山区高填方回填地基处理效果的现场试验评价

依托重庆万州机场高填方回填地基处理工程实践 ,针对西南山区高填方填料特性及处理要求 ,对不同试验方法在山区高填方加固效果评价中的应用进行了分析 ,并对不同试验指标之间的相关规律进行了探讨 ,为选择经济、便捷的工程检测手段提供了依据 .     

郑州地铁砂性地层盾构长距离掘进技术研究

为解决盾构在砂性地层中长距离掘进可能存在的风险难题,以郑州地铁1号线2期工程为背景,分析盾构在砂性地层长距离掘进施工中可能存在的风险,在盾构掘进前针对所穿越地层的物理力学参数从耐磨性、刀盘开口率等方面对盾构进行适应性设计,在盾构掘进过程中通过现场试验确定合理的土体改良措施和注浆参数,最终顺利完成掘进。结果表明:采取上述技术措施能够有效提高盾构在砂性地层中的耐磨性和掘进效率并且控制了地表沉降,从而克服了盾构在砂性地层中长距离掘进的施工风险。     

泥水盾构穿越赣江断裂破碎带施工关键技术

为研究复杂地质条件下泥水盾构穿越断裂破碎带施工技术,以南昌市轨道交通1号线秋水广场站—中山西路站区间隧道工程为背景,对NFM-07泥水盾构穿越赣江F5断裂破碎带施工难点进行分析,从掘进开挖控制、出碴量与泥水质量控制、同步注浆和二次注浆4个方面研究高水压条件下破碎带开挖面稳定施工技术,并通过对施工记录资料的统计分析,得到泥水盾构掘进参数、泥水参数、同步注浆和二次注浆参数建议值,最后针对穿越破碎带可能出现的施工风险提出建议措施。本工程泥水盾构穿越破碎带施工过程安全、顺利,采取的稳定控制技术实施效果良好。     

Real-time estimation of the road bank and grade angles with unknown input observers

This paper proposes an approach for the estimation of the road angles independent from the road friction conditions. The method employs unknown input observers on the roll and pitch dynamics of the vehicle. The correlation between the road angle rates and the pitch/roll rates of the vehicle is also investigated to increase the accuracy. Dynamic fault thresholds are implemented in the algorithm to ensure reliable estimation of the vehicle body and road angles. Performance of the proposed approach in reliable estimation of the road angles is experimentally demonstrated through vehicle road tests. Road test experiments include various driving scenarios on different road conditions to thoroughly validate the proposed approach.     

中外钢管桩内力验算方法对比

钢管桩作为一种多轴对称的钢结构,性能稳定,受力机理相对明确,在国内外港口工程中主要用于高桩码头的基础结构和板桩码头的主体结构。通过对比研究国标、欧标、美标API和美标AISC共4种国内外规范对于钢管桩内力验算方法,探究4种规范验算方法的差异性,为海外港口工程钢管桩内力验算方法选取提供参考建议。以某港口高桩墩台结构为例对比4种规范钢管桩内力验算方法,结果表明:1) AISC规范计算结果最小,即其充分考虑发挥结构的性能,偏安全。2)欧标计算的结果最大,相对保守。3)国标和API规范计算结果介于AISC规范和欧标之间。     

特长高速公路隧道通风斜井钢波纹板式中隔墙技术研究北大核心CSCD

通风导洞中隔墙一般采用技术较为成熟的混凝土中隔墙,但存在表面粗糙、工艺复杂、施工进度不易控制等缺点,无法适用于风道较为复杂的工程。文章以东天山隧道1号斜井为依托,提出了节能型全拼装式钢波纹板中隔墙技术,通过数值模拟以及理论计算的方法验证其在单洞四风道通风斜井中的可行性。研究结果表明:钢波纹板式中隔墙增大了斜井有效通风截面积,断面风速降低约5.3%,同时大幅减小通风斜井内的沿程阻力,仅为既有混凝土墙方案的17%左右;拱顶变形及二次衬砌混凝土结构受力均远低于结构安全限值。该技术克服了传统钢筋混凝土中隔墙的缺点,在满足隧道通风防灾要求的同时,改善了隧道施工环境,且施工工期可缩短为原方案的三分之一。     

Heuristic estimation of container stacking and reshuffling operations under the containership delay factor and mega-ship challenge

This paper addresses a highly researched area, the reshuffling problem in ports, using a new paradigm-modified containership service order in light of credit risk assessment. Container stacking and reshuffling operations can cause ship delays and additional risk. In deep-sea terminals, outbound containers are tightly stacked according to the retrieval sequence. Due to lack of space, terminals stack containers in multiple tiers. This means any delay in the arrival of a ship can impose extra handlings and reshuffling of containers delaying future cargo handling. This paper addresses the reshuffling problem with a concept similar to the credit scoring and rating of creditworthiness used in the banking industry. By utilizing this comparison to the banking credit risk concept, a heuristic estimation model is proposed that illustrates the side effects of unscheduled modifications in containership service order. Further, the mega-ship trend amplifies the reshuffling debate. Probability of delay, reshuffles given delay, and call size at delay are introduced as the three-point risk metrics of the model. Numerical simulations illustrate the functionality to develop terminal stacking strategies as well as emphasize the mega-ship phenomenon and its side effects on terminals (i.e. yard operation deadlock).     

Estimating the most likely space–time paths,dwell times and path uncertainties from vehicle trajectory data: A time geographic method

Global Positioning System and other location-based services record vehicles’ spatial locations at discrete time stamps. Considering these recorded locations in space with given specific time stamps, this paper proposes a novel time-dependent graph model to estimate their likely space–time paths and their uncertainties within a transportation network. The proposed model adopts theories in time geography and produces the feasible network–time paths, the expected link travel times and dwell times at possible intermediate stops. A dynamic programming algorithm implements the model for both offline and real-time applications. To estimate the uncertainty, this paper also develops a method based on the potential path area for all feasible network–time paths. This paper uses a set of real-world trajectory data to illustrate the proposed model, prove the accuracy of estimated results and demonstrate the computational efficiency of the estimation algorithm.     

A model for national freight flows,distribution centers,empty trucks and urban truck movements

Trucks travel both short distances for local deliveries and long distances for transporting goods across the country. Often their travel behavior is tour-based, they run under tight schedules and under curfew on selected roads. Despite these differences from personal travel, in practice truck models largely follow person travel methods. To overcome this shortcoming, a two-layer truck model is developed for the Chicago Metropolitan Area. Long-distance trucks are driven by commodity flows, with distribution centers, rail yards, marine ports and airports being represented explicitly. Empty trucks are accounted for as well. For the short-distance truck model, a novel parameter estimation method makes use of limited data to derive region-specific parameters. The model is fully operational and validates reasonably well against traffic counts.     

Methodological challenges in modelling the choice of mode for a new travel alternative using binary stated choice data – The case of high speed rail in Norway

Binary stated choices between traveller’s current travel mode and a not-yet-existing mode might be used to build a forecasting model with all (current and future) travel alternatives. One challenge with this approach is the identification of the most appropriate inter-alternative error structure of the forecasting model.By critically assessing the practise of translating estimated group scale parameters into nest parameters, we illustrate the inherent limitations of such binary choice data. To overcome some of the problems, we use information from both stated and revealed choice data and propose a model with a cross-nested logit specification, which is estimated on the pooled data set.