Journal Articles - Engineering - 2022
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PublicationFractional evolution equation with Cauchy data in Lp spaces( 2022)"In this paper, we consider the Cauchy problem for fractional evolution equations with the Caputo derivative. This problem is not well posed in the sense of Hadamard. There have been many results on this problem when data is noisy in L2 and Hs. However, there have not been any papers dealing with this problem with observed data in Lp with p = 2. We study three cases of source functions: homogeneous case, inhomogeneous case, and nonlinear case. For all of them, we use a truncation method to give an approximate solution to the problem. Under different assumptions on the smoothness of the exact solution, we get error estimates between the regularized solution and the exact solution in Lp. To our knowledge, Lp evaluations for the inverse problem are very limited. This work generalizes some recent results on this problem."
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PublicationCP-violating effects on gravitational waves in a complex singlet extension of the Standard Model with degenerate scalars( 2022)"We examine CP-violating effects on electroweak phase transition (EWPT) in the standard model with a complex singlet scalar focusing particularly on a scenario where additional scalars have masses close to 125 GeV. Such a high mass degeneracy makes collider signatures in the scenario standard model like, and current experimental data cannot distinguish them from the standard model predictions. We utilize a simplified scalar potential to understand impacts of CP violation on EWPT qualitatively. Then, one-loop effective potential with a thermal resummation is employed for full numerical evaluations. As a phenomenological consequence, gravitational waves from the first-order EWPT are also evaluated. We find that the strength of the first-order EWPT would get weaker as the CP-violating effect becomes larger. As a result, gravitational wave amplitudes are diminished by the size of the CP violation. Future gravitational wave experiments may shed light on CP violation in the singlet scalar sector as well as the experimental blind spot due to the high mass degeneracy"
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PublicationDamage assessment of suspension footbridge using vibration measurement data combined with a hybrid bee‑genetic algorithm( 2022)"Optimization algorithms (OAs) are a vital tool to deal with complex problems, and the improvement of OA is inseparable from practical strategies and mechanisms. Among the OAs, Bee Algorithm (BA) is an intelligent algorithm with a simple mechanism and easy implementation, in which effectiveness has been proven when handling optimization problems. Nevertheless, BA still has some fundamental drawbacks, which can hinder its effectiveness and accuracy. Therefore, this paper proposes a novel approach to tackle the shortcomings of BA by combining it with Genetic Algorithm (GA). The main intention is to combine the strengths of both optimization techniques, which are the exploitative search ability of BA and the robustness with the crossover and mutation capacity of GA. An investigation of a real-life suspension footbridge is considered to validate the effectiveness of the proposed method. A baseline Finite Element model of the bridge is constructed based on vibration measurement data and model updating, which is used to generate different hypothetical damage scenarios. The proposed HBGA is tested against BA, GA, and PSO to showcase its effectiveness in detecting damage for each scenario. The results show that the proposed algorithm is effective in dealing with the damage assessment problems of SHM."
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PublicationPrediction of resisting force and tensile load reduction in GFRP composite materials using Artificial Neural Network-Enhanced Jaya Algorithm( 2022)"This work presents an experimental and a numerical studies on the effect of the phenomenon of porosity on the mechanical properties of Glass Fiber Reinforced Polymer (GFRP). In a first part, material elaboration, as well as its characterization using a three-point bending test to extract the basic mechanical properties of the material, is considered. In a second part, a finite element model is created to simulate the problem of air bubbles broadly. Several cases of different shapes and sizes are simulated. The results show a significant effect on the reduction of load in both tensile and bending cases as the size of the bubbles increases. Furthermore, the second part includes the application of the Artificial Neural Network-Enhanced Jaya Algorithm (ANN-E JAYA) to predict the reduction of the tensile load as a function of different crack lengths obtained from an Extended Finite Element Method (XFEM) model. Next, to verify the accuracy of provided application , a comparison is made with two other applications such as Artificial Neural Network-Jaya Algorithm (ANN-JAYA) and Artificial Neural Network- Particle Swarm Optimization (ANN-PSO). The results of the three algorithms show good convergence, with a slight increase in accuracy for ANN-E JAYA. MATLAB code and data used in this article can be found at https:// github.com/Samir-Khatir/GFRP-ANN-E-JAYA.git."
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PublicationA current sensor fault diagnosis method based on phase angle shift technique applying to induction motor drive( 2022)An improved method using the phase angle shift characteristic of the sine wave is proposed to diagnose the fault states of the current sensors in an induction motor drive. The induction motor drive (IMD) system applied in this study uses the field-oriented control (FOC) loop with integrated two current sensors and a speed encoder to control the rotor speed. The space vectors created from the phase angle shift technique are compared to the estimated current for the fault diagnosis algorithm. Various types of current sensor failures are investigated by MATLAB/Simulink software to check the effectiveness of the proposed method. The simulation results have proved the performance of the proposed method in enhancing the reliability and stability of the IMD system.