Hydrodynamic Tidal Model of the Persian Gulf Based on Spatially Variable Bed Friction Coefficient

The aim of this study is to develop a two-dimensional hydrodynamic tidal model for the Persian Gulf (PG2017) using 2D-MIKE21 software. The advantages of present study is accounting for the spatial variation of bed friction coefficient besides a precise bathymetry together with a 23-year of combined records of satellite altimetry data. We found that the bed friction coefficient has a significant effect on sea level changes in the region under our modeling consideration. Since the tidal behavior in the northern part of the Qeshm Island is significantly different from the other parts of the Persian Gulf, to present a more accurate hydrodynamic tidal model, the Gulf is divided into two regions where the bed friction coefficient is modeled separately for each region. The root mean square value of the differences between the amplitude of dominant constituents; M2, S2, K1, and O1 derived from the PG2017 model and that of 98 altimetry and coastal tide gauge stations are respectively equal to 1.6, 1.9, 2.8, and 1.3?cm. Moreover, comparing the PG2017 model efficiency with the FES2014, OSU12, EOT11a, DTU10, and Admiralty models shows that the PG2017 model has an improvement of 22.1%, 47.2%, 43.2%, 44.2%, and 57.6% in terms of relative error, respectively.     

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.     

<Emphasis Type="Italic">3D</Emphasis> Modelling of Urban Area Using Synthetic Aperture Radar (SAR)

Synthetic aperture radar (SAR) is a newly-developed remote sensing technology that works in all weather and independent of daylight. Recent satellite designs such as TerraSAR-x, which have resolutions of a couple of meters and sub-meters, have provided appropriate data for modelling and monitoring of urban areas. Image classification and height information extraction is possible considering the nature of SAR data. In this paper, a proper classification method for high-resolution SAR images has been used in urban areas. This classifier is based on statistical models. First, statistical models that are well adapted to urban SAR images are selected. Initial labelling is performed using the maximum likelihood method. A method based on Markov random fields is applied to improve the results by considering neighbourhood information. Meanwhile, topographic information is extracted using the phase difference obtained from SAR interferometry. After classification and height extraction, the homogeneous regions consisting of locations with similar objects are determined. The homogeneous region adjacency graph are generated using vectors containing classification information, extracted objects, height of pixels forming each region, and information on the neighbouring areas. Height and classification information are then merged by assigning height conditions based on the nature of objects and optimizing an energy function. The results obtained, including buildings, streets, and corner reflectors, are easily recognizable. The overall accuracy is improved from 57% in the initial classification to 95% in the employed procedure. Moreover, the accuracy of height estimation is about 2.74 m, which is acceptable for height estimations of buildings with more than one floor.     

Broadband seismic source data acquisition and processing to delineate iron oxide deposits in the Blötberget mine-central Sweden

A prototype electromagnetic vibrator, referred to here as E-Vib, was upgraded and developed for broadband hardrock and mineral exploration seismic surveys. We selected the iron oxide mine in Blötberget, central Sweden, for a test site in 2019 for the newly developed E-Vib because of the availability of earlier seismic datasets (from 2015 to 2016) for verification of its performance for hardrock imaging purposes. The two-dimensional data acquisition consisted of a fixed geometry with 550 receiver locations spaced at every 5 m, employing both cabled and wireless seismic recorders, along an approximately 2.7 km long profile. The E-Vib operated at every second receiver station (i.e. 10 m spacing) with a linear sweep of 2–180 Hz and with a peak force of 7 kN. The processing workflow took advantage of the broadband signal generated by the E-Vib in this challenging hardrock environment with varying ground conditions. The processed seismic section shows a set of reflections associated with the known iron oxide mineralization and a major crosscutting reflection interpreted to be from a fault system likely to be crosscutting the mineralization. The broadband source data acquisition and subsequent processing helped to improve signal quality and resolution in comparison with the earlier workflows and data where a drophammer seismic source was used as the seismic source. These results suggest new possibilities for the E-Vib source for improved targeting in hardrock geological settings.     

Optimization of Flue Gas Composition to Maximize Base Gas Replacement During UGS Process

Natural Resources Research - Base gas replacement by a cheap gas is one of the approved methods to reduce the cost of investment in underground gas storage process. Maximizing the amount of...     

Laboratory Study of Topographic Effects on the Near-surface Tornado Flow Field

To study topographic effects on the near-surface tornado flow field, the Iowa State University tornado simulator was used to simulate a translating tornado passing over three different two-dimensional topographies: a ridge, an escarpment and a valley. The effect of the translation speed on maximum horizontal wind speeds is observed for translation speeds of 0.15 and 0.50 \(\hbox {m}\,\hbox {s}^{-1}\), with the lower value resulting in a larger maximum horizontal wind speed. The tornado translation over the three topographies with respect to flat terrain is assessed for changes in: (a) the maximum horizontal wind speeds in terms of the flow-amplification factor; (b) the maximum aerodynamic drag in terms of the tornado speed-up ratio; (c) the maximum duration of exposure at any location to high wind speeds of a specific range in terms of the exposure amplification factor. Results show that both the maximum wind amplification factor of 14%, as well as the maximum speed-up ratio of 14%, occur on the ridge. For all topographies, the increase in aerodynamic drag is observed to be maximized for low-rise buildings, which illustrates the importance of the vertical profiles of the horizontal wind speed near the ground. The maximum exposure amplification factors, estimated for the range of wind speeds corresponding to the EF2 (50–60 \(\hbox {m}\,\hbox {s}^{-1}\)) and EF3 (61–75 \(\hbox {m}\,\hbox {s}^{-1})\) scales, are 86 and 110% for the ridge, 4 and 60% for the escarpment and ? 6 and 47% for the valley, respectively.     

A general weighted total Kalman filter algorithm with numerical evaluation

An applicable algorithm for Total Kalman Filter (TKF) approach is proposed. Meanwhile, we extend it to the case in which we can consider arbitrary weight matrixes for the observation vector, the random design matrix and possible correlation between them. Also the updated dispersion matrix of the predicted unknown is given. This approach makes use of condition equations and straightforward variance propagation rules. It is applicable to data fusion within a dynamic errors-in-variables (DEIV) model, which usually appears in the determination of the position and attitude of mobile sensors. Then, we apply for the first time the TKF algorithm and its extended version named WTKF to a DEIV model and compare the results. The results show the efficiency of the proposed WTKF algorithm. In particular in the case of large weights, WTKF shows approximately 25% improvement in contrast to TKF approach.     

Application of Remote Sensing in Monitoring Unsustainable Wetlands: Case Study Hamun Wetland

Monitoring wetland as one of the important parts of the global ecosystem is necessary for conservational programs. But, usually, collecting in situ data is restricted in these areas because of their remote locations, vast area and dynamic conditions. Remote sensing provides a cost effective tool to investigate hydrological patterns and the seasonal trend of changes in wetlands. In this paper, Land-use/land-cover change during water inundation period of Hamun wetland was investigated in order to determine change trend during this period. Hamun wetland is an unsustainable ecosystem, and monitoring this wetland is essential for conservation goals. This trend is critical for decision makers in order to plan the conservational scheme in all unsustainable ecosystems. To reach this objective, the land-use/land-cover maps during inundation period of Hamun were produced using Landsat 8 time series images. The results of accuracy assessment showed the classification of water and vegetation have the highest accuracy (94% and 93%, respectively). And the accuracy of plants in the water classes was the lowest (water–veg?=?89.9%, veg–water 1?=?88.8%, veg–water 2?=?87.6%). This means the higher misclassification is in determining the vegetation in the water. Then, the changes in the land-cover classes in relation to wetland inundation were investigated. Results of land-use/land-cover change illustrate the regions that were suitable for water birds but lost their suitability when the wetland dried out. These areas are crucial for water bird’s conservation. Satellite data determined these areas with acceptable accuracy.     

Discrimination of sand dunes and loess deposits using grain-size analysis in northeastern Iran

Identification and characterization of aeolian deposits in arid environments provide information on mechanisms of loess and sand accumulation. The objectives of this study were to (i) identify the distribution of aeolian deposits, (ii) discriminate loess and sand deposits using granulometric data, and (iii) describe the aeolian deposition in Sarakhs area, northeastern Iran. Particle size distributions of 26 surface samples were determined using a laser grain-size analyzer. Fine sand, very fine sand, and very coarse silt were dominant fractions in studied sediments, and the sum of these fractions ranged from 46.9% in loess deposits to 93.8% in sand dunes. The mean grain size (M _z ) of sand dunes ranged from 3.31 to 3.54 ?, which gradually changed to 4.09 to 5.50 ? in loess deposits. Sorting, skewness, and kurtosis ranged from 0.84 to 1.94 ?, 0.18 to 0.49, and 0.76 to 2.38, respectively. Aeolian deposits in the area resulted in the incorporation of Hariroud River system and Kopeh Dagh Mountains for aeolian particle production and accumulation. Alluvial comminution in Hariroud River is suggested the main mechanism of sand and silt production and flood plain environment the main reservoir of these particles. The mountains of Kopeh Dagh act as a barrier and play a key role for sand and loess accumulation.