On integration of a cyclic soil plasticity model     

Majid T. Manzari  Rung Prachathananukit 《国际地质力学数值与分析法杂志》2001,25(6):525-549

Performance of three classes of explicit and implicit time‐stepping integrators is assessed for a cyclic plasticity constitutive model for sands. The model is representative of an important class of cyclic plasticity models for soils and includes both isotropic and nonlinear kinematic hardening. The implicit algorithm is based on the closest point projection method and the explicit algorithm follows a cutting‐plane integration procedure. A sub‐stepping technique was also implemented. The performance of these algorithms is assessed through a series of numerical simulations ranging from simulations of laboratory tests (such as triaxial and bi‐axial compression, direct shear, and cyclic triaxial tests) to the analysis of a typical boundary value problem of geotechnical earthquake engineering. These simulations show that the closest point projection algorithm remains stable and accurate for relatively large strain increments and for cases where the mean effective stress in a soil element reaches very small values leading to a liquefaction state. It is also shown that while the cutting plane (CP) and sub‐stepping (SS) algorithms provide high efficiency and good accuracy for small to medium size strain increments, their accuracy and efficiency deteriorate faster than the closest point projection method for large strain increments. The CP and SS algorithms also face convergence difficulties in the liquefaction analysis when the soil approaches very small mean effective stresses. Copyright © 2001 John Wiley & Sons, Ltd.  相似文献   

Derivation of basic equations of mass transport in porous media, Part 2. Generalized Darcy''s and Fick''s laws     

S. Majid Hassanizadeh 《Advances in water resources》1986,9(4)

  相似文献   

Calibration of the Angström-Prescott solar radiation model for accurate estimation of reference evapotranspiration in the absence of observed solar radiation     

Roya Mousavi  Ali Akbar Sabziparvar  Safar Marofi  Niaz Ali Ebrahimi Pak  Majid Heydari 《Theoretical and Applied Climatology》2015,119(1-2):43-54

  相似文献   

Quantifying uncertainties associated with depth duration frequency curves     

Majid Mirzaei  Yuk Feng Huang  Teang Shui Lee  Ahmed El-Shafie  Abdul Halim Ghazali 《Natural Hazards》2014,71(2):1227-1239

Uncertainty in depth–duration–frequency (DDF) curves is usually disregarded in the view of difficulties associated in assigning a value to it. In central Iran, precipitation duration is often long and characterized with low intensity leading to a considerable uncertainty in the parameters of the probabilistic distributions describing rainfall depth. In this paper, the daily rainfall depths from 4 stations in the Zayanderood basin, Iran, were analysed, and a generalized extreme value distribution was fitted to the maximum yearly rainfall for durations of 1, 2, 3, 4 and 5 days. DDF curves were described as a function of rainfall duration (D) and return period (T). Uncertainties of the rainfall depth in the DDF curves were estimated with the bootstrap sampling method and were described by a normal probability density function. Standard deviations were modeled as a function of rainfall duration and rainfall depth using 10⁴ bootstrap samples for all the durations and return periods considered for each rainfall station.  相似文献   

Hydrochemical and isotopic investigation of groundwater of Al-Batin alluvial fan aquifer,Southern Iraq     

Majid Alkinani  Broder Merkel 《Environmental Earth Sciences》2017,76(7):301

Major ions and important trace elements in addition to δ¹⁸O and δ²H were analysed for 43 groundwater samples sampled from the Al-Batin alluvial fan aquifer, South Iraq. The most dominant ions (with respect to molarity) were: Na⁺ > Cl^? > SO₄ ^2? > Ca²⁺ > Mg²⁺ > NO₃ ^? > HCO₃ ^?, with total dissolved solids (TDS) averaging 7855 mg/L. High concentrations were found for the trace elements U, Mo, V, B, Sr, and Cr. This study suggests a hydraulic connection exists near the fan apex between the uppermost part of the Al-Batin aquifer and the underlying Dammam aquifer by means of the Abu-Jir fault system. Except for the effects of extensive irrigation, fertilizer use, and poorly maintained sewers, the groundwater chemistry is mainly controlled by geological processes such as dissolution of evaporites and the enrichment of dissolved ions as a result of the high evaporation and low recharge rate. Furthermore, it is shown that the Kuwaiti fuel–oil burning during Gulf War in 1991 contributed to the enrichment of V and Mo in the studied aquifer. The spatial distribution of most ions appears to generally increase from the south-west towards the north-east, in the direction of groundwater flow. The stable isotopes show heavier values in groundwater with a gradually increasing trend in the direction of groundwater flow due to the decreasing depth to groundwater and thus increasing of evaporation from both groundwater or irrigation return water. Additionally, the stable isotope signature suggests that rainfall from sources in the Arabian Gulf and the Arabian Sea is the major source of recharge for the Al-Batin aquifer. Except for two samples of groundwater, all samples were not suitable for potable use according to the WHO standards. Most of the groundwater is suitable for some agricultural purpose and for livestock water supply. Apart from the high salinity, boron represents the most critical element in the groundwater with respect to agricultural purposes.  相似文献   

Evaluation of dynamic regression and artificial neural networks models for real-time hydrological drought forecasting     

Majid Dehghani  Bahram Saghafian  Firoozeh Rivaz  Ahmad Khodadadi 《Arabian Journal of Geosciences》2017,10(12):266

In this study, application of a class of stochastic dynamic models and a class of artificial intelligence model is reported for the forecasting of real-time hydrological droughts in the Black River basin in the USA. For this purpose, the Standardized Hydrological Drought Index (SHDI) was adopted in different time scales to represent the hydrological drought index. Six probability distribution functions (PDF) were fitted to the discharge time series to obtain the best fit for SHDI calculation. Then, a dynamic linear spatio-temporal model (DLSTM) and artificial neural network (ANN) were used to forecast SHDI. Although results indicated that both models were able to forecast SHDI in different time scales, the DLSTM was far superior in longer lead times. The DLSTM could forecast SHDI up to 6 months ahead while ANN was only capable of forecasting SHDI up to 2 months ahead appropriately. For short lead times (1–6 months), the DLSTM has performed nearly perfect in test phase and CE oscillates between 0.97 and 0.86 while for ANN modeling, CE is between 0.72 and 0.07. However, the performance of DLSTM and ANN reduced considerably in medium lead times (7–12 months). Overall, the DLSTM is a powerful tool for appropriately forecasting SHDI at short time scales; a major advantage required for drought early warning systems.  相似文献   

Spatial variability of rainfall trends in Iran     

Majid Javari 《Arabian Journal of Geosciences》2017,10(4):78

The main objective of this paper is to analyze the spatial variability of rainfall trends using the spatial variability methods of rainfall trend patterns in Iran. The study represents a method on the effectiveness of spatial variability for predicting rainfall trend patterns variations. In rainfall trend analysis and spatial variability methods, seven techniques were used: Mann–Kendall test, Sen’s slope method, geostatistical tools as a global polynomial interpolation and the spatial autocorrelation (Global Moran’s I), high/low clustering (Getis-Ord General G), precipitation concentration index, generate spatial weights matrix tool, and activation functions of semiliner, sigmoid, bipolar sigmoid, and hyperbolic tangent in the artificial neural network technique .For the spatial variability of monthly rainfall trends, trend tests were used in 140 stations of spatial variability of rainfall trends in the 1975–2014 period. We analyzed the long and short scale spatial variability of rainfall series in Iran. Spatial variability distribution of rainfall series was depicted using geostatistical methods (ordinary kriging). Relative nugget effect (RNE) predicted from variograms which showed weak, moderate, and strong spatial variability for seasonal and annual rainfall series. Moreover, the rainfall trends at each station were examined using the trend tests at a significance level of 0.05. The results show that temporal and spatial trend patterns are different in Iran and the monthly rainfall had a downward (decreasing) trend in most stations, and the trend was statistically significant for most of the series (73.5% of the stations demonstrated a decreasing trend with 0.5 significance level). Rainfall downward trends are generally temporal-spatial patterns in Iran. The monthly variations of rainfall decreased significantly throughout eastern and central Iran, but they increased in the west and north of Iran during the studied interval. The variability patterns of monthly rainfall were statistically significant and spatially random. Activation functions in the artificial neural network models, in annual time scale, had spatially dispersed distribution with other clustering patterns. The results of this study confirm that variability of rainfall revealing diverse patterns over Iran should be controlled mainly by trend patterns in the west and north parts and by random and dispersed patterns in the central, southern, and eastern parts.  相似文献