悬吊式钢混结构体系抗震试验与分析

悬吊式钢混结构体系是一种新型结构体系，通过一榀1／2比例此种框架的拟静力试验，研究了这种结构在低周反复水平荷载作用下的受力特点、变形和耗能能力以及破坏机理等，试验表明此种框架与传统异形柱框架的性能不同，为此种结构体系的应用提供了试验基础。     

结构动力模型试验相似理论及其验证

通过几何比尺为2的两个有机玻璃模型的结构动力试验，验证了结构动力模型试验的弹性相似律和弹性力一重力相似律。得到了以下结论：(1)大小模型频率符合相似律，一阶频率误差为2．7％、4．1％，二阶频率误差为O、6．05％。弹性相似律比弹性力一重力相似律更适合于频率预测的试验。(2)大小模型的加速度、应变符合相似律，弹性相似律的加速度误差为-1．55％～8．75％，应变误差为O．377％～7．297％。弹性力-重力相似律的加速度误差为3．07％～4．158％，应变误差为6．849％～12．959％。(3)不同相似律大小模型的时问比尺吻合很好。加速度与应变时程曲线的波形一致，既无漏峰也无错峰。     

变形监测基准点的稳定性检验

基准点的稳定性评价，是变形观测数据处理时不可忽视的重要内容。该文对基准点构网和不构网2种情况时的数据处理方法进行了探讨。     

载荷试验确定基床系数修正方法的讨论

Winkler地基模型是目前工程界应用最广的一种地基模型，但对其关键参数——基床系数k的确定，许多文献的表述并不一致。该文在大量试验资料的基础上，通过对该问题的深入研究，阐明了通过载荷试验确定基床系数修正方法的有关概念。对于砂性土地基，载荷板试验得出的基准基床系数仅需要进行基础大小修正，而对于粘性土地基，则需要进行基础大小和基础形状两项修正。     

爆炸液化场地中浅埋钢筋混凝土结构动力响应的现场试验研究

饱和砂土地基在爆炸荷载作用下会发生液化,地基上的结构物将受到爆炸荷载及地基液化的双重作用,从而产生不均匀沉降和破坏性变形。基于大型现场爆炸液化试验,对场地上钢筋混凝土(RC)结构的动力响应和地基液化后RC结构的变形进行了分析研究。结果表明:液化场地中浅埋RC结构产生了明显的不均匀沉降,且最大沉降量达到结构高度的10%,结构差异沉降达到最大沉降量的1/5,结构沉降变形在液化后15 h时基本稳定;RC结构表面未产生明显的裂缝,动态拉、压应变均在400??以内,不会对结构造成显著破坏;结构动力响应表现为柱侧加速度峰值明显大于梁侧,但柱侧动力稳定所需时间较梁侧短,即柱承受了更大的瞬时冲击力且其抵抗瞬时冲击力的能力更强。研究结果可以为在可液化地基中的浅埋RC结构稳定设计等工程情况提供参考。     

BIBLIOGRAPHIE

Abstract

Time series modelling approaches are useful tools for simulating and forecasting hydrological variables and their change through time. Although linear time series models are common in hydrology, the nonlinear time series model, the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, has rarely been used in hydrology and water resources engineering. The GARCH model considers the conditional variance remaining in the residuals of the linear time series models, such as an ARMA or an ARIMA model. In the present study, the advantages of a GARCH model against a linear ARIMA model are investigated using three classes of the GARCH approach, namely Power GARCH, Threshold GARCH and Exponential GARCH models. A daily streamflow time series of the Matapedia River, Quebec, Canada, is selected for this study. It is shown that the ARIMA (13,1,4) model is adequate for modelling streamflow time series of Matapedia River, but the Engle test shows the existence of heteroscedasticity in the residuals of the ARIMA model. Therefore, an ARIMA (13,1,4)-GARCH (3,1) error model is fitted to the data. The residuals of this model are examined for the existence of heteroscedasticity. The Engle test indicates that the GARCH model has considerably reduced the heteroscedasticity of the residuals. However, the Exponential GARCH model seems to completely remove the heteroscedasticity from the residuals. The multi-criteria evaluation for model performance also proves that the Exponential GARCH model is the best model among ARIMA and GARCH models. Therefore, the application of a GARCH model is strongly suggested for hydrological time series modelling as the conditional variance of the residuals of the linear models can be removed and the efficiency of the model will be improved.

Editor D. Koutsoyiannis; Associate editor C. Onof

Citation Modarres, R. and Ouarda, T.B.M.J., 2013. Modelling heteroscedasticty of streamflow times series. Hydrological Sciences Journal, 58 (1), 1–11.     

A six-step practical approach to semivariogram modeling

Geostatistical prediction and simulation are being increasingly used in the earth sciences and engineering to address the imperfect knowledge of attributes that fluctuate over large areas or volumes—pollutant concentration, electromagnetic fields, porosity, thickness of a geological formation. Central to the application of such techniques is the need to know the spatial continuity, knowledge that is commonly condensed in the form of covariance or semivariogram models. Their preparation is subdivided here into the following steps: (1) Data editing, (2) Exploratory data analysis, (3) Semivariogram estimation, (4) Directional investigation, (5) Simple modeling, (6) Nested modeling. I illustrate these stages practically with a real data set from a geophysical survey from Elk County, Kansas, USA. The applicability of the approach is not limited by the physical nature of the attribute of interest.     

Land use change under conditions of high population pressure: the case of Java

A long history of increases in population pressure in Java has caused agricultural land use to expand and intensify. More recent land use changes caused the conversion of prime agricultural land into residential and industrial area. Results of a dynamic, regional-scale, land use change model are presented, defining the spatial distribution of these land use changes. The model is based on multi-scale modelling of the relations between land use and socio-economic and biophysical determinants. Historical validation showed that the model can adequately simulate the pattern of land use change. Future patterns of land use change between 1994 and 2010 are simulated assuming further urbanization. The results suggest that most intensive land use changes will occur in Java's lowland areas.     

藏南卡鲁雄峰枪勇冰川新冰期冰川发育探讨

山地冰川对气候变化响应敏感,全新世以来,冰川呈加速退缩趋势。冰川地貌是冰川变化最直接的证据。枪勇冰川发源于卡鲁雄峰,位于喜马拉雅山中段北坡雨影区,雅鲁藏布江以南,冰川末端在海拔5000 m附近,冰川面积约为6.63 km2。枪勇沟从外至内共保存有4期冰碛垄,其中以"大枪勇错"外侧的新冰期冰碛垄最为高大,终碛垄高约30 m,且形态清晰。文章基于野外观察及谷歌影像（Google Earth）上冰碛垄的分布范围,恢复并计算了新冰期时枪勇冰川面积约为10.0 km2,较现代冰川扩张了1.5倍。采用VOLTA模型计算了现代冰川的体积为0.21±0.04 km3,平均厚度约为31.7 m。基于纵剖线模型模拟了新冰期冰川表面高程,新冰期冰川平均厚度约为58.5 m,冰川体积约0.59±0.12 km3,是现代冰川体积的2.8倍,体积减小较面积退缩更为剧烈。利用积累区面积比率法（Accumulation Area Ratio Method,简称AAR）,采用AAR值为0.7±0.05,基于现代冰川表面高程和模拟的新冰期冰川表面高程,计算现代冰川和新冰期冰川的物质平衡线高度（Equilibrium Line Altitude,简称ELA）分别为5780±70 m和5660±100 m,新冰期时平衡线高度降低了约120 m。而不利用模型恢复新冰期表面高程时,平衡线降低值为240 m,可能高估约120 m。新冰期时,枪勇冰川扩张受区域降温控制,冰川前进可能是对4.2 ka冷事件的响应。冰碛垄形成时代和大枪勇错孢粉数据表明,冰川可能在2.5 ka左右已经退缩,2.2 ka时退缩加剧。