Glass Fiber Reinforced Polymer (GFRP) beams have gained attention due to their promising mechanical properties and potential for structural applications. Combining GFRP core and encasing materials creates a composite beam with superior mechanical properties. This paper describes the testing encased GFRP beams as composite Reinforced Concrete (RC) beams under low-velocity impact load. Theoretical analysis was used with practical results to simulate the tested beams' behavior and predict the generated energies during the impact loading. The impact response was investigated using repeated drops of 42.5 kg falling mass from various heights. An analysis was performed using accelerometer readings to calculate the generalized inertial load. The integrated acceleration record and the measured hammer load vs. time data were utilized to determine the generalized bending load and fracture energy. Four forms of energy were calculated at the maximum load. The total energy was calculated and divided into two parts: The first part was gained by the beam's rotational kinetic energy, the bending energy in the specimen, and the elastic strain energy. The second part was the hammer's kinetic energy before striking the beam. The analytical results showed that the bending energy was less than its rotational kinetic energy for the encased GFRP beams and the reference specimens. In contrast, the encased steel beams had high bending energy due to the higher impact load and deflection. Strain energy recorded lower energy values for all specimens with higher bending energy. There is a good agreement between the tested and the calculated inertial and bending force for all beams. The ratio of inertia force to the total impact load for the encased GFRP and encased steel beams to the reference beam is about 9% and 5%, respectively.
This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi
The current research aims at: - Identifying the role played by the leadership in empowerment and organizational learning abilities and their reflection on the knowledge capital, and the extent to which these concepts can be applied effectively at Wasit University. The problem of research .... In a series of questions: The most important is that the dimensions leadership empowerment and distance learning organizational capacity correlation relationship and impact and significant statistical significance with the capital knowledge.
To understand the nature of the relationship and the impact between the variables, leadership was adopted by empowerment as the fir
... Show MoreThe purpose of this research is to a treatment the impact of Views outliers to the estimators of a distributed arrival and service to the theory of queues and estimate the distribution parameters depending on the robust estimators, and when he was outliers greatest impact in the process of estimating the both distributions mentioned parameters, it was necessary to use way to test that does these data contain abnormal values or not? it was used the method ( Tukey ) for this purpose and is of the most popular ways to discover the outliers , it shows that there are views abnormal (outliers ) in the estimators of each of the distributional arrival and service, which have a significant impact on the calculation of these estimato
... Show MoreThis study aimed to identify and describe one of the bacterial feeder nematode Acrobeloides varius Kim, Kim and Park, 2017 (Rhabditida, Cephalobidae), which was isolated from soil samples that were collected from Baghdad, central of Iraq, and was classified using both morphological and molecular criteria. All specimens of A. varius were cultured, identified and described using morphometric criteria. Selected specimens (Zah. IRQ3 OR994579.1 isolate) of this species were characterized by having the body length of the male ranging from (184.94 – 221.72 μm), the body length of the female ranging (507.38 – 521.92 μm) and the body length of the juvenile ranging from (355.53 – 490.35 μm). Selected specimens of this species were m
... Show MoreFor the design of a deep foundation, piles are presumed to transfer the axial and lateral loads into the ground. However, the effects of the combined loads are generally ignored in engineering practice since there are uncertainties to the precise definition of soil–pile interactions. Hence, for technical discussions of the soil–pile interactions due to dynamic loads, a three-dimensional finite element model was developed to evaluate the soil pile performance based on the 1 g shaking table test. The static loads consisted of 50% of the allowable vertical pile capacity and 50% of the allowable lateral pile capacity. The dynamic loads were taken from the recorded data of the Kobe e
Herein, we report designing a new Δ (delta‐shaped) proton sponge base of 4,12‐dihydrogen‐4,8,12‐triazatriangulene (compound
This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big
... Show MoreThis paper analyzes the effect of scaling-up model and acceleration history on seismic response of closed-ended pipe pile using a finite element modeling approach and the findings of 1 g shaking table tests of a pile embedded in dry and saturated soils. A number of scaling laws were used to create the numerical modeling according to the data obtained from 1 g shake table tests performed in the laboratory. The current study found that the behaviors of the scaled models, in general have similar trends. From numerical modeling on both the dry and saturated sands, the normalized lateral displacement, bending moment, and vertical displacement of piles with scale factors of 2 and 35 are less than those of the pile with a scale factor of 1 and the
... Show More