The Jinadriyah anticlines: a surface model for oil fields in eastern Saudi Arabia

Mesozoic oil in Saudi Arabia exists in north/south-oriented anticlines. Such anticlines are usually studied using subsurface data. The present study introduces, for the first time in Saudi Arabia, a surface analog for these anticlines. The study covers two northerly oriented anticlines located in the Jinadriyah area at 15 km to the northeast of the Riyadh city. They are named herein the North and South Jinadriyah anticlines. The outcrops in both anticlines belong to the Lower Cretaceous Yamama Formation which consists of limestone in its lower part and limestone with shale in its upper part. The study included initially detailed interpretation of Google Earth and Landsat TM images to map the structural pattern of the anticlines. Detailed field mapping confirmed the satellite image interpretation and helped describe the geometry of the two anticlines in detail. The 3.5-km-long South Jinadriyah anticline is an open doubly plunging asymmetric anticline. The western flank is dissected by 13 minor reverse faults of north–south orientation. The North Jinadriyah anticline is about 5.5 km long and is relatively more complex than the South Jinadriyah anticline. It consists of northern, central, and southern segments that differ from each others in orientation and style. The anticline is dissected by 18 minor faults of different orientations and sense of displacement. Two perpendicular fracture sets with one being parallel to the anticline axes were recorded in the two anticlines. Both anticlines are interpreted as fault-propagation folds that were formed during the Late Cretaceous first Alpine orogeny. The mid-Late Tertiary second Alpine orogeny and Late Tertiary eastward tilting of the Arabian Plate increased the degree of folding and faulting.     

A phased approach to enable hybrid simulation of complex structures

Hybrid simulation has been shown to be a cost-effective approach for assessing the seismic performance of structures. In hybrid simulation, critical parts of a structure are physically tested, while the remaining portions of the system are concurrently simulated computationally, typically using a finite element model. This combination is realized through a numerical time-integration scheme, which allows for investigation of full system-level responses of a structure in a cost-effective manner. However, conducting hybrid simulation of complex structures within large-scale testing facilities presents significant challenges. For example, the chosen modeling scheme may create numerical inaccuracies or even result in unstable simulations; the displacement and force capacity of the experimental system can be exceeded; and a hybrid test may be terminated due to poor communication between modules (e.g., loading controllers, data acquisition systems, simulation coordinator). These problems can cause the simulation to stop suddenly, and in some cases can even result in damage to the experimental specimens; the end result can be failure of the entire experiment. This study proposes a phased approach to hybrid simulation that can validate all of the hybrid simulation components and ensure the integrity large-scale hybrid simulation. In this approach, a series of hybrid simulations employing numerical components and small-scale experimental components are examined to establish this preparedness for the large-scale experiment. This validation program is incorporated into an existing, mature hybrid simulation framework, which is currently utilized in the Multi-Axial Full-Scale Sub-Structuring Testing and Simulation (MUST-SIM) facility of the George E. Brown Network for Earthquake Engineering Simulation (NEES) equipment site at the University of Illinois at Urbana-Champaign. A hybrid simulation of a four-span curved bridge is presented as an example, in which three piers are experimentally controlled in a total of 18 degrees of freedom (DOFs). This simulation illustrates the effectiveness of the phased approach presented in this paper.     

Modeling and Optimization of Fluoride and Cadmium Trapping in Phosphogypsum Using Design Methodology

The manufacturing of phosphoric acid from natural calcium phosphate generates a solid residue containing 25–30% humidity. This solid residue (phosphogypsum) generates acidic solution (pH ≈ 2.5) containing several toxic ionic species, that coat its grains. Fluorides and heavy metals such as cadmium are considered the most harmful species contained in the released solution from phosphogypsum. The purpose of this work is to study the trapping of fluorides and cadmium in phosphogypsum as well as effluent neutralization before its discharge into natural recipient. Therefore, calcium carbonate finely ground was added and fully mixed with wet phosphogypsum. A four factors central composite design was used to model and to optimize the operating parameters that govern the process. The studied factors were temperature, reaction time, mass, and grains size of CaCO₃. Considered responses were pH, F⁻, and Cd²⁺ concentrations in the released solution after reaction with CaCO₃. The optimum operating conditions were quite efficient to trap, respectively, 99% Cd²⁺ and 97% of F⁻ with a final pH of 6.66. So an original, easy, simple, and cost effective method to trap some toxic species on phosphogypsum through CaCO₃ addition would likely to be integrated in phosphoric acid manufacturing plant.     

Free Amino Acids Content in Some Halophytes under Salinity Stress in Arid Environment,Jordan

The variation in free amino acids concentration was examined in halophytes under salt stress conditions during spring and autumn in an arid environment, Jordan. The experiment was conducted in the southern region of the Jordan valley, using four different halophytes namely: Atriplex halimus, Atriplex nummularia, Tamarix aphylla L., and Portulaca oleracea L. Free amino acid concentrations showed changeable patterns under salinity stress conditions compared to the non‐stress (control) with respect to plant species and seasonal variation. In general, the amino acid pool during the spring experienced increases in A. halimus with increasing salinity; and decreased in A. nummularia, P. oleracea L., and T. aphylla L., respectively. Whereas, during the autumn, the overall amino acids decreased in A. halimus and A. nummularia, and increased in T. aphylla L. and P. oleracea with increasing salinity. The amino acid pool concentrations of A. halimus L. during the autumn was similar to that in spring under stress condition. Similarly, T. aphylla L. and P. oleracea showed higher rates in the autumn. In contrast, A. nummularia L. exhibited a slight increase in amino acid composition in the autumn under stress conditions. The plantation of salt tolerant plants such as halophytes in saline sodic soils showed an effective decline in soil salinity and can be recommended to be used as a bioreclamation method instead of the traditional leaching method, which requires large amount of fresh water.     

General variational method for Milne's integral equation

In this paper, we establish a general variational method for Milne's integral equation. Moreover, a recursive computational algorithm for the method is also constructed. To illustrate the precision of the method as well as the computational algorithm, a numerical example forN=20 is given.     

Neural network model for liquefaction potential in soil deposits using Turkey and Taiwan earthquake data

Simplified methods have been practiced by researchers to assess nonlinear liquefaction potential of soil. Derived from several field and laboratory tests, various simplified procedures such as stress-based, strain-based, Chinese criteria, etc. have been developed by utilizing case studies and undisturbed soil specimens. In order to address the collective knowledge built up in conventional liquefaction engineering, an alternative general regression neural network model is proposed in this paper.To meet this objective, a total of 620 sets of data including 12 soil and seismic parameters are introduced into the model. The data includes the results of field tests from the two major earthquakes that took place in Turkey and Taiwan in 1999 and some of the desired input parameters are obtained from correlations existing in the literature.The proposed GRNN model was developed in four phases, mainly: identification phase, collection phase, implementation phase, and verification phase. An iterative procedure was followed to maximize the accuracy of the proposed model. The case records were divided randomly into testing, training, and validation datasets.Generating a model that takes into account of 12 soil and seismic parameters is not feasible by using simplified techniques; however, the proposed GRNN model effectively explored the complex relationship between the introduced soil and seismic input parameters and validated the liquefaction decision obtained by simplified methods. The proposed GRNN model predicted well the occurrence/nonoccurrence of soil liquefaction in these sites. The model provides a viable tool to geotechnical engineers in assessing seismic condition in sites susceptible to liquefaction.     

Characteristics of the internal and external sources of the Mediterranean synoptic cyclones for the period 1956–2013

This paper investigates the main sources and features of the Mediterranean synoptic cyclones affecting the basin, using the cyclone tracks. The cyclones’ tracks are identified using sea level pressure (SLP) from the NCEP/NCAR reanalysis data for the period 1956–2013. The identified cyclones are classified into two categories: basin affected and basin non-affected. Most of the basin-affected (non-affected) cyclones are internal (external), i.e., generated inside (outside) the Mediterranean basin. This study reveals four (five) main sources of internal (external) cyclones. These four (five) main sources generated about 63.76% (57.25%) of the internal (external) cyclones. Seasonal analysis shows that most of the basin-affected internal (external) cyclones were generated in the winter (spring) season. The lowest number of cyclones were found in the summer. Moreover, the synoptic study of the atmospheric systems accompanied the highest- and lowest-generated years demonstrates that the deepening of the north Europe cyclones and the relative positions of Azores- and Siberian-high systems represent the important factors that influence the number of internal cyclones. Essential factors influencing the external cyclones are the strength of the maximum upper wind, Azores high, Siberian high, and orientations of their ridges.     

Optimisation of deep mixing technique by artificial neural network based on laboratory and field experiments

ABSTRACT

Ground improvement techniques are inevitable for weak soils that cannot endure the design load imposed by superstructures. Deep mixing technique (DMT) as one of these methods is promising and effective when a deep soil layer with low bearing capacity is encountered. Such deposits are quite common in the South-west of Iran where the studied site is located. In order to validate the influence of DMT on the enhancement of strength, both in-situ and laboratory tests were conducted. Afterwards, a parametric study was carried out to investigate the influence of key factors including cement content, water–cement ratio, curing time and plasticity index (PI) on the performance of DMT. In summary, a total of 192 different conditions were examined in this study by using two methods of 3D plotting and artificial neural networks (ANNs) as the optimisation tool. Results proved the importance of water–cement ratio as a key parameter in DMT. Based on the trained networks, ANN was revealed to give satisfactory predictions on the strength of an improved soil with different admixture conditions. More important, the optimisation made by ANN could determine the specific values for selected key admixture factors to reach a desired strength level with the coefficient of determination higher than 0.85.