预应力CFRP加筋土技术原理研究

预应力CFRP加筋土技术是一种新型的加筋土技术。这项技术充分地利用了CFRP材料的高强度、高弹性模量、耐腐蚀性、轻质等优点，应用该技术施工的加筋土工程具有变形小、强度高、施工速度快的特点。应用三轴试验研究了CFRP材料加筋中砂、粘土试件的应力应变关系，提出了伪粘聚力的概念，成功地解释预应力CFRP加筋土技术的基本原理。     

基于偏好顺序集的非补偿式铁路旅客选择行为估计方法

精细化需求预测是铁路提高收益的重要基础.本文考虑了铁路产品属性对于旅客选择行为的影响,构建具有一定偏好顺序的产品集合来表征不同类型的旅客.在此基础上,利用客票存根及余票数据,建立预售期内旅客选择过程的极大似然函数,求解得到不同旅客类型的出现概率.首先通过仿真算例验证了模型的计算可行性,然后通过实证数据,估算了北京南至上海虹桥方向不同旅客类型在各时段的出现概率,进一步统计得到旅客在不同时段下铁路旅客buy-up行为概率及属性敏感度的变化,并提出一些可用于优化售票策略的建议.     

基于插补原理的船体复杂曲面加热线布置方法

船体曲面成形技术是船舶加工过程中重要的环节。如何更好更快实现船体复杂曲面加工,一致以来备受国内外学者的关注。本文借鉴插补原理,对传统船体复杂曲面加热线布置进行了优化设计,得到了圆弧形板、s形板、帆形板和马鞍板的加热线。采用COMSOL Multiphysics多物理场仿真软件,分析四种加热线下钢板变形情况,并通过实验检验了插补形式下的船体曲面成形效果。结果表明：(1)插补算法得到的船体曲面加热线路程比传统加热线路程节约75%以上。(2)对有限元计算位移进行曲面拟合,得到的预测模型与实际船体曲面基本一致。(3)实验了四种曲面加热线,并将有限元预测位移与实验进行对比,二者误差在6%以内,有限元计算与实验结果基本吻合。该方法降低加工时间,提高加工效率。     

港口岸线环境补偿人工沙滩工程理论与实践

依托港口岸线建设环境补偿人工沙滩工程是践行国家生态文明建设战略,实现港、城一体化发展的有益举措。针对人工沙滩建设中的理论和关键技术问题,通过自主研发,取得以下主要创新性成果:1)发展了沙、泥并存下沙滩动力地貌学基础理论;2)形成先进的数值、物理模拟技术;3)提出适用于各种复杂泥沙环境下的人工沙滩设计原则;4)研发了人工沙滩防侵蚀、防泥化的整治与养护措施。研究成果已成功应用于不同复杂泥沙环境下的实际沙滩工程中,实现了良好的经济、社会和生态环境效益,具有广阔的推广应用前景。     

基于多元回归方法的海洋执法船主尺度分析

为分析海洋执法船主尺度之间的变化规律,对海洋执法船的发展趋势进行了介绍,并对其相关船型数据资料进行整理分析。采用多元回归的数学方法,建立了基于多变量的海洋执法船主尺度数学模型,有利于对海洋执法船主尺度的变化规律进行分析与掌握,为海洋执法船的报价设计与初步设计提供一定的科学依据。     

On a link-based day-to-day traffic assignment model

In this paper, we perform a rigorous analysis on a link-based day-to-day traffic assignment model recently proposed in He et al. (2010). Several properties, including the invariance set and the constrained stability, of this dynamical process are established. An extension of the model to the asymmetric case is investigated and the stability result is also established under slightly more restrictive assumptions. Numerical experiments are conducted to demonstrate the findings.     

Subjective-utility travel time budget modeling in the stochastic traffic network assignment

ABSTRACT

In this article, we propose a new model called subjective-utility travel time budget (SU-TTB) model to capture travelers' risk-averse route choices. In the travel time budget (TTB) and mean-excess travel time (METT) model, a predefined confidence level is needed to capture the risk-aversion in route choice. Due to the day-to-day route travel time variations, the exact confidence level is hard to be predicted. With the SU-TTB model, we assume travelers' confidence level belongs to an interval that they may comply with in the route choice. The two main components of SU-TTB are the utility function and the TTB model. We can show that the SU-TTB can be reduced to the TTB and METT model with proper utility function for the confidence levels. We can also prove its equivalence with our recently proposed nonlinear-expectation route travel time (NERTT) model in some cases and give some new interpretation on the NERTT with this equivalence. Finally, we formulate the SU-TTB model as a variational inequality (VI) problem to model the risk-averse user equilibrium (RAUE), termed as generalized RAUE (GRAUE). The GRAUE is solved via a heuristic gradient projection algorithm, and the model and solution algorithm are demonstrated with the Braess's traffic network and the Nguyen and Dupuis's traffic network.     

一种基于广义S变换增强的柴油机失火故障特征提取方法

为有效提取柴油机缸盖振动信号失火故障特征,提出一种基于广义S变换增强的柴油机失火故障特征提取方法。首先根据柴油机燃烧过程与配气相位的关系对信号进行等角度重采样,然后利用广义S变换对信号进行消噪处理,并按工作循环将信号的周期性瞬态特征进行同步增强。通过仿真信号验证和某柴油机缸盖振动信号的实例应用,结果表明,此方法能有效地提取柴油机缸盖振动信号的失火故障特征,实现失火故障的准确诊断。     

码头面高程计算方法探讨

针对码头项面高程确定中遇到的实际问题,提出一种新的计算方法。新方法在吸收现行规范中有掩护式码头和开敞式码头顶面高程计算方法特点的基础上,对于各种掩护程度码头采用统一公式,可以避开因半开敞式码头界定的不明确性给码头顶面高程计算带来的麻烦,在考虑波浪荷载与水位组合方面概念更清晰,应用较方便。     

Efficient missing data imputing for traffic flow by considering temporal and spatial dependence

The missing data problem remains as a difficulty in a diverse variety of transportation applications, e.g. traffic flow prediction and traffic pattern recognition. To solve this problem, numerous algorithms had been proposed in the last decade to impute the missed data. However, few existing studies had fully used the traffic flow information of neighboring detecting points to improve imputing performance. In this paper, probabilistic principle component analysis (PPCA) based imputing method, which had been proven to be one of the most effective imputing methods without using temporal or spatial dependence, is extended to utilize the information of multiple points. We systematically examine the potential benefits of multi-point data fusion and study the possible influence of measurement time lags. Tests indicate that the hidden temporal–spatial dependence is nonlinear and could be better retrieved by kernel probabilistic principle component analysis (KPPCA) based method rather than PPCA method. Comparison proves that imputing errors can be notably reduced, if temporal–spatial dependence has been appropriately considered.