Upper Cretaceous carbonate hosted zinc–lead–barite deposits in Northern Thrust Zone, northern Iraq: petrography and geochemistry

Zinc–lead–barite deposits located in Lefan and Lower Banik localities of about 25 km northeast of Zakho City, Northern Iraq consist of a group of strata-bound sulfides hosted in Upper Cretaceous (Upper Campanian–Maastrichtian) dolomitic limestone. Carbonate-hosted ores contain 3.77% Zn, 2% Pb, and 5% Fe, while in lower Banik, they contain 1.5% Zn, 0.37% Pb, and 1.4% Fe. Diagenetic processes, such as dolomitization and recrystalization in addition to the type of microfacies, provided appropriate physical and chemical conditions that permitted the passage of ore-bearing fluids and participated in precipitation and ore localization. These deposits are precipitated in a platform and developed within the Foreland Thrust Belt. Ore precipitated as infill of intergranular dolomite porosity with replaced dolomite and rudist shells forming disseminated crystals that occupy intergranular pore spaces around dolomite and calcite and as infill of dissolution spaces and fractures.     

Integrated GIS and remote sensing for mapping groundwater potentiality in the Tulul al Ashaqif,Northeast Jordan

Jordan with its limited water resources is currently classified as one of the four water-poor countries worldwide. This study was initiated to explore groundwater potential areas in Tulul al Ashaqif area, Jordan, by integrating remote sensing, geographic information systems (GIS), and multicriteria evaluation techniques. Eight thematic layers were built in a GIS and assigned using multicriteria evaluation techniques suitable weights and ratings regarding their relative contribution in groundwater occurrence. These layers include lithology, geomorphology, lineaments density, drainage density, soil texture, rainfall, elevation, and slope. The final groundwater potentiality map generated by GIS consists of five groundwater potentiality classes: very high, high, moderate, low, and very low. The map showed that the study area is generally of moderate groundwater potentiality (76.35 %). The very high and high potential classes occupy 2.2 and 12.75 % of study area, respectively. The validity of results of this GIS-based model was carried out by superimposing existing hand dug wells on the final map. The single parameter sensitivity test was conducted to assess the influence of the assigned weights on the groundwater potential model, and new effective weights were derived. The resulted groundwater potentiality map showed that the area occupied by each of the groundwater potentiality classes has changed. However, the study area remains generally of moderate groundwater potentiality (70.93 % of the study area). The area occupied by the very high and high potential classes comprises 4.53 and 18.56 % of the study area, respectively.     

Linking the explicit probability of entrainment of instrumented particles to flow hydrodynamics

Obtaining a better understanding of the underlying dynamics of the interaction of turbulent flows and the bed surface that contains them, leading to the transport of coarse particles in fluvial, coastal, and aeolian environments, is considered as one of the fundamental objectives and the most complex problems in Earth surface dynamics and engineering. Recent technological advancements have made it possible to directly assess sediment entrainment rather than monitoring surrogate flow metrics, which could be related indirectly to sediment entrainment. In this work, a novel and low-cost instrumented particle, 7 cm in diameter, is used to directly assess the incipient entrainment of a coarse particle resting on a bed surface. The particle has inertial measurement units (IMUs) embedded within its waterproof shell, enabling it to track the particle's motions and quantify its inertial dynamics. The sensors of the instrumented particle are calibrated using simple and easy-to-validate theoretically physical motions to estimate the uncertainties in their readings, which are reduced using an inertial sensor fusion process. A series of well-designed laboratory flume incipient motion experiments are performed to assess the entrainment of the instrumented particle for a range of flowrates near the threshold of motion. The readings of the instrumented particle are used to derive metrics that are related to the probability of its incipient entrainment. The flow velocity measurements are obtained for the experiment runs, and the derived metrics are explicitly linked to the flow hydrodynamics responsible for the entrainment. The framework presented in this work can be used for a range of similar applications of low-cost instrumented particles, spanning the interface of sensing and instrumentation in engineering (i.e., infrastructure and environmental monitoring) and geosciences (e.g., habitat assessment).     

Experimental study of identification and control of structures using neural network. Part 2: control

Experimental verifications of a recently developed active structural control method using neural networks are presented in this paper. The experiments were performed on the earthquake simulator at the University of Illinois at Urbana—Champaign. The test specimen was a 1/4 scale model of a three-storey building. The control system consisted of a tendon/pulley system controlled by a single hydraulic actuator at the base. The control mechanism was implemented through four active pre-tensioned tendons connected to the hydraulic actuator at the first floor. The structure modelling and system identification has been presented in a companion paper. (Earthquake Engng. Struct. Dyn. 28 , 995–1018 (1999)). This paper presents the controller design and implementation. Three controllers were developed and designed: two neurocontrollers, one with a single sensor feedback and the other with three sensor feedback, and one optimal controller with acceleration feedback. The experimental design of the neurocontrollers is accomplished in three steps: system identification, multiple emulator neural networks training and finally the neurocontrollers training with the aid of multiple emulator neural networks. The effectiveness of both neurocontrollers are demonstrated from experimental results. The robustness and the relative stability are presented and discussed. The experimental results of the optimal controller performance is presented and assessed. Comparison between the optimal controller and neurocontrollers is presented and discussed. Copyright © 1999 John Wiley & Sons, Ltd.     

Semi‐active neuro‐control for base‐isolation system using magnetorheological (MR) dampers

Vibration mitigation using smart, reliable and cost‐effective mechanisms that requires small activation power is the primary objective of this paper. A semi‐active controller‐based neural network for base‐isolation structure equipped with a magnetorheological (MR) damper is presented and evaluated. An inverse neural network model (INV‐MR) is constructed to replicate the inverse dynamics of the MR damper. Next, linear quadratic Gaussian (LQG) controller is designed to produce the optimal control force. Thereafter, the LQG controller and the INV‐MR models are linked to control the structure. The coupled LQG and INV‐MR system was used to train a semi‐active neuro‐controller, designated as SA‐NC, which produces the necessary control voltage that actuates the MR damper. To evaluate the proposed method, the SA‐NC is compared to passive lead–rubber bearing isolation systems (LRBs). Results revealed that the SA‐NC was quite effective in seismic response reduction for wide range of motions from moderate to severe seismic events compared to the passive systems. In addition, the semi‐active MR damper enjoys many desirable features, such as its inherent stability, practicality and small power requirements. The effectiveness of the SA‐NC is illustrated and verified using simulated response of a six‐degree‐of‐freedom model of a base‐isolated building excited by several historical earthquake records. Copyright © 2006 John Wiley & Sons, Ltd.