A modified NARX approach for evaluating the time history effect of climate change on load combination in designing façade structures

Abstract

Abstract In recent years, researchers, designers, and project owners have deemed the dry facade system to be a suitable option. Consequently, much research has been conducted on the structural behavior of the dry facade system when subjected to seismic loads, climate change, thermal loads, etc. Of particular concern is the destructive phenomenon of corrosion due to climate change in coastal areas which can damage the infrastructure of the dry façade. To address this issue, a modified NARX method was employed in this study to predict climate change variables for use in dry facade analysis. The author of this paper developed a flowchart and subroutines in MATLAB as a new toolbox for this purpose. Temperature was identified as the most influential parameter in consequent configurations and was thus considered in load combination for the design of a dry facade structure. The statistical results obtained from NARX showed good agreement with measured data; specifically, there was a low mean absolute error (MAE) of 0.345 °C, a low root-mean-square error (RMSE) of 0.442 °C, and a high coefficient of determination (R 2) of 0.998 (P-value = 0.918 > 0.05). Finally, this study proposed a modified formula for load combination to ensure durability and constructability of dry facades in coastal cities.

Keywords

• Climate change
• Artificial neural network
• Building façades
• Structure design
• Load combination