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Abstract

The literature emphasizes the role of the early-stage design process, particularly early design decisions related to mid-rise residential buildings. On the other hand, the futuristic concepts of high-performance architecture represent a paradigm shift that requires a data-conscious approach to climate change mitigation. This research adopts a designer approach to address the complex and ill-defined sci-tech problems within the architectural field. The study aims to develop a framework for a user-friendly, data-driven Designerly Decision Support System (DDSS) to categorize and automate the architectural design process, with a particular focus on the early design stage. The methodology is based on in-depth structured interviews with architects to identify and classify influential parameters in the early design stages. These parameters were extracted to construct a metamodel. Subsequently, sensitivity analysis was employed to investigate the background of key performance metrics and the relationships among them. The research calculates the energy loads of nine mid-rise residential building patterns in Tehran using Energy Plus software. Based on the quantitative results, three representative patterns—1) high-consumption, 2) low-consumption, and 3) mid-rise—were selected for further sensitivity analysis. The findings indicate that a reference database can be created to comprehensively guide designers working on mid-rise residential patterns. This database can also serve as a resource for revising urban planning guidelines with energy metrics in mind. Additionally, the north and south Window-to-Wall Ratios (WWRs) are identified as the most significant design parameters, directly and interactively influencing heating, cooling, and lighting functions.

Keywords

Design process Designerly approach Design support system (DSS) Simulation Sensitivity analyses High-performance architecture

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Al-Kazee, M. F., Negin Taji, S., Nasr, T. ., Mansoori, R. ., & Mahdavinejad, M. (2025). Reframing the early-stage design process of residential buildings based on an energy-efficient, designerly decision support system (DDSS). Future Technology, 4(2), 30–40. Retrieved from https://fupubco.com/futech/article/view/285
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