The effects of method of generating circular slip surfaces on determining the critical slip surface by particle swarm optimization

The main objectives of slope stability analysis are evaluating factor of safety for a given slip surface and determining the critical slip surface for a given slope. Factor of safety is usually calculated by limit equilibrium method. The main steps to determine the critical slip surface are generating trial slip surfaces as probable solutions and searching among them to determine the one with the lowest factor of safety. Although the process of searching the critical slip surface received much attention between researchers, the significance of method of generating slip surfaces is seldom addressed in the literature. The authors believe that this ignorance can affect the accuracy of the results of slope stability analysis even in the simplest problems with circular slip surfaces. Consequently, this paper focused on the method of generating circular trial slip surfaces as the simplest mechanism of sliding and considered its effect on determining the critical slip surface. A new method of generating circular slip surface was presented, which is more efficient and less restricted than the conventional method. A computer program was also developed to determine the critical slip surface of slopes by using particle swarm optimization. The performances of the proposed method and developed computer program were verified during comparative studies and sensitivity analysis. Based on the results, the effect of method of generating circular slip surfaces on determining the critical slip surface was confirmed successfully. In all considered problems, the proposed method of generating circular slip surfaces led to the lower values of factor of safety compare with the conventional method.     

地貌特征对约旦南部阿尔阿加河(WadiAl-Arja)流域产沙影响分析(英文)

This study addresses the morphometric variables that determine the sediment yield in Wadi Al-Arja through the analysis of the impact of different morphometric characteristics along the course of the valley on its sediment yield, as well as the analysis of spatial and formal dimensions and morphologies of the basin and its relationship to the sediment yield. The study also addresses the size of variation in the volume of sediment yield of the river tributaries that make up the water network of the valley under the differences of its morphometric and hydrological characteristics. The study found several results, most notably: The classification of Wadi Al-Arja basin according to the hypsometric integral value(72.1%) within an uneven topography, which increases the force of the erosive activity and the size of the sediment yield if the basin was exposed to moist climatic periods. The study also showed the presence of convergence in the intra-spaces between the river tributaries in the water network. This increases the volume of water flows when these tributaries meet with each other and thus increasing their erosive ability and sediment yield. The study also showed the presence of marked variation in the sediment yield of the river tributaries depending on the differences in its morphometric characteristics. The results of the step-wise regression analysis confirmed the importance of the morphometric and hydrological variables, and plant coverage in interpreting the variation in the size of the sediment yield of the river tributaries of different stream order in Wadi Al-Arja basin, where these variables interpreted 43% of the total variation, with statistical significance less than 0.05.     

Assessment of sediment yield estimations for large watershed areas: a case study for the Seyhan,Demirköprü and Hirfanlı reservoirs in Turkey

Abstract

Analyses of data from reservoir surveys and sediment rating curves are compared to predict sediment yield in three large reservoir watershed areas in Turkey. Sediment yield data were derived from reservoir sedimentation rates and suspended sediment measurements at gauging stations. The survey data were analysed to provide the volume estimates of sediment, the time-averaged sediment deposition rates, the long-term average annual loss rates in the reservoir storage capacity, and the long-term sediment yield of the corresponding watershed areas. Four regression methods, including linear and nonlinear cases, were applied to rating curves obtained from gauging stations. Application of the efficiency test to a power function form of a rating curve with nonlinear regression yielded the highest efficiency values. Based on the analysis of the sediment rating curves, sediment load fluxes were calculated by using average daily discharge data at each gauging station. Comparison of these two sediment yield values for each reservoir showed that the sediment yields from the suspended sediment measurements, SY_GS, are 0.99 to 3.54 times less than those obtained from the reservoir surveys, SY_RS. The results from the reservoir surveys indicate that all three reservoirs investigated have lost significant storage capacity due to high sedimentation rates.     

Uncertainty assessment of the multilayer perceptron (MLP) neural network model with implementation of the novel hybrid MLP-FFA method for prediction of biochemical oxygen demand and dissolved oxygen: a case study of Langat River

Accurate prediction of the chemical constituents in major river systems is a necessary task for water quality management, aquatic life well-being and the overall healthcare planning of river systems. In this study, the capability of a newly proposed hybrid forecasting model based on the firefly algorithm (FFA) as a metaheuristic optimizer, integrated with the multilayer perceptron (MLP-FFA), is investigated for the prediction of monthly water quality in Langat River basin, Malaysia. The predictive ability of the MLP-FFA model is assessed against the MLP-based model. To validate the proposed MLP-FFA model, monthly water quality data over a 10-year duration (2001–2010) for two different hydrological stations (1L04 and 1L05) provided by the Irrigation and Drainage Ministry of Malaysia are used to predict the biochemical oxygen demand (BOD) and dissolved oxygen (DO). The input variables are the chemical oxygen demand (COD), total phosphate (PO₄), total solids, potassium (K), sodium (Na), chloride (Cl), electrical conductivity (EC), pH and ammonia nitrogen (NH₄-N). The proposed hybrid model is then evaluated in accordance with statistical metrics such as the correlation coefficient (r), root-mean-square error, % root-mean-square error and Willmott’s index of agreement. Analysis of the results shows that MLP-FFA outperforms the equivalent MLP model. Also, in this research, the uncertainty of a MLP neural network model is analyzed in relation to the predictive ability of the MLP model. To assess the uncertainties within the MLP model, the percentage of observed data bracketed by 95 percent predicted uncertainties (95PPU) and the band width of 95 percent confidence intervals (d-factors) are selected. The effect of input variables on BOD and DO prediction is also investigated through sensitivity analysis. The obtained values bracketed by 95PPU show about 77.7%, 72.2% of data for BOD and 72.2%, 91.6% of data for DO related to the 1L04 and 1L05 stations, respectively. The d-factors have a value of 1.648, 2.269 for BOD and 1.892, 3.480 for DO related to the 1L04 and 1L05 stations, respectively. Based on the values in both stations for the 95PPU and d-factor, it is concluded that the neural network model has an acceptably low degree of uncertainty applied for BOD and DO simulations. The findings of this study can have important implications for error assessment in artificial intelligence-based predictive models applied for water resources management and the assessment of the overall health in major river systems.     

A new empirical estimator of coseismic landslide displacement for Zagros Mountain region (Iran)

Earthquake-induced landslides are responsible worldwide for significant socioeconomic losses and historically have a prominent position in the list of natural hazards affecting the Iran plateau. As a step toward the development of tools for the assessment and the management of this kind of hazard at regional scale, an empirical estimator of coseismic displacements along potential sliding surfaces was obtained through a regression analysis for the Zagros region, a mountainous Iranian region subjected to earthquake-induced landslides. This estimator, based on the Newmark’s model, allows to evaluate the expected permanent displacement (named “Newmark displacement”) induced by seismic shaking of defined energy on potential sliding surface characterized by a given critical acceleration. To produce regression models for Newmark displacement estimators, a data set was constructed for different critical acceleration values on the basis of 108 accelerometric recordings from 80 Iranian earthquakes with moment magnitudes between 3.6 and 7. The empirical estimator has a general form, proposed by Jibson (Eng Geol 91:209–218, 2007), relating Newmark displacement to Arias intensity (as parameter representing the energy of the seismic forces) and to critical acceleration (as parameter representing the dynamic shear resistance of the sliding mass). As an example of application, this relation was employed to provide a basic document for earthquake-induced landslide hazard assessment at regional scale, according to a method proposed by Del Gaudio et al. (Bull Seismol Soc Am 93:557–569, 2003), applied to the whole Iranian territory, including Zagros region. This method consists in evaluating the shear resistance required to slopes to limit the occurrence of seismically induced failures, on the basis of the Newmark’s model. The obtained results show that the exposure to landslide seismic induction is maximum in the Alborz Mountains region, where critical accelerations up to ~0.1 g are required to limit the probability of seismic triggering of coherent type landslides within 10% in 50 years.     

Geoelectric model and hydrochemistry of salinity affected lower Atrai floodplain aquifer,NW Bangladesh: An approach for irrigation management

In the salinity affected lower Atrai floodplain aquifer in the NW Bangladesh, geoelectric resistivity survey and hydrochemical analysis are carried out with an aim to identify fresh and saline groundwater zones; investigate the status of salinity; evaluate hydrochemical processes involved and suggest management approaches for irrigation. Here a two-fold aquifer system, inter-layered by silt, clay and silty-clay aquitard and aquiclude is classified as: upper aquifer — spatially affected by salinity of varying degrees; and lower aquifer — generally characterized by high salinity. The aquifer with resistivity values greater than 69 Ωm is safe for irrigation use. Concentrations of major ions vary as: Ca²⁺>Na⁺>Mg²⁺>K⁺ and HCO₃>Cl>NO₃>SO₄ ^2?. Groundwater is dominated by Na-Ca to Ca-Na, HCO₃-Cl-SO₄, Cl-SO₄-HCO₃ and Cl-SO₄ ^2? facies where Ca²⁺, Mg²⁺, SO₄ ^2?, HCO₃ ^?, Cl^? and NO₃ ^2? ion concentrations are statistically dominant and water is of Ca-Mg, HCO₃-SO₄-Cl and NO₃ types. Geochemically, groundwater is hard and saline to fresh water type. Salinity increases with depth, but spatially towards the southern part. Groundwater quality is a product of water-rock interaction, direct mixing and marine spraying, or fall-out of airborne marine salts, where silicate weathering is the primary source of bivalent cations. Sediment provenance of alkaline earth silicates and higher concentrations of alkalis are derived from sources other than precipitation. In general partially or fully salinity affected upper and lower aquifers in the area except in its eastern part are not suitable for tubewell irrigation. As groundwater demand for irrigation is increasing, the saline water has progressively invaded relatively fresher parts of the aquifer by upconning. So, special salinity control management approaches can be adopted through engineering techniques such as groundwater abstraction optimization, as also through scientific behavioral approaches like groundwater demand management, salt tolerant crops production. In this context, surface water conservation and rain water harvesting for domestic and irrigational uses are recommended in the salinity affected area.     

Estimation of ship velocities from MODIS and OCM

Detection of ships and their tracks in the atmosphere from satellites was earlier demonstrated by Porch, Noone, and Kaufman, among others. In this letter, we have gone one step further to estimate the ship speed and direction by locating them and their tracks from multisatellite imagery. Exhausts from the ships create streaks of clouds in the atmosphere that help identify the same ship from two satellites. Ship velocities are estimated from displacements of ships. We have used optical sensors data from Moderate Resolution Imaging Spectroradiometer (MODIS) and Ocean Color Monitor (OCM) to demonstrate this technique. Estimated velocities of ships are within the expected range. Application of this approach has general interest to the navy, coast guards, shipping corporations, commercial ship owners, and fishermen. More satellite observations can be used to continuously monitor the ship velocities.     

Investigation on the Effect of Geometrical and Geotechnical Parameters on Elongated Offshore Piles Using Fuzzy Inference Systems

Among numerous offshore structures used in oil extraction, jacket platforms are still the most favorable ones in shallow waters. In such structures, log piles are used to pin the substructure of the platform to the seabed. The pile’s geometrical and geotechnical properties are considered as the main parameters in designing these structures. In this study, ANSYS was used as the FE modeling software to study the geometrical and geotechnical properties of the offshore piles and their effects on supporting jacket platforms. For this purpose, the FE analysis has been done to provide the preliminary data for the fuzzy-logic post-process. The resulting data were implemented to create Fuzzy Inference System (FIS) classifications. The resultant data of the sensitivity analysis suggested that the orientation degree is the main factor in the pile’s geometrical behavior because piles which had the optimal operational degree of about 5° are more sustained. Finally, the results showed that the related fuzzified data supported the FE model and provided an insight for extended offshore pile designs.