The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-201

This work presents the modeling of the electrical response of monocrystalline photovoltaic module by using five parameters model based on manufacture data-sheet of a solar module that measured in stander test conditions (STC) at radiation 1000W/m² and cell temperature 25 . The model takes into account the series and parallel (shunt) resistance of the module. This paper considers the details of Matlab modeling of the solar module by a developed Simulink model using the basic equations, the first approach was to estimate the parameters: photocurrent I_ph, saturation current I_s, shunt resistance R_sh, series resistance R_s, ideality factor A at stander test condition (STC) by an ite

This research work as an attempt has been made to find robust estimations for Hotelling-T² test when the data is from amultivariate normal distribution and the sample of the multivariate contain outliers also this research gives an easily high breakdown point robust consistent estimators of multivariate location and dispersion for multivariate analysis by using two types of robust estimators, of these methods are minimum covariance determinant estimator and reweighted minimum covariance determinant estimator.