• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년 영문 학술대회
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• pp.330-339
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• 2008

Ground-based interceptors(GBI) comprise a major element of the strategic defense against hostile targets like Intercontinental Ballistic Missiles(ICBM) and reentry vehicles(RV) dispersed from them. An optimum design of the subsystems is required to increase the performance and reliability of these GBI. Propulsion subsystem design and optimization is the motivation for this effort. This paper describes an effort in which an entire GBI missile system, including a multi-stage solid rocket booster, is considered simultaneously in a Genetic Algorithm(GA) performance optimization process. Single goal, constrained optimization is performed. For specified payload and miss distance, time of flight, the most important component in the optimization process is the booster, for its takeoff weight, time of flight, or a combination of the two. The GBI is assumed to be a multistage missile that uses target location data provided by two ground based RF radar sensors and two low earth orbit(LEO) IR sensors. 3Dimensional model is developed for a multistage target with a boost phase acceleration profile that depends on total mass, propellant mass and the specific impulse in the gravity field. The monostatic radar cross section (RCS) data of a three stage ICBM is used. For preliminary design, GBI is assumed to have a fixed initial position from the target launch point and zero launch delay. GBI carries the Kill Vehicle(KV) to an optimal position in space to allow it to complete the intercept. The objective is to design and optimize the propulsion system for the GBI that will fulfill mission requirements and objectives. The KV weight and volume requirements are specified in the problem definition before the optimization is computed. We have considered only continuous design variables, while considering discrete variables as input. Though the number of stages should also be one of the design variables, however, in this paper it is fixed as three. The elite solution from GA is passed on to(Sequential Quadratic Programming) SQP as near optimal guess. The SQP then performs local convergence to identify the minimum mass of the GBI. The performance of the three staged GBI is validated using a ballistic missile intercept scenario modeled in Matlab/SIMULINK.

• 한국소음진동공학회논문집
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• 제12권6호
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• pp.461-468
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• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of the given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a surrogate model that has a regression model performed on a data sampling of the simulation. In general, metamodels(surrogate model) take the form y($\chi$)＝f($\chi$)＋$\varepsilon$, where y($\chi$) is the true output, f($\chi$) is the metamodel output, and is the error. In this paper, a second order polynomial equation is used as the RSM(response surface model) for high speed train that have twenty-nine design variables and forty-six responses. After the RSM is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called VMM(variable matric method) This paper shows that the RSM is a very efficient model to solve the complex optimization problem.

• 대한기계학회논문집A
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• 제27권8호
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• pp.1353-1362
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• 2003

This paper considers a simultaneous optimization problem of structure and control systems. The problem is generally formulated as a non-convex optimization problem for the design parameters of mechanical structure and controller. Therefore, it is not easy to obtain the global solutions for practical problems. In this paper, we parameterize all design parameters of the mechanical structure such that the parameters work in the control system as decentralized static output feedback gains. Using this parameterization, we have formulated a simultaneous optimization problem in which the design specification is defined by the Η$_2$and Η$\_$$\infty$/ norms of the closed loop transfer function. So as to lead to a convex problem we approximate the nonlinear terms of design parameters to the linear terms. Then, we propose a convex optimization method that is based on linear matrix inequality (LMI). Using this method, we can surely obtain suboptimal solution for the design specification. A numerical example is given to illustrate the effectiveness of the proposed method.

• Smart Structures and Systems
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• 제16권1호
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• pp.1-26
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• 2015

Minimizing construction cost and reducing seismic damage are two conflicting objectives in the design of any new structure. In the present work, we try to develop a framework in order to solve the optimum performance-based design problem considering the construction cost and the seismic damage of steel moment-frame structures. The Park-Ang damage index is selected as the seismic damage measure because it is one of the most realistic measures of structural damage. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. To improve the time efficiency of the proposed framework, three simplifying strategies are adopted: first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication; second, fitness approximation decreasing the number of fitness function evaluations; third, wavelet decomposition of earthquake record decreasing the number of acceleration points involved in time-history loading. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency's (FEMA) recommended seismic design specifications. The results from numerical application of the proposed framework demonstrate the efficiency of the framework in solving the present multi-objective optimization problem.

• Journal of Magnetics
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• 제21권4호
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• pp.544-553
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• 2016

Torque ripple minimization without decrease in average torque is a vital attribute in the design of Synchronous Reluctance (SynRel) motor. As the design of SynRel motor is an arduous task, which encompasses many design variables, this work first analyses the significance of the effect of varying the geometrical parameters on average torque and torque ripple and then proposes an extensive optimization procedure to obtain configurations with improved average torque and minimized torque ripple. A hardware prototype is fabricated and tested. The Finite Element Analysis (FEA) software tool used for validating the test results is MagNet 7.6.0.8. Multi Objective Particle Swarm Optimization (MOPSO) is used to determine the various designs meeting the requirements of reduced torque ripple and improved torque performance. The results indicate the efficacy of the proposed methodology and substantiate the utilization of MOPSO as a significant tool for solving design problems related to SynRel motor.

• Nuclear Engineering and Technology
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• 제56권7호
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• pp.2595-2609
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• 2024

This paper introduces a base isolation system-tuned mass damper inerter (BIS-TMDI) hybrid system to the AP1000 nuclear power plant (NPP), which reduces seismic damage potential of the NPP structure. The effects of fluid-structure interaction (FSI) caused by the passive containment cooling system water storage tank (PCCWST) on NPP's seismic performance are investigated. The FSI of water tank theoretical model is considered based on the Housner's model, and a series of time history analyses are performed to prove the rationality of the proposed model. Three single-objective optimization strategies are employed to minimize the relative displacement variance and absolute acceleration variance of the upper structure, as well as the filtered energy index (FEI). Furthermore, a multi-objective optimization strategy considering all these three indexes is proposed to obtain optimal parameters of vibration control. The influence of vibration control strategies on the relative deformation and acceleration of the upper structure is explored with various water level ratios. The analytical results indicate that the proposed BIS-TMDI strategy has significantly reduced the NPP structure's seismic response. The effectiveness of the vibration control strategy is influenced by the water level ratio, emphasizing the significance of designing an appropriate water level ratio to reduce NPP structure's seismic response.

• 제어로봇시스템학회논문지
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• 제17권9호
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• pp.932-940
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• 2011

This paper presents an integrated analysis of supply chain and financing decisions of multi-national corporation. We construct a model in which multiple currency storage units are installed to manage the currency flows associated with multi-national supply chain activities such as raw material procurement, process operation, inventory control, transportation and finished product sales. Core contribution of this study is to quantitatively investigate the influence of macroscopic economic factors such as exchange rates and taxes on operational decisions. The supply chain is modeled by the Process-Storage Network with recycle streams. The objective function of the optimization is minimizing the opportunity costs of annualized capital investments and currency/material inventories minus the benefit to stockholders interpreted by home currency. The major constraints of the optimization are that the material and currency storage units must not be depleted. A production and inventory analysis formulation, the periodic square wave (PSW) model, provides useful expressions for the upper/lower bounds and average levels of the currency and material inventory holdups. The expressions for the Kuhn-Tucker conditions of the optimization problem are reduced to a subproblem and analytical lot sizing equations. The procurement, production, transportation and financial transaction lot sizes can be determined by analytical expressions after the average flow rates are already known. We show that, when corporate income tax is taken into consideration, the optimal production lot and storage sizes are smaller than is the case when such factors are not considered typically by 20 %.

• Journal of Biosystems Engineering
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• 제41권3호
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• pp.221-231
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• 2016

Purpose: The objective of this study was to develop cushion curves models and analyze the cushioning performance of multi-layered corrugated structures (MLCS) using a method based on dynamic stress-energy relationship. Methods: Cushion tests were performed for developing cushion curve models under 12 combinations of test conditions: three different combinations of drop height, material thickness, and static stress for each of four levels of energy densities between 15 and $60kJ/m^3$. Results: Dynamic stress and energy density for MLCS followed an exponential relationship. Cushion curve models were developed as a function of drop height, material thickness, and static stress for different paperboards and flute types. Generally, the differences between the shock pulse (transmitted peak acceleration) and cushion curve (position and width of belly portion) for the first drop and the averaged second to fifth drop were greater than those for polymer-based cushioning materials. Accordingly, the loss of cushioning performance of MLCS was estimated to be greater than that of polymer-based cushioning materials with the increasing number of drops. The position of the belly of the cushion curve of MLCS tends to shift upward to the left with increasing drop height, and the belly portion became narrower. However, depending on material thickness, under identical conditions, the cushion curve of MLCS showed an opposite tendency. Conclusions: The results of this study can be useful for environment-friendly and optimal packaging design as shock and vibrations are the key factors in cushioning packaging design.

• 한국해양공학회지
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• 제27권1호
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• pp.85-92
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• 2013

This paper deals with the resonant type of a WEC (wave energy converter) and the determination method of its geometric parameters which were obtained to construct the robust and optimal structure, respectively. In detail, the optimization problem is formulated with the constraints composed of the response surfaces which stand for the resonance period(heave, pitch) and the meta center height of the buoy. Use of a signal-to-noise ratio calculated from normalized multi-objective results with the weight factor can help to select the robust design level. In order to get the sample data set, the motion responses of the power buoy were analyzed using the BEM (boundary element method)-based commercial code. Also, the optimization result is compared with a robust design for a feasibility study. Finally, the power efficiency of the WEC with the optimum design variables is estimated as the captured wave ratio resulting from absorbed power which mainly related to PTO (power take off) damping. It could be said that the resultant of the WEC design is the economical optimal design which satisfy the given constraints.

• International Journal of Control, Automation, and Systems
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• 제2권4호
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• pp.423-434
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• 2004

In this paper, we introduce a new topology of Self-Organizing Polynomial Neural Networks (SOPNN) based on genetically optimized Multi-Layer Perceptron (MLP) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. Let us recall that the design of the 'conventional' SOPNN uses the extended Group Method of Data Handling (GMDH) technique to exploit polynomials as well as to consider a fixed number of input nodes at polynomial neurons (or nodes) located in each layer. However, this design process does not guarantee that the conventional SOPNN generated through learning results in optimal network architecture. The design procedure applied in the construction of each layer of the SOPNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomials, and input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between the approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented using pH neutralization process data as well as sewage treatment process data. A comparative analysis indicates that the proposed SOPNN is the model having higher accuracy as well as more superb predictive capability than other intelligent models presented previously.reviously.