Application of high density resistivity method in accuracy of goaf detection

Based on the relationship between the diameter and buried depth of goaf,the authors establish the forward modeling by Res2dmod and inverse the model by Res2dinv. Thus,three kinds of models are obtained:the model of single resistivity anomalous body,model of double different distance resistivity anomalous body,and model of layered resistivity anomalous body. Using forward and inversion,the image of detection is simulated,and the reliability is proved by comparing with the engineering examples.     

Multiobjective optimization-based design of stabilizing piles in earth slopes

Though the technology of using stabilizing piles to prevent landsliding is not new, the design of such piles with a meaningful optimization framework has been rarely reported. In this paper, a multiobjective optimization-based framework for design of stabilizing piles is presented, in which both reinforcement effectiveness and cost efficiency could be explicitly considered. The design parameters considered in the proposed design framework are the pile parameters, including pile diameter, spacing, length, and position, and the design objectives considered are the reinforcement effectiveness and cost efficiency. The design of stabilizing piles is then implemented as a multiobjective optimization problem. In that the desire to maximize the reinforcement effectiveness and that to maximize the cost efficiency are two conflicting objectives, the output of this multiobjective optimization will be a Pareto front that depicts a trade-off between these two design objectives. With the obtained Pareto front, an informed decision regarding the design of stabilizing piles is reached. The effectiveness and significance of the proposed multiobjective optimization-based design framework for stabilizing piles are demonstrated through two illustrative examples: one is the design of stabilizing piles in a one-layer earth slope and the other the design of stabilizing piles in a two-layer earth slope. Further, parametric analyses are conducted to investigate the influences of the pile design parameters on the stability of reinforced slopes.     

陇南地区房屋震害调查与易损性矩阵的建立

汶川地震后,作者赴陇南文县、武都区、康县、成县等地详细调查了房屋建筑的震害情况。在整理分析了大量现场第一手资料后,分别建立了各类房屋的地震易损性矩阵,并列举了一些典型震害现象,可为汶川地震后灾区的重建工作提供一定的参考。     

鄂西恩施地区岩石物理力学参数的相关性

岩石物理力学性质指标是反映岩体工程特性的重要参数。通过对鄂西恩施地区典型滑坡区白垩系砂岩、三叠系粉砂岩、三叠系薄层泥灰岩、三叠系粉砂质泥岩、泥盆系石英砂岩和三叠系、二叠系、奥陶系灰岩等岩石单轴抗压强度σ_c、弹性模量E、泊松比μ、岩块的块体密度ρ和纵波速度V_p等试验数据的聚类和相关分析,表明白垩系砂岩和三叠系粉砂岩、三叠系粉砂质泥岩和二叠系灰岩参数间关联模式完全一致,其中岩块密度和纵波速度的关系最密切,将两者的乘积作为组合参数进行参数关联式拟合可提高拟合精度。分别对各地层岩石拟合出考虑多种因素且形式简明的参数关联式,并对拟合残差进行正态性检验,结果表明拟合出的参数关联式比较合理。      

粗粒土试验与力学特性研究现状

粗粒土既是一种天然地质体,又能用作建筑材料,在自然界中广泛存在,其力学性质研究对实际工程实践至关重要.在大量关于粗粒土试验与力学性质研究文献的基础上做了以下分析和总结：将粗粒土试验分为三类,包括室内试验、原位试验和数值试验,分别对每种试验的试验原理、仪器、方法和适用范围进行了详细介绍;根据粗粒土力学性质研究现状,重点对粗粒土的剪胀性、颗粒破碎性和软化性这三种特性从形成机制、影响因素和描述方法上进行了深入总结.在此基础上,指出粗粒土力学性质研究方面存在如下不足：现有方法和理论存在一定局限性、宏观特性发生机理假设缺乏客观验证、宏观特性难以用细观力学演绎、多相耦合下的力学性质鲜有研究.最后,从试验、理论和数值仿真试验角度提出关于粗粒土力学性质研究的展望.     

北碚与重庆主城核心区的空间联系——基于交通和居民出行调查数据的分析

城镇体系中的空间联系研究可以分为大尺度的网络联系和小尺度的地域联系两种。以国内外研究相对较少的小尺度范围的城市空间联系为研究对象,选择处于快速城镇化进程中的重庆主城核心区与作为其卫星城之一的北碚为案例地,借用数据量需求较大、结论更符合实际的经验主义研究方法,系统分析了北碚区与重庆主城核心区间的空间联系。研究显示:北碚区与重庆主城核心区空间联系发展历程经历了4 个阶段,联系日益紧密;城市功能方面,北碚区已经从独立城市成为重庆主城核心区重要的功能组团,有别于传统的"卧城"概念;空间联系强度方面呈现出明显的距离衰减特征,并与地区的社会因素、经济发展水平等因素有密切关系;通过对二者空间联系解释的框架分析,表明城市政府的政策和规划在两地空间联系发展中起到主导作用。     

Predictive vegetation mapping approach based on spectral data, DEM and generalized additive models

This study aims to provide a predictive vegetation mapping approach based on the spectral data, DEM and Generalized Additive Models (GAMs). GAMs were used as a prediction tool to describe the relationship between vegetation and environmental variables, as well as spectral variables. Based on the fitted GAMs model, probability map of species occurrence was generated and then vegetation type of each grid was defined according to the probability of species occurrence. Deviance analysis was employed to test the goodness of curve fitting and drop contribution calculation was used to evaluate the contribution of each predictor in the fitted GAMs models. Area under curve (AUC) of Receiver Operating Characteristic (ROC) curve was employed to assess the results maps of probability. The results showed that: 1) AUC values of the fitted GAMs models are very high which proves that integrating spectral data and environmental variables based on the GAMs is a feasible way to map the vegetation. 2) Prediction accuracy varies with plant community, and community with dense cover is better predicted than sparse plant community. 3) Both spectral variables and environmental variables play an important role in mapping the vegetation. However, the contribution of the same predictor in the GAMs models for different plant communities is different. 4) Insufficient resolution of spectral data, environmental data and confounding effects of land use and other variables which are not closely related to the environmental conditions are the major causes of imprecision.     

城市物流园区类型及运营模式——以深圳市为例

物流园区作为城市物流活动的重要空间载体,其发展对城市物流产业的发展具有重要意义。但对物流园区相关研究主要以园区未来规划为主,缺少对发展成熟物流园区的案例研究。鉴于此,文章以物流园区发展较早的深圳市9大物流园区为案例,将其划分为货运枢纽型、城市配送型和综合功能型物流园区3种类型,并总结其在选址、用地规模、业务类型方面的特征;根据政府参与管理程度,将其划分为政府主导型、企业主导型和半政府主导型3种运营模式,并认为城市物流园区运营模式与园区类型具有密切关系。文章从物流园区的依附设施、用地规模、投资规模3方面分析了其对运营模式的影响。     

Application of back-propagation neural network on bank destruction forecasting for accumulative landslides in the three Gorges Reservoir Region,China

In recent years, a large number of bank destruction occur in the reservoir area under the effect of water fluctuation, which may be lead to reservoir accumulative landslide geological hazards finally. The paper conducted the bank destruction forecasting study for accumulative landslides in the Three Gorges Reservoir Region, China utilizing back-propagation (BP) neural network approach. A representative scenario of Jinle landslide is then taken for analysis purposes. On the basis of the existing data sets of bank destruction cases, the BP neural network forecasting model and the corresponding programs for bank destruction are both presented, whose forecasting result is validated by two independent approaches, namely empirical method and numerical modeling method. Furthermore, the BP neural network model had obvious advantages over the convention approaches in the aspects of the fast calculation speed and high convenience. According to the bank destruction forecasting scale presented above, the corresponding revetment measures can be proposed to prevent the occurring of the bank destruction, whose effectiveness has been further validated by the actual engineering practice.     

决策树法在雷电潜势预报中的应用

利用2005年7～9月、2006年6—9月、2007年6月共8个月的闪电定位仪、常规探空以及T213,数值预报产品等资料作样本,应用决策树方法生成四川省未来12小时雷电潜势预报决策树,并通过雷电潜势预报决策树作四川省2007年8～9月雷电潜势预报。结果表明：该方法对雷电潜势预报效果较好。