Computational Design for Multi-Optimized Geometry of Sustainable Flood-Resilient Urban Design Habitats in Indonesia

Aref Maksoud (), Sarah Isam Abdul-Rahman Alawneh, Aseel Hussien, Ahmed Abdeen and Salem Buhashima Abdalla
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Aref Maksoud: Department of Architectural Engineering, College of Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
Sarah Isam Abdul-Rahman Alawneh: Department of Architectural Engineering, College of Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
Aseel Hussien: Department of Architectural Engineering, College of Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
Ahmed Abdeen: Department of Architectural Engineering, College of Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
Salem Buhashima Abdalla: Department of Architectural Engineering, College of Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates

Sustainability, 2024, vol. 16, issue 7, 1-42

Abstract: Unfortunately, flooding is a major worldwide problem that especially affects low-lying cities like Semarang, Indonesia. Therefore, this study focuses on the flood-prone areas of Semarang, where recurring high tides and surges from severe precipitation cause havoc. In order to create water-resistant dwelling topologies, the paper explores the early incorporation of computational design approaches. Ultimately, the objective is to explore the strategic application of generative design techniques to support the development of a highly adaptive urban environment using optimization-based data-driven design approaches. With careful consideration, advanced computational methods were used to find concepts that may manage and lessen possible consequences in an efficient manner, increasing the urban landscape’s overall flexibility. Achieving the best possible solutions, which consider issues like feasibility, sustainability, durability, adaptability, and user comfort, requires the application of computational studies such as microclimatic, rainfall, energy performance, and fluid simulations. Consequently, promising advances in water retention and trajectory control features are shown by evaluations that concentrate on wind dynamics and energy considerations. One such example is GEN_8, the most optimal typology produced by additive massing approaches. In addition to showing less water retention than usual building typologies, GEN_8 optimizes energy performance to improve user experience overall. Accordingly, the computationally created geometry GEN_8’s shaded areas and facades effectively account for between 191.4 and 957 kWh/m 2 of yearly solar radiation. In contrast, average building typologies show higher amounts of annual solar radiation, with a minimum of 574.32 kWh/m 2 and a maximum of 1148.65 kWh/m 2 . This paper’s comprehensive approach not only addresses worldwide issues but also highlights how computational design techniques may be used to construct, assess, and validate workable solutions for flood-prone locations within a flexible framework that has been painstakingly designed. As a result, the research also highlights the significance of technological advancements and computational tools in assessing, producing, and validating workable solutions for flood-prone locations by carefully curating a flexible framework that ensures efficiency, comfort, and design optimization.

Keywords: computational design; design optimization; analytical simulations; data-driven design; grasshopper (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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