• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.351-358
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• 2005

Many methods have been developed and are in use for structural size optimization problems, In which the cross-sectional areas or sizing variables are usually assumed to be continuous. In most practical structural engineering design problems, however, the design variables are discrete. This paper proposes an efficient optimization method for structures with discrete-sized variables based on the harmony search (HS) meta-heuristic algorithm. The recently developed HS algorithm was conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary In this paper, a discrete search strategy using the HS algorithm is presented in detail and its effectiveness and robustness, as compared to current discrete optimization methods, are demonstrated through a standard truss example. The numerical results reveal that the proposed method is a powerful search and design optimization tool for structures with discrete-sized members, and may yield better solutions than those obtained using current method.

• Journal of the Society of Naval Architects of Korea
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• v.47 no.3
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• pp.430-437
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• 2010

In this paper, we develop a shape design optimization method for thermo-elastoplasticity problems that is applicable to the welding or thermal deformation problems of ship structures. Shell elements and a programming language APDL in a commercial finite element analysis code, ANSYS, are employed in the shape optimization. The point of developed method is to determine the design parameters such that the deformed shape after welding fits very well to a desired design. The geometric parameters of surfaces are selected as the design parameters. The modified method of feasible direction (MMFD) and finite difference sensitivity are used for the optimization algorithm. Two numerical examples demonstrate that the developed shape design method is applicable to existing hull structures and effective for the structural design of ships.

• Smart Structures and Systems
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• v.26 no.4
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• pp.533-544
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• 2020

Effective bridge maintenance reduces bridge operation costs and extends its service life. The possibility of storing bridge life-cycle data in a 3D parametric model of the bridge through Bridge Information Modeling (BrIM) provides new opportunities to enhance current practices of bridge maintenance management. This study develops a Decision Support System (DSS), namely BrDSS, which employs BrIM and an efficient optimization model for bridge maintenance planning. The BrIM model in BrDSS extracts basic data of elements required for the optimization process and visualizes the inspection data and the optimization results to the user to help in decision makings. In the optimization module of the DSS, the specifically formulated Genetic Algorithm (GA) eliminates the chances of producing infeasible solutions for faster convergence. The practicality of the presented DSS was explored by utilizing the DSS in the maintenance planning of a bridge under operation in the southwest of Iran.

• International Journal of Naval Architecture and Ocean Engineering
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• v.3 no.4
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• pp.254-262
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• 2011

This study aims to optimize an arrangement of ship compartments with knowledge-based systems. Though great attention has been shown to the optimization of hull forms in recent years, the study on arrangement design optimization has received relatively little attention. A ship is both an engineering system and a kind of assembly of many spaces. This means that, to design an arrangement of ship compartments, it is necessary to treat not only geometric data but also knowledge on topological relations between spaces and components of a ship. In this regard, we select a suitable knowledge representation scheme for describing ship compartments and their relations, and then develop a knowledge-based system using expert system shell. This new approach is applied to create design variations for optimization on an arrangement of a pressure hull of a submerged vehicle. Finally, we explicate how our approach improves the design process.

• International Journal of CAD/CAM
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• v.9 no.1
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• pp.1-16
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• 2010

When Deterministic Design Optimization (DDO) methods are used, deterministic optimum designs are frequently pushed to the design constraint boundary, leaving little or no room for tolerances (or uncertainties) in design, manufacture, and operating processes. In the Reliability-Based Design Optimization (RBDO) model for robust system design, the mean values of uncertain system variables are usually used as design variables, and the cost is optimized subject to prescribed probabilistic constraints as defined by a nonlinear mathematical programming problem. Therefore, a RBDO solution that reduces the structural weight in uncritical regions does not only provide an improved design but also a higher level of confidence in the design. In this work, we seek to improve the quality of RBDO processes using efficient optimization techniques with object of improving the resulting objective function and satisfying the required constraints. Our recent RBDO developments show its efficiency and applicability in this context. So we present some recent structural engineering applications demonstrate the efficiency of these developed RBDO methods.

• Journal of Power Electronics
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• v.19 no.4
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• pp.989-999
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• 2019

This paper proposes a fault-tolerant control strategy with finite control set model predictive control (FCS-MPC) based on hierarchical optimization for five-level H-bridge neutral-point-clamped (5L-HNPC) inverter-fed induction motor drives. Fault-tolerant operation is analyzed, and the fault-tolerant control algorithm is improved. Adopting FCS-MPC based on hierarchical optimization, where the voltage is used as the controlled objective, called model predictive voltage control (MPVC), the postfault controller is simplified as a two layer control. The first layer is the voltage jump limit, and the second layer is the voltage following control, which adopts the optimal control strategy to ensure the current following performance and uniqueness of the optimal solution. Finally, simulation and experimental results verify that 5L-HNPC inverter-fed induction motor drives have strong fault tolerant capability and that the FCS-MPVC based on hierarchical optimization is feasible.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.12
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• pp.1811-1820
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• 2010

Most components in the real world show nonlinear response. The nonlinearity may arise because of contact between the parts, nonlinear material, or large deformation of the components. Structural optimization considering nonlinearities is fairly expensive because sensitivity information is difficult to calculate. To overcome this difficulty, the equivalent load method was proposed for nonlinear response optimization. This method was originally developed for size and shape optimization. In this study, the equivalent load method is modified to perform topology optimization considering all kinds of nonlinearities. Equivalent load is defined as the load for linear analysis that generates the same response field as that for nonlinear analysis. A simple example demonstrates that results of the topology optimization using equivalent load are very similar to the numerical results. Nonlinear response topology optimization is performed with a practical example and the results are compared with those of conventional linear response topology optimization.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.4
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• pp.407-417
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• 2003

Enen though several GA-based optimization algorithms have been successfully applied to complex optimization problems in various engineering fields, GA-based optimization methods are computationally too expensive for practical use in the field of structural optimization, particularly for large- scale problems. Furthermore, a successful implementation of GA-based optimization algorithm requires a cumbersome and trial-and-error routine related to setting of parameters dependent on a optimization problem. Therefore, to overcome these disadvantages, a high-performance GA is developed in the form of distributed hybrid genetic algorithm for structural optimization on a cluster of personal computers. The distributed hybrid genetic algorithm proposed in this paper consist of a simple GA running on a master computer and multiple μ-GAs running on slave computers. The algorithm is implemented on a PC cluster and applied to the minimum weight design of steel structures. The results show that the computational time required for structural optimization process can be drastically reduced and the dependency on the parameters can be avoided.

• Structural Engineering and Mechanics
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• v.45 no.3
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• pp.391-410
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• 2013

A numerical method is presented here to detect and assess structural damages from changes in natural frequencies using Ant Colony Optimization (ACO) algorithm. It is possible to formulate the inverse problem in terms of optimization and then to utilize a solution technique employing ACO to assess the damage/damages of structures using natural frequencies. The laboratory tested data has been used to verify the proposed algorithm. The study indicates the potentiality of the developed code to solve a wide range of inverse identification problems in a systematic manner. The developed code is used to assess damages of beam like structures using a first few natural frequencies. The outcomes of the simulated results show that the developed method can detect and estimate the amount of damages with satisfactory precision.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1863-1871
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• 2016

This paper presents an application of fractional order controller for the control of multi input multi output twin rotor aerodynamic system. Dynamics of the considered system are highly nonlinear and there exists a significant cross-coupling between the horizontal and vertical axes (pitch & yaw). In this paper, a fractional order model of twin rotor aerodynamic system is identified using input output data from nonlinear system. Based upon identified fractional order model, a fractional order PID controller is designed to control the angular position of level bar of twin rotor aerodynamic system. The parameters of controller are tuned using Nelder-Mead optimization and compared with particle swarm optimization techniques. Simulation results on the nonlinear model show a significant improvement in the performance of fractional order PID controller as compared to a classical PID controller.