Scholarlink

Urban heat waves are becoming more frequent and severe due to climate change, posing significant challenges to residential buildings, particularly in regions like Helsinki, where structures are designed for cold climates. Nordic buildings, with high insulation and air tightness, are particularly prone to overheating during heat waves, leading to discomfort and health risks to the occupants. Previous research has analyzed the overheating patterns and effect of urban microenvironment parameters based on measurements in more than 2000 apartments in the Helsinki area during the 2018, 2020 and 2021 summer heat waves. This study examines the impact of urban microenvironmental factors such as greenery and urbanization via a Digital Twin prediction model, based on the IDA ICE simulation results. Simulations were carried out in various building groups with different orientations, levels of greenery, degrees of urbanization, with 2018 summer weather data from the Finnish Meteorological Institute. The simulation results were utilized to train a Digital Twin prediction model to assess the impact of these factors on thermal comfort parameters. Subsequently, an optimal configuration was found by using a Genetic Algorithm. This study highlights the importance of considering urban microenvironmental factors in building design, to enhance resilience against future climate challenges and reduce heat-related health risks in urban settings in the Nordic countries.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Combining Digital Twin and Genetic Algorithms to Quantify the Effect of Urban and Microenvironmental Factors on Thermal Comfort in Residential Buildings

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Maliheh Jahanbakhsh,
  • Ilia Kravchenko,
  • Andrea Ferrantelli

摘要

Urban heat waves are becoming more frequent and severe due to climate change, posing significant challenges to residential buildings, particularly in regions like Helsinki, where structures are designed for cold climates. Nordic buildings, with high insulation and air tightness, are particularly prone to overheating during heat waves, leading to discomfort and health risks to the occupants. Previous research has analyzed the overheating patterns and effect of urban microenvironment parameters based on measurements in more than 2000 apartments in the Helsinki area during the 2018, 2020 and 2021 summer heat waves. This study examines the impact of urban microenvironmental factors such as greenery and urbanization via a Digital Twin prediction model, based on the IDA ICE simulation results. Simulations were carried out in various building groups with different orientations, levels of greenery, degrees of urbanization, with 2018 summer weather data from the Finnish Meteorological Institute. The simulation results were utilized to train a Digital Twin prediction model to assess the impact of these factors on thermal comfort parameters. Subsequently, an optimal configuration was found by using a Genetic Algorithm. This study highlights the importance of considering urban microenvironmental factors in building design, to enhance resilience against future climate challenges and reduce heat-related health risks in urban settings in the Nordic countries.