surface reflectivity, sunshine time, and precipitation factors would all affect the mode of heat transfer between road and external environment. Sreedhar and Biligiri [28] suggested that pavement temperature was a function of various climatic and thermal properties, including wind speed, relative humidity, air temperature, and so on. Tan et al [29] pointed out that most pavements were exposed to harsh natural environments so that their internal temperature was often affected by local climate and hydrological and meteorological factors (such as air temperature, air humidity, solar radiation, rainfall, and wind speed).…”

Section: Introductionmentioning

confidence: 99%

Prediction Model for Asphalt Pavement Temperature in High-Temperature Season in Beijing

Jing

Zhang

2018

Advances in Civil Engineering

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Asphalt pavement temperatures greatly influence on the bearing capacity and performance, especially in high-temperature season. e variation rules of pavement temperatures under the high-temperature range affect the design and maintenance management of the asphalt pavement, as well as the accurate prediction for pavement temperatures. However, asphalt pavement temperature is greatly affected by various strongly correlated environmental factors and cannot be measured directly or predicted effectively. In this project, temperature sensors were embedded in the pavement of in-service road to collect temperature data by continuous record measurement, and regression model was conducted by the partial least squares method through comprehensive analysis on the pavement temperature data and synchronously environmental data from local weather station measured in July 2013, July 2014, and July 2015. e quantitative relationships in high-temperature season between environmental factors and pavement temperature were determined, and a model was established to predict the temperature of asphalt pavement based on environmental data. e model was verified by the recorded data from July 1, 2016, to July 31, 2016, and the results indicated that the pavement temperature can be predicted accurately and reliably by the proposed model.

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Development of pavement temperature predictive models using thermophysical properties to assess urban climates in the built environment

Cited by 27 publications

References 8 publications

Evaluation of Stone Mastic Asphalt Containing Ceramic Waste Aggregate for Cooling Asphalt Pavement

Evaluation of Stone Mastic Asphalt Containing Ceramic Waste Aggregate for Cooling Asphalt Pavement

Assessing the wall energy efficiency design under climate change using POD reduced order model

Prediction Model for Asphalt Pavement Temperature in High-Temperature Season in Beijing

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