• International Journal of Aeronautical and Space Sciences
• /
• v.7 no.1
• /
• pp.1-12
• /
• 2006

In this study, a surrogate model is applied to multi-objective aerodynamic optimization design. For the balanced exploration and exploitation, each objective function is converted into the Expected Improvement (EI) and this value is used as fitness value in the multi-objective optimization instead of the objective function itself. Among the non-dominated solutions about EIs, additional sample points for the update of the Kriging model are selected. The present method was applied to a transonic airfoil design. Design results showed the validity of the present method. In order to obtain the information about design space, two data mining techniques are applied to design results: Analysis of Variance (ANOVA) and the Self-Organizing Map (SOM).

• International Journal of Aeronautical and Space Sciences
• /
• v.4 no.1
• /
• pp.45-52
• /
• 2003

A three-dimensional aerodynamic shape optimization technique in inviscid compressible flows is developed by using a parallel continuous adjoint formulation on unstructured meshes. A new surface mesh modification method is proposed to overcome difficulties related to patch-level remeshing for unstructured meshes, and the effect of design sections on aerodynamic shape optimization is examined. Applications are made to three-dimensional wave drag minimization problems including an ONERA M6 wing and the EGLIN wing-pylon-store configuration. The results show that the present method is robust and highly efficient for the shape optimization of aerodynamic configurations, independent of the number of design variables used.

• International Journal of Aeronautical and Space Sciences
• /
• v.12 no.3
• /
• pp.288-295
• /
• 2011

This paper addresses minimum-fuel, two-dimensional trajectory optimization for a soft lunar landing from a parking orbit to a desired landing site. The landing site is usually not considered when performing trajectory optimization so that the landing problem can be handled. However, for precise trajectories for landing at a desired site to be designed, the landing site has to be considered as the terminal constraint. To convert the trajectory optimization problem into a parameter optimization problem, a pseudospectral method was used, and C code for feasible sequential quadratic programming was used as a numerical solver. To check the reliability of the results obtained, a feasibility check was performed.

• Korean Journal of Computational Design and Engineering
• /
• v.15 no.1
• /
• pp.24-32
• /
• 2010

This paper introduces a B-spline based branch & bound algorithm for global optimization. The branch & bound is a well-known algorithm paradigm for global optimization, of which key components are the subdivision scheme and the bound calculation scheme. For this, we consider the B-spline hypervolume to approximate an objective function defined in a design space. This model enables us to subdivide the design space, and to compute the upper & lower bound of each subspace where the bound calculation is based on the LHS sampling points. We also describe a search tree to represent the searching process for optimal solution, and explain iteration steps and some conditions necessary to carry out the algorithm. Finally, the performance of the proposed algorithm is examined on some test problems which would cover most difficulties faced in global optimization area. It shows that the proposed algorithm is complete algorithm not using heuristics, provides an approximate global solution within prescribed tolerances, and has the good possibility for large scale NP-hard optimization.

• International Journal of Aeronautical and Space Sciences
• /
• v.17 no.2
• /
• pp.268-283
• /
• 2016

Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet new market demands while keeping the development time and cost to a minimum. Many researchers have studied the derivative design process, but these research efforts consider baseline and derivative designs together, while using the whole set of design variables. Therefore, an efficient process that can reduce cost and time for aircraft derivative design is needed. In this research, a more efficient design process is proposed which obtains global changes from local changes in aircraft design in order to develop aircraft derivatives efficiently. Sensitivity analysis was introduced to remove unnecessary design variables that have a low impact on the objective function. This prevented wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, uncertainty from the fidelity of analysis tools was considered in design optimization to increase the probability of optimization results. The Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were proposed to handle the uncertainty in aircraft conceptual design optimization. In this paper, Collaborative Optimization (CO) based framework with RBDO and PBDO was implemented to consider uncertainty. The proposed method was applied for civil jet aircraft derivative design that increases cruise range and the number of passengers. The proposed process provided deterministic design optimization, RBDO, and PBDO results for given requirements.

• Journal of Korean Association for Spatial Structures
• /
• v.1 no.2 s.2
• /
• pp.59-66
• /
• 2001

This paper describes three modules for development of the Space Frame Integrated Design System(SFIDS). The Control Module is implemented to control the developed system. The Model Generation Module based on PATRAN user interface enables users to generate a complicated finite element model for space frame structures. The Optimum Design Module base on a branch of combinatorial optimization techniques which can realize the optimization of a structure having a large number of members designs optimum members of a space frame after evaluating analysis results. The Control Module and the Model Generation Module Is implemented by PATRAN Command Language(PCL) while C++ language is used in the Optimum Design Module. The core of the system is PATRAN database, in which the Model Generation Module creates information of a finite element model. Then, PATRAN creates Input files needed for the analysis program from the information of the finite element model in the database, and in turn, imports output results of analysis program to the database. Finally, the Optimum Design Module processes member grouping of a space frame based on the output results, and performs optimal member selection of a space frame. This process is repeated until the desired optimum structural members are obtained.

• Journal of Power Electronics
• /
• v.16 no.3
• /
• pp.946-959
• /
• 2016

A novel Virtual Space Vector (VSV) modulation strategy for complete control of potential neutral point (NP) issues is proposed in this paper. The neutral point potential balancing problems of multi-level converters, which include elimination of low frequency oscillations and self-balancing for NP dc unbalance, are investigated first. Then a set of improved virtual space vectors with dynamic adjustment factors are introduced and a multi-objective optimization algorithm which aims to optimize these adjustment factors is presented in this paper. The improved virtual space vectors and the multi-objective optimization algorithm constitute the novel Virtual Space Vector modulation. The proposed novel Virtual Space Vector modulation can simultaneously recover NP dc unbalance and eliminate low frequency oscillations of the neutral point. Experiment results show that the proposed strategy has excellent performance, and that both of the neutral point potential issues can be solved.

• Journal of Astronomy and Space Sciences
• /
• v.30 no.4
• /
• pp.291-298
• /
• 2013

The concept of the satellite formation flight is area where it is actively study with expandability and safety compare to existing satellite. For execution of duty with more safety issue, it needs to consider hot topic of space debris for operation of formation flight. In this paper, it suggests heuristic algorithm to have avoidance maneuver for space debris towards operating flight formation. Indeed it covers, using common software, operating simulation to nearest space environment and not only to have goal of avoidance but also minimizing the usage of fuel and finding optimization for maximizing cycle of formation flight. For improvement on convergence speed of existing heuristic algorithm, it substitute to hybrid heuristic algorithm, PSOGSA, and the result of simulation, it represents the satisfaction of minimum range for successful avoidance maneuver and compare to not using avoidance maneuver, it keeps more than three times of formation maintenance performance. From these, it is meaningful results of showing several success goals like simple avoidance collision and fuel usage and decreasing number of times of maintaining formation maneuver.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.1 no.1
• /
• pp.35-43
• /
• 2001

In this paper, we propose a design method for GBSB (generalized brain-state-in-a-box) based associative memories. Based on the theoretical investigation about the properties of GBSB, we parameterize the solution space utilizing the limited number of parameters sufficient to represent the solution space and appropriate to be searched. Next we formulate the problem of finding a GBSB that can store the given pattern as stable states in the form of constrained optimization problems. Finally, we transform the constrained optimization problem into a SDP(semidefinite program), which can be solved by recently developed interior point methods. The applicability of the proposed method is illustrated via design examples.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.3 no.2
• /
• pp.233-238
• /
• 2003

Living creatures maintain their variety through speciation, which helps them to have more fitness for an environment. So evolutionary algorithm based on biological evolution must maintain variety in order to adapt to its environment. In this paper, we utilize the concept of speciation. Each individual of population creates their offsprings using mutation, and next generation consists of them. Each individual explores search space determined by mutation. Useful search space is extended by differentiation, then population explorers whole search space very effectively. If evolvable hardware evolves through mutation, it is useful way to explorer search space because of less varying inner structure. We verify the effectiveness of the proposed method by applying it to two optimization problems.