KUFA JOURNAL OF ENGINEERING

In the last decades, wind turbines have been extensively studied due to the increasing demand for renewable energy sources. Based on a very strong background of operational experience with wind turbine generators of varying sizes and the development of high-performance power electronics, these most recent wind turbine generators offer the requisite and enhanced performance for their safe integration into the power systems. In the past, wind turbine generators were simply connected to distribution networks; however, current projects and wind turbine generators sizes require a direct connection to the transmission system level through a project-specific substation. Due to these developments, an integrated strategy is needed to maximize the allocation of control responsibilities between substation control and wind turbine control. Dual-Fed Induction Generator (DFIG) systems can be used in many ways to make complex solutions. In this paper, the design and control of DFIG systems are presented to improve WT operating performance in different cases. Given the strong association between converter control strategies and working conditions, it is important to better understand to demonstrates the importance of developing an appropriate modelling approach. The key findings are discussed, and recommendations are provided for future research in this paper.

Despite the industrial popularity of nylon 6 composites, their wear performance portrays a substantial knowledge gap on parametric importance. Consequently, this study optimizes and prioritizes the wear performance parameters of nylon 6/boron nitride composites using the Taguchi-Pareto and Taguchi-ABC methods based on 80-20 Pareto rule and the ABC analysis, using signal-to-noise ratios. From the literature information, the principal parameters considered are the %wt of reinforcement, normal load, sliding speed, and sliding distance, respectively. The results showed that the optimal parametric setting using the Taguchi-Pareto method is 4wt % of boron nitride Nanocomposite, 15 N of normal load, 100 rpm of sliding speed and 500m of sliding distance. The limitation of this study is the difficulty in deducing the most significant delta values or ranks through the parameters. This work drive towards more practically focused wear performance studies by industrial practitioners, showing critical optimization and prioritization procedures in a single study.

Generalized frequency division multiplexing (GFDM) is one of the candidate waveforms beyond 5G for wireless communication. Channel estimation is challenging in wireless transmission because of inherent interference. It is based on a pilot signal that uses Least Square (LS) and Normalized Least Mean Square (NLMS) to perform the estimation. This paper used the Artificial Neural Network (ANN) as a channel estimation method, considered a novel estimation process for the GFDM transceiver. The channel estimation based on ANN depends on the data set generated from LS estimation, which considers the proposed method is optimized to LS based on the backpropagation neural network. The ANN algorithm considered a fitness function to estimate the channel. Levenberg-Marquardt backpropagation (LM), Bayesian Regularization backpropagation (BR), and Scaled Conjugate Gradient backpropagation (SCG) training methods training by using the Matlab toolbox used to perform the estimation. BR training method gives the best performance than LS and other training methods at 22 neurons in hidden layers, which at 20dB give BER = 0.0369 that enhanced over LS by 0.08.

The Steel-fiber reinforced polymer (FRP) composite bar (SFCB) is a recently proposed bar, it has a steel inner and an exterior layer of FRP, and an adhesive resin to bond the two materials. The SFCB bar used in this paper was made by using a handmade technique; this technique includes a manufacturing procedure that was described in this paper. SFCBs were tested using the standard uniaxial tensile test (ASTM A370) to figure out their mechanical properties and stress-strain relationship and compare them with the normal steel bars. Moreover, the bonding test was conducted to comprehend the bonding performance of SFCB in the concrete and to compare it with the normal steel performance, the bonding test was conducted according to ACI 440.3R-12. The experimental results illustrated that the values of yielding and ultimate tensile strengths of SFCB were slightly less than that of the conventional steel with percentages of 4% for both, the modulus of elasticity values which were found theoretically in good agreement with the test results values, the behavior of SFCB stress-strain curve was slightly different than the conventional steel behavior, with a stable post-yield modulus. Also, the results showed that the SFCB/Steel (SFCB/Steel) ratio between the bond strength of SFCB and the bond strength of steel bar was approximately 0.86, which means that the SFCB had lesser bond strengths than the normal steel with a percentage of 14%, the results also showed that the SFCB had less slip than the steel bar with a percentage of 10%.

Recent years have seen a movement in research from monolithic to composite materials due to the worldwide need for low-cost, high-performance, and high-quality materials. Aluminum matrix composites are used extensively in structural applications and the aerospace and car industries, owing to their high strength-to-weight ratio, cheap cost, and excellent wear resistance. A simple and cost-effective process for producing composites is also critical for broadening their use. Using the inexpensive and commonly used stir-casting process, reinforcements including particle alumina, silicon carbide, graphite, fly ash, etc. may be readily integrated into the melt. In the present paper, the 7075 Aluminum alloy metal matrix composite, with varied Phosphogypsum (PG) contents (2, 5, and 10% wt.%) reinforced particles having 53-106 µm in size, have been created utilizing the stir casting process. The influence of Phosphogypsum particle content on the mechanical characteristics of Metal Matrix Composite has been investigated, and the results manifested that the material reinforcement significantly improved the BHN hardness, tensile strength, and wear. These enhancements were made possible by the regular distribution of Phosphogypsum and the refining of Al-7075 grains. The most significant improvement in BHN hardness (123), tensile strength (160 MPa), and wear (0.2032 gm) were recorded at 10% Phosphogypsum.