Prediction of longitudinal dispersion coefficient in natural rivers using a cluster-based Bayesian network

The longitudinal dispersion coefficient is a key element in determining the distribution and transmission of pollution, especially when cross-sectional mixing is completed. However, the existing predictive techniques for this purpose exhibit great amounts of uncertainty. The main objective of this study is to present a more accurate model for predicting longitudinal dispersion coefficient in natural rivers and streams. Bayesian network (BN) approach was considered in the modeling procedure. Two forms of input variables including dimensional and dimensionless parameters were examined to find the best model structure. In order to increase the performance of the model, the clustering method as a preprocessing data technique was applied to categorize the data in separate groups with similar characteristics. An expansive data set consisting of 149 field measurements was used for training and testing steps of the developed models. Three performance evaluation criteria were adopted for comparison of the results of the different models. Comparison of the present results with the artificial neural network (ANN) model and also well-known existing equations showed the efficiency of the present model. The performance of dimensionless BN model 30% is more than dimensional ones in terms of the root mean square error. The accuracy criterion was increased from 70 to 83% by performing clustering analysis on the BN model. The BN-cluster model 43% is more accurate than ANN model in terms of the accuracy criterion. The results indicate that the BN-cluster model give 16% better results than the best available considered model in terms of the accuracy criterion. The developed model provides a suitable approach for predicting pollutant transport in natural rivers.     

Sedimentological and geoenvironmental evaluation of the coastal area between Al-Khowkhah and Al-Mokha,southeastern Red Sea,Republic of Yemen

The increasing anthropogenic activities (e.g., constructing touristic resorts) have led to notable changes in the Yemeni Red Sea coastal regions. In this context, recent sediments have been investigated to infer possible natural and man-induced processes on these coastal areas. The target area lies between longitudes 43°13′–43°30′E and latitudes 13°15′–13°55′N. It extends about 90 km along the coastline as a part of the Tihama plain. Geomorphologically, it forms a long-curved stretch with pronounced headlands, embayments and bays. Generally, it is covered by recent sediments (wadi, lagoon, beach and spit deposits along with sabkha, coastal dunes and mangrove). Textural studies reveal that most of the studied sediments are mainly poorly to moderately sorted and are composed mainly of sandy fractions with few gravel and mud, mostly bimodal with minor unimodal patterns. The igneous (granites) as well as basic (basalt, andesite and andesitic pyroclastics) and acidic (dacite and rhyolite) volcanic rocks of Tertiary age, which are exposed to the east of the study area, are believed to be the source of pyroxenes, amphiboles, epidotes, biotite, sphene, zircon, tourmaline and rutile, in a decreasing order of abundance. Moreover, smectite, kaolinite, chlorite, illite and palygorskite are the predominant clay minerals, mainly of detrital origin. The total carbonate content fluctuates from 37.41% (lagoon sediments) to 53.74% (sabkha sediments). The high amount of sea grasses, which covers the tidal flat zone and relates to the fine-grained sediments, accounts for the high organic matter content. The mineralogy of the source rocks has controlled the general distribution of major elements (Fe, Mg, Na, K and Mn) in the beach sediments. In such sediments, the concentrations of the heavy metals (Cu, Zn, Cd, Ni, Pb and Co) may reflect the sediment pollution using different approaches. The enrichment factors (EFs) of the trace metals for most samples reveal values that are greater than 1, referring to three groupings, which are: moderate to moderately severe (Zn, Cu and Mn), minor to moderate (Pb and Co) and zero to minor (Cd and Ni) enrichment. The EFs for Pb, Cd, Ni and Co metals (<5) may be attributed to the crustal materials and/or natural weathering processes. But, those for Zn, Cu and Mn (>5), especially in Al-Khowkhah–Abu-Zahr, Moushij–Zahari–Ruays, Yokhtol and Mokha localities, are possible of anthropogenic contributions.     

Applying different scenarios for landslide spatial modeling using computational intelligence methods

Landslides every year impose extensive damages to human beings in various parts of the world; therefore, identifying prone areas to landslides for preventive measures is essential. The main purpose of this research is applying different scenarios for landslide susceptibility mapping by means of combination of bivariate statistical (frequency ratio) and computational intelligence methods (random forest and support vector machine) in landslide polygon and point formats. For this purpose, in the first step, a total of 294 landslide locations were determined from various sources such as aerial photographs, satellite images, and field surveys. Landslide inventory was randomly split into a testing dataset 70% (206 landslide locations) for training the different scenarios, and the remaining 30% (88 landslides locations) was used for validation purposes. To providing landslide susceptibility maps, 13 conditioning factors including altitude, slope angle, plan curvature, slope aspect, topographic wetness index, lithology, land use/land cover, distance from rivers, drainage density, distance from fault, distance from roads, convergence index, and annual rainfall are used. Tolerance and the variance inflation factor indices were used for considering multi-collinearity of conditioning factors. Results indicated that the smallest tolerance and highest variance inflation factor were 0.31 and 3.20, respectively. Subsequently, spatial relationship between classes of each landslide conditioning factor and landslides was obtained by frequency ratio (FR) model. Also, importance of the mentioned factors was obtained by random forest (RF) as a machine learning technique. The results showed that according to mean decrease accuracy, factors of altitude, aspect, drainage density, and distance from rivers had the greatest effect on the occurrence of landslide in the study area. Finally, the landslide susceptibility maps were produced by ten scenarios according to different ensembles. The receiver operating characteristics, including the area under the curve (AUC), were used to assess the accuracy of the models. Results of validation of scenarios showed that AUC was varying from 0.668 to 0.749. Also, FR and seed cell area index indicators show a high correlation between the susceptibility classes with the landslide pixels and field observations in all scenarios except scenarios 10_RF and 10_SVM. The results of this study can be used for landslides management and mitigation and development activities such as construction of settlements and infrastructure in the future.     

Evaluation of relative tectonic activity of Buin Zahra-Avaj area,northern Iran

Present active tectonics is affecting central Alborz and created various dynamic landforms in Buin Zahra-Avaj area, northern Iran. The area, located between the southern central Alborz and the edge of northwestern central Iran, is the result of both the Arabian–Eurasian convergence and clockwise rotation of the south Caspian Basin with respect to Eurasia in which most of the steep fault planes have a left lateral strike-slip component and most of the dip-slip faults are reverse, dipping SW. Since this region consists of several residential and industrial areas and includes several fault zones, the assessment of the structures of the present activity is vital. Six significant morphometric indices have been applied for this evaluation including stream length–gradient (SL), drainage basin asymmetry factor (Af), hypsometric integral (Hi), ratio of valley floor width to valley height (Vf), drainage basin shape (Bs), and mountain front sinuosity (Smf). The combined analyzed indices, represented through the relative tectonic activity (Iat), were used. The study area was divided into four regions according to the values of Iat. These classes include class 1 (very high activity,18%), class 2 (high, 20%), class 3 (moderate, 44%), and class 4 (low, 18%). The results of these indices are consistent with field observations on landforms and the deformation of Quaternary deposits.     

Prediction of local scour around complex piers using GEP and M5-Tree

Local scour around piers is one of the main causes of bridge failures. In this study, three robust techniques, artificial neural networks (ANNs), M5-Tree, and Gene Expression Programming (GEP), were employed for prediction of scour depth around complex piers. The clear water condition was chosen for all experimental tests. The results indicated that pier diameter (b _c) and foundation level (Y) are the main parameters for local scour. Furthermore, the minimum scour depth occurs in range of Y/b _c = 1.1~1.3. In next step, to evaluate the mentioned techniques, a wide range of dataset was collected from the present study and literature. The radial base function (RBF) with R ² = 0.945 and RMSE = 0.031 provides better prediction in comparison with conventional equations, M5-Tree (R ² = 0.883, RMSE = 0.292) and the GEP techniques (R ² = 0.811 and RMSE = 0.263). The equations developed by M5-Tree and GEP are more useful for practical purposes and can be easily employed to predict the depth of scour at complex piers.     

Effect of polymer and fiber usage on dewatering and compressibility behavior of fly ash slurries

Coal ash producing is an increasing trend because of its high energy demand worldwide. For transportation, disposal, and reuse of the industrial waste materials, geotextile tube’s dewatering technology has been widely used over the last three decades, which helps to decrease the volume of the dewatered slurry. In this study, effect of usage of polymer and fibers on dewatering characteristic of fly ash slurries was investigated. For the experimental investigation, an anionic polymer and short nylon fibers were used. As a new concept, centrifuge test is introduced as an alternative for the widely used pressure filtration test (PFT). Centrifuge test was used to evaluate final solid content of the retained sediments and change in slurry volume of fly ash. Tests were conducted on unconditioned and anionic polyacrylamide and/or fiber conditioned fly ash slurries. Centrifuge test results were compared with PFT results with respect to final solid content. It was found that fiber and/or polymer usage has remarkable effect on the dewatering rate of fly ash slurry. It was also found that final solid content of fly ash slurries was decreased by inclusion of fibers and polymer, which indicates that fiber and/or polymer usage can create more permeable soil body.     

Surface soil assessment in the Ubhur area,north of Jeddah,western Saudi Arabia,using a multichannel analysis of surface waves method

Ten boreholes drilled in Ubhur area up to the depth of bedrock indicted the shallow depth of bedrock where the average depth ranges between 10 and 15 m. The standard penetration test N-values of these boreholes were measured and averaged. Based on N-values to the depth of bedrock, Ubhur area can be classified as site class C and D. Multichannel analysis of surface waves technique has been applied along seventy six profiles using 24-channel geophone array and 4.5Hz vertical geophones with 1m geophone spacing and sledgehammer and/or weight drop as seismic energy sources. Values of shear wave velocity to 30 m are calculated and then averaged (Vs30) where it ranges between 310.08 m/s and 1139.8 m/s. Therefore, Ubhur area can be classified into site class B, C and D based on site classification of the national earthquake hazards reduction program (NEHRP) recommendations. Accordingly, the greatest part of the study area falls in site class C while class B and D covered limited areas in the western and the eastern parts respectively. Depending on the shallow depth of bedrock in the study area, the Vs30 parameter is not applicable in the study area so the average values of Vs for the soil thickness, excluding the bedrock, have been calculated and mapped for site class C and D only. So Vs30 approach is not applicable for areas with shallow depth of bedrock which gives higher classification.     

A new rating system approach for risk analysis of rock slopes

In this paper, an approach is presented to analyze the stability risk of rock slopes based on a new rating system. Three factors are used to estimate the risk level of rock slopes: (1) failure probability, (2) element at risk rating, and (3) vulnerability rating. Element at risk and vulnerability ratings are both given a range from 0 to 10, and the probability of failure is varied between 0 and 1, so the risk rating ranges between 0 and 100. This risk rating can be used to determine both the quantitative and qualitative risk levels of slopes at the same time. The method is tested on the western sector of the slopes facing Songun copper plant phase III, Iran, to clarify its procedures and assess its validity. Deterministic kinematic analyses showed that the slope has a potential for circular failure. Risk assessments revealed that the risk levels of the slope in both static and pseudo-static conditions are “very low” and “high,” respectively.

     

Protostellar evolution during time-dependent anisotropic collapse

The formation and collapse of a protostar involves the simultaneous infall and outflow of material in the presence of magnetic fields, self-gravity and rotation. We use self-similar techniques to self-consistently model the anisotropic collapse and outflow by using a set of angle-separated self-similar equations. The outflow is quite strong in our model, with the velocity increasing in proportion to radius, and material formally escaping to infinity in the finite time is required for the central singularity to develop.
Analytically tractable collapse models have been limited mainly to spherically symmetric collapse, with neither magnetic field nor rotation. Other analyses usually employ extensive numerical simulations, or either perturbative or quasistatic techniques. Our model is unique as an exact solution to the non-stationary equations of self-gravitating magnetohydrodynamics (MHD), which features co-existing regions of infall and outflow.
The velocity and magnetic topology of our model is quadrupolar, although dipolar solutions may also exist. We provide a qualitative model for the origin and subsequent evolution of such a state. However, a central singularity forms at late times, and we expect the late-time behaviour to be dominated by the singularity, rather than depend on the details of its initial state. Our solution may, therefore, have the character of an attractor among a much more general class of self-similarity.     

The solar lithium abundance

A detailed observational study of the solar photospheric lithium feature has been carried out with emphasis on center-limb observations, continuum location, possible effects of telluric lines, effects of blending by atomic and molecular lines, and decomposition of the solar spectrum around λ6707 Å.