Hong Kong New Town Sustainability Analysis from the Perspective of Low-Carbon Eco-City—Taking Tseung Kwan O New Town as an Example

Liu, Siqi; Huang, Guanqi

doi:10.1088/1755-1315/108/4/042007

Cited by 2 publications

(1 citation statement)

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“…Currently, the development of most Chinese cities is constrained by the urban environment, and there is a growing shift in urban development towards prioritizing "quality" over "quantity". Therefore, exploring optimization and renewal strategies for urban negative spaces has become crucial [4][5][6]. Simultaneously, many international competitions have begun to focus on various types of negative spaces within high-density cities, investigating the relationships between individuals, negative spaces, and urban development [7].…”

Section: Introductionmentioning

confidence: 99%

Optimizing Built Environment in Urban Negative Spaces Using Parametric Methods—Research on a High-Density City in China

Bai,

Wu,

et al. 2024

Buildings

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In the early stage of architectural design, addressing the challenges posed by negative spaces in high-density urban environments is crucial for enhancing spatial efficiency and building sustainability. Multiple studies employed digital methods and tools to address these issues, such as parametric design, simulation, and genetic algorithms, to investigate architectural generation approaches for urban negative spaces. This article proposes an integrated design process that involves finding the location and form of negative spaces, generating solutions using slime mold and wasp algorithms, and optimizing and analyzing solutions using the Wallacei plugin in Grasshopper. This comprehensive approach underscores the potential of parametric design to yield a multitude of solutions while also acknowledging the convergence challenges encountered during simulations, particularly in optimizing for optimal sunlight exposure during the winter solstice and minimal solar radiation in the summer. Analyzing the optimization goals and parameter values of the 15th Pareto optimal solution in the 100th generation reveals: (1) a higher number of units leads to positive correlation growth in both objectives; (2) within a certain number of units, parametrically generated solutions facilitate the convergence of optimization goals, yielding optimal outcomes. Therefore, factors such as the range of unit quantities and proportions need consideration during early-stage parametric design and simulation. This study explores a design methodology for negative spaces in high-density urban cities, validating the feasibility of various mainstream generation methods and offering insights for future research.

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Section: Introductionmentioning

confidence: 99%