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Response-surface-model based on influencing factor analysis of subway tunnel temperature

机译：基于地铁隧道温度影响因素分析的响应面模型

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Subway tunnel temperature has the significant effects on the thermal environment in both tunnel and public station area. Taking good control of this parameter is meaningful for operating safely and effectively. However, the simulation of subway tunnel temperature is both complex and time-consuming. In this research, tunnel temperature was studied by numerical simulation. The three influencing factors concerning internal heat generation (passenger number, carriage weight, and Regenerative Braking System (RBS) efficiency), and two factors concerning transmission load (soil conductivity and thermal capacity) were analyzed. In order to figure out the overall effect of these five factors, a Response Surface Model (RSM) of the subway tunnel temperature was established by Box-Behnken design, and it is found that the response value of each experiment setup fits well with the simulated result. According to the RSM, if the passenger number, carriage weight, RBS efficiency, soil conductivity, and soil thermal capacity change from the possible minimum to maximum values, the tunnel temperature increases 3.34 degrees C, 1.76 degrees C, 9.26 degrees C, 1.02 degrees C, and 0.46 degrees C, respectively. Therefore, the passenger number and carriage weight have a positive impact on the tunnel temperature; the RBS efficiency, soil conductivity, and thermal capacity have a negative impact. RBS efficiency plays the most important role among the five factors. The response-surface model is an approximated mathematical model with multi-factors, it provides a quick way of predicting subway tunnel temperature in different situations, which could be helpful in both design and operation stages in subway.
机译：地铁隧道温度对隧道和公共车站区域的热环境都有重要影响。对此参数进行良好的控制对于安全有效地运行非常重要。然而，地铁隧道温度的模拟既复杂又费时。在这项研究中，通过数值模拟研究了隧道温度。分析了与内部热量产生有关的三个影响因素（乘客数量，车厢重量和再生制动系统（RBS）效率），以及与传递载荷有关的两个影响因素（土壤电导率和热容量）。为了找出这五个因素的总体影响，通过Box-Behnken设计建立了地铁隧道温度响应面模型（RSM），发现每个实验设置的响应值都与模拟值吻合得很好。结果。根据RSM，如果乘客人数，车厢重量，RBS效率，土壤电导率和土壤热容量从可能的最小值更改为最大值，则隧道温度将升高3.34摄氏度，1.76摄氏度，9.26摄氏度，1.02摄氏度C和0.46摄氏度。因此，乘客人数和车厢重量对隧道温度有积极影响； RBS的效率，土壤电导率和热容量都有负面影响。 RBS效率在这五个因素中起着最重要的作用。响应面模型是具有多种因素的近似数学模型，它提供了一种在不同情况下预测地铁隧道温度的快速方法，这可能对地铁的设计和运营阶段都有帮助。

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