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厦门地铁隧道变形控制指标的确定方法 被引量:3
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作者 李东明 《长江科学院院报》 CSCD 北大核心 2020年第4期90-95,共6页
依托厦门风化花岗岩地层的盾构隧道工程,以土体参数的空间变异性为切入点,针对当前隧道变形控制指标体系存在的针对性不足、科学性不够及适用性不强等问题,结合现场监测数据的统计分析和基于随机场理论的可靠度分析,提出了厦门轨道交通... 依托厦门风化花岗岩地层的盾构隧道工程,以土体参数的空间变异性为切入点,针对当前隧道变形控制指标体系存在的针对性不足、科学性不够及适用性不强等问题,结合现场监测数据的统计分析和基于随机场理论的可靠度分析,提出了厦门轨道交通隧道工程变形控制指标的综合确定方法。结果表明:厦门典型风化花岗岩地层中,盾构隧道施工引起最大地表沉降的统计平均值为-13.50 mm,监测数据的95%分位数约为-32.42 mm;根据可靠度分析,最大地表沉降服从标准正态或对数正态分布形式,随机计算所得最大地表沉降的95%分位数为-35.43 mm。从安全角度出发,建议将-35.0 mm作为厦门典型风化花岗岩地层盾构隧道施工地表沉降的控制值。 展开更多
关键词 隧道变形 地表沉降 控制指标体系 随机场理论 随机可靠度分析 厦门轨道交通
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STOCHASTIC BOUNDARY ELEMENT METHODS FOR 3D PROBLEMS WITH BODY FORCES AND ITS APPLICATION IN RELIABILITY OF TURBINE DISKS
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作者 温卫东 康继东 孙晓玲 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 1995年第2期143-148,共6页
The stochastic boundary element method(SBEM)is developed in this paper for 3D problems with body forces and reliability analysis of engineering structures.The integral equations of SBEM are established by the approach... The stochastic boundary element method(SBEM)is developed in this paper for 3D problems with body forces and reliability analysis of engineering structures.The integral equations of SBEM are established by the approach of partial derivation with respect to stochastic variables,considering the yield limit,rotation speeds and material density to be the fundamental stochastic variables.Through analyzing a numerical example and a turbo-disk of an aeroengine,the results show that the method developed is successful. 展开更多
关键词 boundary element stochastic method STRENGTH RELIABILITY numerical analysis
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Dependence patterns associated with the fundamental diagram:a copula function approach
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作者 Jia LI Yue-ping XU 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 SCIE EI CAS CSCD 2010年第1期18-24,共7页
Randomness plays a major role in the interpretation of many interesting traffic flow phenomena,such as hysteresis,capacity drop and spontaneous breakdown. The analysis of the uncertainty and reliability of traffic sys... Randomness plays a major role in the interpretation of many interesting traffic flow phenomena,such as hysteresis,capacity drop and spontaneous breakdown. The analysis of the uncertainty and reliability of traffic systems is directly associated with their random characteristics. Therefore,it is beneficial to understand the distributional properties of traffic variables. This paper focuses on the dependence relation between traffic flow density and traffic speed,which constitute the fundamental diagram (FD). The traditional model of the FD is obtained essentially through curve fitting. We use the copula function as the basic toolkit and provide a novel approach for identifying the distributional patterns associated with the FD. In particular,we construct a rule-of-thumb nonparametric copula function,which in general avoids the mis-specification risk of parametric approaches and is more efficient in practice. By applying our construction to loop detector data on a freeway,we identify the dependence patterns existing in traffic data. We find that similar modes exist among traffic states of low,moderate or high traffic densities. Our findings also suggest that highway traffic speed and traffic flow density as a bivariate distribution is skewed and highly heterogeneous. 展开更多
关键词 Nonparametric copula Dependence patterns Traffic flow Loop detector
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