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出 处:《路基工程》2018年第1期120-124,共5页Subgrade Engineering
基 金:湖南省教育厅青年基金(16B255)
摘 要:通过对长沙地铁五号线三一大道站基坑开挖过程中周近地表土体沉降监测数据的分析,利用Origin绘图与数据软件对沉降监测数据进行绘图与拟合,采用了指数曲线模型、对数曲线模型以及三类生长曲线模型拟合了沉降量与时间的关系曲线。结果表明:采用生长曲线模型中Logistic模型拟合效果最优,并利用该模型后续曲线的发展情况对地表的沉降进行预测,对可能出现的风险提前做出预警,从而达到规避风险的目的。For the foundation pit engineering at Sanyi Ave Station of Changsha Metro Line 5, the surrounding ground subsidence during the excavation was under supervision. The monitoring data was plotted and fitted with Origin graphics and data software, and then the settlement-time curve was obtained by use of exponential curve model, logarithmic curve model and three types of growth curve model. The result shows that, the logistic model in growth curve model may offer optimal fitting effect, and it could predict the ground surface subsidence in virtue of the extrapolated curve, and make alarm in advance on any possible risk for the purpose of risk control.
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