应用遗传-神经网络方法预测软土路基沉降

理论方法预测软土地基沉降与实际存在较大的差距,使得预测结果很难达到设计要求,不利于指导施工。将现有的理论方法同现场观测信息相结合,对软土地基变形作出更为准确的预测,有利于指导和控制工程施工。采用遗传算法和BP最优化法相结合的算法来训练网络,用遗传算法来优化BP神经网络中权值;用龚帕斯曲线来分解沉降时序,通过沉降趋势线偏移量来训练网络。采用这种方法预测软土路基沉降取得了较好的应用效果。     

Studies on Construction Pre-control of a Connection Aisle Between Two Neighbouring Tunnels in Shanghai by Means of 3D FEM,Neural Networks and Fuzzy Logic

The ground freezing construction technique is one of the most effective and widely applied site construction methods in soft soil areas, like Shanghai. Some elevation-inclined refrigeration pipes are arranged for the artificial freezing excavation of the Pudong-side first-storey connection aisle, which is designed to connect two adjacent tunnel lanes of Shanghai East-Fuxing-Road tunnel project. No advanced research results could be found for computing the temperature field of tunnels and aisles frozen with inclined refrigeration pipes. Anyhow the computation of the relevant temperature field is of high importance for the safe and economical excavation of the above-mentioned aisle. In this paper, a method for computing the aisle temperature field using 3D FEM is given, and the computation accuracy is verified by contrasting the computed and site measured results. The back propagation neural networks are also applied to the temperature prediction using self-developed Neural Network-Expert System software, the predicted results are also very satisfactory. The mechanism during freezing and aisle excavation will be discussed on the basis of 3D FEM simulation. The authors believe that studying the parameter-sensitivity of temperature field is very important for the optimum selection of parameter values. So, in this paper, the parameter-sensitivity of temperature field is also discussed. In order to obtain the optimum frozen wall thickness, the relation between the frozen wall thickness and the initial freezing brine temperature is studied. At the end, an excavation pre-control plan is proposed by means of fuzzy logic theory for improving the excavation safety. The research result of the current paper is very helpful for projects that will be excavated by freezing construction technique.     

Piles shaft capacity from CPT and CPTu data by polynomial neural networks and genetic algorithms

Cone penetration test (CPT) is one of the most common in situ tests which is used for pile design because it can be realized as a model pile. The measured cone resistance (q_c) and sleeve friction (f_s) usually are employed for estimation of pile unit toe and shaft resistances, respectively. Thirty three pile case histories have been compiled including static loading tests performed in uplift, or in push with separation of shaft and toe resistances at sites which comprise CPT or CPTu sounding. Group method of data handling (GMDH) type neural networks optimized using genetic algorithms (GAs) are used to model the effects of effective cone point resistance (q_E) and cone sleeve friction (f_s) as input parameters on pile unit shaft resistance, applying some experimentally obtained training and test data. Sensitivity analysis of the obtained model has been carried out to study the influence of input parameters on model output. Some graphs have been derived from sensitivity analysis to estimate pile unit shaft resistance based on q_E and f_s. The performance of the proposed method has been compared with the other CPT and CPTu direct methods and referenced to measured piles shaft capacity. The results demonstrate that appreciable improvement in prediction of pile shaft capacity has been achieved.     

神经网络在建筑物沉降分析中的应用

建筑物沉降的诱因与沉降量之间有一个复杂的非线性相关性,应用回归法对这种复杂的相关性进行分析有较大的局限性.人工神经网络是由许多神经元组成的大规模非线性系统,具有较强的动态处理能力,能对简单的非线性函数进行多次复合,来实现一个复杂的非线性函数.神经网络这些特性满足建筑物沉降分析的需求.实例表明,应用神经网络BP算法可以对建筑物沉降原因进行更客观的分析,对沉降趋势预测效果也较好.     

不同侧压力系数下裂隙网络岩体非线性渗流特性

基于人工裂隙网络模型,展开一系列不同边界荷载作用下含不同交叉点个数的裂隙网络渗流试验。针对所有试验工况,模型进水口水压力范围均为0～0.6 MPa,侧压力系数均由1.0增加至5.0。试验结果表明：裂隙网络体积流速和水力梯度之间的相关性可以通过Forchheimer函数进行拟合,拟合方程中线性和非线性项系数均随着侧压力系数的增加逐渐增大,而随着裂隙网络交叉点个数的增加逐渐减小;渗流试验过程中,非线性效应系数E和水力梯度J之间的相关性可采用一个幂指数函数进行描述,随着水力梯度的增加,非线性效应系数逐渐增大;随着侧压力系数的增加,裂隙网络临界水力梯度呈现逐渐增大的趋势,对于所有裂隙网络交叉点个数（1～12）,当侧压力系数由1.0增加至5.0,临界水力梯度由0.63～12.13增加至6.01～81.55;提出数学模型 对归一化导水系数 随水力梯度的增大而减小的特征进行分析,随着侧压力系数的增加,两者之间的拟合曲线逐渐上移,拟合系数 整体呈现逐渐增大的趋势。裂隙网络的等效渗透系数随侧压力系数的增加逐渐降低。     

北京市道路尘中重金属时空分布特征及污染程度评价

北京市作为我国的经济和文化中心,高速的城市化进程带来了一系列的环境问题。城市道路尘可以通过不同途径进入人体,对人体健康造成伤害。本研究采集了春、冬两季北京市6类功能区中道路尘样品46件,研究了其中Cr、Pb、Cd、As和Hg元素的含量和空间分布特征,并采用单因子指数法和内梅罗污染指数法,评价了道路尘中重金属污染程度。结果表明:除冬季As元素外,其余元素平均含量均高于北京市土壤背景值; 5种重金属元素平均含量一般为市区最高,郊区最低。单因子污染评价表明,冬、春两季各个功能区道路尘中除As元素无污染外,其余元素均具有一定程度的污染,其中Cd元素污染程度最高;冬季各功能区道路尘中重金属元素综合污染指数评价均为轻度污染;春季郊区为尚清洁,工厂区、居民区和商业区为轻度污染,休闲区和教育区为中度污染。     

Late Cretaceous stratigraphy,sediments and structure: Gems of the Dorset and East Devon Coast World Heritage Site (Jurassic Coast), England

Extraordinary, long-distance litho-marker beds such as the Lewes and Shoreham Tubular Flints and associated marl seams and fossils, recognised in cliff exposures and cliff-fall boulders, are keys to unlocking the stratigraphy and tectonic structures in the Late Cretaceous of the Dorset and East Devon Coast World Heritage Site (Jurassic Coast). Durdle Cove is a special gem exposing the Lewes and Seaford Chalk stratigraphy where new marker beds are identified and sediments and tectonic structures provide clues to timing of movements that produced a Late Cretaceous pericline which grew into a Miocene monocline along the line of the underlying Purbeck Reverse Fault. During ‘inversion’ along this fault some Late Cretaceous Chalk formations were in part or completely ‘lost’ (e.g. Middle Turonian New Pit Chalk Formation) and others were condensed (e.g. Late Santonian and Early Campanian Newhaven Chalk Formation). Excavation of the A354 road cutting at the Lower Bincombe Farm, has greatly added to the stratigraphical records of Late Cretaceous fossils in South Dorset, especially Coniacian and Early Campanian inoceramid bivalves and the various stratigraphically specific forms of the Late Santonian to Early Campanian echinoid fossil Echinocorys scutata spp. not recorded before in this coastline. The very large bivalve fossil Platyceramus sp. provides clues to chalk sea-floor environments.     

一种改进的快速浮动车地图匹配方法

浮动车地图匹配算法能够实现浮动车离散点与路段的快速准确匹配,是浮动车路况信息生成技术中的核心环节。本文针对现有方法的不足,实现了建立定位点的有效阈值缓冲区,并依据空间关系检索候选匹配路段,研究实现了一种利用行驶速度、行驶方向、投影距离、行驶距离4个参数进行行车轨迹判别的逻辑匹配算法。试验表明,该方法无需对路网数据进行大量的前期处理工作,简化了候选匹配路段的检索过程,在保证匹配正确率的同时也表现出了更高的效率。     

一种基于里程参数的道路平面几何解析模型

随着主动安全技术、自动驾驶技术的发展,高精度导航地图得到越来越多的运用。本文提出了一种面向高精度导航地图的、基于里程参数的道路平面几何解析模型。通过动态地构造点集上的正交多项式系和约束最小二乘法,根据拟合最大误差动态地计算道路的几何描述参数。使用该模型进行了120 km高速道路高精度地图数据生产,以三段典型道路为实例进行试验,表明该方法能对道路几何进行准确的描述,保证道路几何的连续与光滑,同时最大限度地减少数据冗余。该模型对高精度地图道路几何描述具有一定优势。