Groundwater in Assiut governorate has a particular importance where it is the second source for fresh water used for drinking, agricultural, domestic, and industrial purposes. Three hundred and thirty five wells were available during the period 2006 to 2009, and were subjected to analysis for chemicalcharacteristics. These data has been used to conclude two main results; the first one is preliminary evaluation of suitability of groundwater for drinking and irrigation purposes by comparing those parameters with world health organization (WHO) standards and Egyptian standards. the second one is building the correlation matrix between the groundwater quality parameters which are major ions, EC, TDS, SAR, Na%, RSC, TH, KI, PI, MH, CAI, and C.R. with comparing chemical parameters with WHO (1996) and Egyptian standards for drinking, it shows that concentrations of Na+, K+, Ca2+, Mg2+, Hco3-, SO42−, and Fe are lower than the permissible limits in 80% of well s. Groundwater wells were classified according TDS as about 93 % of wells have TDS less than 3000 mg/l, thus groundwater is suitable for irrigation.

This paper presents a Genetic Algorithm (GA)- based method to determine the location and size of DG sources in distribution systems using single DG placement algorithm for determining the locations at first. Then, the GA is utilized to determine the global sizes of DG sources which minimize single- or multi-objective function related to these systems. The influence of active- and reactive-power injection on the sizing and placement of DG sources is investigated. The predictions of the proposed method as regards the sizing and placement of DG sources are compared with those obtained before using particle swarm optimization at steady weather conditions.

This paper presents a Genetic Algorithm (GA)- based method to determine the location and size of DG sources in distribution systems using single DG placement algorithm for determining the locations at first. Then, the GA is utilized to determine the global sizes of DG sources which minimize single- or multi-objective function related to these systems. The influence of active- and reactive-power injection on the sizing and placement of DG sources is investigated. The predictions of the proposed method as regards the sizing and placement of DG sources are compared with those obtained before using particle swarm optimization at steady weather conditions.

This paper presents a Genetic Algorithm (GA)- based method to determine the location and size of DG sources in distribution systems using single DG placement algorithm for determining the locations at first. Then, the GA is utilized to determine the global sizes of DG sources which minimize single- or multi-objective function related to these systems. The influence of active- and reactive-power injection on the sizing and placement of DG sources is investigated. The predictions of the proposed method as regards the sizing and placement of DG sources are compared with those obtained before using particle swarm optimization at steady weather conditions.

This paper presents a Genetic Algorithm (GA)- based method to determine the location and size of DG sources in distribution systems using single DG placement algorithm for determining the locations at first. Then, the GA is utilized to determine the global sizes of DG sources which minimize single- or multi-objective function related to these systems. The influence of active- and reactive-power injection on the sizing and placement of DG sources is investigated. The predictions of the proposed method as regards the sizing and placement of DG sources are compared with those obtained before using particle swarm optimization at steady weather conditions.

This paper presents a Genetic Algorithm (GA)- based method to determine the location and size of DG sources in distribution systems using single DG placement algorithm for determining the locations at first. Then, the GA is utilized to determine the global sizes of DG sources which minimize single- or multi-objective function related to these systems. The influence of active- and reactive-power injection on the sizing and placement of DG sources is investigated. The predictions of the proposed method as regards the sizing and placement of DG sources are compared with those obtained before using particle swarm optimization at steady weather conditions.

The main target of this research is to allow the DSTATCOM using 6-pulse inverter to participate effectively in mitigating voltage sags. The basic idea of the voltage sag reduction using a D-STATCOM, which is connected in shunt with the system, is to dynamically inject a reactive power into the utility grid. In this study, 6-pulse inverter operation is conducted using the sinusoidal PWM. The voltage magnitude as well as phase angle are taken as a base to convert the DC link voltage (Vdc) on the capacitor to a voltage source using the developed D- STATCOM. This method offers structural simplicity and less calculation complexity by using Power System Computer Aided Design (PSCAD) software. Simulation results indicate that this method is effective and D-STATCOM has good performance and capable of mitigating voltage sag as well as improving power quality of a distribution system. Static and dynamic loads are used to deem the effectiveness of the developed DSTATCOM.

The main target of this research is to allow the DSTATCOM using 6-pulse inverter to participate effectively in mitigating voltage sags. The basic idea of the voltage sag reduction using a D-STATCOM, which is connected in shunt with the system, is to dynamically inject a reactive power into the utility grid. In this study, 6-pulse inverter operation is conducted using the sinusoidal PWM. The voltage magnitude as well as phase angle are taken as a base to convert the DC link voltage (Vdc) on the capacitor to a voltage source using the developed D- STATCOM. This method offers structural simplicity and less calculation complexity by using Power System Computer Aided Design (PSCAD) software. Simulation results indicate that this method is effective and D-STATCOM has good performance and capable of mitigating voltage sag as well as improving power quality of a distribution system. Static and dynamic loads are used to deem the effectiveness of the developed DSTATCOM.

We investigate the L2 -stabilization of linear systems using output feedback event-triggered controllers. In particular, we are interested in the scenario where the plant output and the control input are transmitted to the controller and to the actuators, respectively, over two different digital channels, which have their own sampling rule. The plant dynamics is affected by external disturbances and the output measurement and the control input are corrupted by noises. We present a co-design procedure to simultaneously synthesize dynamic output feedback laws and event-triggering conditions such that the closed-loop system is L2 -stable with a given upper-bound on the L2 -gain. The required conditions are formulated in terms of the feasibility of linear matrix inequalities (LMIs). Then, we exploit these LMIs to maximize the guaranteed minimum time between two transmissions of the plant output and/or of the control input. We also present a heuristic method to reduce the amount of transmissions for each channel. The developed technique encompasses time-driven (and so periodic) sampling as a particular case and the result is also new in this context. The effectiveness of the proposed methods is illustrated on a numerical example.

In this study, 13 typical wide-flange steel columns, each carrying an axial load equal to 25% of its axial capacity, are field tested using live explosives, involving charge size of 50 to 250 kg of ammonium nitrate/fuel oil (ANFO) and ground stand-off distance of 7.0 to 10.3 m. The reflected pressure time histories, time-dependent displacements, accelerations, and strains of the columns are measured, and their postblast damages and failure modes are reported. Maximum deformations, vibration periods, strain-rate, and contributing modes in the dynamic response of the columns are compared to those of companion steel beams (without axial load) tested in the same setup. Results show that columns that exhibit elastic response, due to the elongation of the column vibration period caused by the axial load, the lateral deformation caused by blast load is reduced rather than magnified by the axial load. The axial-bending interaction, or P-δ effect, may be neglected for steel columns with axial load up to 25% of their axial capacity, provided the column response remains within the elastic range—but if it crosses into the plastic range, the interaction cannot be ignored.