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61.
This paper presents an elastic continuum model using an extended nonlinear Davies and Budhu equations, which enables the nonlinear behavior of the soil around the long elastic pile to be modeled using a simple expression of pile-head stiffness method. The calculated results were validated with the measured full-scale dynamic field tests data conducted in Auckland residual clay. An idealized soil profile and soil stiffness under small strain (i.e. shear modulus, G s and shear wave velocity, V s of the soil) determined from in situ testing was used to model the single pile tests results. The predictions of these extended equations are also confirmed by using the three-dimensional finite-element OpenSeesPL (Lu et al. in OpenSeesPL 3D lateral pile-ground interaction: user manual, University of California, San Diego, 2010). A soil stiffness reduction factor, G s /G s,max of 0.36 was introduced to the proposed method and model. It was found to give a reasonable prediction for a single pile subjected to dynamic lateral loading. The reduction in soil stiffness found from the experiment arises from the cumulative effects of pile–soil separation as well as a change in the soil properties subjected to cyclic load. In summary, if the proposed method and model are accurately verified and properly used, then they are capable of producing realistic predictions. Both models provide good modelling tools to replicate the full-scale dynamic test results.  相似文献   
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Scrub rangelands support livestock grazing and provide ecosystem services to their inhabitants.The present study was conducted in Chakwal,an important tract of ...  相似文献   
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Many unicellular cyanobacteria were isolated from different places: fields, ponds, polluted water, and soils from Muredkey and Kasur tannery areas, near Lahore, Pakistan. Different media like BG 11 medium, Bold Basal medium, Chu's # 10 medium and Gotham's medium, in standard forms and with slight variations of ingredients, and different pH, temperature and light regimes were checked for the optimum growth of the isolates. The isolation pro- cedure was repeated with different concentrations of chromium to select the resistant strains. These selected strains grew on chromium of the range 100-200 μg/ml in BG 11 medium. Cyanobacteria were maintained in solid and liquid media with/without shaking. Cyanobacterial strains were collected from natural habitats that were accompanied by a diversified group of organisms including bacteria, protozoan, and rotifers etc. In order to eliminate these agents termed as contaminants, we used several methods including phenol treatment, use of antibiotic and careful manual picking of unicellular cyanobacteria. Resistance of these strains against different heavy metals (ZnSO4, MnSO4, NiSO4, COCl2, Pb(NO3)3, CuSO4, HgCl2, AgNO3 and CdCl2) and antibiotics (erythromycin, streptomycin, kanamycin, chloramphenicol, neomycin) was evaluated. Optimum temperature was 30℃ with variable pH for the reduction of Cr^6+ in to Cr^3+ in majority of strains.  相似文献   
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This paper presents a three‐dimensional energy‐based solution for the time‐dependent response of a deeply embedded and unsupported semi‐infinite tunnel of circular cross‐section. The tunnel is taken to be excavated quasi‐instantaneously from an infinite rock body that initially exhibits an isotropic stress state and that is made up of a homogeneous, isotropic and viscoelastic material. The viscoelastic behaviour is modelled by means of Burger's model, and the rock is taken to behave volumetrically linear elastic and to exhibit exclusively deviatoric creep. This viscoelastic problem is transformed into the Laplace domain, where it represents a quasi‐elastic problem. The displacement fields in the new solution are taken to be the products of independent functions that vary in the radial and longitudinal directions. The differential equations governing the displacements of the system and appropriate boundary conditions are obtained using the principle of minimum potential energy. The solutions for these governing equations in the Laplace domain are then obtained analytically and numerically using a one‐dimensional finite difference technique. The results are then transformed back into the time domain using an efficient numerical scheme. The accuracy of the new solution is comparable with that of a finite element analysis but requires much less computation effort. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   
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1INTRODUCTIONIn impervious area dry dustand dirtbuildup con-tains heavy metals,nutrients,pesticides and organ-ics.Many studies(APWA,1969;Sartor and Boyd,1972;Pitt and Amy,1973;Pitt,1979,1985;Yousef and Wanielista,1990;Wanielista andYousef,1993,Ball,et al.…  相似文献   
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Real time, accurate and reliable estimation of maize yield is valuable to policy makers in decision making. The current study was planned for yield estimation of spring maize using remote sensing and crop modeling. In crop modeling, the CERES-Maize model was calibrated and evaluated with the field experiment data and after calibration and evaluation, this model was used to forecast maize yield. A Field survey of 64 farm was also conducted in Faisalabad to collect data on initial field conditions and crop management data. These data were used to forecast maize yield using crop model at farmers’ field. While in remote sensing, peak season Landsat 8 images were classified for landcover classification using machine learning algorithm. After classification, time series normalized difference vegetation index (NDVI) and land surface temperature (LST) of the surveyed 64 farms were calculated. Principle component analysis were run to correlate the indicators with maize yield. The selected LSTs and NDVIs were used to develop yield forecasting equations using least absolute shrinkage and selection operator (LASSO) regression. Calibrated and evaluated results of CERES-Maize showed the mean absolute % error (MAPE) of 0.35–6.71% for all recorded variables. In remote sensing all machine learning algorithms showed the accuracy greater the 90%, however support vector machine (SVM-radial basis) showed the higher accuracy of 97%, that was used for classification of maize area. The accuracy of area estimated through SVM-radial basis was 91%, when validated with crop reporting service. Yield forecasting results of crop model were precise with RMSE of 255 kg ha?1, while remote sensing showed the RMSE of 397 kg ha?1. Overall strength of relationship between estimated and actual grain yields were good with R2 of 0.94 in both techniques. For regional yield forecasting remote sensing could be used due greater advantages of less input dataset and if focus is to assess specific stress, and interaction of plant genetics to soil and environmental conditions than crop model is very useful tool.  相似文献   
67.
Acta Geotechnica - This article presents an experimental program under the constant volume condition to investigate the influence of over-consolidation on flow instability of clean and silty sand...  相似文献   
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