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.     

Air pollution forecasting from sky images with shallow and deep classifiers

Air pollution is one of the most important problems in the new era. Detecting the level of air pollution from an image taken by a camera can be informative for the people who are not aware of exact air pollution level be declared daily by some organizations like municipalities. In this paper, we propose a method to predict the level of the air pollution of a location by taking an image by a camera of a smart phone then processing it. We collected an image dataset from city of Tehran. Afterward, we proposed two methods for estimation of level of air pollution. In the first method, the images are preprocessed and then Gabor transform is used to extract features from the images. At the end, two shallow classification methods are employed to model and predict the level of air pollution. In the second proposed method, a Convolutional Neural Network(CNN) is designed to receive a sky image as an input and result a level of air pollution. Some experiments have been done to evaluate the proposed method. The results show that the proposed 9 method has an acceptable accuracy in detection of the air pollution level. Our deep classifier achieved accuracy about 59.38% which is 10 about 6% higher than traditional combination of feature extraction and classification methods.     

Probabilistic rainfall thresholds for flood forecasting: evaluating different methodologies for modelling rainfall spatial correlation (or dependence)

Rainfall threshold (RT) method is one of the evolving flood forecasting approaches. When the cumulative rainfall depth for a given initial soil moisture condition intersects the threshold rainfall curve, the peak discharge is expected to be equal or greater than the threshold discharge for flooding at the target site. Besides the total rainfall depth, spatial and temporal distribution of rainfall impacts the flood peak discharge and the time to peak. To revisit a previous study conducted by the authors, in which spatially independent rainfall pattern was assumed, the spatial distribution of rainfall was simulated following a Monte Carlo approach. The structure of the spatial dependence among sub‐watersheds' rainfalls was taken into account under three different scenarios, namely independent, bivariate copula (2copula) and multivariate Gaussian copula (MGC). For each set of generated random dimensionless rainfalls, the probabilistic RT curves were derived for dry moisture condition. Results were evaluated with both historical and simulated events. For the simulated events, threshold curves were assessed by means of categorical statistics, such as hit rate, false rate and critical success index (CSI). Results revealed that the best performance based on the CSI criterion corresponded to 50% curve in 2copula and MGC scenarios as well as 90% curve in the independent scenario. The recognition of 50% curve in 2copula and MGC scenarios is in agreement with our expectations that the mean probable curve should have the best performance. Moreover, the proposed inclusion of spatially dependent rainfall scenario improved the performance of RT curves by about 25% in comparison with the presumed spatially uniform rainfall scenario. Copyright © 2011 John Wiley & Sons, Ltd.     

Three‐dimensional nonlinear finite element analysis of pile groups in saturated porous media using a new transmitting boundary

The dynamic behaviour of pile groups subjected to an earthquake base shaking is analysed. An analysis is formulated in the time domain and the effects of material nonlinearity of soil, pile–soil–pile kinematic interaction and the superstructure–foundation inertial interaction on seismic response are investigated. Prediction of response of pile group–soil system during a large earthquake requires consideration of various aspects such as the nonlinear and elasto‐plastic behaviour of soil, pore water pressure generation in soil, radiation of energy away from the pile, etc. A fully explicit dynamic finite element scheme is developed for saturated porous media, based on the extension of the original formulation by Biot having solid displacement (u) and relative fluid displacement (w) as primary variables (u–w formulation). All linear relative fluid acceleration terms are included in this formulation. A new three‐dimensional transmitting boundary that was developed in cartesian co‐ordinate system for dynamic response analysis of fluid‐saturated porous media is implemented to avoid wave reflections towards the structure. In contrast to traditional methods, this boundary is able to absorb surface waves as well as body waves. The pile–soil interaction problem is analysed and it is shown that the results from the fully coupled procedure, using the advanced transmitting boundary, compare reasonably well with centrifuge data. Copyright © 2007 John Wiley & Sons, Ltd.     

Limiting equilibrium method for slope/drilled shaft system

The use of drilled shafts to stabilize an unstable slope has been a widely accepted practice. There are two basic design and analysis issues involved: one is to determine the global factor of safety of the drilled shafts stabilized slope and the other one is to determine the design earth thrust on the drilled shafts for structural design of the shafts. In this paper, a limiting equilibrium method of slices based solution for calculating global factor of safety (FS) of a slope with the presence of a row of drilled shafts is developed. The arching mechanisms due to the presence of the drilled shafts on slope were taken into account by a load transfer factor. The method for calculating the net force applied to the drilled shaft from the soil mass was also developed. The interrelationships among the drilled shaft location on the slope, the load transfer factor, and the global FS of the slope/shaft system were derived utilizing the developed numerical closed‐form solution. An illustrative example is presented to elucidate the use of the solution in optimizing the location of the drilled shafts on slope to achieve the desired global factor of safety of the slope/shaft system. Copyright © 2009 John Wiley & Sons, Ltd.     

Mineral chemical composition and geodynamic significance of peridotites from Nain ophiolite,central Iran

The peridotites from north of the town of Nain in central Iran consist of clinopyroxene-bearing harzburgite and lherzolite with small lenses of dunite and chromitite pods. The lherzolite contains aluminous spinel with a Cr number (Cr^# = Cr/[Cr + Al]) of 0.17. The Cr number of spinels in harzburgite and chromitite is 0.38–0.42 and 0.62, respectively. This shows that the lherzolite and harzburgite resulted from <18% of partial melting of the source materials. The estimated temperature is 1100 ± 200 °C for peridotites, the estimated pressure is <15 ± 2.3 kbar for harzburgites and >16 ± 2.3 kbar for lherzolites and estimated fo₂ is 10^?1±0.5 for peridotites. Discriminant geochemical diagrams based on mineral chemistry of harzburgites indicate a supra-subduction zone (SSZ) to mid-oceanic ridge (MOR) setting for these rocks. On the basis of their Cr^#, the harzburgite and lherzolite spinels are analogous to those from abyssal peridotites and oceanic ophiolites, whereas the chromites in the chromitite (on the basis of Cr^# and boninitic nature of parental melts) resemble those from SSZ ophiolitic sequences. Therefore, the Nain ophiolite complex most likely originated in an oceanic crust related to supra-subduction zone, i.e. back arc basin. Field observations and mineral chemistry of the Nain peridotites, indicating the suture between the central Iran micro-continent (CIM) block and the Sanandaj–Sirjan zone, show that these peridotites mark the site of the Nain–Baft seaway, which opened with a slow rate of ocean-floor spreading behind the Mesozoic arc of the Sanandaj–Sirjan zone as a result of change of Neo Tethyan subduction régime during middle Cretaceous.     

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     

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.     

Application of artificial intelligence techniques for predicting the flyrock distance caused by blasting operation

Flyrock arising from blasting operations is one of the crucial and complex problems in mining industry and its prediction plays an important role in the minimization of related hazards. In past years, various empirical methods were developed for the prediction of flyrock distance using statistical analysis techniques, which have very low predictive capacity. Artificial intelligence (AI) techniques are now being used as alternate statistical techniques. In this paper, two predictive models were developed by using AI techniques to predict flyrock distance in Sungun copper mine of Iran. One of the models employed artificial neural network (ANN), and another, fuzzy logic. The results showed that both models were useful and efficient whereas the fuzzy model exhibited high performance than ANN model for predicting flyrock distance. The performance of the models showed that the AI is a good tool for minimizing the uncertainties in the blasting operations.