• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.20 no.1
• /
• pp.19-28
• /
• 2007

Discrete topology optimization processes of structures start from an initial design domain which is described by the topology of constant material densities. During optimization procedures, the structural topology changes in order to satisfy optimization problems in the fixed design domain, and finally, the optimization produces material density distributions with optimal topology. An introduction of initial holes in a design domain presented by Eschenauer et at. has been utilized in order to improve the optimization convergence of boundary-based shape optimization methods by generating finite changes of design variables. This means that an optimal topology depends on an initial topology with respect to topology optimization problems. In this study, it is investigated that various optimal topologies can be yielded under constraints of usable material, when partial solid phases are deposited in an initial design domain and thus initial topology is finitely changed. As a numerical application, structural topology optimization of a simple MBB-Beam is carried out, applying partial circular solid phases with varying sizes to an initial design domain.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.12
• /
• pp.1811-1820
• /
• 2010

Most components in the real world show nonlinear response. The nonlinearity may arise because of contact between the parts, nonlinear material, or large deformation of the components. Structural optimization considering nonlinearities is fairly expensive because sensitivity information is difficult to calculate. To overcome this difficulty, the equivalent load method was proposed for nonlinear response optimization. This method was originally developed for size and shape optimization. In this study, the equivalent load method is modified to perform topology optimization considering all kinds of nonlinearities. Equivalent load is defined as the load for linear analysis that generates the same response field as that for nonlinear analysis. A simple example demonstrates that results of the topology optimization using equivalent load are very similar to the numerical results. Nonlinear response topology optimization is performed with a practical example and the results are compared with those of conventional linear response topology optimization.

• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.15 no.1
• /
• pp.61-70
• /
• 2005

This study investigated the spinal loads(L5/S1 disc compression and shear forces) predicted from four biomechanical models: one EMG model and three optimization models. Three objective functions used in the optimization models were to miminize 1) the cubed muscle forces : MF3, 2) the cubed muscle stress : MS3, 3) maximum muscle intensity : MI. Twelve healthy male subjects participated in the isometric voluntary exertion tests to six directions : flexion/extension, left/right lateral bending, clockwise/ counterclockwise twist. EMG signals were measured from ten trunk muscles and spinal loads were assessed at 10, 20, 30, 40, 50, 60, 70, 80, 90%MVE(maximum voluntary exertion) in each direction. Three optimization models predicted lower L5/S1 disc compression forces than the EMG model, on average, by 31%(MF3), 27%(MS3), 8%(MI). Especially, in twist and extension, the differences were relatively large. Anterior-posterior shear forces predicted from optimization models were lower, on average, by 27%(MF3), 21%(MS3), 9%(MI) than by the EMG model, especially in flexion(MF3 : 45%, MS3 : 40%, MI : 35%). Lateral shear forces were predicted far less than anterior-posterior shear forces(total average = 124 N), and the optimization models predicted larger values than the EMG model on average. These results indicated that the optimization models could underestimate compression forces during twisting and extension, and anterior-posterior shear forces during flexion. Thus, future research should address the antagonistic coactivation, one major reason of the difference between optimization models and the EMG model, in the optimization models.

• Journal of the Ergonomics Society of Korea
• /
• v.31 no.6
• /
• pp.733-740
• /
• 2012

Objective: The present study systematically analyzed the characteristics of ergonomic layout optimization methods by a comprehensive literature survey. Background: Although layout design methods for ergonomic placement of controls and displays on a console have been developed, understanding of their characteristics is lacking. Method: The present study analyzed layout optimization papers published past 20 years from the following four aspects: optimization model, optimization algorithm, design principle, and constraint/assumption. Results: The existing layout optimization methods based on various optimization techniques consider only a partial set of four layout principles(importance, frequency of use, sequence of use, and functional grouping) and two ergonomic criteria(visibility and reach). In addition, the existing methods oversimplify components in various sizes, shapes, and angles by assuming the equality of the components in size and shape. Conclusion: A more effective layout optimization method is needed which considers the layout principles and ergonomic criteria in a comprehensive manner and reflect the diversity of components in size and shape. Application: The identified characteristics on the existing layout optimization methods can be applicable to development of a better ergonomic console layout design method.

• Structural Engineering and Mechanics
• /
• v.65 no.2
• /
• pp.173-181
• /
• 2018

In this paper, finite element (FE) model updating based on multi-objective optimization with the surrogate model for a steel plate girder bridge is investigated. Conventionally, FE model updating for bridge structures uses single-objective optimization with finite element analysis (FEA). In the case of the conventional method, computational burden occurs considerably because a lot of iteration are performed during the updating process. This issue can be addressed by replacing FEA with the surrogate model. The other problem is that the updating result from single-objective optimization depends on the condition of the weighting factors. Previous studies have used the trial-and-error strategy, genetic algorithm, or user's preference to obtain the most preferred model; but it needs considerable computation cost. In this study, the FE model updating method consisting of the surrogate model and multi-objective optimization, which can construct the Pareto-optimal front through a single run without considering the weighting factors, is proposed to overcome the limitations of the single-objective optimization. To verify the proposed method, the results of the proposed method are compared with those of the single-objective optimization. The comparison shows that the updated model from the multi-objective optimization is superior to the result of single-objective optimization in calculation time as well as the relative errors between the updated model and measurement.

• Journal of the Optical Society of Korea
• /
• v.20 no.3
• /
• pp.389-395
• /
• 2016

A Carbon Fiber Composite (CFC) framework was designed for a small lightweight space camera. According to the distribution characteristics of each optical element in the optical system, CFC (M40J) was chosen to accomplish the design of the framework. TC4 embedded parts were used to solve the low accuracy of the CFC framework interface problem. An integrated optimization method and the optimization strategy which combined a genetic global optimization algorithm with a downhill simplex local optimization algorithm were adopted to optimize the structure parameters of the framework. After optimization, the total weight of the CFC framework and the TC4 embedded parts is 15.6 kg, accounting for only 18.4% that of the camera. The first order frequency of the camera reaches 104.8 Hz. Finally, a mechanical environment test was performed, and the result demonstrates that the first order frequency of the camera is 102 Hz, which is consistent with the simulation result. It further verifies the rationality and correctness of the optimization result. The integrated optimization method mentioned in this paper can be applied to the structure design of other space cameras, which can greatly improve the structure design efficiency.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.16 no.4
• /
• pp.407-417
• /
• 2003

Enen though several GA-based optimization algorithms have been successfully applied to complex optimization problems in various engineering fields, GA-based optimization methods are computationally too expensive for practical use in the field of structural optimization, particularly for large- scale problems. Furthermore, a successful implementation of GA-based optimization algorithm requires a cumbersome and trial-and-error routine related to setting of parameters dependent on a optimization problem. Therefore, to overcome these disadvantages, a high-performance GA is developed in the form of distributed hybrid genetic algorithm for structural optimization on a cluster of personal computers. The distributed hybrid genetic algorithm proposed in this paper consist of a simple GA running on a master computer and multiple μ-GAs running on slave computers. The algorithm is implemented on a PC cluster and applied to the minimum weight design of steel structures. The results show that the computational time required for structural optimization process can be drastically reduced and the dependency on the parameters can be avoided.

• Earthquakes and Structures
• /
• v.23 no.1
• /
• pp.35-57
• /
• 2022

This article presents a computationally efficient framework for multi-objective seismic design optimization of steel moment-resisting frame (MRF) structures based on the nonlinear dynamic analysis procedure. This framework employs the uniform damage distribution philosophy to minimize the weight (initial cost) of the structure at different levels of damage. The preliminary framework was recently proposed by the authors based on the single excitation and the nonlinear static (pushover) analysis procedure, in which the effects of record-to-record variability as well as higher-order vibration modes were neglected. The present study investigates the reliability of the previous framework by extending the proposed algorithm using the nonlinear dynamic design procedure (optimization under multiple ground motions). Three benchmark structures, including 4-, 8-, and 12-story steel MRFs, representing the behavior of low-, mid-, and high-rise buildings, are utilized to evaluate the proposed framework. The total weight of the structure and the maximum inter-story drift ratio (IDRmax) resulting from the average response of the structure to a set of seven ground motion records are considered as two conflicting objectives for the optimization problem and are simultaneously minimized. The results of this study indicate that the optimization under several ground motions leads to almost similar outcomes in terms of optimization objectives to those are obtained from optimization under pushover analysis. However, investigation of optimal designs under a suite of 22 earthquake records reveals that the damage distribution in buildings designed by the nonlinear dynamic-based procedure is closer to the uniform distribution (desired target during the optimization process) compared to those designed according to the pushover procedure.

• Journal of Distribution Science
• /
• v.13 no.11
• /
• pp.123-130
• /
• 2015

Purpose - Due to highly elevated levels of competition, many companies today have to face the problem of decreasing profits even when their actual sales volume is increasing. This is a common phenomenon that is seen occurring among companies that focus heavily on quantitative growth rather than qualitative growth. These two aspects of growth should be well balanced for a company to create a sustainable business model. For supply chain management (SCM) planners, the optimized, quantified flow of resources used to be of major interest for decades. However, this trend is rapidly changing so that managers can put the appropriate balance between sales volume and sales quality, which can be evaluated from the profit margin. Profit optimization is a methodology for companies to use to achieve solutions focused more on profitability than sales volume. In this study, we attempt to provide executional insight for companies considering implementation of the profit optimization system to enhance their business profitability. Research design, data, and methodology - In this study, we present a comprehensive explanation of the subject of profit optimization, including the fundamental concepts, the most common profit optimization logic algorithm -linear programming -the business functional scope of the profit optimization system, major key success factors for implementing the profit optimization system at a business organization, and weekly level detailed business processes to actively manage effective system performance in achieving the goals of the system. Additionally, for the purpose of providing more realistic and practical information, we carefully investigate a profit optimization system implementation case study project fulfilled for company S. The project duration was about eight months, with four full-time system development consultants deployed for the period. To guarantee the project's success, the organization adopted a proven system implementation methodology, supply chain management (SCM) six-sigma. SCM six-sigma was originally developed by a group of talented consultants within Samsung SDS through focused efforts and investment in synthesizing SCM and six-sigma to improve and innovate their SCM operations across the entire Samsung Organization. Results - Profit optimization can enable a company to create sales and production plans focused on more profitable products and customers, resulting in sustainable growth. In this study, we explain the concept of profit optimization and prerequisites for successful implementation of the system. Furthermore, the efficient way of system security administration, one of the hottest topics today, is also addressed. Conclusion - This case study can benefit numerous companies that are eagerly searching for ways to break-through current profitability levels. We cannot guarantee that the decision to deploy the profit optimization system will bring success, but we can guarantee that with the help of our study, companies trying to implement profit optimization systems can minimize various possible risks across various system implementation phases. The actual system implementation case of the profit optimization project at company S introduced here can provide valuable lessons for both business organizations and research communities.

• Journal of Mechanical Science and Technology
• /
• v.20 no.4
• /
• pp.494-504
• /
• 2006

This research proposes a reliability-based topology optimization (RBTO) using the finite element method. RBTO is a topology optimization based on probabilistic (or reliability) constraints. Young's modulus, thickness, and loading are considered as the uncertain variables and RBTO is applied to static and eigenvalue problems. The RBTO problems are formulated and a sensitivity analysis is performed. In order to compute probability constraints, two methods-RIA and PMA-are used. Several examples show the effectiveness of the proposed method by comparing the classical safety factor method.