Hashemite University

About: Hashemite University is a education organization based out in Zarqa, Jordan. It is known for research contribution in the topics: Population & Metric space. The organization has 1761 authors who have published 4342 publications receiving 72235 citations.

Performance trends and deteriorations of lignocellulosic grape fiber/polyethylene biocomposites under harsh environment for enhanced sustainable bio-materials

Abstract: This work aimed to make novel lignocellulosic based composites utilizing lignocellulosic grape fiber waste with polyethylene matrix for the first time. The purpose was also extended to systematically investigate their mechanical performance trends and deteriorations under harsh environments that include the presence of wet conditions, alkaline and sulfate ash chemicals. This work was also capable of determining the most appropriate and optimized reinforcing conditions of such novel composites to evidently demonstrate their failure trends under various circumstances. Effects of treatments on the overall mechanical performance trends and deteriorations were revealed. Results have demonstrated the efficiency of utilizing the lignocellulosic grape fibers in bio-composites. The tensile strength property was dramatically enhanced for various dry and treated composites. The best strengths were achieved by the 30 wt% dry fiber case and the 20 wt% water soaked one. The modulus of elasticity for the oil-soaked fibers increased with fiber content. Its maximum was at 40 wt % fiber content with a value of 292.06 MPa. Break property on the other hand, favored dry fibers. Morphological characteristics of the prepared lignocellulosic grape fiber/polyethylene composites were clarified using a scanning electron microscope.

Optimal placement of FACTS devices and power-flow solutions for a power network system integrated with stochastic renewable energy resources using new metaheuristic optimization techniques

Abstract: Flexible AC transmission systems (FACTS) and optimal power-flow (OPF) solutions play an important role in solving power operation problems. The volatile nature of the power generation profiles from renewable energy sources, solar and wind systems, and determining the optimal locations and sizes of FACTS devices increase the complexity of the OPF problems in modern power network models, such as transmission power loss, power generation operation cost and voltage deviation, as a highly nonlinear-nonconvex optimization problem. Therefore, this article introduces and employs four new independent, reliable and efficient optimization algorithms inspired by nature and biological nature, namely: Slime Mould Algorithm (SMA), Artificial Ecosystem-based Optimization (AEO), Marine Predators Algorithm (MPA) and Jellyfish Search (JS), for solving both multi- and single-OPF objective problems for a power network incorporating FACTS and stochastic renewable energy sources. The proposed new metaheuristic optimization techniques are compared to the common and available alternatives in the literature, Particle Swarm Optimization (PSO), Moth Flame Optimization (MFO) and Grey Wolf Optimizer (GWO), using IEEE 30-bus test system. To consider and address the challenges of the OPF in modern power network models, the proposed optimization techniques tested under different operation cases such as an increasing in the load, with and without FCTAS and renewable energy sources, different renewable energy sources locations on the network. The result showed that the MPA, SMA, JS and AEO algorithms are more effective solvers for the OPF problems cases compared to the PSO, GWO and MFO algorithms. For example, the AEO obtained 0.0844 p.u. in case of minimizing the voltage deviation compared to 0.1155 p.u. for PSO, which means that the AEO algorithm improved the voltage deviation term by 27% compared to the PSO algorithm.