Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.csite.2019.100395
Title: Modelling surface temperature of granite seawalls in Singapore
Authors: Zhao, K 
Yuan, J 
Loke, LHL 
Chan, SHM
Todd, PA 
Li-Fan Liu, P 
Issue Date: 1-Mar-2019
Publisher: Elsevier BV
Citation: Zhao, K, Yuan, J, Loke, LHL, Chan, SHM, Todd, PA, Li-Fan Liu, P (2019-03-01). Modelling surface temperature of granite seawalls in Singapore. Case Studies in Thermal Engineering 13 : 100395-100395. ScholarBank@NUS Repository. https://doi.org/10.1016/j.csite.2019.100395
Abstract: © 2019 The Authors. Temperature is a critical abiotic factor structuring intertidal life on hard-bottom habitats, including manmade coastal defense structures. To quantitatively describe the daily surface temperature variations of a seawall in Singapore, a physically based mathematical model is developed, which considers key thermal processes (i.e., solar radiation absorption, long wave emission, and heat convection). This model is nonlinear because of the nonlinear boundary conditions and the moving seawater level boundary. It is therefore solved numerically with appropriate initial conditions. Good model - data comparison is confirmed with field measurements. Results show that the maximum seawall temperature reached as high as about 48 °C. Temperature variation was illustrated using contour plots. A high temperature index on the seawall, T 95% , is defined as the threshold temperature that 95% of all temperatures at a given elevation do not exceed. T 95% will be useful for investigating the effects of temperature on biodiversity in intertidal systems. The effect of seawall slopes and monsoons on T 95% is further examined. For Singapore's seawalls, it is found that the extreme temperature decreases with increasing slope, and the T 95% during the southwest monsoon season is approximately 4 °C higher than that during the northeast monsoon.
Source Title: Case Studies in Thermal Engineering
URI: https://scholarbank.nus.edu.sg/handle/10635/155843
ISSN: 2214157X
DOI: 10.1016/j.csite.2019.100395
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