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| 基于迭代模型的地铁车站空气温度逐年演化特性研究 |
| Study on annual evolution characteristics of subway station air temperature based on an iterative model |
| 投稿时间：2023-11-12 |
| DOI：10.13259/j.cnki.eri.2025.03.003 |
| 中文关键词: 地铁车站|空气-土体流固耦合迭代模型|空气温度|逐年演化特性 |
| 英文关键词:subway station iterative fluid-solid coupling model of air and soil air temperature annual evolution characteristics |
| 基金项目:国家自然科学基金面上项目（51878408） |
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| 中文摘要: |
| 基于地铁车站空气热平衡原理，提出地铁车站空气–土体流固耦合迭代模型，对地铁车站空气温度与围岩土体蓄放热量逐年演化特性进行研究，得到现有空调送风状态、标准工况下地铁车站空气温度逐年演化规律。结果表明，随着地铁车站空气热平衡动态参数的输入，迭代输出的地铁车站空气温度逐年升高，最热月份8月温度由第1年24.2 ℃升高到第15年27.3 ℃，最冷月份1月温度由第1年11 ℃升高到第15年16.8 ℃；地铁车站运营初期围岩土体吸热量逐年减少，达到饱和后蓄放热量逐年变化不大；地铁车站空调季室外侧进入车站热量占比、土体吸热量占比以及设备与照明散热量占比均逐年降低，隧道侧进入车站热量占比和人员散热量占比逐年升高。相较于课题组前期既有研究方案，该迭代方案能更精确地得到车站空气温度逐年演化特性，更具工程实际意义。 |
| 英文摘要: |
| Based on the principle of air heat balance in subway stations, an iterative fluid-solid coupling model of subway station air and soil was proposed to study the annual evolution characteristics of air temperature and the heat storage and release in surrounding rock and soil. This approach reveals the yearly evolution law of subway station air temperature under standard operating conditions with current air-conditioning supply settings. Results show that with dynamic input of the subway station air heat balance parameters, the iteratively calculated air temperature increases annually. The hottest month, August, rises from 24.2 ℃ in the first year to 27.3 ℃ in the 15th year, while the coldest month, January, increases from 11 ℃ in the first year to 16.8 ℃ in the 15th year. During the early operation of the subway station, the heat absorption by surrounding soil decreases yearly; after reaching saturation, the heat storage and release show little annual change. The proportions of heat entering the station from the outdoor side during the air-conditioning season, soil heat absorption, and equipment and lighting heat dissipation all decrease annually, while the proportions of heat entering from the tunnel side and heat from passengers increase over the years. Compared with previous research schemes by the project team, this iterative model more accurately captures the annual evolution characteristics of station air temperature, offering greater engineering practical significance. |
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