The aim of this study is to evaluate the indoor temperature of a double-skin façades (DSF) high-rise building in Xi’an under different window opening arrangements, and to assess their impact on the operating time of the air-conditioning system. Compared to conventional buildings, double-skin façade (DSF) buildings can reduce energy consumption. While current research trends focus primarily on heat transfer and materials, there is limited exploration of window opening arrangements. To address this gap, VENT engineering software 2018 was used to simulate indoor temperatures at various window opening angles and determine the optimal arrangement. Additionally, the extreme random tree (ET) algorithm was employed to develop a model for indoor temperature prediction. Climate data were sourced from an online database and processed using the Spearman correlation coefficient method. Window opening arrangements were designed using orthogonal tests, and the performance of the DSF was evaluated with computational fluid dynamics (CFD) software (Fluent) 2023R1. An analysis of temperature variation in the double-skin façade (DSF) curtain wall revealed that the ET algorithm predicted indoor temperatures with 93% accuracy at a 50° window opening angle. Optimal window opening arrangement 2 resulted in a 2.7% reduction in the average interior temperature, a 3.6% reduction at a height of 1.2 m, and a decrease in air-conditioning runtime by 1.33 h. The extreme random tree (ET) algorithm was found to be more accurate than other methods in predicting DSF performance. These findings provide insights for optimizing the control and application of double-skin façades and suggest potential synergies with other systems.
