Application of Computational Fluid Dynamics and Open-Source Technologies for Indoor Thermal Comfort Modeling: A Systematic Review and Evidence Synthesis of the Last Decade

Abstract

Over the past decade, Computational Fluid Dynamics (CFD) has become a fundamental tool for the assessment, modeling, and optimization of thermal comfort in controlled architectural environments, enabling detailed simulation of airflow behavior, heat transfer processes, and the spatial distribution of thermo-environmental variables within indoor spaces. The integration of human thermophysiological models has enhanced the predictive capability of these simulations, allowing for more realistic estimations of occupants’ thermal responses and perceptual comfort. In parallel, the growth and maturation of open-source platforms have democratized access to these technologies, facilitating their implementation across multiple scales and building typologies, ranging from offices and residential buildings to vehicle cabins and urban environments. Recent studies have further addressed the evaluation of passive environmental conditioning strategies such as solar chimneys and natural ventilation indoor air quality assessment, and the adaptation of models to local climatic conditions, reflecting a transition toward more comprehensive, resilient, and sustainable design approaches. Moreover, the incorporation of artificial intelligence techniques and predictive control systems has opened new opportunities for operational automation and improved building energy efficiency. Within this context, the present systematic review synthesizes methodological advances, emerging applications, and current trends in the use of CFD and open-source platforms for indoor thermal comfort assessment in architecture, identifying their main contributions, technical limitations, and future research directions.