• 한국CDE학회논문집
• /
• 제16권3호
• /
• pp.236-245
• /
• 2011

Many researchers have recently studied multi-level formulation strategies to solve the MDO problems and they basically distributed the coupling compatibilities across all disciplines, while single-level formulations concentrate all the controls at the system-level. In addition, approximation techniques became remedies for computationally expensive analyses and simulations. This paper studies comparisons of the MDO methods with respect to computing performance considering both conventional sequential and modem distributed/parallel processing environments. The comparisons show Individual Disciplinary Feasible (IDF) formulation is the most efficient for sequential processing and IDF with approximation (IDFa) is the most efficient for parallel processing. Results incorporating to popular design examples show this finding. The author suggests design engineers should firstly choose IDF formulation to solve MDO problems because of its simplicity of implementation and not-bad performance. A single drawback of IDF is requiring more memory for local design variables and coupling variables. Adding cheap memories can save engineers valuable time and effort for complicated multi-level formulations and let them free out of no solution headache of Multi-Disciplinary Analysis (MDA) of the Multi-Disciplinary Feasible (MDF) formulation.

• 전기학회논문지
• /
• 제57권3호
• /
• pp.369-374
• /
• 2008

This paper presents the evaluation procedures and the estimation method for the estimation of optimal rebate level for EE(Energy Efficiency) programs. The penetration amount of each appliance is estimated by applying price function to preferred diffusion model resulted from model compatibility test. To estimate the optimal rebate level, two objective functions which express the maximum energy saving and operation benefit are introduced and by multi-objective function which can simultaneously consider two objective functions the optimal rebate level of each appliance is estimated. And then, using the decided rebate level and each penetration amount, the priority order for reasonable investment of each high-efficiency appliance is estimated compared to the results of conventional method. Finally, using a benefit/cost analysis based on California standard practice manual, the economic analysis is implemented for the four perspectives such as participant, ratepayer impact measure, program administrator cost and total resource cost.

• Earthquakes and Structures
• /
• 제7권3호
• /
• pp.271-294
• /
• 2014

In recent years, along with the advances made in performance-based design optimization, the need for fast calculation of response parameters in dynamic analysis procedures has become an important issue. The main problem in this field is the extremely high computational demand of time-history analyses which may convert the solution algorithm to illogical ones. Two simplifying strategies have shown to be very effective in tackling this problem; first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication, second, wavelet analysis of earthquake records decreasing the number of acceleration points involved in time-history loading. In this paper, we try to develop an efficient framework, using both strategies, to solve the performance-based multi-objective optimal design problem considering the initial cost and the seismic damage cost of steel moment-frame structures. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency (FEMA) recommended design specifications. The results from numerical application of the proposed framework demonstrate the capabilities of the framework in solving the present multi-objective optimization problem.

• Structural Engineering and Mechanics
• /
• 제63권6호
• /
• pp.825-835
• /
• 2017

Significant improvements to methodologies on structural damage detection (SDD) have emerged in recent years. However, many methods are related to inversion computation which is prone to be ill-posed or ill-conditioning, leading to low-computing efficiency or inaccurate results. To explore a more accurate solution with satisfactory efficiency, a PSO-INM algorithm, combining particle swarm optimization (PSO) algorithm and an improved Nelder-Mead method (INM), is proposed to solve multi-sample objective function defined based on Bayesian inference in this study. The PSO-based algorithm, as a heuristic algorithm, is reliable to explore solution to SDD problem converted into a constrained optimization problem in mathematics. And the multi-sample objective function provides a stable pattern under different level of noise. Advantages of multi-sample objective function and its superior over traditional objective function are studied. Numerical simulation results of a two-storey frame structure show that the proposed method is sensitive to multi-damage cases. For further confirming accuracy of the proposed method, the ASCE 4-storey benchmark frame structure subjected to single and multiple damage cases is employed. Different kinds of modal identification methods are utilized to extract structural modal data from noise-contaminating acceleration responses. The illustrated results show that the proposed method is efficient to exact locations and extents of induced damages in structures.

• 경영과학
• /
• 제31권3호
• /
• pp.61-76
• /
• 2014

There are three methods for calculating the optimal level for spare part inventories in a MIME (Multi Indenture and Multi Echelon) system : marginal analysis, Lagrangian relaxation method, and genetic algorithm. However, their solutions are sub-optimal solutions because the MIME system is neither convex nor separable by items. To be more specific, SRUs (Shop Replaceable Units) are required to fix a defected LRU (Line Replaceable Unit) because one LRU consists of several SRUs. Therefore, the level of both SRU and LRU cannot be calculated independently. Based on the limitations of three existing methods, we proposes a improved algorithm applying marginal analysis on determining LRU stock level and genetic algorithm on determining SRU stock level. It can draw optimal combinations on LRUs through separating SRUs. More, genetic algorithm enables to extend the solution search space of a SRU which is restricted in marginal analysis applying greedy algorithm. In the numerical analysis, we compare the performance of three existing methods and the proposed algorithm. The research model guarantees better results than the existing analytical methods. More, the performance variation of the proposed method is relatively low, which means one execution is enough to get the better result.

• Journal of Mechanical Science and Technology
• /
• 제20권1호
• /
• pp.133-146
• /
• 2006

Collaborative optimization (CO) is a multi-level decomposed methodology for a large-scale multidisciplinary design optimization (MDO). CO is known to have computational and organizational advantages. Its decomposed architecture removes a necessity of direct communication among disciplines, guaranteeing their autonomy. However, CO has several problems at convergence characteristics and computation time. In this study, such features are discussed and some suggestions are made to improve the performance of CO. Only for the system level optimization, genetic algorithm is used and gradient-based method is used for subspace optimizers. Moreover, response surface models are replaced as analyses in subspaces. In this manner, CO is applied to aero-structural design problems of the aircraft wing and its results are compared with the multidisciplinary feasible (MDF) method and the original CO. Through these results, it is verified that the suggested approach improves convergence characteristics and offers a proper solution.

• Journal of Computing Science and Engineering
• /
• 제6권4호
• /
• pp.294-309
• /
• 2012

In the age of multi-core and specialized accelerators in high performance computing (HPC) systems, it is critical to understand application characteristics and apply suitable optimizations in order to fully utilize advanced computing system. Often time, the process involves multiple stages of application performance diagnosis and a trial-and-error type of approach for optimization. In this study, a general guideline of performance optimization has been demonstrated with two class-representing applications. The main focuses are on node-level optimization and inter-node scalability improvement. While the number of optimization case studies is somewhat limited in this paper, the result provides insights into the systematic approach in HPC applications performance engineering.

• 한국신재생에너지학회:학술대회논문집
• /
• 한국신재생에너지학회 2005년도 제17회 워크샵 및 추계학술대회
• /
• pp.541-544
• /
• 2005

This study presents the integrated modeling approach to simulate the proton exchange membrane (PEM) fuel cell system for vehicle application. The fuel cell system consisting of stack and balance of plant (BOP) was simulated with MATLAB/Simulink environment to estimate the maximum system power and investigate the effect of BOP component sizing on system performance and efficiency. The PEM fuel cell stack model was established by using a semi-empirical modeling. To maximize the net efficiency of fuel cel1 system, multi-variable optimization code was adopted. Using this method the optimized operating values were obtained according to various system net power levels. The fuel cell model established was co-linked to AVL CRUISE, a vehicle simulation package. Through the vehicle simulation software, the fuel economy of fuel cell powered electric vehicle for two types of driving cycles was presented and compared. It is expected that this study tan be effectively employed in the basic BOP component sizing and in establishing system operation map with respect to net power level of fuel cell system.

• 한국안전학회지
• /
• 제33권2호
• /
• pp.61-67
• /
• 2018

This study proposes a new vibration control approach for adjacent twin structures, which is termed as viscous damper asymmetric coupling system in this paper. The proposed system takes a concept that the diagonal bracing viscous dampers are asymmetrically distributed in two buildings to break the behavior symmetry of the twin buildings and then the coupling viscous damper is additionally installed at the top floor of the two buildings to couple both buildings and interactively transfer the asymmetric behavior-caused damping forces into both buildings. These asymmetric damping distributions and interacting damping forces of the connection damper efficiently suppress the overall vibration of the damper-coupled adjacent twin buildings efficiently. Genetic algorithm (GA) based multi-objective optimization technique is adopted for optimal design of the proposed system. In the numerical example of adjacent twin 10-story building structures, the conventional control approach, that is, uniform damping distribution system (UDS) is also taken into account for comparison purpose. The optimization results verify that the proposed system either can improve the control performance over the UDS with the same damping capacity, or can save the damping capacity significantly while maintaining the similar level of control performance to the UDS.

• 신재생에너지
• /
• 제1권4호
• /
• pp.43-48
• /
• 2005

This study presents the integrated modeling approach to simulate the proton exchange membrane [PEM] fuel cell system for vehicle application. The fuel cell system consisting of stack and balance of plant (BOP) was simulated with MATLAB/Simulink environment to estimate the maximum system power and investigate the effect of BOP component sizing on system performance and efficiency. The PEM fuel cell stack model was established by using a semi-empirical modeling. To maximize the net efficiency of fuel cell system, multi-variable optimization code was adopted. Using this method, the optimized operating values were obtained according to various system net power levels. The fuel cell model established was co-linked to AVL CRUISE, a vehicle simulation package. Through the vehicle simulation software, the fuel economy of fuel cell powered electric vehicle for two types of driving cycles was presented and compared. It is expected that this study can be effectively employed in the basic BOP component sizing and in establishing system operation map with respect to net power level of fuel cell system.