• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.8
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• pp.649-656
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• 2013

High-lift devices have a major influence on takeoff, landing and stall performance of an aircraft. Therefore, a slotted flap design optimization process is proposed in this paper to obtain the most effective flap configuration from supported 2D flap configuration. Flap deflection, Gap and Overlap are considered as main contributors to flap lift increment. ANSYS Fluent 13.0.0$^{(R)}$ is used as aerodynamic analysis software that provides accurate solution at given flight conditions. Optimum configuration is obtained by Sequential Quadratic Programing (SQP) algorithm. Performance of the aircraft with optimized flap is estimated using Aircraft Design Synthesis Program (ADSP), the in-house performance analysis code. Obtained parameters such as takeoff, landing distance and stall speed met KAS-VLA airworthiness requirements.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.6
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• pp.607-612
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• 2012

The wear problem of wheel flange occurs at sharp curves of rail. This paper proposes a procedure for optimum design of a wheel profile wherein flange wear is reduced by improving an interaction between wheel and rail. Application of optimization method to design problem mainly depends on characteristics of design space. This paper compared local optimization method with global optimization according to sensitivity value of objective function for design variables to find out which optimization method is appropriable to minimize wear of wheel flange. Wheel profile is created by a piecewise cubic Hermite interpolating polynomial and dynamic performances are analyzed by a railway dynamic analysis program, VAMPIRE. From the optimization results, it is verified that the global optimization method such as genetic algorithm is more suitable to wheel profile optimization than the local optimization of SQP (Sequential Quadratic Programming) in case of considering the lack of empirical knowledge for initial design value.

• Composites Research
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• v.26 no.4
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• pp.207-212
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• 2013

In this study, the thickness optimization for uni-directional (UD) glass fiber reinforced polymer (GFRP) laminates of the spar cap of composite tidal blades was performed under the tip deflection constrains. The spar cap was composed of GFRP composites and carbon fiber reinforced polymer (CFRP) composites. The stress distributions in the blade as well as its material costs for the optimized results were additionally investigated. The optimized thickness was obtained by interacting a sequential quadratic programming (SQP) algorithm and an ABAQUS software to calculate an objective function. It was confirmed that the thickness of UD GFRP increased with a decrease of the restrained tip deflection when a thickness of UD CFRP laminates was constrained to 9 mm. The weight of the optimized spar-cap increased up to 96.2% while the maximum longitudinal tensile stress decreased up to 24.6%. The thickness of UD GFRP laminates increased with a decrease of the thickness of UD CFRP laminates when the tip deflection was constrained to 126.83 mm. The weight increased up to 40.1%, but the material cost decreased up to 16.97%. Finally, the relationships among the weight, internal tensile stress, and material costs were presented based on the optimized thicknesses of the spar cap.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.7
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• pp.559-564
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• 2016

The objectives of this paper are to develop a finite element analysis model to analyze press-fitted and bending load conditions in a press-fitted assembly, and propose a hub shape optimization method to minimize contact pressure near the shaft contact edge. Numerical asymmetric-axisymmetric finite element models have been developed to predict contact stress on press-fitted shafts. The global optimization method, genetic algorithm, local optimization method, and sequential quadratic programming were applied to a press-fitted assembly to optimize the hub contact edge geometry. The results showed that the maximum contact pressure with the optimized hub shape decreased more than 60 % compared to conventional hubs and the maximum contact stress affecting fatigue life was reduced about 47 %. Hub shape optimization can be useful to increase the load capability of press fits in terms of wear and fatigue behavior.

• Journal of Welding and Joining
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• v.27 no.5
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• pp.81-87
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• 2009

Recently, extruded aluminium-alloy panels have been used in the car bodies for the purpose of the light-weight of railway vehicles and FSW(Friction Stir Welding), which is superior to the arc weldings, has been applied in the railway vehicles. This paper presents the optimum design of the FSW process on A6005 extruded alloy for railway vehicles to improve its mechanical properties. Rotational speed, welding speed and tilting angle of the tool tip were chosen as design parameters. Three objective functions were determined; maximizing the tensile strength, minimizing the hardness and maximizing the difference between the normalized tensile strength and hardness. The tensile tests and the hardness tests for fifteen FSW experiments were carried out according to the central composite design table. Recursive model functions on three characteristic values, such as the tensile strength, the hardness difference(${\Delta}Hv$) and the difference of normalized tensile strength and ${\Delta}Hv$, were estimated according to the classical response surface analysis methodology. The reliability of each recursive function was verified by F-test using the analysis of variance table. Sensitivity analysis on each characteristic value was done. Finally, the optimum values of three design parameters were found using Sequential Quadratic Programming algorithm.

• Smart Structures and Systems
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• v.26 no.5
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• pp.545-558
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• 2020

A design method of a Multiple Tuned Mass Damper (MTMD) system is presented for wind induced vibration control of a cable-supported roof structure. Modal contribution analysis is carried out to determine the dominating modes of the structure for the MTMD design. Two MTMD systems are developed for two most dominating modes. Each MTMD system is composed of multiple TMDs with small masses spread at multiple locations with large responses in the corresponding mode. Frequencies of TMDs are distributed uniformly within a range around the dominating frequencies of the roof structure to enhance the robustness of the MTMD system against uncertainties of structural frequencies. Parameter optimizations are carried out by minimizing objective functions regarding the structural responses, TMD strokes, robustness and mass cost. Two optimization approaches are used: Single Objective Approach (SOA) using Sequential Quadratic Programming (SQP) with multi-start method and Multi-Objective Approach (MOA) using Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The computation efficiency of the MOA is found to be superior to the SOA with consistent optimization results. A Pareto optimal front is obtained regarding the control performance and the total weight of the TMDs, from which several specific design options are proposed. The final design may be selected based on the Pareto optimal front and other engineering factors.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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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.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.33-44
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• 2012

In this study, the optimal operating conditions for the dual mixed refrigerant(DMR) cycle were determined by considering the power efficiency. The DMR cycle consists of compressors, heat exchangers, seawater coolers, valves, phase separators, tees, and common headers, and the operating conditions include the equipment's flow rate, pressure, temperature, and refrigerant composition per flow. First, a mathematical model of the DMR cycle was formulated in this study by referring to the results of a past study that formulated a mathematical model of the single mixed refrigerant(SMR) cycle, which consists of compressors, heat exchangers, seawater coolers, and valves, and by considering as well the tees, phase separators, and common headers. Finally, in this study, the optimal operating conditions from the formulated mathematical model was obtained using a hybrid optimization method that consists of the genetic algorithm(GA) and sequential quadratic programming(SQP). Moreover, the required power at the obtained conditions was decreased by 1.4% compared with the corresponding value from the past relevant study of Venkatarathnam.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.68-78
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• 2012

A layout of an LNG FPSO should be elaborately determined as compared with that of an onshore plant because many topside process systems are installed on the limited area; the deck of the LNG FPSO. Especially, the layout should be made as multi-deck, not single-deck and have a minimum area. In this study, a multi-floor layout for the liquefaction process, the dual mixed refrigerant(DMR) cycle, of LNG FPSO was determined by using the optimization technique. For this, an optimization problem for the multi-floor layout was mathematically formulated. The problem consists of 589 design variables representing the positions of topside process systems, 125 equality constraints and 2,315 inequality constraints representing limitations on the layout of them, and an objective function representing the total layout cost. To solve the problem, a hybrid optimization method that consists of the genetic algorithm(GA) and sequential quadratic programming(SQP) was used in this study. As a result, we can obtain a multi-floor layout for the liquefaction process of the LNG FPSO which satisfies all constraints related to limitations on the layout.