Centrifuge model test and field measurement analysis for foundation pit with confined water

The similarity law of centrifuge test was developed for the seepage field and stress field of a foundation pit with confined water by analyzing control equations, and a similarity index and a similarity coefficient of centrifuge test were obtained. Based on the deep foundation pit of the Huangxing Road Station of the Shanghai metro line M8, the deformation stability of the pit was tested. Finally, a comparative study was conducted on the test results of the pit deformation and the field measurement results. Comparison results show that the pit deformation regularity of the test is basically identical with that of the field measurement, and the difference in pit deformation between the test and the field measurement is within 50%. The centrifuge model test can effectively simulate the displacement response of the ground and retaining structure during dewatering and excavation for the pit with confined water, which provides a reliable basis for the design and construction of the pit with confined water.     

基于安全性分析的山区公路弯坡组合路段设计指标研究

我国当前设计方法对于山区公路,尤其是弯坡组合路段安全性考虑不足。基于车辆在弯坡组合路段行驶的安全性分析,以事故临界状态为限制条件建立弯坡组合路段安全模型。基于安全模型计算讨论了大小代表车型下,弯坡组合路段最小半径、最大坡长等关键设计指标受车路参数的影响及变化规律,利用Carsim仿真软件对变化规律进行了一致性验证,验证了该安全模型的有效性。根据安全模型及仿真计算结果,弯坡组合路段最小半径值与设计车速、路段坡度成正比,与路段超高、横向附着系数值成反比;弯坡组合路段最大坡长值与道路滚动阻力系数、滑移率成正比,与设计车速、路段坡度,以及车型大小成反比,但总体受超高值影响较小。进一步计算分析了考虑车辆实际运行车速下的弯坡组合路段设计指标阈值,并指出对于弯坡组合路段应尽可能采取小纵坡并增大最小半径值,以提高山区公路弯坡组合路段安全水平。     

基于DEM-FDM耦合的普通铁路碎石道床-土质基床界面接触应力分析

引入离散元法（DEM）-有限差分法（FDM）耦合算法对普通铁路碎石道床-土质基床的界面应力进行分析。首先,基于激光扫描以及室内三轴试验,实现碎石道砟颗粒二维精细化离散元建模,并通过设置界面单元进行道砟与土两类不同介质层间速度与力的相互传递,实现离散元法与有限差分法耦合,建立了轨枕-碎石道床-连续土体耦合模型,并通过现场实测结果验证模型的合理性。在此基础上,计算列车通过时耦合模型中基床动应力分布特征,讨论轨枕-道床接触状态对其影响,并将计算结果与轨枕-道床-基床的整体有限元模型的计算结果进行对比。结果表明,轨枕-道床未完全密贴接触状态下,道床中力链呈离散型传递,反之,道床中力链呈向下扩散发展;两种接触状态下,基床表面应力分布差别显著,但是应力峰值接近。耦合模型得到的基床表面应力峰值显著高于有限元模型的计算结果;耦合模型中因道砟散体特性引起的基床表面局部应力集中,在路基中的影响深度约为道砟最大粒径（63 mm）的8倍,即近似基床表层深度。     

局部加卸载下立方体阵列接触力残留的细观特性

基于光弹试验分析立方体阵列在一个分级加卸载周期下力链和颗粒位移的演化过程,结果表明,接触力和颗粒位移在卸载阶段均存在残留,且接触力和颗粒位移的演化特征一致表明,卸载过程中存在一个临界荷载值。通过建立主力链颗粒的串联接触模型,得出残留接触力取决于力链所受侧向摩阻力,包括颗粒间接触摩擦与咬合力。结合光弹条纹解析所得特征颗粒所受接触力,分析加卸载作用下主力链所受摩阻力的演化特征,得出加卸载过程中主力链所受摩阻力与外荷载呈正相关,表明随着外荷载的增大,颗粒体系的内摩擦作用逐渐发挥以抵抗外力;但相同外荷载下,加载和卸载阶段主力链所受摩阻力并不相等,是立方体阵列产生残留接触力的根源。     

Proactive,Backward Analysis and Learning in Road Probabilistic Bayesian Network Models

Some probabilistic safety assessment models based on Bayesian networks have been recommended recently for safety analysis of highways and roads. These methods provide a very natural and powerful alternative to traditional approaches, such as fault and event tree based methods. In this article, we present several new and original contributions to complement the inference engine tools of these models to provide new and relevant information about safety and backward analysis on one hand, and to learn the complex multidimensional joint probabilities of all variables, on the other hand. More precisely, we show how standard tools combined with the partitioning technique can be used in new ways to solve three relevant problems (1) to prognosticate the most probable combinations of variables leading to incidents, (2) to perform a backward analysis to identify the causes of accidents, and (3) to learn the model parameters using Bayesian conjugate methods (categorical and Dirichlet families). Finally, some real examples of applications are used to illustrate the proposed methods.     

Robust Optimal Lane Allocation for Isolated Intersections

Lane allocation including approach and exit lane numbers and lane markings of approach lanes plays an important role in improving the capacity of an intersection. Conventional approaches for optimizing lane allocation often ignore fluctuations in traffic demand (TD). This article presents a stochastic model for robust optimal lane allocation of an isolated intersection under stochastic traffic conditions. This model is built in three steps. In the first step, an enhanced lane‐based model in the form of a binary mixed‐integer nonlinear program is proposed to optimize lane allocation and traffic signals for both vehicles and pedestrians in a unified framework under deterministic traffic conditions. In the second step, a two‐level stochastic model is developed to obtain a robust lane allocation that is less sensitive to traffic flow fluctuations considering the flexibility of traffic signals. In the third step, the two‐level model is further transformed into a TD‐based stochastic model in a two‐phase form to reduce the solution dimension for efficient computation. A TD‐based genetic algorithm procedure is presented for solvability. Numerical studies are conducted to validate the model formulations and solution algorithms.     

Increasing the Capacity of the Intersection Downstream of the Freeway Off‐Ramp Using Presignals

High volume from urban freeway off‐ramps coupled with extensive traffic weaving and limited capacity at downstream intersections create major bottlenecks in urban road networks. This article presents an integrated design model to eliminate traffic weaving and to maximize the section's overall capacity by using the presignal and sorting area concept. The selection of movements controlled by the presignal, the layout of the section, and the signal timing are optimized in a uniform framework by a mixed‐integer nonlinear program model. The mathematical model was linearized and solved using the standard branch‐and‐bound technique. Extensive numerical analysis and a case study validate the effectiveness of the proposed integrated model in improving capacity with the comparison of conventional design under various geometric configuration and traffic demand pattern scenarios. The proposed model has promising application at locations where the queuing space is long enough and the number of exit lanes is enough to receive the traffic stream from the sorting area.     

Condition state evaluation of existing reinforced concrete bridges using neuro-fuzzy hybrid system

This article presents a new approach for developing a concrete bridge rating expert system for deteriorated concrete bridges, constructed from multi-layer neural networks. The system evaluates the performance of concrete bridges on the basis of a simple visual inspection and technical specifications. The main reason of applying the neural network is that it performs fuzzy inference in the network, facilitates refinement of the knowledge base by use of the back-propagation method, and prevents not only the inference mechanism of the expert system but also the knowledge base after machine learning from becoming a black box.     

二级公路短隧道多孔混凝土磨耗层设计与施工

根据隧道内部环境和车辆运行特性,提出了采用多孔混凝土来克服隧道路面抗滑耐久性不足的问题.针对多孔混凝土的强度性能和施工特性,通过强度试验提出了多孔混凝土的合理配比和合适的施工工艺.结果表明,采用湿-湿法施工可以显著提高多孔混凝土路面上、下层间界面的粘结强度.     

沥青混凝土永久变形预估方法研究

提出了一种新的沥青混凝土永久变形预估模型,该模型理论明确,有效考虑了剪切因素,用单轴贯入抗剪强度表征沥青混合料本身的抗变形能力,用面层内剪应力表示结构的抗车辙属性.通过不同温度、压力及厚度下的车辙试验,基于分层叠加的基本思想确定了沥青混凝土永久变形预估模型;同时根据波尔兹曼线性叠加原理,在永久变形预估模型中考虑了行车速度;最后采用不同的沥青混合料对该模型进行了验证.结果表明:永久变形预估模型能够较精确模拟沥青混凝土的变形规律,对不同的沥青混合料具有通用性,从而为建立正确的车辙预估方法奠定了基础.