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作 者:古林强[1] 李建军[1] 邹君 徐士伟 张东旭 GU Lin-qiang;LI Jian-jun;ZOU Jun;XU Shi-wei;ZHANG Dong-xu(School of Architecture and Urban Planning,Guangzhou University,Guangzhou 510006,China;Guangzhou Transportation Planning Research Institute Corporation,Guangzhou 510180,China)
机构地区:[1]广州大学建筑与城市规划学院,广东广州510006 [2]广州市交通规划研究院有限公司,广东广州510180
出 处:《广州大学学报(自然科学版)》2023年第3期10-18,74,共10页Journal of Guangzhou University:Natural Science Edition
基 金:广州大学科研基金资助项目(PT252022006)。
摘 要:近年来,随着国内大城市轨道交通运输的快速发展,地铁网络建设日新月异。地铁在给人们带来快捷和便利的同时,地铁列车运行引起的振动和噪声对周围环境和周边居民生活造成负面影响的问题日益凸显。为了评估地铁引起的二次辐射噪声影响并提高预测精度,文章以广州市地铁二号线列车运行产生的振动噪声对临近的云珠酒店的影响为例,采用声学-固体边界声振耦合计算的有限元方法,分析了地铁导致的周围建筑物室内二次噪声的空间分布特征。模拟结果显示,建筑物内测点实测值与仿真值比较,除了20~50 Hz的低频预测值比实测值稍小外,其他频段的一致性较好,二者的误差均在3 dB以内,说明本研究选用的声振耦合仿真方法可以减少人为设定的误差,提高了对地铁运行产生的周围建筑物二次噪声的预测精度,为将来进行相关的研究提供了一种较为可靠的预测方法。In recent years,with the rapid development of urban mass transit,the construction of subway networks is changing rapidly.The subway brings convenience and rapidity to people.At the same time,the vibration and noise caused by the running of the subway train have a negative effect on the surrounding environment and the lives of the residents.In order to evaluate the influence of the secondary radiation noise caused by subways and to improve prediction accuracy,this paper takes the impact of the vibration noise caused by the train running of Guangzhou Metro Line 2 on the nearby Yunzhu hotel as an example,based on the finite element method,the spatial distribution characteristics of secondary noise in surrounding buildings caused by subway were analyzed.The simulation results show that,when comparing the measured values with the simulated values,the consistency of the other frequency bands is good,except that the predicted values of 20~50 Hz are slightly smaller than the measured values,and the errors of the two bands are all within 3 dB,it shows that the simulation method of acoustic-vibration coupling can reduce the artificial and set error,and improve the prediction accuracy of secondary noise in the surrounding buildings,this provides a more reliable prediction method for the related research in the future.
分 类 号:TP332[自动化与计算机技术—计算机系统结构]
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