• International Journal of Aeronautical and Space Sciences
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• v.15 no.3
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• pp.219-231
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• 2014

We develop a preliminary design optimization procedure in this paper regarding the wing planform in a solar-powered high-altitude long-endurance unmanned aerial vehicle. A high-aspect-ratio wing has been widely adopted in this type of a vehicle, due to both the high lift-to-drag ratio and lightweight design. In the preliminary design, its characteristics need to be addressed correctly, and analyzed in an appropriate manner. In this paper, we use the three-dimensional Euler equation to analyze the wing aerodynamics. We also use an advanced structural modeling approach based on a geometrically exact one-dimensional beam analysis. Regarding the structural integrity of the wing, we determine detailed configuration parameters, specifically the taper ratio and the span length. Next, we conduct a multi-objective optimization scheme based on the response surface method, using the present baseline configuration. We consider the structural integrity as one of the constraints. We reduce the wing weight by approximately 25.3 % from that in the baseline configuration, and also decrease the power required approximately 3.4 %. We confirm that the optimized wing has sufficient flutter margin and improved static longitudinal/directional stability characteristics, as compared to those of the baseline configuration.

• Structural Engineering and Mechanics
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• v.52 no.1
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• pp.149-172
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• 2014

Four algorithms for damage detection of trusses are presented in this paper. These approaches can detect damage by using both complete and incomplete measurements. The suggested methods are based on the minimization of the difference between the measured and analytical static responses of structures. A non-linear constrained optimization problem is established to estimate the severity and location of damage. To reach the responses, the successive quadratic method is used. Based on the objective function, the stiffness matrix of the truss should be estimated and inverted in the optimization procedure. The differences of the proposed techniques are rooted in the strategy utilized for inverting the stiffness matrix of the damaged structure. Additionally, for separating the probable damaged members, a new formulation is proposed. This scheme is employed prior to the outset of the optimization process. Furthermore, a new tactic is presented to select the appropriate load pattern. To investigate the robustness and efficiency of the authors' method, several numerical tests are performed. Moreover, Monte Carlo simulation is carried out to assess the effect of noisy measurements on the estimated parameters.

• Journal of Ocean Engineering and Technology
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• v.24 no.1
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• pp.161-165
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• 2010

In the present study, process optimization for thermal-sprayed STS316 coating has been performed using $L_9(3^4)$ orthogonal array and analysis of variance (ANOVA). STS316 coatings were fabricated by flame spray process on steel substrate, and the hardness test and microstructure observation of the coatings were studied. The results of hardness test were analyzed by ANOVA. The ANOVA results showed that the spray distance had the greatest effect on hardness of the coating, on the other hands, the effects of oxygen gas flow and spray distance were ignorable. From these results, the optimal combination of the flame spray parameters could be derived, and confirmation experiment was carried out to verify these derived results. The calculated hardness of the coatings by ANOVA was found to approximately close to that of confirmation experimental result. Thus, it was considered that design of experiments using orthogonal array and ANOVA was effective for process optimization of thermal-sprayed STS316 coating.

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.533-538
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• 2001

In general, shape optimization design of the flow system has done to obtain the effects, which are required in the engineering fields. Most of these designs are accomplished by empirical or numerical analysis. But, in empirical analysis case, it is difficult to obtain an optimal shape in the feasible design region. And, in numerical method case, it usually needs many design parameters, because of the required object-function. In this paper, we present a newly numerical analysis, the growth-strain method having only one design parameter. That optimizes a shape by distributing a design parameter such as dissipation energy to be uniformed in the flow system. Also, we apply this shape design process to the three-flow systems, and then we identify that the resulting shape approaches the known optimal shape in the numerical values. Consequently, we confirm that the proposed method is very efficient and practical in the shape optimization of the flow system.

• Fire Science and Engineering
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• v.22 no.4
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• pp.65-69
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• 2008

An accurate knowledge of the flash point is important in developing appropriate preventive and control measures in industrial fire protection. The lower flash points for the n-propanol+formic acid system were measured by Pensky-Martens closed cup apparatus. This binary mixture exhibited MFPB (minimum flash point behavior), which leads to the minimum on the flash point vs composition curve. The Raoult's law and optimization method using Wilson equation were used to predict the lower flash points and were compared with experimental data. The calculated values based on the optimization method were found to be better than those based on the Raoult's law.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7775-7780
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• 2014

This paper addresses cancer prediction based on radial basis function neural network optimized by particle swarm optimization. Today, cancer hazard to people is increasing, and it is often difficult to cure cancer. The occurrence of cancer can be predicted by the method of the computer so that people can take timely and effective measures to prevent the occurrence of cancer. In this paper, the occurrence of cancer is predicted by the means of Radial Basis Function Neural Network Optimized by Particle Swarm Optimization. The neural network parameters to be optimized include the weight vector between network hidden layer and output layer, and the threshold of output layer neurons. The experimental data were obtained from the Wisconsin breast cancer database. A total of 12 experiments were done by setting 12 different sets of experimental result reliability. The findings show that the method can improve the accuracy, reliability and stability of cancer prediction greatly and effectively.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.299-306
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• 2006

Using a level set method and topological derivatives, a topological shape optimization method that is independent of an initial design is developed for linearly elastic structures. In the level set method, the initial domain is kept fixed and its boundary is represented by an implicit moving boundary embedded in the level set function, which facilitates to handle complicated topological shape changes. The 'Hamilton-Jacobi (H-J)' equation and computationally robust numerical technique of 'up-wind scheme' lead the initial implicit boundary to an optimal one according to the normal velocity field while minimizing the objective function of compliance and satisfying the constraint of allowable volume. Based on the asymptotic regularization concept, the topological derivative is considered as the limit of shape derivative as the radius of hole approaches to zero. The required velocity field to update the H -J equation is determined from the descent direction of Lagrangian derived from optimality conditions. It turns out that the initial holes is not required to get the optimal result since the developed method can create holes whenever and wherever necessary using indicators obtained from the topological derivatives. It is demonstrated that the proper choice of control parameters for nucleation is crucial for efficient optimization process.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.2
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• pp.169-176
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• 2008

This paper presents optimal design of controllable magnetorheological(MR) shock absorbers for passenger vehicle. In order to achieve this goal, two MR shock absorbers (one for front suspension; one for rear suspension) are designed using an optimization methodology based on design specifications for a commercial passenger vehicle. The optimization problem is to find optimal geometric dimensions of the magnetic circuits for the front and rear MR shock absorbers in order to improve the performance such as damping force as an objective function. The first order optimization method using commercial finite element method(FEM) software is adopted for the constrained optimization algorithm. After manufacturing the MR shock absorbers with optimally obtained design parameters, their field-dependent damping forces are experimentally evaluated and compared with those of conventional shock absorbers. In addition, vibration control performances of the full-vehicle installed with the proposed MR shock absorbers are evaluated under bump road condition and obstacle avoidance test.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.389-394
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• 2003

In this paper, a shape optimization technique is applied to design of an air-conditioner mounting bracket. The mounting bracket is a structural component of an engine, on which bolts attach an air-conditioner compressor. The air-conditioner mounting bracket has a large portion of weight among the engine components. To reduce weight of the bracket, the shape is optimized using a finite element software. The compressor assembly, composed of a compressor and a bracket is modeled using finite elements. An objective function for the shape optimization of the bracket is the weight of the bracket. Two design constraints on the bracket are the first resonant frequency of the compressor assembly and the fatigue life of the bracket. The design variables are the shape of the bracket including thickness profiles of the front and back surfaces of the bracket, radius of outer bolt-holes, and side edge profiles. The coordinates of the FE nodes control the shape parameters. Optimal shapes of the bracket are obtained by using SOL200 of MSC/NASTRAN.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.1
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• pp.153-158
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• 2006

To optimize the combustion system in a HSDI diesel engine, a new analysis technology was developed. The in-cylinder 3-D combustion analysis was carried out by the modified KIVA-3V, and the spray characteristics for the high pressure injection system were analyzed by HYDSIM. The combustion design parameters were optimized by coupling the KIVA-3V and the iSIGHT. The optimization procedure consists of 3 steps. The $1^{st}$ step is the sampling method by the Design of Experiment(DOE), the $2^{nd}$ step is the approximation using the Neural Network method, and the $3^{rd}$ step is the optimization using the Genetic Algorithm. The developed procedures have been approved as very effective and reliable, and the computational results agree well with the experimental data. The analysis results show that the optimized combustion system in a HSDI diesel engine is capable of reducing NOx and Soot emissions simultaneously keeping a same level of the fuel consumption(BSFC).