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Design and Additive Manufacturing of Nerve Guide Conduits Using Triple Periodic Minimal Surface Structures

Scaffold design is a key study area in tissue engineering. A scaffold is a three-dimensional framework that provides temporary support for the formation of new tissue before being implanted with isolated cells. The aim of tissue engineering scaffolds is to be colonized by cells. To ensure sufficient tissue growth, scaffolds need to transmit the necessary chemical and physical signals. The design of the scaffold determines its functionality. The design and manufacturing of tissue engineering scaffolds is a highly complex procedure. Scaffolds must have the necessary qualities to create an optimal architecture for cell growth, proliferation, and differentiation in order to form tissue. However, constrained structural designs and outdated manufacturing procedures impede the enhancement of scaffold qualities. To address these restrictions, researchers are merging computer-aided scaffold design with 3D printing processes during production. This method permits the design and manufacture of scaffolds with extremely intricate microstructures. The literature shows that computer-aided design combined with 3D printing technology is often utilized to design and manufacture nerve guide conduits for nerve regeneration. In this study, three different nerve guide conduit structures were designed and produced. Two of them are based on triple periodic minimal surfaces derived from Gyroid, schwarz. Although triple periodic minimal surfaces used as the basis for scaffold designs offer promising advantages for tissue engineering applications, limited information is available regarding their manufacturability. The designs created in this study, as well as their fabrication, will add to the literature on the manufacturability of triple periodic minimum surfaces.

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Regression Model Extractions of a T-Equivalent Circuit Modelling for Medium-Length Transmission Line Based-on the Parametric Simulation Approach

In medium-length power transmission line models, the difference between the end-of-line and head-of-line voltage can be calculated with classical mathematical expressions. However, since the line parameters are not linear, these calculations can be approximated according to certain assumptions. The parametric data analysis approach proposed in this study obtained a data set for different variations by changing the line length and line parameters (transmission line specific parameters such as resistance, inductance, and capacitance) with certain steps. Then, using this data set, a classification is made with machine learning. In addition, data analysis is carried out with the end-of-line voltage value graphs obtained with different line parameters and the proposed approach is verified by constructing a test simulation circuit of a three-phase 200 km length with 154 kV line voltage value. Thus, a parametric simulation study has been presented, especially in electrical engineering education. In addition, Support Vector Regression (SVR) and Decision Tree Regression (DTR) models in the field of machine learning were used to measure the consistency of the data set created for 5 pF, 8 pF and 10 pF capacity values. With the figures and numerical data presented comparatively, it is clearly seen that the Long Short-Term Memory (LSTM) algorithm produces more successful scores in all three categories. In this context, the prediction accuracy was between 97% and 98% with DTR, while the accuracy was between 81% and 85% with SVR. Thus, prediction results in the range of 98% - 99% were obtained in the LSTM model.

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A Cascade PID Controller Design with Cuckoo Optimization Algorithm (COA) and Input Shaping (IS)

From past to present, Proportional-Integral-Derivative (PID) controllers stand out as the most widely used types of controllers. Due to the high-performance requirements, experimentally determined controller coefficients necessitate the application of modern optimization techniques. In this study, Ziegler-Nichols, Chien-Hrones-Reswick, and Cohen-Coon methods, which allow parameter calculation through the open-loop system's step response method, were compared with the Cuckoo Optimization Algorithm for PID controllers designed for a brush-commutated DC motor with unknown parameters in the Matlab environment. The comparison was based on Integral of Absolute Error (IAE), Integral of Square Error (ISE), Integral of Time-weighted Absolute Error criterion. Similarly, the performance of the Cuckoo Algorithm was discussed in terms of stability margins and stability peaks. In this comparison, it was observed that the PID controller optimized with the Cuckoo Algorithm operated with high proportional and integral coefficients to minimize the cost function, resulting in overshoot in the system response. Input shaping, a commonly used method in open-loop control of both brushed and brushless DC motor systems, was integrated into the system to mitigate this overshoot. The hybrid controller achieved the best performance in terms of IAE, ISE and ITAE in the system response, with less overshoot compared to the other mentioned methods.

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Effects of the Shaft Speed on Stiffness and Damping Coefficients of Hydrodynamic Bearing-Shaft System under Variable Viscosity

The rotating shaft-hydrodynamic bearings systems operated with high speed and/or heavy load conditions expose serious rotor-dynamics instability problems due to characteristics of the supporting bearings. The stability and the dynamics of these systems, directly relate to the lubricant properties that are directly affect by the heat generation. In this study, the dynamic characteristics of a shaft-hydrodynamic journal bearing and its stability were investigated under variable viscosity. The equations of lubricant flow were derived by Dowson’s equation under variable viscosity, and the perturbation equations were obtained for 2 degrees-of-freedom system. The heat transfers between oil and the journal surface was modelled in a 3-dimensional energy equation, and the heat transfer on the journal structure was also modelled with heat conduction equation. An algorithm based on finite difference scheme with successive over relaxation method was developed to solve the theoretical models, simultaneously, and a serial simulation was performed to investigate the variations of the dynamic coefficients of the bearing-shaft system concerning the rotating speed for different radial clearance values. It was determined that the high speed increases the lubricant temperature, and so the static and dynamic performance characteristics decrease, moreover, this effect is more dominant for the smaller radial clearance.

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Use of Friction Pendulum System for Seismic Isolation of Museum Artifacts: Mathematical Modeling and Parametric Study

ABSTRACT
 Earthquakes seriously threaten precious artifacts in museums worldwide. Many historical pieces of inestimable importance that are considered the common heritage of humanity have been damaged by earthquakes. Robust measures must be put in place to protect museum artifacts from the perils associated with seismic risks. Seismic isolation devices like spherically shaped bearings are one of the best options to prevent seismic damage of museum artifacts thanks to achieving a long period under low weights. Therefore, the objective of this research is to assess the effectiveness of friction pendulum-type isolators, one of the spherically shaped bearings, in seismic isolation of museum artifacts and to identify the appropriate design parameters. In this study, a non-isolated single-degree-of-freedom model and a 2-degree-of-freedom model isolated with a single friction pendulum bearing inside a building were established for a museum artifact. A parametric study was conducted using the root mean square and the maximum accelerations and displacements of the isolated mass at different values of friction coefficient and effective radius of curvature, as well as the maximum displacement of the friction pendulum system. Afterward, the non-isolated and isolated mass responses were compared in the time domain based on selected parameters obtained from the parametric study. The behavior of the isolator was analyzed, and its effectiveness was evaluated.

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Finite Elements Analysis and Topology Optimization of Parking Brake Lever and Ratchet

Topology optimization is known as one of the basic categories of structural optimization. Topology optimization is received increasing attention in many engineering disciplines. Topology optimization contributes to minimizing emissions and environmental effects by increasing material utilization efficiency and manufacturing sustainability. The mechanical parking brake is still used in many vehicles. This study aims to contribute to the reduction in vehicle weight by applying topology optimization. In addition, it also purposes to promote sustainability in manufacturing by reducing material usage and energy consumption. A CAD model was created by considering the existing mechanism element dimensions. The parking brake lever mechanism component was evaluated using topology optimization and finite element analysis methods. Static analyses were performed using a finite element analysis program. The results of this analysis were used as input data for topology optimization. In the topology optimization, the response constraint mass was increased by 5 increments from 50% to 95%. As a result, the maximum equivalent (von Mises) stress for the parking brake lever is 230,29 MPa, and for the ratchet is 11,559 MPa. The maximum total deformation value for the brake lever is 0,95853 mm and for the ratchet is 0,0079482 mm. The parking brake lever mass decreased by 18,48% from 0.27751 kg to 0.22622 kg. The ratchet mass decreased from 0.095042 kg to 0.061911 kg by 34.85%.

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