Carbon-fiber-reinforced polymer (CFRP) is widely acknowledged as a leading advanced material structure, offering superior properties compared to traditional materials, and has found diverse applications in several industrial sectors, such as that of automobiles, aircrafts, and power plants. However, the production of CFRP composites is prone to fabrication problems, leading to structural defects arising from cycling and aging processes. Identifying these defects at an early stage is crucial to prevent service issues that could result in catastrophic failures. Hence, routine inspection and maintenance are crucial to prevent system collapse. To achieve this objective, conventional nondestructive testing (NDT) methods are utilized to i

One of the most severe problems with flexible asphalt pavements is permanent deformation in the form of rutting. Accordingly, the practice of adding fiber elements to asphalt mix to improve performance under dynamic loading has grown significantly in order to prevent rutting distress and ensure a safe and long-lasting road surface. This paper explores the effects of a combination of ceramic fiber (CF), a low-cost, easily available mineral fiber, and thermal insulator fiber reinforced to enhance the Marshall properties and increase the rutting resistance of asphalt mixes at high temperatures. Asphalt mixtures with 0%, 0.75%, 1.5%, and 2.25% CF content were prepared, and Marshall stability and wheel tracking tests were employed to stu

The Halabja earthquake occurred on 12/11/2017 in Iraq, with a magnitude of 7.3 Mw, which happened in the Iraqi-Iranian borders. This earthquake killed and injured many people in the Kurdish region in the north of the country. There is no natural disaster more dangerous than earthquake, especially it occurs without warning, great attention must be paid to the impact of earthquakes on the soil and preparing for a wave of earthquakes. Numerical modeling using specific elements is considered a powerful tool to investigate the required behavior of structures in Geotechnical engineering, and the main objective of this is to assess the response of the Al-Wand dam to the Halabja earthquake, as this dam is located in an area that has been su

Two common iron oxide-bearing wastes—a drinking water treatment residual and a passive mine water treatment sludge (MWTS)—were utilised with and without modification as media in microcosm experiments to treat artificial benzene, toluene, ethylbenzene, and xylene (BTEX)-contaminated wastewater. In all cases, the removal of BTEX was observed over the 160-day experiments, with benzene being the most recalcitrant. The solubilisation of iron was observed, which, alongside the syntropic relationship between the methanogens and firmicutes, allowed several anaerobic processes to occur, including iron reduction in concert with the biodegradation of BTEX. Nitrogen sparging prior to microcosm establishment, compared to aeration, was seen t

Zinc Oxide thin film of 2 μm thickness has been grown on glass substrate by pulsed laser deposition technique at substrate temperature of 500 oC under the vacuum pressure of 8×10-2 mbar. The optical properties concerning the absorption, and transmission spectra were studied for the prepared thin film. From the transmission spectra, the optical gap and linear refractive index of the ZnO thin film was determined. The structure of the ZnO thin film was tested with X-Ray diffraction and it was formed to be a polycrystalline with many peaks.

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

organic chmistry