Recent years have witnessed an increase in the use of composite coatings for numerous applications, including aerospace, aircraft, and maritime vessels. These materials owe this popularity surge to the superior strength, weight, stiffness, and electrical insulation they exhibit over conventional substances, such as metals. The growing demand for such materials is accompanied by the inevitable need for fast, accurate, and affordable nondestructive testing techniques to reveal any possible defects within the coatings or any defects under coating. However, typical nondestructive testing (NDT) techniques such as ultrasonic testing (UT), infrared thermography (IRT), eddy current testing (ECT), and laser shearography (LS) have failed to provide successful results when inspecting composite coatings. Consequently, microwave NDT techniques have emerged to compensate for the shortcomings of traditional NDT approaches. Numerous microwave NDT methods have been reported for composite coatings inspection. Although existing microwave NDT methods have shown successful inspection of composite coatings, they often face several challenges, such as low spatial image quality and extensive data interpretation. Nevertheless, many of these limitations can be addressed by utilizing microwave NDT techniques with modern technologies such as soft computing. Artificially intelligent techniques have greatly enhanced the reliability and accuracy of microwave NDT techniques. This paper reviews various traditional NDT techniques and their limitations in inspecting composite coatings. In addition, the article includes a detailed review of several microwave NDT techniques and their benefits in evaluating composite coatings. The paper also highlights the advantages of using the recently reported microwave NDT approaches employing artificial intelligence approaches. This review demonstrates that microwave NDT techniques in conjunction with artificial intelligence approaches have excellent prospects for further enhancing composite coatings inspection and assessment efficiency. The review aimed to provide the reader with a comprehensive overview of most NDT techniques used for composite materials alongside their most salient features.
Most of drinking water consuming all over the world has been treated at the water treatment plant (WTP) where raw water is abstracted from reservoirs and rivers. The turbidity removal efficiency is very important to supply safe drinking water. This study is focusing on the use of multiple linear regression (MLR) and artificial neural network (ANN) models to predict the turbidity removal efficiency of Al-Wahda WTP in Baghdad city. The measured physico-chemical parameters were used to determine their effect on turbidity removal efficiency in various processes. The suitable formulation of the ANN model is examined throughout many preparations, trials, and steps of evaluation. The predict
This study has aimed to measure the relationship between the skills required for the labor market and the employment of graduates of community colleges at King Khalid University. For gathering the required data, a questionnaire has been designed and distributed to the faculty members of community colleges at King Khalid University in a random sample method. The chosen sample size has covered (123) individuals. Questionnaire forms have been distributed and retrieved from (117) participants. Therefore, the estimated response has reached 95 % of the total sample size. The results of the study have shown that there is not any significant relationship between the skills which the graduates acquire and the requirements of employmen
... Show MoreCopper (I) complex containing folic acid ligand was prepared and characterized on the basis of metal analyses, UV-VIS, FTIR spectroscopies and magnetic susceptibility. The density functional theory (DFT) as molecular modeling calculations was used to determine the donor atoms of folic acid ligand which appear clearly at oxygen atoms binding to hydrogen. Detection of donation sights is supported by theoretical parameters such as geometry, mulliken population, mulliken charge and HOMO-LUMO gap obtained by DFT calculations.