• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.5 s.248
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• pp.595-601
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• 2006

Design space optimization using design space adjustment and refinement is used to optimize a knuckle in the suspension system of an automobile. This approach is a new efficient method for large-scale topology optimization by virtue of two reasons. First, design space adjustment including design space expansion and reduction is suitable for large-scale problems. Second, the design space refinement can be done globally or locally where and when necessary and thus is very effective in obtaining a target resolution with much less number of elements. Compliance minimization for a knuckle is considered with a realistic working condition to show the effectiveness and superiority of the new approach.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.408-413
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• 2001

The structural optimization is carried out in the continuous design space or discrete design space. Methods for discrete variables such as genetic algorithms are extremely expensive in computational cost. In this research, an iterative optimization algorithm using orthogonal arrays is developed for design in discrete space. An orthogonal array is selected on a discrete design space and levels are selected from candidate values. Matrix experiments with the orthogonal array are conducted. New results of matrix experiments are obtained with penalty functions for constraints. A new design is determined from analysis of means(ANOM). An orthogonal array is defined around the new values and matrix experiments are conducted. The final optimum design is found from iterative process. The suggested algorithm has been applied to various problems such as truss and frame type structures. The results are compared with those from a genetic algorithm and discussed.

• Structural Engineering and Mechanics
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• v.62 no.3
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• pp.259-272
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• 2017

In this study, recently developed swarm intelligence algorithm called Social Spider Optimization (SSO) approach and its enhanced version of SSO algorithm with spider jump techniques is used to develop a structural optimization technique for steel space structures. The improved version of SSO uses adaptive randomness probability in generating new solutions. The objective function of the design optimization problem is taken as the weight of a steel space structure. Constraints' functions are implemented from American Institute of Steel Construction-Load Resistance factor design (AISC-LRFD) and Ad Hoc Committee report and practice which cover strength, serviceability and geometric requirements. Three steel space structures are optimized using both standard SSO and SSO with spider jump (SSO_SJ) algorithms and the results are compared with those available in the literature in order to investigate the performance of the proposed algorithms.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1005-1010
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• 2004

The structural optimization has been carried out in the continuous design space or in the discrete design space. Generally, available designs are discrete in design practice. But methods for discrete variables are extremely expensive in computational cost. In order to overcome this weakness, an iterative optimization algorithm was proposed for design in the discrete space, which is called as a sequential algorithm using orthogonal arrays (SOA). We focus to verify the fact that the local solution can be obtained throughout the optimization with this algorithm. The local solution is defined in discrete design space. Then the search space, which is the set of candidate values of each design variables formed by the neighborhood of current design point, is defined. It is verified that a local solution can be founded by moving sequentially the search space. The SOA algorithm has been applied to problems such as truss type structures. Then it is confirmed that a local solution can be obtained using the SOA algorithm

• 한국전산유체공학회:학술대회논문집
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• 2000.10a
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• pp.46-53
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• 2000

To improve the performance at all design points, multi-point optimization method is implemented for the nose fairing shape design of space launcher. The response surface method is used to effectively reduce the huge computational loads during the optimization process. The drag is selected as the objective function, and the surface heat transfer characteristics, and the internal volume of the nose fairing ate considered as design constraints. Full Wavier-Stokes equations are selected as governing equations. Two points drag minimization, and two points drag / heat flux optimization were successfully performed and configurations which have good performance for the wide operation range were derived. By considering three design points, the space launcher shape which undergoes the least drag during whole flight mission was designed. For all the design cases, the constructed response surfaces show good confidence level with only 23 design points with the proper stretching of the design space.

• Journal of Korean Association for Spatial Structures
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• v.10 no.4
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• pp.59-66
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• 2010

This study presents the topology optimization technique by density method to determine the initial shape of space truss structures. Most initial shape design is performed by designer's previous experiences and trial and error method instead of the application of reasonable optimization method. Thus, the reasonable and economical optimization methods are needed to be introduced for the initial shape design. Therefore, we set design domain for cantilever space truss structure as an example model. And topology optimization is used to obtain optimum layout for them, and then size optimization method is used to find the optimum member size. Therefore, the reasonable initial optimal shapes of spatial truss structures can be obtained through the topology and size optimization using density method.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.780-787
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• 2017

The propellant grain configuration is a design variable that determines the shape and performance of a solid rocket motor. Grain configuration variables have complicated effects on the motor performance; so the global optimization problem has to be solved in order to design the configuration variables. The grain performance has been analyzed by means of the grain burn-back and internal ballistic analysis, and the optimization technique searches for the configuration variables that satisfy the requirements. The deterministic and stochastic optimization techniques have been applied for the grain optimization, but the results are imperfect. In this study, the optimization design of the configuration variables has been performed using the hybrid optimization technique, which combines those two techniques. As a result, the hybrid optimization technique has proved to be efficient for the grain optimization design.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.10
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• pp.1621-1626
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• 2001

The structural optimization have been carried out in the continuous design space or in the discrete design space. Methods fur discrete variables such as genetic algorithms , are extremely expensive in computational cost. In this research, an iterative optimization algorithm using orthogonal arrays is developed for design in discrete space. An orthogonal array is selected on a discrete des inn space and levels are selected from candidate values. Matrix experiments with the orthogonal array are conducted. New results of matrix experiments are obtained with penalty functions leer constraints. A new design is determined from analysis of means(ANOM). An orthogonal array is defined around the new values and matrix experiments are conducted. The final optimum design is found from iterative process. The suggested algorithm has been applied to various problems such as truss and frame type structures. The results are compared with those from a genetic algorithm and discussed.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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• pp.247-265
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• 2010

Multi-objective design exploration (MODE) and its applications are reviewed as an attempt to utilize numerical simulation in aerospace engineering design. MODE reveals the structure of the design space based on trade-off information. A self-organizing map (SOM) is incorporated into MODE as a visual data mining tool for the design space. SOM divides the design space into clusters with specific design features. This article reviews existing visual data mining techniques applied to engineering problems. Then, we discuss three applications of MODE: multidisciplinary design optimization for a regional-jet wing, silent supersonic technology demonstrator and centrifugal diffusers.

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