钢筋混凝土剪力墙非线性单元模型的研究

本文首先对等效框架模型、多竖直杆单元模型作了改进.然后应用改进等效框架模型、改进多竖直杆单元模型及分层壳单元模型,对不同轴压比的三片剪力墙构件模型与一个14层筒中筒结构模型进行了计算分析,并与实验结果作了比较.结果表明:改进多竖直杆单元模型在所有情况下均可取得较好结果,是适用性较强的剪力墙非线性单元模型;多层壳单元模型...     

强震作用下多层土质边坡破坏规律与变形特征

通过对汶川地震受灾区北川县陈家坝地区的地质灾害调查,根据现场松散土质边坡破坏情况,由工程地质类比法选择了计算模型和地震波,采用岩土弹塑性理论和FLAC3D软件分析了多层土质边坡在动荷载作用下边坡单元的剪切拉伸破坏和剪切应变动力响应规律。研究表明,在水平和竖直地震波联合作用下,地震边坡单元首先在坡体内产生剪切破坏。随着震动时间的增加,剪切破坏单元向坡脚和坡肩处延伸,而在坡肩处主要产生拉破坏,一旦剪切破坏面和拉破坏面贯通,将导致边坡失稳。强震过后边坡坡脚鼓出,坡肩下凹,整个坡体呈弧形破坏。      

Improving long-range hydrological forecasts with extended Kalman filters

Abstract

There is a continuing effort to advance the skill of long-range hydrological forecasts to support water resources decision making. The present study investigates the potential of an extended Kalman filter approach to perform supervised training of a recurrent multilayer perceptron (RMLP) to forecast up to 12-month-ahead lake water levels and streamflows in Canada. The performance of the RMLP was compared with the conventional multilayer perceptron (MLP) using suites of diagnostic measures. The results of the forecasting experiment showed that the RMLP model was able to provide a robust modelling framework capable of describing complex dynamics of the hydrological processes, thereby yielding more accurate and realistic forecasts than the MLP model. The performance of the method in the present study is very promising; however, further investigation is required to ascertain the versatility of the approach in characterizing different water resources and environmental problems.

Citation Muluye, G. Y. (2011) Improving long-range hydrological forecasts with extended Kalman filters. Hydrol. Sci. J. 56(7), 1118–1128.     

Caractérisation hydrogéochimique de la nappe du Continental Intercalaire (sud tunisien) / Hydrogeochemical characterization of the Continental Intercalaire aquifer (southern Tunisia)

Abstract

The study of the Continental Intercalaire aquifer system of southern Tunisia, based on the interpretation of geochemical (major elements) and isotopic (¹⁸O, ²H, ¹³C and ¹⁴C) data, has aided the understanding of the hydrodynamics of this multi-layer aquifer system, which is greatly influenced by tectonics. The determination of the origin of groundwater salinization and the understanding of the hydrogeological and geochemical behaviour of this aquifer were achieved by studying the correlation between the major elements and total mineralization (TDS). By using isotopic tools, it was shown that the water of this aquifer has been recharged under cooler, palaeoclimatic conditions. The technique also made it possible to better understand the hydrodynamic functioning of the aquifer system: it showed that the relatively recent recharge of the aquifer has been by direct infiltration from carbonate and sandy outcrops of the Cretaceous and Miocene, respectively, located in the eastern and northeastern parts of the aquifer. The ¹⁸O content was used to calculate the altitude of recharge basins. The isotopic gradient defined in this study is ?0.5 δ¹⁸O ‰/100 m.     

A neurocomputing approach to the forecasting of monthly maximum temperature over Kolkata, India using total ozone concentration as predictor

The association between the monthly total ozone concentration and monthly maximum temperature over Kolkata (22.56° N, 88.30° E), India, has been explored in this paper. For this, the predictability of monthly maximum temperature based on the total ozone as predictor is investigated using Artificial Neural Network. The presence of persistence and similar cyclic patterns are revealed through autocorrelation and cross-correlation coefficients. Common cycles of length 12 and 6 have been identified through periodogram. Hence, a predictive model has been generated by Artificial Neural Network in the form of Multi Layer Perceptron (MLP) using scaled conjugate gradient learning with sigmoid non-linearity. After training and testing the network, an MLP with total ozone of month n as predictor and maximum temperature of month (n + 1) as the target output is found as the best model. Performance of the model has been judged statistically. Finally, the MLP model has been compared with linear and non-linear regressions and the efficiency of MLP has been established over the regression models.     

多层次格网模型的近邻指数聚类生态区划算法与实验——以新疆北部地区区划为例

在综合考虑气候、植被、地貌等凶素的基础上,提出一种基于多层次格网模型的最近邻指数-模糊聚类生态区域划分算法(Nearest Neighbor Index Fuzzy clustering,NNI-FIC).该算法采用"自下而上"的方式,首先,利用离散格网单元之间的严格相似性形成区划的核心分区;然后,通过最近邻指数统计分...     

Artificial neural network model for prediction of rock properties from sound level produced during drilling

In many rock engineering applications such as foundations, slopes and tunnels, the intact rock properties are not actually determined by laboratory tests, due to the requirements of high quality core samples and sophisticated test equipments. Thus, predicting the rock properties by using empirical equations has been an attractive research topic relating to rock engineering practice for many years. Soft computing techniques are now being used as alternative statistical tools. In this study, artificial neural network models were developed to predict the rock properties of the intact rock, by using sound level produced during rock drilling. A database of 832 datasets, including drill bit diameter, drill bit speed, penetration rate of the drill bit and equivalent sound level (L_eq) produced during drilling for input parameters, and uniaxial compressive strength (UCS), Schmidt rebound number (SRN), dry density (ρ), P-wave velocity (V_p), tensile strength (TS), modulus of elasticity (E) and percentage porosity (n) of intact rock for output, was established. The constructed models were checked using various prediction performance indices. Goodness of the fit measures revealed that recommended ANN model fitted the data as accurately as experimental results, indicating the usefulness of artificial neural networks in predicting rock properties.     

倾角导向体控制的气烟囱识别技术及其在海拉尔盆地贝尔凹陷中的应用

在调研了国内外气烟囱研究成果与思路的基础上,通过全新的地震解决方案——OpendTect平台提供的基于属性多层感知器(MLP)的人工神经网络(ANN)的方法预测气烟囱的发生概率体,并利用倾角导向体对算法进行改进,提出倾角控制下的地震气烟囱识别技术,很好地补充并发展了模式识别技术在地震勘探领域的应用。通常该技术一方面可以解释运移通道和浅层气成藏的原因;另一方面,形成的气烟囱地震数据体还可以预测源岩的发育情况;此外,对于判别断层封闭性也非常适用。最后应用这一技术对海拉尔盆地贝尔凹陷一含油区块的运移通道和成藏规律进行研究,分析该研究区的断裂发育特征和运移通道类型,总结了油源、通道、储层和盖层的空间配置关系,并建立相应的成藏模式。     

制备TJ-1模拟月壤空心圆柱试样的新方法

针对TJ-1模拟月壤颗粒级配跨度大、粒径〉2mm．的颗粒含量多,采用常规方法制备空心圆柱试样容易出现粗细颗粒分离、试样整体不均匀的特点,提出改良型制备方法．首先采用分层欠压法与冰冻法相结合制备出孔隙比e=1．0的实心圆柱试样,并对实心样的均匀性进行评价,得到分层制备相同孔隙比的TJ-1模拟月壤均匀试样时每层试样的高度;...     

MLP在雷达定量降水估测中的应用

通过临近时次、临近空间降水回波性质相似假设,以人工智能技术结合快速动态分级法(Fast Dynamic Categorical method,FDC)为核心,设计广西区域分钟级雷达定量降水估测产品模型。在单部雷达估测降水时,分两层三次使用感知器寻求合理的降水类型分类Z-I关系,首先将FDC看为一种多分类算法,根据单站雷达各级回波的降水估测结果误差将回波区内的站点分为强站点和弱站点两类,然后分别对这两类站点再次使用FDC建立新的强、弱两类Z-I关系。在多部雷达组网联合估测定量降水时,将各雷达估测值等权重看待,将单部雷达估测作为一个分支,通过连结方式构建一个多层感知器(Multilayer Perceptron,MLP)。无站点回波区采用K近邻算法(K-Nearest Neighbor,KNN)选择合适的MLP求得的Z-I关系估算降水量。对2019年3—10月试验产品进行检验分析,结果表明以区域站组成的训练组小时降水相关系数达0.973 7,以国家级气象台站组成的测试组相关系数达0.825 6。