青岛台体应变短周期气压系数变化原因探讨

青岛台体应变短周期(小于128 min)气压系数2018-01出现阶变，通过对观测系统、台站周边施工情况、监测环境等逐项现场核实，排除观测系统、周边施工的影响。利用离散小波变换和回归分析发现，钻孔水位的气压系数与体应变气压系数同步阶变，结合台站钻孔施工当天体应变钻孔水位变化、体应变趋势变化、其他相邻台站水位气压系数变化等数据认为，台站钻孔施工是导致体应变气压系数变化的原因，并定性分析其变化机理。     

铁路路基粗粒土填料临界动应力试验研究

粗粒土填料被广泛应用于铁路基床填料中,直接承受轨道结构传递的列车动循环荷载的长期作用,研究其在列车动荷载作用下的动力行为特征及塑性变形特性可为路基状态评估、沉降控制提供思路。采用GDS动三轴试验系统对铁路基床表层的粗粒土填料动力响应开展研究,通过引入塑性应变率和安定理论,将不同频率、围压、循环动应力比等条件下路基填料的轴向塑性应变的发展规律划分为塑性安定、塑性蠕变和增量塑性破坏3种类型,并确定了塑性安定和塑性蠕变状态的临界动应力水平。研究表明：粗粒土填料的临界循环应力比随着围压的增大而增大,随着荷载频率的增加而减小。通过对试验结果的拟合分析,提出了以围压为变量的临界动应力经验公式,为合理评估列车荷载作用下路基任意深度的动力稳定提供了理论依据。     

花岗岩残积土动态冲击性能的SHPB试验研究

为研究花岗岩残积土的动态冲击性能,开展了高速冲击下的分离式霍普金森压杆（SHPB）试验,与常规应变率下的试验结果比较,分析了高应变率对花岗岩残积土的应力?应变特性和强度的影响。结果表明：低、高应变率下的花岗岩残积土的?-?a（轴向应力?轴向应变）曲线均呈现出软化型。随着应变率 增加,?-?a曲线向?a增大的方向移动,破坏应变?af增加。但高应变率下?af增加的程度更加明显。花岗岩残积土的峰值强度普遍具有应变率依赖性,二者可用直线关系拟合,但低、高应变率下的拟合关系并不一致。提出了率敏性因子m定量评价依赖性强弱。研究发现,随着应变率的提高,强度的应变率依赖性减弱,低应变率下的m为26.694,而高应变率下仅为0.013。相关试验结果指出,高速冲击荷载对土体总体有害。工程中应该采取合理措施控制冲击荷载的危害。该研究有助于深化花岗岩残积土动态冲击性能的理解,为相关工程的施工与设计提供技术参考。     

多功能水合物沉积物三轴试验系统的研制与应用

研制了新型多功能水合物沉积物三轴试验系统,系统由供-排气模块、应力加载模块、温控模块、数据采集模块和辅助模块组成。利用泵驱动高压液体施加围压和轴压,加载方式有恒压、恒流、梯度增压、跟踪气压模式,可以实现不同条件下的水合物合成、三轴剪切。围压跟踪气压的功能使水合物生成过程中净围压不变,保证了试样初始条件一致性。根据围压液体积变化测量试样体积变形,通过设置回压泵压力变化方式控制水合物气压,可以模拟不同降压速率条件下的水合物沉积物分解变形。以泥质粉细砂和二氧化碳为材料制作了三轴试样,进行了水合物合成、三轴剪切和降压分解试验,检验了仪器的可靠性。     

级配碎石填料大三轴试验及累积塑性应变预测模型

级配碎石作为重载铁路基床表层的主要填料,其受列车荷载的影响最大。因此,研究级配碎石在循环荷载作用下的动力行为及累积塑性应变演化特征变得尤为重要。首先,通过制备不同细粒含量的级配碎石填料,开展一系列大型动三轴试验,探究细粒含量、围压及动应力幅值对循环荷载作用下试样累积塑性应变的耦合影响机制。其次,基于塑性安定理论,确定不同应力水平下试样的动力行为,得到考虑围压及细粒含量参数的塑性蠕变状态临界动应力计算模型。最后,结合试验数据,建立考虑应力水平及细粒含量参数的塑性蠕变动力行为累积塑性应变预测模型,并明确各参数的物理意义。其研究成果可为既有重载铁路路基健康状态评估及考虑强度、变形综合控制的路基结构设计提供参考。     

Modelling road surface sediment production using a vector geographic information system

Field investigations indicate that unpaved roads are the largest sediment source on St John, US Virgin Islands. Cross-sectional measurements of eroded road surfaces were used to establish an empirical relationship to predict annual road surface erosion as a function of road gradient and contributing drainage area. A model (ROADMOD) for estimating and mapping average annual sediment production from a road network was developed by combining this empirical relationship with a series of network algorithms to analyse road data stored in a vector geographic information system. ROADMOD was used to estimate road surface erosion in two St John catchments with very different road densities but similar land cover, topography and soils. Unpaved roads were found to increase sediment production in the more densely roaded catchment by a factor of three to eight, and in the less-roaded catchment by a factor of 1·3–2·0. Turbidity measurements in the receiving bays of these two catchments are consistent with model predictions and observed sediment delivery processes. Although this model was developed specifically for St John, it can easily be adapted to other locations by substituting a locally derived predictive equation for road erosion. Model assumptions, limitations and potential improvements are discussed. © 1998 John Wiley & Sons, Ltd.     

Anisotropic dual-continuum representations for multiscale poroelastic materials: Development and numerical modelling

Dual-continuum (DC) models can be tractable alternatives to explicit approaches for the numerical modelling of multiscale materials with multiphysics behaviours. This work concerns the conceptual and numerical modelling of poroelastically coupled dual-scale materials such as naturally fractured rock. Apart from a few exceptions, previous poroelastic DC models have assumed isotropy of the constituents and the dual-material. Additionally, it is common to assume that only one continuum has intrinsic stiffness properties. Finally, little has been done into validating whether the DC paradigm can capture the global poroelastic behaviours of explicit numerical representations at the DC modelling scale. We address the aforementioned knowledge gaps in two steps. First, we utilise a homogenisation approach based on Levin's theorem to develop a previously derived anisotropic poroelastic constitutive model. Our development incorporates anisotropic intrinsic stiffness properties of both continua. This addition is in analogy to anisotropic fractured rock masses with stiff fractures. Second, we perform numerical modelling to test the DC model against fine-scale explicit equivalents. In doing, we present our hybrid numerical framework, as well as the conditions required for interpretation of the numerical results. The tests themselves progress from materials with isotropic to anisotropic mechanical and flow properties. The fine-scale simulations show that anisotropy can have noticeable effects on deformation and flow behaviour. However, our numerical experiments show that the DC approach can capture the global poroelastic behaviours of both isotropic and anisotropic fine-scale representations.     

Simulation of the direct runoff hydrograph at basin outlet

A simple model describing the transformation of effective rainfall to direct runoff through the overland flow mechanism is presented. The model is based on the classical representation of a watershed by a combination of planes and channels. The dynamics of overland flow in each plane is simulated by the non-linear kinematic wave, but the outflow from a given plane is concentrated in the middle of the corresponding drainage channel. The water routing in the channels is carried out by a piece-wise linearized formulation in space of the kinematic wave approximation. Using synthetic events on 10 watersheds, the model was tested by comparing it with results obtained by applying the non-linear kinematic wave to all the elements of the watershed. The model was found to be adequate, even in a form that simplifies the geometric features of the planes through an averaging procedure based on the Horton–Strahler ordering scheme of the watershed. © 1998 John Wiley & Sons, Ltd.     

A study on relation between acoustic emission and characteristic displacement field on the sample with multi en echelon structures — The theoretic and experimental explorations of strain gap

Based on the phenomena that the deformation gap was observed before the great Tangshang earthquake, this paper discusses the strain gap according to test and theory. The (strain) patterns were recorded photographically by realtime holographic interferometry and shadow optical method of caustics, as soon as the loading process started. In the meantime, the AE (acoustic emission) signals were recorded by a micro crack information storage-analysis system. According to damage theory and location of micro fracture, we have studied the stain gap and gained: a) It is necessary that strain gap appears under the condition of linear elasticity theory, and its situation is relatively stable, corresponding to stress concentration. b) Micro fractures, which appear initially at area of high stress, occur rarely at the strain gap, and their locations are finally in the zone between the stress concentration area and the strain gap, which indicate the clusters or groups. However, the major macro fracture (final rupture) started from the shadow areas, and then grew quickly towards the strain gaps, which resulted in failure of sample. Foundation item: The Dual Project of China Seismological Bureau (9691309020301), the Specialized Funds for National Key Basic Study (G1998040704), the project for the MOST under contract (2001BA601B02) and Youth Funds for applied basic study of the Science and Technology Bureau of Yunnan Province (98D019Q).     

How do machine learning techniques help in increasing accuracy of landslide susceptibility maps?

Landslides are abundant in mountainous regions.They are responsible for substantial damages and losses in those areas.The A1 Highway,which is an important road in Algeria,was sometimes constructed in mountainous and/or semi-mountainous areas.Previous studies of landslide susceptibility mapping conducted near this road using statistical and expert methods have yielded ordinary results.In this research,we are interested in how do machine learning techniques help in increasing accuracy of landslide susceptibility maps in the vicinity of the A1 Highway corridor.To do this,an important section at Ain Bouziane(NE,Algeria) is chosen as a case study to evaluate the landslide susceptibility using three different machine learning methods,namely,random forest(RF),support vector machine(SVM),and boosted regression tree(BRT).First,an inventory map and nine input factors were prepared for landslide susceptibility mapping(LSM) analyses.The three models were constructed to find the most susceptible areas to this phenomenon.The results were assessed by calculating the receiver operating characteristic(ROC) curve,the standard error(Std.error),and the confidence interval(CI) at 95%.The RF model reached the highest predictive accuracy(AUC=97.2%) comparatively to the other models.The outcomes of this research proved that the obtained machine learning models had the ability to predict future landslide locations in this important road section.In addition,their application gives an improvement of the accuracy of LSMs near the road corridor.The machine learning models may become an important prediction tool that will identify landslide alleviation actions.