On Inflow to a Tunnel in a Fractured Double-Porosity Aquifer

Inflow to a tunnel is a great public concern and is closely related to groundwater hydrology, geotechnical engineering, and mining engineering, among other disciplines. Rapid computation of inflow to a tunnel provides a timely means for quickly assessing the inflow discharge, thus is critical for safe operation of tunnels. Dewatering of tunnels is another engineering practice that should be planned. In this study, an analytical solution of the inflow to a tunnel in a fractured unconfined aquifer is obtained. The solution takes into account either the spherical or slab-shaped matrix block and the unsteady state interporosity flow. The instantaneous drainage water table and anisotropic hydraulic conductivities of the fractures network are also considered. Both uniform flux and uniform head boundary condition are considered to simulate the constant head boundary condition in the tunnel. The effects of the hydraulic parameters of the fractured aquifer on the inflow variation of the tunnel are explored. The application of the presented solution to obtain the optimum location and discharge of the well to minimize the inflow to a tunnel is illustrated.     

CHDS: conflict handling in direct sampling for stochastic simulation of spatial variables

Stochastic Environmental Research and Risk Assessment - In recent years, multiple-point geostatistical (MPS) approaches have gained significant popularity for modeling subsurface heterogeneity in...     

Location of Areas Prone to Flood Spreading Using GIS (Ilam Province,Iran)

Water Resources - The present study aimed to locate the areas prone to flood spreading in order to manage surface water resources. Therefore, the information layers of slope, land capability,...     

Context-aware abstraction and generalization of street networks: two cognitively engineered user-oriented approaches using network Voronoi diagrams

Generalization and spatial contextual awareness are prevalent concepts in geographic information systems. This study adopted a context-dependent user-centred network generalization method to create a sub-network for optimal route finding. The results show an increase in the number of preferred traversed edges. A route presentation approach is suggested that is based on cognitively engineered user-oriented abstraction of street network. Successive abstractions hierarchize the street network to create a hierarchical presentation structure. The route is projected onto one level in the structure. Then, instead of showing the exact route, the network Voronoi regions represented by the projected route are shown. Experience indicates that the suggested method is an efficient way of route presentation for a hierarchical regionalized structure of a human cognitive map.     

Regional geopotential model improvement for the Iranian geoid determination

Spherical harmonic expansions of the geopotential are frequently used for modelling the earth’s gravity field. Degree and order of recently available models go up to 360, corresponding to a resolution of about50 km. Thus, the high degree potential coefficients can be verified nowadays even by locally distributed sets of terrestrial gravity anomalies. These verifications are important when combining the short wavelength model impact, e.g. for regional geoid determinations by means of collocation solutions. A method based on integral formulae is presented, enabling the improvement of geopotential models with respect to non-global distributed gravity anomalies. To illustrate the foregoing, geoid computations are carried out for the area of Iran, introducing theGPM2 geopotential model in combination with available regional gravity data. The accuracy of the geoid determination is estimated from a comparison with Doppler and levelling data to ±1.4m.     

An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and <Emphasis Type="Italic">t</Emphasis>-distributed deviations

In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student’s) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.     

Equatorial radius of the Earth: A dynamical determination

An intrresting variation on the familiar method of determining the earth's equatorial radius a_e, from a knowledge of the earth's equatorial gravity is suggested. The value of equatorial radius thus found is 6378,142±5 meters. The associated parameters are GM=3.986005±.000004 × 10²⁰ cm³ sec-⁻² which excludes the relative mass of atmosphere ≅10⁻⁶ ξ GM, the equatorial gravity γ_e 978,030.9 milligals (constrained in this solution by the Potsdam Correction of 13.67 milligals as the Potsdam Correction is more directly, orless indirectly, measurable than the equatorial gravity) and an ellipsoidal flattening of f=1/298.255.     

Adaptive neuro-fuzzy prediction of the optimum parameters of protective spur dike

This study proposes a new approach for determining the optimum dimensions of a protective spur dike to mitigate the amount of scour around existing spur dikes. Several parameters of a protective spur dike were studied to determine their optimum values, including length, angle, and distance. Also the effect of changes of flow intensity and sediment size were examined. The main objective of this article was to predict the optimum values of protective spur dikes to attain the best performance. To predict the parameters of protective spur dikes for controlling the scour around spur dikes, we used the adaptive neuro-fuzzy inference system method to construct a process that simulates the optimal parameters of a protective spur dike, including the actual length of the protective spur dike, the actual length of the main spur dikes, the distance between the protective spur dike and the first spur dike, the angle between the protective spur dike and the direction of flow, the intensity of the flow, and median size of the bed sediments. This intelligent estimator was implemented using MATLAB/Simulink, and the performances were investigated. The simulation results presented in this paper show the effectiveness of the developed method.     

Predicting groundwater level of wells in the Diyala River Basin in eastern Iraq using artificial neural network

Al-Mansourieh zone is a part of Al-Khalis City within the province of Diyala and located in the Diyala River Basin in eastern Iraq with a total area about 830 km2.Groundwater is the main water source for agriculture in this zone.Random well drilling without geological and hydraulic information has led the most of these wells to dry up quickly.Therefore,it is necessary to estimate the levels of groundwater in wells through observed data.In this study,Alyuda NeroIntelligance 2.1 software was applied to predict the groundwater levels in 244 wells using sets of measured data.These data included the coordinates of wells(x,y),elevations,well depth,discharge and groundwater levels.Three ANN structures(5-3-3-1,5-10-10-1 and 5-11-11-1)were used to predict the groundwater levels and to acquire the best matching between the measured and ANN predicted values.The coefficient of correlation,coefficient determination(R2)and sum-square error(SSE)were used to evaluate the performance of the ANN models.According to the ANN results,the model with the three structures has a good predictability and proves more effective for determining groundwater level in wells.The best predictor was achieved in the structure 5-3-3-1,with R2 about 0.92,0.89,0.84 and 0.91 in training,validation,testing and all processes respectively.The minimum average error in the best predictor is achieved in validation and testing processes at about 0.130 and 0.171 respectively.On the other hand,the results indicated that the model has the potential to determine the appropriate places for drilling the wells to obtain the highest level of groundwater.     

Early Cretaceous sedimentary provenance and structural evolution of the central Sanandaj–Sirjan Zone,Iran: implications for palaeogeographic reconstructions of the northern Neo-Tethyan margin

ABSTRACT

The Early Cretaceous was an important epoch in the evolution of the Earth system in which major tectonic episodes occurred, especially along the Alpine–Himalayan belt. The paucity of reliable palaeogeographic data from the central segment of this geological puzzle, however, hampers the reconstruction of a panoramic view of its Early Cretaceous palaeogeography and geodynamic setting. Here we present multidisciplinary provenance data from Lower Cretaceous strata of the overriding plate of the Neo-Tethyan subduction zone (the Sanandaj–Sirjan Zone; SSZ, of central Iran), including structural, basin-fill evolution, petrographic and geochemical analyses. Sandstone provenance analysis of Lower Cretaceous red beds suggests the occurrence of sub-mature litho-quartzose sandstones attributed to an active continental arc margin in convergent setting predominantly derived from plutonic, quartzose sedimentary and metamorphic rocks exposed in the central SSZ. Weathering indices indicate moderate chemical weathering in the source area which may be related to close source-to-sink relationships or arid climate. Our palaeogeographic reconstructions and original geological mapping indicate that the erosion of uplifted basement rocks exposed in horst blocks provided the sediment sources for the syn-extensional deposition of uppermost Jurassic–lowermost Cretaceous conglomerates and Lower Cretaceous siliciclastic red beds within a continental retro-arc basin during initiation of the ‘Neo-Tethys 2?. The polyphase tectonic reactivation along the principal fault of the study area controlled the syn- and post-extensional tectonostratigraphic evolution that reflect the corresponding mechanical decoupling/coupling along the northern Neo-Tethyan plate margin.