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This Special Issue focuses on the need for advanced simulation techniques and computational methods in improving building energy efficiency. With increasing trends in global energy consumption and the escalating impact of climate change, reliable predictive modeling of building performance and energy consumption has become a critical part of sustainable construction. This Reprint gathers the state-of-the-art research that fills the gap between theoretical modeling and practice in the energy management and environmental performance of buildings. This collection includes a variety of methodological approaches, such as machine learning models for predicting thermal loads and advanced computation methods used to optimize an HVAC system. The presented studies have explored diverse building typologies in diverse climate regions, covering retrofit impact in various climatic regions, energy disaggregation for buildings, and improved methods of thermal bridge analysis. Collectively, these contributions extend the scientific understanding of optimizing building performance using advanced modeling approaches, facilitating the shift toward a net-zero energy future and sustainable development for the building sector.
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