• Earthquakes and Structures
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• v.27 no.4
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• pp.285-302
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• 2024

Conducting nonlinear pushover analysis typically demands intricate and resource-intensive computational efforts, involving a highly iterative process necessary for meeting both design-defined and requirements of codes in performance-based design. This study presents a computer-based technique for reinforced concrete (RC) buildings, incorporating optimization numerical approaches, optimality criteria and pushover analysis to automatically enhance seismic design performance. The optimal design of concrete beams, columns and shear walls in concrete frames is presented using the artificial bee colony optimization algorithm. The methodology is applied to three frames: a 4-story, an 8-story and a 12-story. These structures are designed to minimize overall weight while satisfying the levels of performance including Life Safety (LS), Collapse Prevention (CP), and Immediate Occupancy (IO). The process involves three main steps: first, optimization codes are implemented in MATLAB software, and the OpenSees software is used for nonlinear static analysis. By solving the optimization problem, several top designs are obtained for each frame and shear wall. Pushover analysis is conducted considering the constraints on relative displacement and plastic hinge rotation based on the nonlinear provisions of the FEMA356 nonlinear provisions to achieve each level of performance. Subsequently, convergence, pushover, and drift history curves are plotted for each frame, and leading to the selection of the best design. The results demonstrate that the algorithm effectively achieves optimal designs with reduced weight, meeting the desired performance criteria.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2610-2624
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• 2024

Liquid metal heat pipes play a critical role in various high-temperature applications, with their optimization being pivotal to achieving optimal thermal performance. In this study, a deep learning based genetic algorithm is suggested to optimize the operating conditions of liquid metal heat pipes. The optimization performance was investigated in both single and multi-variable optimization schemes, considering the operating conditions of heat load, inclination angle, and filling ratio. The single-variable optimization indicated reasonable performance for various conditions, reinforcing the potential applicability of the optimization method across a broad spectrum of high-temperature industries. The multi-variable optimization revealed an almost congruent performance level to single-variable optimization, suggesting that the robustness of optimization method is not compromised with additional variables. Furthermore, the generalization performance of the optimization method was investigated by conducting an experimental investigation, proving a similar performance. This study underlines the potential of optimizing the operating condition of heat pipes, with significant consequences in sectors such as high temperature field, thereby offering a pathway to more efficient, cost-effective thermal solutions.

• Structural Engineering and Mechanics
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• v.53 no.4
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• pp.833-845
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• 2015

Natural frequencies of the structural systems should be far away from the excitation frequency in order to avoid or reduce the destructive effects of dynamic loads on structures. To accomplish this goal, a structural optimization on size and shape has been performed considering frequency constraints. Such an optimization problem has highly nonlinear property. Thus, the quality of the solution is not independent of the optimization technique to be applied. This study presents the performance evaluation of the recently proposed meta-heuristic algorithm called Teaching Learning Based Optimization (TLBO) as an optimization engine in the weight optimization of the truss structures under frequency constraints. Some examples regarding the optimization of trusses on shape and size with frequency constraints are solved. Also, the results obtained are tabulated for comparison. The results demonstrated that the performance of the TLBO is satisfactory. Additionally, TLBO is better than other methods in some cases.

• Journal of Digital Convergence
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• v.10 no.4
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• pp.207-215
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• 2012

This paper proposes a proxy-based caching optimization scheme for improving the streaming media services in wireless mobile ad hoc networks. The proposed scheme utilizes the proxy for data packet transmission between media server and nodes in WLANs, and the proxy locates near the wireless access pointer. For caching optimization, this paper proposes NFCO (non-full cache optimization) and CFO (cache full optimization) scheme. When performs the streaming in the proxy, the NFCO and CFO is to optimize the caching performance. This paper compared the performance for optimization between the proposed scheme and the server-based scheme and rate-distortion scheme. Simulation results show that the proposed scheme has better performance than the existing server-only scheme and rate distortion scheme.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.182-191
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• 2011

Genetic algorithms (GA) and particle swarm optimization (PSO) are the most famous optimization techniques among various modern heuristic optimization techniques. These two approaches identify the solution to a given objective function, but they employ different strategies and computational effort; therefore, a comparison of their performance is needed. This paper presents the application and performance comparison of the PSO and GA optimization techniques for a static synchronous series compensator-based controller design. The design objective is to enhance power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem, and both PSO and GA optimization techniques are employed to search for the optimal controller parameters.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.637-644
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• 2010

This paper presents a reliability-based shape optimization (RBSO) using the growth-strain method. An actual design involves uncertain conditions such as material property, operational load, Poisson's ratio and dimensional variation. The purpose of the RBSO is to consider the variations of probabilistic constraint and performances caused by uncertainties. In this study, the growth-strain method was applied to shape optimization of reliability analysis. Even though many papers for reliability-based shape optimization in mathematical programming method and ESO (Evolutionary Structural Optimization) were published, the paper for the reliability-based shape optimization using the growth-strain method has not been applied yet. Growth-strain method is applied to performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints in the change of average mises stress. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization. It was verified that the reliability-based shape optimization using growth-strain method are very effective for general structure. The purpose of this study is to improve structure's safety considering probabilistic variable.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2125-2138
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• 2023

The printed circuit heat exchanger (PCHE) with airfoil fins has the benefits of high compactness, high efficiency and superior heat transfer performance. A novel multi-objective optimization approach is presented to design the airfoil fin PCHE in this paper. Three optimization design variables (the vertical number, the horizontal number and the staggered number) are obtained by means of dimensionless airfoil fin arrangement parameters. And the optimization objective is to maximize the Nusselt number (Nu) and minimize the Fanning friction factor (f). Firstly, in order to investigate the impact of design variables on the thermal-hydraulic performance, a parametric study via the design of experiments is proposed. Subsequently, the relationships between three optimization design variables and two objective functions (Nu and f) are characterized by an improved particle swarm optimization-backpropagation artificial neural network. Finally, a multi-objective optimization is used to construct the Pareto optimal front, in which the non-dominated sorting genetic algorithm II is used. The comprehensive performance is found to be the best when the airfoil fins are completely staggered arrangement. And the best compromise solution based on the TOPSIS method is identified as the optimal solution, which can achieve the requirement of high heat transfer performance and low flow resistance.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2542-2547
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• 2005

In this paper, we propose a support vector machine (SVM) hyper and kernel parameter optimization method which is based on minimizing radius/margin bound which is a kind of estimation of leave-one-error. This method uses dynamic encoding algorithm for search (DEAS) and gradient information for better optimization performance. DEAS is a recently proposed optimization algorithm which is based on variable length binary encoding method. This method has less computation time than genetic algorithm (GA) based and grid search based methods and better performance on finding global optimal value than gradient based methods. It is very efficient in practical applications. Hand-written letter data of MNI steel are used to evaluate the performance.

• Steel and Composite Structures
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• v.27 no.5
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• pp.613-622
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• 2018

The requirement to safe and economical buildings caused to the exploitation of nonlinear capacity structures and optimization of them. This requirement leads to forming seismic design method based on performance. In this study, concentrically braced frames (CBFs) have been optimized at the immediate occupancy (IO) and collapse prevention (CP) levels. Minimizing structural weight is taken as objective function subjected to performance constraints on inter-story drift ratios at various performance levels. In order to evaluate the seismic capacity of the CBFs, pushover analysis is conducted, and the process of optimization has been done by using Bee Algorithm. Results indicate that performance based design caused to have minimum structural weight and due to increase capacity of CBFs.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.691-697
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• 2010

Reliability-based topology optimization (RBTO) is to get an optimal topology satisfying uncertainties of design variables. In this study, reliability-based topology optimization method is applied to the inner reinforcement of vehicle's hood based on BESO. A multi-objective topology optimization technique was implemented to obtain optimal topology of the inner reinforcement of the hood. considering the static stiffness of bending and torsion as well as natural frequency. Performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints. To evaluate the obtained optimal topology by RBTO, it is compared with that of DTO of the inner reinforcement of the hood. It is found that the more suitable topology is obtained through RBTO than DTO even though the final volume of RBTO is a little bit larger than that of DTO. From the result, multiobjective optimization technique based on the BESO can be applied very effectively in topology optimization for vehicle's hood reinforcement considering the static stiffness of bending and torsion as well as natural frequency.