• Journal of Aerospace System Engineering
• /
• v.17 no.1
• /
• pp.10-15
• /
• 2023

Wet multi-disk clutch, a power switching device of the ducted fan, was optimized and results were analyzed. The clutch was divided into two types depending on whether a mechanical lock-up was applied or not. It was optimized under each design condition. Transfer torque capacity, friction material surface pressure, friction surface temperature, and drag torque were calculated as factors to optimize the clutch. The volume of separator plate and drag torque were used as the objective function for optimization. In the case of Type 1, which did not include a mechanical lock-up, the clutch could be operated regardless of the pitch angle of the ducted fan. However, the outer diameter of the friction surface was doubled, the volume was increased by 5~7 times, and the drag torque was increased by 7~12 times compared to those of Type 2, which included a mechanical lock-up.

• Korean Journal of Optics and Photonics
• /
• v.33 no.6
• /
• pp.295-302
• /
• 2022

In this paper, a wedge prism application method was studied to design a full-high-definition (FHD)-class high-resolution flexible endoscope. In the case of the conventional flexible endoscope optical system, the F number is made large or a liquid lens is applied to obtain the same imaging performance in a wide depth of field. However, there is a problem in that the diameter of the optical system increases because an additional light guide and equipment are required. To solve this problem, two wedge prisms were applied to the flexible endoscope optical system to adjust the image distance for each object distance. First, two wedge prisms were symmetrically placed on the designed endoscopic optical system. An image distance satisfying the target imaging performance according to each objective distance was derived. Next, the wedge prism decenter value for controlling the image distance was derived. By combining these two data, a wedge prism decenter value that satisfied the target imaging performance at each object distance was applied in multi configurations. As a result of the optimal design applied with the wedge prism, a target imaging performance of more than 20% of the modulation transfer function for a resolution of 178 cycles/mm was satisfied in the entire depth of field of 100 mm-7 mm.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.3
• /
• pp.375-381
• /
• 2005

Usually genetic algorithms are used to design optimal system. However the performance of the algorithm is determined by the fitness function and the system environment. It is expected that a co-evolutionary algorithm, two populations are constantly interact and co-evolve, is one of the solution to overcome these problems. In this paper we propose three types of co-evolutionary algorithm to solve GA-Hard problem. The first model is a competitive co-evolutionary algorithm that solution and environment are competitively co-evolve. This model can prevent the solution from falling in local optima because the environment are also evolve according to the evolution of the solution. The second algorithm is schema co-evolutionary algorithm that has host population and parasite (schema) population. Schema population supply good schema to host population in this algorithm. The third is game model-based co-evolutionary algorithm that two populations are co-evolve through game. Each algorithm is applied to visual servoing, robot navigation, and multi-objective optimization problem to verify the effectiveness of the proposed algorithms.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.13 no.2
• /
• pp.73-84
• /
• 1993

In this research, configuration design optimization of plane truss structure has been tested by using decomposition technique. In the first level, the problem of transferring the nonlinear programming problem to linear programming problem has been effectively solved and the number of the structural analysis necessary for doing the sensitivity analysis can be decreased by developing stress constraint into member stress approximation according to the design space approach which has been proved to be efficient to the sensitivity analysis. And the weight function has been adopted as cost function in order to minimize structures. For the design constraint, allowable stress, buckling stress, displacement constraint under multi-condition and upper and lower constraints of the design variable are considered. In the second level, the nodal point coordinates of the truss structure are used as coordinating variable and the objective function has been taken as the weight function. By treating the nodal point coordinates as design variable, unconstrained optimal design problems are easy to solve. The decomposition method which optimize the section areas in the first level and optimize configuration variables in the second level was applied to the plane truss structures. The numerical comparisons with results which are obtained from numerical test for several truss structures with various shapes and any design criteria show that convergence rate is very fast regardless of constraint types and configuration of truss structures. And the optimal configuration of the truss structures obtained in this study is almost the identical one from other results. The total weight couldbe decreased by 5.4% - 15.4% when optimal configuration was accomplished, though there is some difference.

• Journal of KIISE:Software and Applications
• /
• v.32 no.12
• /
• pp.1217-1228
• /
• 2005

Recently, since DNA computing has been widely studied for various applications, DNA sequence design which is the most basic and important step for DNA computing has been highlighted. In previous works, DNA sequence design has been formulated as a multi-objective optimization task, and solved by elitist non-dominated sorting genetic algorithm (NSGA-II). However, NSGA-II needed lots of computational time. Therefore, we use an $\varepsilon$- multiobjective evolutionarv algorithm ($\varepsilon$-MOEA) to overcome the drawbacks of NSGA-II in this paper. To compare the performance of two algorithms in detail, we apply both algorithms to the DTLZ2 benchmark function. $\varepsilon$-MOEA outperformed NSGA-II in both convergence and diversity, $70\%$ and $73\%$ respectively. Especially, $\varepsilon$-MOEA finds optimal solutions using small computational time. Based on these results, we redesign the DNA sequences generated by the previous DNA sequence design tools and the DNA sequences for the 7-travelling salesman problem (TSP). The experimental results show that $\varepsilon$-MOEA outperforms the most cases. Especially, for 7-TSP, $\varepsilon$-MOEA achieves the comparative results two tines faster while finding $22\%$ improved diversity and $92\%$ improved convergence in final solutions using the same time.