Coastal Wave Height Prediction using Recurrent Neural Networks (RNNs) in the South Caspian Sea

The prediction of wave parameters has a great significance in the coastal and offshore engineering. For this purpose, several models and approaches have been proposed to predict wave parameters, such as empirical, soft computing, and numerical based approaches. Recently, soft computing techniques such as recurrent neural networks (RNN) have been used to develop sea wave prediction models. In this study, the RNN for wave prediction based on the data gathered and the measurement of the sea waves in the Caspian Sea, in the north of Iran is used for this study. The efficiency of RNNs for 3, 6, and 12 hourly and diurnal wave prediction using correlation coefficients is calculated to be 0.96, 0.90, 0.87, and 0.73, respectively. This indicates that wave prediction by using RNNs yields better results than the previous neural network approaches.     

Fault diagnosis using noise modeling and a new artificial immune system based algorithm

A new fault classification/diagnosis method based on artificial immune system(AIS) algorithms for the structural systems is proposed. In order to improve the accuracy of the proposed method, i.e., higher success rate, Gaussian and non-Gaussian noise generating models are applied to simulate environmental noise. The identification of noise model, known as training process, is based on the estimation of the noise model parameters by genetic algorithms(GA) utilizing real experimental features. The proposed fault classification/diagnosis algorithm is applied to the noise contaminated features. Then, the results are compared to that obtained without noise modeling. The performance of the proposed method is examined using three laboratory case studies in two healthy and damaged conditions. Finally three different types of noise models are studied and it is shown experimentally that the proposed algorithm with non-Gaussian noise modeling leads to more accurate clustering of memory cells as the major part of the fault classification procedure.     

Robust Automatic Reduction of Multibeam Bathymetric Data Based on M-estimators

Multibeam echosounders have commonly been employed for a wide range of applications including offshore survey, navigation, hydrogeology, and oceanography. Because the tremendous volume of the bathymetric data is demanding for some purposes and requires significant storage space, the data reduction plays a prominent role in practice. Additionally, the multibeam soundings are inevitably contaminated with sporadic outliers, and as such, the data cleaning can be challenging especially in shallow waters. We present a speedily robust method for reliably reducing the volume of the bathymetric data within grid cells. In this respect, robust M-estimators are recursively applied to the data in a patch-wise manner to alleviate the undesirable effects of the outlying observations. Accordingly, the reduced bathymetry is automatically made unaffected by the possible outliers once their equivalent weights have been downweighted. The performance of the presented method has been demonstrated by synthetic datasets and an experimental dataset collected by an ATLAS FS 20/100 kHz shallow-water multibeam echosounder in the offshore waters of Kish wharf. The reliability, efficiency, and capability of the proposed method have been verified, which makes it quite possible to meet the IHO requirements for special-order seafloor mapping.     

Accumulation of heavy metals in soil and uptake by plant species with phytoremediation potential

Contamination of heavy metals represents one of the most pressing threats to water and soil resources, as well as human health. Phytoremediation can be potentially used to remediate metal contaminated sites. In this study, concentrations of copper, zinc, iron, and magnesium accumulated by native plant species were determined in field conditions of Hame Kasi iron and copper mine in the central part of Iran in Hamadan province. The results showed that metal accumulation by plants differed among species and tissue bodies. Species grown in substrata with elevated metals contained significantly higher metals in plants. Metals accumulated by plants were mostly distributed in root tissues, suggesting that an exclusion strategy for metal tolerance exists widely amongst them. The mentioned species could accumulate relatively higher metal concentrations far above the toxic concentration in the plant shoots. With high translocation factor, metal concentration ratio of plant shoots to roots indicates internal detoxification metal tolerance mechanism; thus, they have potential for phytoextraction. The factors affecting metal accumulation by plant species including metal concentrations, pH, electrical conductivity, and nutrient status in substrata were measured. Mostly, concentrations of zinc and copper in both aboveground and underground tissues of the plants were significantly, positively related to their total in substrata, while iron, zinc, and copper were negatively correlated to soil phosphorus.     

Roadheader performance prediction using genetic programming (GP) and gene expression programming (GEP) techniques

Roadheading machines play a vital role in excavation operation in tunneling and mining industries notably when selective mining is required. Roadheaders are more effective in soft to medium rock formations due to a higher cutting rate in such strata. A precise prediction of machine’s performance is a crucial issue, as it has considerable effects on excavation planning, project’s cost estimation, machine specification selection as well as safety of the project. In this research, a database of machine performance and some geomechanical parameters of rock formations from Tabas coal mine project, the largest and fully mechanized coal mine in Iran, has been established, including instantaneous cutting rate (ICR), uniaxial compressive strength, Brazilian tensile strength, rock quality designation, influence of discontinuity orientation (Alpha angle) and specific energy. Afterward, the parameters were analyzed through genetic programming (GP) and gene expression programming (GEP) approaches to yield more accurate models to predict the performance of roadheaders. As statistical indices, coefficient of determination, root mean square error and variance account were used to evaluate the efficiency of the developed models. According to the obtained results, it was observed that developed models can effectively be implemented for prediction of roadheader performance. Moreover, it was concluded that performance of the GEP model is better than the GP model. A high conformity was observed between predicted and measured roadheader ICR for GEP model.     

Interlobate esker architecture and related hydrogeological features derived from a combination of high-resolution reflection seismics and refraction tomography,Virttaankangas, southwest Finland

A novel high-resolution (2–4 m source and receiver spacing) reflection and refraction seismic survey was carried out for aquifer characterization and to confirm the existing depositional model of the interlobate esker of Virttaankangas, which is part of the Säkylänharju-Virttaankangas glaciofluvial esker-chain complex in southwest Finland. The interlobate esker complex hosting the managed aquifer recharge (MAR) plant is the source of the entire water supply for the city of Turku and its surrounding municipalities. An accurate delineation of the aquifer is therefore critical for long-term MAR planning and sustainable use of the esker resources. Moreover, an additional target was to resolve the poorly known stratigraphy of the 70–100-m-thick glacial deposits overlying a zone of fractured bedrock. Bedrock surface as well as fracture zones were confirmed through combined reflection seismic and refraction tomography results and further validated against existing borehole information. The high-resolution seismic data proved successful in accurately delineating the esker cores and revealing complex stratigraphy from fan lobes to kettle holes, providing valuable information for potential new pumping wells. This study illustrates the potential of geophysical methods for fast and cost-effective esker studies, in particular the digital-based landstreamer and its combination with geophone-based wireless recorders, where the cover sediments are reasonably thick.

     

New evidence for Jurassic continental rifting in the northern Sanandaj Sirjan Zone,western Iran: the Ghalaylan seamount,southwest Ghorveh

ABSTRACT

We address the growing controversy about the tectonic setting in which Jurassic magmatism of Iran occurred: arc or continental rift. In the Ghorveh area of the northern Sanandaj Sirjan zone (SaSZ), the Ghalayan metabasites are interlayered with marble and schist and locally cut by acidic dikes. Zircon U-Pb dating of the metabasitic rocks shows that these crystallized at ca. 145–144 Ma ago in the Late Jurassic (Tithonian). This complex was metamorphosed in the lower greenschist facies, however, some protolithic structures such as pillow lava and primary minerals are preserved. The metabasites are tholeiites with low SiO₂ (45.6–50.5 wt.%), moderate Al₂O₃ (11.3–17.0 wt.%), and high TiO₂ (0.7–2.9 wt.%) and Fe₂O₃ (9.4–14.1 wt.%). The Ghalayan metabasites are enriched in Light rare earth elements (LREEs) without significant Nb, Ta, Pb, Sr and Ba anomalies, similar to modern continental intra-plate tholeiitic basalts such as Afar and East African rifts. The Ghalaylan metabasites show wide ranges for ⁸⁷Sr/⁸⁶Sr_(i) (0.7039–0.7077) and positive ε_Nd(t) values (+0.1 to +4.6). These isotopic compositions are similar to those expected for slightly depleted subcontinental lithospheric mantle sources. Independently built discrimination diagrams indicate an intra-continental rifting regime for the source of Jurassic metabasites in the northern SaSZ. Geochemical and tectonic evidence suggests that rifting or a mantle plume was responsible for volcanic activity in the Upper Jurassic SaSZ. Considering the variation of ages of basaltic volcanism along the SaSZ, we suggest that Ghalayan basaltic magmatism reflected a submarine volcano that formed as part of the late stage continental rift, similar to Afar in the East African Rift system. Our results indicate that an extensional tectonic regime dominated SaSZ tectonics in the Middle to Late Jurassic.     

Envrionmental impact assessment of urban development plan by vulnerability model application

Urban development plans have significant potential impacts on affected environment according to the various activities and due to their different construction and operation phases. Establishment and development of the new-established Municipality of Tehran District-22, with about 10,000 hectares area has been planned as the last limit of continuous extension of Great Tehran and as the largest urban city of the country. It is based on the general lay out of Tehran master development plan, ratified in 1970 and 1991. In terms of current facilities, it has been anticipated necessary spaces to establish various activities including residential, commercial and urban services, establishing green spaces, man-made lake and other necessary infrastructures of urban development. Griding method was used in order to determine the environment vulnerability of the development plan of the region. In this method, the studied district has been divided into 1 to 10 square kilometers grids. To improve the accuracy of the study, the grids dimension is smaller than the common size. After griding, the most appropriate layers out of the required layers have been used to determine the vulnerability. These layers are, land slope, geographical aspect, pedology, geology, plant density and ground water vulnerability. The limited codes of each layer have also been defined. Summary of the above-mentioned layers results have been analyzed in the map form 1:50,000 scale by Arc-View software in GIS system in order to determine the specification of impact units. After the determination of limitation, the most prevailing limited code of each grid was selected. The obtained results were transferred to excel program and the final amount of vulnerability were then calculated by using equation E =∑ (a-b)/4. The final vulnerability was substitute by each grid code as a new data and the last map of vulnerability was set. Regarding to this map at the studied region affected by current limitation of environmental condition, the north part of the district especially A₉, B₁₀, B₁₁ B₁₂, C₉, C₁₁, C₁₈, D₁₂ and E₁₄ showed the highest amount of vulnerability. According to the final vulnerability map, it is distinguished that the north parts of the district mainly in parts 1 or 2 vulnerability codes have had high vulnerability.     

Agricultural activities impact on groundwater nitrate pollution

Concern over agricultural diffuse pollution sources in integrated water quality management has been growing recently. High nitrogen fertilizers application rates may increase the potential groundwater pollution. These effects were investigated in Andimeshk and Susa plains that cover an area of 1100 km² between the Dez and Karkhe rivers in north of Khozestan-Iran. This region divided to 4 sub-regions A, B, C, and D. Additionally 168 groundwater samples were collected from 42 water wells during the months April, May, August, and September of 2004. The Hackspectrophotometer nitrate test was used to measure the NO₃ ^? concentration in water samples. Information about further nitrate data was obtained. A questionnaire procedure was used for collection N-fertilizers application rate data in studied area. The results demonstrated that all of the groundwater samples have NO₃ ^t- concentration below the EPA MCL (44.27 mg/l) and WHO guideline (50 mg/l). The mean nitrate concentrations are 16.1, 19.5, 13.3, and 7.9 mg/l in sub-regions A, B, C, and D respectively. There are different amount of N-fertilizers applied in sub-regions A, B, C, and D. Correlation between NO₃t- concentrations and N-fertilizers rate suggests a inverse correlation between Nfertilizers application rate and ground waters nitrate concentrations in studied area (r=?0.69).