• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.6
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• pp.526-534
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• 2022

The modular multilevel converter (MMC) has been widely applied to various industrial areas because of its various advantages and structural characteristics. Therefore, many methods for synthesizing the output voltage of MMC have been studied. Among these methods, phase-shifted pulse width modulation (PSPWM) is frequently used in MMC systems because it has diverse merits, such as excellent output qualities even with a small number of cells and uniform power distribution among cells. In this study, the total harmonic distortion (THD) of the output voltage is analyzed in accordance with the number of cells in one arm of a single-delta bridge cell MMC in order to compare PSPWM methods in terms of the THD of the output voltage. The physical characteristics of the triangle and sawtooth carrier waves used for the PSPWM and the mathematical modeling of output voltage are introduced. Then, the obtained results are verified through real-time simulation of a 1 MW single-delta bridge cell MMC system.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.443-456
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• 2022

An efficient and reasonable resource allocation strategy can greatly improve the service quality of Internet of Vehicles (IoV). However, most of the current allocation methods have overestimation problem, and it is difficult to provide high-performance IoV network services. To solve this problem, this paper proposes a network resource allocation strategy based on deep learning network model DDQN. Firstly, the method implements the refined modeling of IoV model, including communication model, user layer computing model, edge layer offloading model, mobile model, etc., similar to the actual complex IoV application scenario. Then, the DDQN network model is used to calculate and solve the mathematical model of resource allocation. By decoupling the selection of target Q value action and the calculation of target Q value, the phenomenon of overestimation is avoided. It can provide higher-quality network services and ensure superior computing and processing performance in actual complex scenarios. Finally, simulation results show that the proposed method can maintain the network delay within 65 ms and show excellent network performance in high concurrency and complex scenes with task data volume of 500 kbits.

• Journal of Ocean Engineering and Technology
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• v.37 no.4
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• pp.129-136
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• 2023

To evaluate manoeuvring performance of merchant ships, the mathematical modeling group (MMG) or computational fluid dynamics (CFD) simulations are used. However, it is difficult to use the MMG to evaluate the manoeuvring performance of fishing vessels, thus research using CFD simulations is necessary. Also, since the course-changing and turning ability is crucial in fishing operations, a rudder design suitable for fishing vessels is necessary. This study designs a rudder using National Advisory Committee for Aeronautics (NACA) airfoil sections and evaluates its manoeuvring performance. A CFD model is used to evaluate the manoeuvring performance of the fishing vessel, and turning and zig-zag tests are conducted. The effectiveness of using CFD simulations based on Reynolds averaged Navier-Stokes equations to assess the manoeuvring performance of fishing vessels was validated. No significant difference was found in the manoeuvring performance for hull forms and rudder designs for course-changing ability. However, the original hull form showed superior turning performance. Among five rudders with varying aspect ratios and shapes, the rudder with 5.5% aspect ratio had the best turning performance. Regarding the rudder design for fishing vessels, NACA airfoil was employed, and a rudder aspect ratio of 5.5% based on the immersed hull side area is recommended.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.4
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• pp.129-135
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• 1996

The area of gear vibration and noise, has recently been the focus of many studies. The proper kinematic and geometric design of gears, the mathematical modeling of gear system are essential for a good design. This work present a gear disign for reducing noise, and practical approaches used for machinery noise reduction slong with the summary of methods available for predicting gear noise in terms of the transmis- sion error, and show a comparative study with other methods. A new tooth profile modification is proposed for reducing vibration and noise of involute gears. The method is based on the use of cubic spline curves. The tooth profile is constrained to assume an involute shape during the loaded operation. Thus the new gear profile assures conjugate motion at all points along the line of action. The new profile is found to result in a more uniform static transmission error compared to not only standard involute profile but also modificated profile therby contributing to the improvement of vibration and noise characteristics of the gear.

• Steel and Composite Structures
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• v.47 no.5
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• pp.569-585
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• 2023

This paper proposes an efficient approach for the structural topology optimization of bi-directional functionally graded structures by incorporating popular radial basis functions (RBFs) into an implicit level set (ILS) method. Compared to traditional element density-based methods, a level set (LS) description of material boundaries produces a smoother boundary description of the design. The paper develops RBF implicit modeling with multiquadric (MQ) splines, thin-plate spline (TPS), exponential spline (ES), and Gaussians (GS) to define the ILS function with high accuracy and smoothness. The optimization problem is formulated by considering RBF-based nodal densities as design variables and minimizing the compliance objective function. A LS-RBF optimization method is proposed to transform a Hamilton-Jacobi partial differential equation (PDE) into a system of coupled non-linear ordinary differential equations (ODEs) over the entire design domain using a collocation formulation of the method of lines design variables. The paper presents detailed mathematical expressions for BiDFG beams topology optimization with two different material models: continuum functionally graded (CFG) and mechanical functionally graded (MFG). Several numerical examples are presented to verify the method's efficiency, reliability, and success in accuracy, convergence speed, and insensitivity to initial designs in the topology optimization of two-dimensional (2D) structures. Overall, the paper presents a novel and efficient approach to topology optimization that can handle bi-directional functionally graded structures with complex geometries.

• Advances in nano research
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• v.13 no.4
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• pp.351-368
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• 2022

Recently, promising structural technologies like multi-function, ultra-load bearing capacity and tailored structures have been put up for discussions. Finite Element (FE) modelling is probably the best-known option capable of treating these superior properties and multi-domain behavior structures. However, advanced materials such as Functionally Graded Material (FGM) and nanocomposites suffer from problems resulting from variable material properties, reinforcement aggregation and mesh generation. Motivated by these factors, this research proposes a unified shape function for FGM, nanocomposites, graded nanocomposites, in addition to traditional isotropic and orthotropic structural materials. It depends not only on element length but also on the beam's material properties and geometric characteristics. The systematic mathematical theory and FE formulations are based on the Timoshenko beam theory for beam structure. Furthermore, the introduced element achieves C1 degree of continuity. The model is proved to be convergent and free-off shear locking. Moreover, numerical results for static and free vibration analysis support the model accuracy and capabilities by validation with different references. The proposed technique overcomes the issue of continuous properties modelling of these promising materials without discarding older ones. Therefore, introduced benchmark improvements on the FE old concept could be extended to help the development of new software features to confront the rapid progress of structural materials.

• Steel and Composite Structures
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• v.44 no.6
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• pp.769-788
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• 2022

In this paper a mathematical model for the prediction of the fire resistance of slim-floor steel beams based on an Artificial Neural Network modeling procedure is presented. The artificial neural network models are trained and tested using an analytical database compiled for this purpose from analytical results based on FEM. The proposed model was selected as the optimum from a plethora of alternatives, employing different activation functions in the context of Artificial Neural Network technique. The performance of the developed model was compared against analytical results, employing several performance indices. It was found that the proposed model achieves remarkably improved predictions of the fire resistance of slim-floor steel beams. Moreover, based on the optimum developed AN model a closed-form equation for the estimation of fire resistance is derived, which can prove a useful tool for researchers and engineers, while at the same time can effectively support the teaching of this subject at an academic level.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.225-234
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• 2020

Reliability-based structural optimization usually requires designers or engineers model different designs manually, which is considered very time consuming and all possibilities cannot be fully explored. Otherwise, a lot of time are needed for designers or engineers to learn mathematical modeling and programming skills. Therefore, a framework that integrates generative design, structural simulation and reliability theory is proposed. With the proposed framework, various designs are generated based on a set of rules and parameters defined based on visual programming, and their structural performance are simulated by OpenSees. Then, reliability of each design is evaluated based on the simulation results, and an optimal design can be found. The proposed framework and prototype are tested in the optimization of a steel frame structure, and results illustrate that generative design based on visual programming is user friendly and different design possibilities can be explored in an efficient way. It is also reported that structural reliability can be assessed in an automatic way by integrating Dynamo and OpenSees. This research contributes to the body of knowledge by providing a novel framework for automatic reliability evaluation and structural optimization.

• Advances in concrete construction
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• v.16 no.4
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• pp.189-203
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• 2023

This study investigates the bending and stability properties of cylindrical constructions, with a focus on their use in the design and implementation of sporting equipment. The work focuses on a cylindrical construction resembling nanomotors, similar to components seen in sports equipment, using mathematical modeling based on high-order beam theory and nonlocal strain gradient theory. The analysis provides important insights into the dynamic behavior of these systems, revealing light on the impact of numerous factors such as rotational velocity, section change rate, and structural dimensions. The results show a relationship between angular velocity growth and section change rate, which leads to an increase in fundamental frequency values. Furthermore, the research emphasizes the effect of structural factors on dynamic deflection, giving critical information for increasing the stability and performance of sporting equipment. This study adds to the area of sports engineering by providing a more nuanced understanding of how cylindrical constructions react under diverse settings. The results will help to guide the design and manufacturing processes of sports equipment, assuring improved stability and performance for players across a wide range of sports.

• Structural Engineering and Mechanics
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• v.90 no.6
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• pp.601-610
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• 2024

Free vibration of layered conical shell frusta of thickness filled with fluid is investigated. The shell is made up of isotropic or specially orthotropic materials. Three types of thickness variations are considered, namely linear, exponential and sinusoidal along the radial direction of the conical shell structure. The equations of motion of the conical shell frusta are formulated using Love's first approximation theory along with the fluid interaction. Velocity potential and Bernoulli's equations have been applied for the expression of the pressure of the fluid. The fluid is assumed to be incompressible, inviscid and quiescent. The governing equations are modified by applying the separable form to the displacement functions and then it is obtained a system of coupled differential equations in terms of displacement functions. The displacement functions are approximated by cubic and quintics splines along with the boundary conditions to get generalized eigenvalue problem. The generalized eigenvalue problem is solved numerically for frequency parameters and then associated eigenvectors are calculated which are spline coefficients. The vibration of the shells with the effect of fluid is analyzed for finding the frequency parameters against the cone angle, length ratio, relative layer thickness, number of layers, stacking sequence, boundary conditions, linear, exponential and sinusoidal thickness variations and then results are presented in terms of tables and graphs.