• Journal of Power System Engineering
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• v.7 no.4
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• pp.67-73
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• 2003

The entry guidance design involves trajectory optimization and generation of a drag acceleration profile as the satisfaction of trajectory conditions during the entry flight. The reference trajectory is parameterized and optimized as piecewise linear functions of the velocity. A regularization technique is employed to achieve desired properties of the optimal drag profile. The regularized problem has smoothness properties and the minimization of performance index then prevents the drag acceleration from varying too fast, thus eliminating discontinuities. This paper shows the trajectory control using the simple control law as well as the information of reference drag acceleration.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.1
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• pp.35-42
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• 2008

By the reason of increased demand of high productivity and quality, the manufacturer have an effort in many directions of a machine tool industries. Among there, we proposed method of decreasing displacement in MC(machining center). In other words, Quality related with vibration of a tool cutting products. For decreasing it, improved by optimizing a shape of the column-part and acceleration curves of motors. In this paper we could find design factors has much influence on decreasing the displacement using the DOE(Design of Experiments) and optimized the level of the factors using $ADAMS^{(R)}$ and $MINITAB.^{(R)}$ And we suggest optimized a acceleration curve using $Matlab^{(R)}$.

• Interaction and multiscale mechanics
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• v.6 no.4
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• pp.339-356
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• 2013

This paper investigates the optimized parameters of Tuned Mass Dampers (TMDs) for vibration control of high-rise structures including Soil Structure Interaction (SSI). The Artificial Bee Colony (ABC) method is employed for optimization. The TMD Mass, damping coefficient and spring stiffness are assumed as the design variables of the controller; and the objective is set as the reduction of both the maximum displacement and acceleration of the building. The time domain analysis based on Newmark method is employed to obtain the displacement, velocity and acceleration of different stories and TMD in response to 6 types of far field earthquakes. The optimized mass, frequency and damping ratio are then formulated for different soil types; and employed for the design of TMD for the 40 and 15 story buildings and 10 different earthquakes, and well results are achieved. This study leads the researchers to the better understanding and designing of TMDs as passive controllers for the mitigation of earthquake oscillations.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.4
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• pp.1-8
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• 1998

In order to solve the conflict problem between the ride comfort and the road holding, the optimal design of shock absorber that minimizes the r.m.s. of sprung mass vertical acceleration and pitch rate with the understeer characteristics constraints in the high speed stability is proposed. The design of experiments and the nonlinear optimization algorithm are used together to obtain the optimal design of shock absorber. The second order regression models of the input variables(front and rear damping coefficients) and the output variables (ride comfort index and road holding one) are obtained by the central composite design in the design of experiments. Then the optimal design of shock absorber can be systematically adjusted with applying the nonlinear optimization algorithm to the obtained second order regression model. The frequency response analysis of sprung mass acceleration and pitch rate shows the effectiveness of the proposed optimal design of shock absorber in the sprung mass resonance range with the understeer characteristics constraints.

• Structural Engineering and Mechanics
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• v.86 no.5
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• pp.647-661
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• 2023

It is recognized that the installation of energy dissipation devices, such as the tuned mass damper (TMD), decreases the dynamic response of structures, however, the best parameters of each device persist hard to determine. Unlike many works that perform only a deterministic optimization, this work proposes a complete methodology to minimize the dynamic response of footbridges by optimizing the parameters of multiple tuned mass dampers (MTMD) taking into account uncertainties present in the parameters of the structure and also of the human excitation. For application purposes, a steel footbridge, based on a real structure, is studied. Three different scenarios for the MTMD are simulated. The proposed robust optimization problem is solved via the Circle-Inspired Optimization Algorithm (CIOA), a novel and efficient metaheuristic algorithm recently developed by the authors. The objective function is to minimize the mean maximum vertical displacement of the footbridge, whereas the design variables are the stiffness and damping constants of the MTMD. The results showed the excellent capacity of the proposed methodology, reducing the mean maximum vertical displacement by more than 36% and in a computational time about 9% less than using a classical genetic algorithm. The results obtained by the proposed methodology are also compared with results obtained through traditional TMD design methods, showing again the best performance of the proposed optimization method. Finally, an analysis of the maximum vertical acceleration showed a reduction of more than 91% for the three scenarios, leading the footbridge to acceleration values below the recommended comfort limits. Hence, the proposed methodology could be employed to optimize MTMD, improving the design of footbridges.

• Structural Engineering and Mechanics
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• v.67 no.3
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• pp.245-254
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• 2018

In this paper, a Cloud Model based Fruit Fly Optimization Algorithm (CMFOA) is presented for structural damage identification, which is a global optimization algorithm inspired by the foraging behavior of fruit fly swarm. It is assumed that damage only leads to the decrease in elementary stiffness. The differences on time-domain structural acceleration data are used to construct the objective function, which transforms the damaged identification problem of a structure into an optimization problem. The effectiveness, efficiency and accuracy of the CMFOA are demonstrated by two different numerical simulation structures, including a simply supported beam and a cantilevered plate. Numerical results show that the CMFOA has a better capacity for structural damage identification than the basic Fruit Fly Optimization Algorithm (FOA) and the CMFOA is not sensitive to measurement noise.

• Transactions of the Society of Information Storage Systems
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• v.1 no.2
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• pp.161-168
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• 2005

This paper optimizes the optical flying head(OFH) suspension using the integrated optimization frame, which automatically integrates the analysis with the optimization and effectively implements the repetitive works between them. The problem formulation for the optimization is suggested to improve the dynamic compliance of OFH and to shift the resonant frequencies caused tracking errors to high frequency domain. Furthermore, the minimization of the effective suspension mass that leads to decrease the so-called 'lift-off' as the disk-head separation acceleration divided by the suspension load is taken into consideration. In particular, this study is carried out the optimal design considering the process of modes tracking through the entire optimization processes. The advanced suspension that reduces the effective mass of the suspension and increases the resonant frequencies of sway and $2^{nd}$ torsion over 10kHz is achieved by using the integrated optimization frame.

• Structural Engineering and Mechanics
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• v.42 no.3
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• pp.335-352
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• 2012

Particle Swarm Optimization (PSO) is a stochastic population based optimization algorithm which has attracted attentions of many researchers. This method has great potentials to be applied to many optimization problems. Despite its robustness the standard version of PSO has some drawbacks that may reduce its performance in optimization of complex structures such as laminated composites. In this paper by suggesting a new variation scheme for acceleration parameters and inertial weight factors of PSO a novel optimization algorithm is developed to enhance the basic version's performance in optimization of laminated composite structures. To verify the performance of the new proposed method, it is applied in two multi-objective design optimization problems of laminated cylindrical. The numerical results from the proposed method are compared with those from two other conventional versions of PSO-based algorithms. The convergancy of the new algorithms is also compared with the other two versions. The results reveal that the new modifications inthe basic forms of particle swarm optimization method can increase its convergence speed and evade it from local optima traps. It is shown that the parameter variation scheme as presented in this paper is successful and can evenfind more preferable optimum results in design of laminated composite structures.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.11
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• pp.1578-1583
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• 2013

In this paper, stochastic optimization algorithms of PSO (Particle Swarm Optimization) and APSO (Adaptive Particle Swam Optimization) are studied and compared. It is revealed that the APSO provides faster convergence and better search efficiency than the conventional PSO when they are adopted to find the global minimum of a two-dimensional function. The advantages of the APSO comes from the ability to control the inertia weight, and acceleration coefficients. To verify that the APSO is working better than the standard PSO, the design of a 10GHz microstrip patch as one of the elements of a high frequency array antenna is taken as a test-case and shows the optimized result with 5 iterations in the APSO and 28 iterations in th PSO.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.2
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• pp.112-121
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• 2013

An approach for composing a performance optimized computational code is suggested for the latest microprocessors. The concept of the code optimization, termed localization, is maximizing the utilization of the second level cache that is common to all the latest computer systems, and minimizing the access to system main memory. In this study, the localized optimization of the LU-SGS (Lower-Upper Symmetric Gauss-Seidel) code for the solution of fluid dynamic equations was carried out in three different levels and tested for several different microprocessor architectures widely used these days. The test results of localized optimization showed a remarkable performance gain of more than two times faster solution than the baseline algorithm for producing exactly the same solution on the same computer system.