Abstract

The study of performance-driven optimization (PDO) in urban block design is essential in the context of architectural form and urban sustainability. PDO focuses on the integrated and comprehensive optimization of various quantifiable performances of buildings, such as solar energy usage, thermal comfort, and energy efficiency. This method aligns urban spaces with sustainable development principles, ensuring they are not only aesthetically pleasing but also functionally efficient. This study explores the existing deficiency in the literature by conducting an in-depth scientometric analysis of PDO in urban block design. Employing science mapping coupled with bibliometric analysis using Python, this study meticulously analyzes the prevailing literature to map out the current intellectual landscape, understand trends, and identify key themes within this domain. This review identifies the key trends, methodologies, and influential works shaping the dynamic field of PDO. It emphasizes the critical roles of computational simulation, artificial intelligence integration, and big data analytics in refining urban block design strategies. This study highlights the growing importance of energy efficiency, environmental sustainability, and human-centric design elements. This review points to an increasing trend towards using sophisticated modeling techniques and data-driven analysis as essential tools in urban planning, crucial for developing sustainable, resilient, and adaptable urban spaces.

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