Development in modeling cyclic loading of sands based on kinematic hardening

In this paper, there is presented an elastoplastic constitutive model to predict sandy soils behavior under monotonic and cyclic loadings. This model is based on an existing model (Cambou‐Jafari‐Sidoroff) that takes into account deviatoric and isotropic mechanisms of plasticity. The flow rule used in the deviatoric mechanism is non‐associated and a mixed hardening law controls the evolution of the yield surface. In this research the critical state surface and history surface, which separates the virgin and cyclic states in stress space, are defined. Kinematic hardening modulus and stress–dilatancy law for monotonic and cyclic loadings are effectively modified. With taking hardening modulus as a function of deviatoric and volumetric plastic strain and with defining the history surface and stress reversal, the model has the ability to predict the sandy soils' behavior. All of the model parameters have clear physical meanings and can be determined from usual laboratory tests. In order to validate the model, the results of homogeneous tests on Hostun and Toyoura sands are used. The results of validation show a good capability of the proposed model. Copyright © 2009 John Wiley & Sons, Ltd.     

List of forthcoming papers

List of forthcoming papers     

Verification of cloud cover forecast with INSAT observation over western India

Since the beginning of the summer monsoon 2009, experimental mesoscale weather forecasts in real time are being generated using WRF model by the Meteorology and Oceanography Group at the Space Applications Centre (ISRO) and are disseminated through MOSDAC () to various users. To begin with, the 12 h, 24 h and 48 h forecasts for the western India region are made available. A study is undertaken to comprehensively assess the cloudiness prediction performance of WRF model. The evaluations have been made over the three months period during monsoon 2009. INSAT cloud imagery data has been used as a reference for these evaluations. The verification strategy includes computation of various skill scores. It is seen that probability of detection (POD) of cloud is 84% and the false alarm rate (FAR) is around 18%. It is hoped that this assessment will provide information on the use of these forecasts in various applications.     

Prediction of Land Subsidence Under Cyclic Pumping Based on Laboratory and Numerical Simulations

In this study subsidence due to groundwater withdrawal was investigated. Kerman Province in Iran is struggling with land subsidence problem due to extensive groundwater withdrawal mainly for farming. The rate and type of groundwater withdrawal has very important impact on settlement rate. In this research, effective parameters on land subsidence caused by groundwater withdrawal were determined by laboratory tests. Sampling had done up to depth of 300 m mainly with remolded specimens from Shams-abad, Nouq plain in Kerman province. Similar to the field preconsolidation pressure was applied on specimens in the laboratory. Rate of applied stress on prepared specimens was similar to effect of oscillation of groundwater level. In order to model the actual soil behavior in the laboratory, one-dimensional consolidation device (odometer) was adopted for testing. In these tests, the effect of loading caused by seasonal oscillation of groundwater table is considered by means of cyclic loading in the testing which has great effect on rate of settlements. The results of tests show that when the water table level periodically increases and decreases the amount of settlement decrease, comparing with the case when the groundwater table drop to a constant level. In order to predict the further effects of groundwater level oscillation and actual field condition on land subsidence, a finite element model based on Biots’ three-dimensional consolidation theory was developed. After calibration of finite element model with laboratory tests, this model was used for prediction the effect of groundwater level oscillation on actual field conditions.     

Geochemical Characteristics,Origin, and Evolution of Ore‐Forming Fluids of the Khut Copper Skarn Deposit,West of Yazd in Central Iran

The Khut copper skarn deposit is located at about 50 km northwest of Taft City in Yazd province in the middle part of the Urumieh‐Dokhtar magmatic arc. Intrusion of granitoid of Oligocene–Miocene age into carbonate rocks of the Triassic Nayband Formation led to the formation of marble and a calcic skarn. The marble contains high grade Cu mineralization that occurs mainly as open space filling and replacement. Cu‐rich sulfide samples from the mineralized marble are also anomalous in Au, Zn, and Pb. In contrast, the calcic skarn is only weakly anomalous in Cu and W. The calcic skarn is divided into garnet skarn and garnet–pyroxene skarn zones. Paragenetic relationships and microthermometric data from fluid inclusions in garnet and calcite indicate that the compositional evolution of skarn minerals occurred in three main stages as follows. (i) The early prograde stage, which is characterized by Mg‐rich hedenbergite (Hd_53.7Di_42.3–Hd_86.1Di_9.5) with Al‐bearing andradite (69.8–99.5 mol% andradite). The temperature in the early prograde skarn varies from 400 to 500°C at 500 bar. (ii) The late prograde stage is manifested by almost pure andradite (96.2–98.4 mol% andradite). Based on the fluid inclusion data from garnet, fluid temperature and salinity in this stage is estimated to vary from 267 to 361°C and from 10.1 to 21.1 wt% NaCl equivalent, respectively. Pyrrhotite precipitation started during this stage. (iii) The retrograde stage occurs in an exoskarn, which consists of an assemblage of ferro‐actinolite, quartz, calcite, epidote, chlorite, sphalerite, pyrite, and chalcopyrite that partially replaces earlier mineral assemblages under hydrostatic conditions during fracturing of the early skarn. Fluids in calcite yielded lower temperatures (T < 260°C) and fluid salinity declined to ～8 wt% NaCl equivalent. The last stage mineralization in the deposit is supergene weathering/alteration represented by the formation of iron hydroxide, Cu‐carbonate, clay minerals, and calcite. Sulfur isotope data of chalcopyrite (δ³⁴S of +1.4 to +5.2‰) show an igneous sulfur source. Mineralogy and mineral compositions of the prograde assemblage of the Khut skarn are consistent with deposition under intermediately oxidized and slightly lower fS₂ conditions at shallow crustal levels compared with those of other typical Fe‐bearing Cu–Au skarn systems.     

Mixed precision parallel preconditioner and linear solver for compositional reservoir simulation

Reservoir simulation role in value creation and strategic management decisions cannot be over emphasized. Simulation of complex challenging reservoirs with millions of grid blocks especially in compositional mode is very time-consuming even with fast modern computers. On the other hand, high price of cluster supercomputers prevents them for being commonly used for fast simulation of such reservoirs. In recent years, the development of many-core processors like cell processors, DSPs, and graphical processing units (GPUs) has provided a very cost-effective hardware platform for fast computational operations. However, programming for such processors is much more difficult than conventional CPUs, and new parallel algorithm design and special parallel implementation methods are needed. Using the computational power of CPUs, GPUs, and/or any other processing unit, Open Computing Language (OpenCL) provides a framework for programming for heterogeneous platforms. In this paper, OpenCL is used to employ the computational power of a GPU to build a preconditioner and solve the linear system arising from compositional formulation of multiphase flow in porous media. The proposed parallel preconditioner is proved to be quite effective, even in heterogeneous porous media. Using data-parallel modules on GPU, the preconditioner/solver runtime reduced at least 1 order of magnitude compared to their serial implementation on CPU.     

Weathering and anthropogenic influences on the water and sediment chemistry of Wular Lake,Kashmir Himalaya

This paper presents a study on the Wular Lake which is the largest fresh water tectonic lake of Kashmir Valley, India. One hundred and ninety-six (196) water samples and hundred (100) sediment samples (n = 296) have been collected to assess the weathering and Anthropogenic impact on water and sediment chemistry of the lake. The results showed a significant seasonal variability in average concentration of major ions being highest in summer and spring and lower in winter and autumn seasons. The study revealed that lake water is alkaline in nature characterised by medium total dissolved solids and electrical conductivity. The concentration of the major ion towards the lake central showed a decreasing trend from the shore line. The order of major cations and anions was Ca²⁺ > Mg²⁺ > Na⁺ > K⁺ and HCO₃ ^? > SO₄ ^2? > Cl^?, respectively. The geochemical processes suggested that the chemical composition lake water is mostly influenced by the lithology of the basin (carbonates, silicates and sulphates) which had played a significant role in modifying the hydrogeochemical facies in the form of Ca–HCO₃, Mg–HCO₃ and hybrid type. Chemical index of alteration values of Wular Lake sediments reflect moderate weathering of the catchment area. Compared to upper continental crust and the post-Archean Shale, the sediments have higher Si, Ti, Mg and Ca contents and lower Al, Fe, Na, K, P, Zn, Pb, Ni, Cu content. Geoaccumulation index (Igeo) and US Environmental Protection Agency sediment quality standards indicated that there is no pollution effect of heavy metals (Zn, Mn, Pb, Ni and Co).The study also suggested that Wular Lake is characterised by both natural and anthropogenic influences.     

Optimal water and waste load allocation in reservoir–river systems: a case study

In this paper, a new methodology is developed for optimization of water and waste load allocation in reservoir–river systems considering the existing uncertainties in reservoir inflow, waste loads and water demands. A stochastic dynamic programming (SDP) model is used to optimize reservoir operation considering the inflow uncertainty, and another model called PSO-SA is developed and linked with the SDP model for optimizing water and waste load allocation in downstream river. In the PSO-SA model, a particle swarm optimization technique with a dynamic penalty function for handling the constraints is used to optimize water and waste load allocation policies. Also, a simulated annealing technique is utilized for determining the upper and lower bounds of constraints and objective function considering the existing uncertainties. As the proposed water and waste load allocation model has a considerable run-time, some powerful soft computing techniques, namely, Regression tree Induction (named M5P), fuzzy K-nearest neighbor, Bayesian network, support vector regression and an adaptive neuro-fuzzy inference system, are trained and validated using the results of the proposed methodology to develop real-time water and waste load allocation rules. To examine the efficiency and applicability of the methodology, it is applied to the Dez reservoir–river system in the south-western part of Iran.