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author:

Zheng, Y. (Zheng, Y..) [1] | Liang, F. (Liang, F..) [2] | Zhu, B. (Zhu, B..) [3] | Hong, T. (Hong, T..) [4] | Xu, D. (Xu, D..) [5]

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Scopus

Abstract:

Marine climate significantly influences the spatial morphology of coastal village’s streets. However, research on coastal villages lacks spatial parameterization analysis that can cope with the complex climatic environment. Focusing on the coastal village’s street in Fuzhou City, China, this paper studies the relationship between street space morphology and the impact of extreme heat and wind conditions. Thermal comfort degree and the average wind speed are main optimization objectives. By using parameterization techniques to establish a dynamic model and conducting multi-objective optimization driven by genetic algorithms, the degree of influence of morphological indicators and climate indicators is revealed. The conclusions of the study indicate that the morphological indicators of the main space have a more significant impact on the climatic environment than the morphological indicators of the interfaces on either side of the street. The influence of thermal comfort indicators on the street space within the climate environment is greater than that of wind speed indicators. This study concludes by proposing a ranking of key morphological indicators along with their optimal intervals for coastal villages adapted to the marine climate. The key morphological indicators, listed in order of importance, include appropriate street widths (2.3–4.3 m), eave height for single-storey buildings (2.0–4.6 m), eave height for double-storey buildings (5.4–7.7 m), eave depth (0.8–1.1 m for brick-timber dwellings and 0.3–0.6 m for masonry dwellings), roof slope (20–28°), entrance space depth (0.8–1.3 m), balcony overhang depth (0.6–0.7 m), colonnade depth (1.5–2.4 m), street orientation (NE-SW) and building depth (3.2–5.0 m). This study provides an empirical reference for climate-adapted village design and renewal. © The Author(s) 2024.

Keyword:

Coastal village’s Street Coupling relationship Genetic algorithm Marine climate Multi-objective optimization

Community:

  • [ 1 ] [Zheng Y.]School of Architecture and Urban-Rural Planning, Fuzhou University, Fuzhou, 350108, China
  • [ 2 ] [Liang F.]School of Architecture and Urban-Rural Planning, Fuzhou University, Fuzhou, 350108, China
  • [ 3 ] [Zhu B.]College of Urban Construction, Zhejiang Shuren University, Hangzhou, 310023, China
  • [ 4 ] [Zhu B.]College of Architecture, Zhejiang University of Technology Zhijiang College, Shaoxing, 312030, China
  • [ 5 ] [Hong T.]School of Architecture and Urban-Rural Planning, Fuzhou University, Fuzhou, 350108, China
  • [ 6 ] [Xu D.]School of Spatial Planning and Design, Hangzhou City University, Hangzhou, 310015, China

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Source :

Scientific Reports

ISSN: 2045-2322

Year: 2025

Issue: 1

Volume: 15

3 . 8 0 0

JCR@2023

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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