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This study aims to optimize thermal comfort in a twin-aisle wide-body aircraft cabin. An intelligent optimization platform was established based on the open-source multi-objective framework JMetal, integrating computational fluid dynamics (CFD) simulations with genetic algorithms to solve key parameters including 3D flow field characteristics, temperature distribution, and air age within the cabin. Considering multiple constraints such as temperature uniformity across different zones and airflow velocity ranges, a non-dominated sorting genetic algorithm (NSGA-II) was employed to co-optimize the spatial configuration parameters of sidewall air supply systems and ceiling vents, ultimately obtaining an optimal ventilation configuration that satisfies all constraints.

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Optimization Design of Thermal Comfort Environment for Dual-Aisle Cabin Based on JMetal

  • 会议论文

  • 发表日期：

    2026年

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  • Shunzhi Pan,
  • Yi Cao,
  • Huayuan Liu

摘要

This study aims to optimize thermal comfort in a twin-aisle wide-body aircraft cabin. An intelligent optimization platform was established based on the open-source multi-objective framework JMetal, integrating computational fluid dynamics (CFD) simulations with genetic algorithms to solve key parameters including 3D flow field characteristics, temperature distribution, and air age within the cabin. Considering multiple constraints such as temperature uniformity across different zones and airflow velocity ranges, a non-dominated sorting genetic algorithm (NSGA-II) was employed to co-optimize the spatial configuration parameters of sidewall air supply systems and ceiling vents, ultimately obtaining an optimal ventilation configuration that satisfies all constraints.