|本期目录/Table of Contents|

[1]朱彦鹏,蔡文霄,杨校辉.高填方路堤沉降模型现场试验[J].建筑科学与工程学报,2017,34(01):84-90.
 ZHU Yan-peng,CAI Wen-xiao,YANG Xiao-hui.Field Test of High Embankment Settlement Model[J].Journal of Architecture and Civil Engineering,2017,34(01):84-90.
点击复制

高填方路堤沉降模型现场试验(PDF)
分享到:

《建筑科学与工程学报》[ISSN:1673-2049/CN:61-1442/TU]

卷:
34卷
期数:
2017年01期
页码:
84-90
栏目:
出版日期:
2017-01-19

文章信息/Info

Title:
Field Test of High Embankment Settlement Model
作者:
朱彦鹏蔡文霄杨校辉
兰州理工大学甘肃土木工程防灾减灾重点实验室
Author(s):
ZHU Yan-peng CAI Wen-xiao YANG Xiao-hui
Key Laboratory of Disaster Prevention and Mitigation in Civil Engineering of Gansu Province, Lanzhou University of Technology
关键词:
单点沉降计高填方路堤预测模型工后沉降组合模型
Keywords:
single point settlement gauge high embankment prediction model post-construction settlement combination model
分类号:
-
DOI:
-
文献标志码:
A
摘要:
通过单点沉降现场实测数据对软土地区兰永一级公路高填方路堤沉降规律进行分析,建立了指数模型、乘幂模型、双曲线模型、对数模型4种沉降预测模型,并将这4种模型的预测值和实测值进行对比,在此基础上,利用最小二乘法建立了指数与双曲线模型的组合模型。结果表明:4种模型中指数模型和双曲线模型的预测精度相对较高,利用指数与双曲线组合模型得到的预测曲线与实测曲线吻合良好,使误差平方和减小到22.789 mm2,能够满足工程要求;高填方路堤工后沉降在730 d左右的时间内基本完成,预测最终沉降量为60.44 mm。
Abstract:
The settlement laws of high embankment on LanzhouYongjing expressway in soft soil area were analyzed through insite measuring data by single point settlement gauge. Four kinds of settlement forecasting models including exponential model, power model, hyperbolic model and logarithmic model were established and the forecasting values and measuring values of settlements were compared. Based on this, combination model of index model and hyperbolic model was established. The results show that exponential model and hyperbolic model are relatively accurate in the four kinds of models, the forecasting curves of combination model of index model and hyperbolic model agreed with the measuring curves, and the error sum of squares is 22.789 mm2, which satisfy the need of engineering, the postconstruction settlement of high embankment will finish within about 730 d, the forecasting final settlement is 60.44 mm.

参考文献/References:

相似文献/References:

备注/Memo

备注/Memo:
更新日期/Last Update: 2017-01-20