膨胀土路基压实和承载强度研究

依托广西崇左~上思二级公路建设项目,在室内试验和现场修建试验路段相结合进行大量数据采集的基础上,较深入地分析弱膨胀土路基填筑中压实度、压实功、含水量、CBR等的特点及其关系。同一种膨胀土,击实功越大,最大干密度越大,最佳含水量越小。不同种类的膨胀土,在相同击实功下,膨胀性越小CBR越大。同一种膨胀土,击实功越大,CBR越大,但最大CBR所对应的含水量都大致相等。项目所在地,干旱季节大部分弱膨胀土的天然含水量大致都在15%~18%之间,这正好与该地区弱膨胀土CBR达到最大值时的含水量相对应。而且,这个含水量区间虽比标准击实时的最佳含水量要大4%~7%,但只要不超出这个区间的上限,在现场路基施工时就可通过增加压实功很易使其达到压实度要求。     

Analysis of interaction factors between two piles

A rigorous analytical method is presented for calculating the interaction factor between two identical piles subjected to vertical loads. Following the technique proposed by Muki and Sternberg, the problem is decomposed into an extended soil mass and two fictitious piles characterized respectively by Young＇s modulus of the soil and that of the difference between the pile and soil. The unknown axial forces along fictitious piles are determined by solving a Fredholm integral equation of the second kind, which imposes the compatibility condition that the axial strains of the fictitious piles are equal to those corresponding to the centroidal axes of the extended soil. The real pile forces and displacements can subequally be calculated based on the determined fictitious pile forces, and finally, the validity of the proposed approach and desired pile interaction factors may be obtained. Results confirm the portray the influence of the governing parameters on the pile interaction.     

侵蚀和冻融环境下水泥土强度的试验研究

某些特殊地区的水泥土地基既受到环境侵蚀又受到冻融循环的影响.通过室内试验的方法,研究水泥土先经受不同浓度和不同pH值的侵蚀性溶液侵蚀下,经过反复冻融后水泥土的强度特征,并探讨其强度改变的机理.试验结果表明,水泥土的强度特性受水化学作用和冻融循环的双重影响,其中水化学作用的影响贯穿全过程,冻融的影响与冻融循环次数关系紧密.结果可为特殊环境地基的设计与工程应用提供指导作用.     

路桥工程中软土地基施工策略

在路桥工程中,施工质量直接决定着工程整体质量.从软土地基本身的基本特点出发,阐述目前工程施工中面临的软土地基问题,并总结有针对性的施工技巧,可供广大同行参考.     

盾构渣土资源化处理工艺及成套系统装备研究

为解决当前盾构渣土资源化装备庞大、操作复杂、对不同类型渣土及狭小场地适应性差等问题，以深圳地铁14号线六约北站盾构隧道工程为背景，研究盾构渣土资源化处理工艺以及智能化、集成化、模块化的振动筛分、絮凝、压滤、管路和中央集中控制平台等成套系统装备，并在六约北站盾构渣土资源化处理工程中得到了成功应用。结果表明： 六约北站采用新装备和新工艺后，设备占地面积仅470 m2，最大处理能力达到1 400 m3/d，仅需4人即可维持整个装备系统的有效运行；设备系统对不同地层渣土的〖JP2〗适应性大幅提高，筛孔淤堵得到解决；所生产的粗骨料、细骨料含泥量和含水率大幅降低。由此可见，盾构渣土资源化处理系统的智能化、集成化、模块化提升是装备升级的发展方向，最终形成智能化、集装箱化成套装备，从而满足不同场地及周边环境的运行需求。     

Productivity change of the Spanish Port System: impact of the economic crisis

ABSTRACT

The main goal of this study was to assess the impact of the economic crisis on the productivity growth of the Spanish Port System (SPS). The Malmquist Productivity Index (MPI) was estimated for the 28 Port Authorities of the SPS, for a ‘non-crisis period’ (2005–2008) and a ‘crisis period’ (2008–2011). From a policy perspective, the MPI is a very useful approach for assessing the productivity change because it can be decomposed into the catching-up index and the frontier productivity index. The results showed that the economic crisis did not impact all of the Spanish Port Authorities equally. Some Port Authorities presented higher productivity growth during the crisis period than in the non-crisis period. Further analysis by the Mann–Whitney test revealed that Port Authority investments and productivity growth were statistically related. Information provided by this study may be very useful for stakeholders and decision-makers, in terms of long-term strategic planning and improving the competitiveness of the SPS. The findings illustrate that the economic crisis should not be seen as an international tragedy, but as an opportunity to adapt port traffics and installations to new needs and market demands.     

Assessment of uncertainty in the CFD simulation of the wave-induced loads on a vertical cylinder

The paper addresses different uncertainty analysis methods commonly used for uncertainty quantification in Computational Fluid Dynamics (CFD) studies and compares a constant Courant–Friedrichs–Lewy (CFL) number based approach for uncertainty estimation to the ITTC recommended grid and time-independent procedures. Four different uncertainty estimation procedures are presented and discussed. To compare their performance and better understand CFD related uncertainty quantification in wave load simulations on offshore structures, the methods are applied to a case study of the wave loads on a fixed vertical cylinder. The numerical or CFD wave tank is generated using the open-source CFD toolkit OpenFOAM. Uncertainty is assessed for the case study using four different uncertainty estimation procedures for verification and later, validation is attempted by comparing the CFD results with experiments. The study concludes that a constant CFL number based uncertainty study provides more stable results and is better suited for uncertainty estimation in CFD than the ITTC recommended individual grid and time step uncertainty study.     

A finite mixture model of vehicle-to-vehicle and day-to-day variability of traffic network travel times

This study proposes an approach to modeling the effects of daily roadway conditions on travel time variability using a finite mixture model based on the Gamma–Gamma (GG) distribution. The GG distribution is a compound distribution derived from the product of two Gamma random variates, which represent vehicle-to-vehicle and day-to-day variability, respectively. It provides a systematic way of investigating different variability dimensions reflected in travel time data. To identify the underlying distribution of each type of variability, this study first decomposes a mixture of Gamma–Gamma models into two separate Gamma mixture modeling problems and estimates the respective parameters using the Expectation–Maximization (EM) algorithm. The proposed methodology is demonstrated using simulated vehicle trajectories produced under daily scenarios constructed from historical weather and accident data. The parameter estimation results suggest that day-to-day variability exhibits clear heterogeneity under different weather conditions: clear versus rainy or snowy days, whereas the same weather conditions have little impact on vehicle-to-vehicle variability. Next, a two-component Gamma–Gamma mixture model is specified. The results of the distribution fitting show that the mixture model provides better fits to travel delay observations than the standard (one-component) Gamma–Gamma model. The proposed method, the application of the compound Gamma distribution combined with a mixture modeling approach, provides a powerful and flexible tool to capture not only different types of variability—vehicle-to-vehicle and day-to-day variability—but also the unobserved heterogeneity within these variability types, thereby allowing the modeling of the underlying distributions of individual travel delays across different days with varying roadway disruption levels in a more effective and systematic way.     

Forecasting demand for high speed rail

It is sometimes argued that standard state-of-practice logit-based models cannot forecast the demand for substantially reduced travel times, for instance due to High Speed Rail (HSR). The present paper investigates this issue by reviewing the literature on travel time elasticities for long distance rail travel and comparing these with elasticities observed when new HSR lines have opened. This paper also validates the Swedish long distance model, Sampers, and its forecast demand for a proposed new HSR, using aggregate data revealing how the air–rail modal split varies with the difference in generalized travel time between rail and air. The Sampers long distance model is also compared to a newly developed model applying Box–Cox transformations. The paper contributes to the empirical literature on long distance travel, long distance elasticities and HSR passenger demand forecasts. Results indicate that the Sampers model is indeed able to predict the demand for HSR reasonably well. The new non-linear model has even better model fit and also slightly higher elasticities.     

A generalized sensor location model for the estimation of network origin–destination matrices

This study examined the network sensor location problem by using heterogeneous sensor information to estimate link-based network origin–destination (O–D) demands. The proposed generalized sensor location model enables different sensors’ traffic monitoring capabilities to be used efficiently and the optimal number and deployment locations of both passive- and active-type sensors to be determined simultaneously without path enumeration. The proposed sensor location model was applied to solve the network O–D demand estimation problem. One unique aspect of the proposed model and solution algorithms is that they provide satisfactory network O–D demand estimates without requiring unreasonable assumptions of known prior information on O–D demands, turning proportions, or route choice probabilities. Therefore, the proposed model and solution algorithms can be practically used in numerous offline transportation planning and online traffic operation applications.