Courtyard design impact on indoor thermal comfort and utility costs for residential households: Comparative analysis and deep-learning predictive model

A courtyard is an architectural design element which is often known as microcli-mate modifiers and is responsible to increase the indoor occupant comfort in traditional archi-tecture. The aim of this study is to conduct a parametric evaluation of courtyard design variants in a residential building of different climates with a focus on indoor thermal comfort and utility costs. A brute-force approach is applied to generate a wide range of design alter-natives and the simulation workflow is conducted by Grasshopper together with the environ-mental plugins Ladybug and Honeybee. The main study objective is the evaluation of the occupant thermal comfort in an air-conditioned residential building, energy load, and cost analysis, derived from different design variables including courtyard geometry, window-to -wall ratio, envelope materials, heating, and cooling set-point dead-bands, and building geographical location. Furthermore, a Deep Learning model is developed using the inputs and outputs of the simulation and analysis to transform the outcomes into the algorithmic and tangible environment feasible for predictive applications. The results suggest that regarding the thermal loads, costs, and indoor thermal comfort index (PMV), there are high correlations between the outdoor weather variation and dead-band ranges, while in extreme climates such as Singapore, courtyard spaces might not be efficient enough as expected. Finally, the highly accurate deep learning model is also developed, delivering superior predic-tive capabilities for the thermal comfort and utility costs of the courtyard designs.(c) 2022 Higher Education Press Limited Company. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

This study evaluates courtyard design variants in different climates, focusing on indoor thermal comfort and utility costs. The results show a high correlation between outdoor weather variation and dead-band ranges in relation to thermal loads, costs, and indoor thermal comfort index. In extreme climates like Singapore, courtyard spaces may not be as efficient as expected. Additionally, a deep learning model is developed to predict thermal comfort and utility costs of courtyard designs accurately.