• Computers and Concrete
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• 제19권5호
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• pp.589-597
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• 2017

Strut-and-tie modeling method, which evolved on truss-model approach, has generally been preferred for the design of complex reinforced concrete structures and structural elements that have critical shear behavior. Some structural members having disturbed regions require exceptional detailing for all support and loading conditions, such as the beam-column connections, deep beams, short columns or corbels. Considering the general expectation of exhibiting brittle behavior, corbels are somewhat dissimilar to other shear critical structures. In this study, reinforcement layout of a corbel model was determined by the participation of structural optimization and strut-and-tie modeling methods, and an experimental comparison was performed against a conventionally designed model.

• 조명전기설비학회논문지
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• 제26권4호
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• pp.14-21
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• 2012

This paper study a method of modeling and simulation of LED driver circuit for a design optimization. Simplified LED modeling is introduced and a driver IC, HV9910, is modeled by implementing the major function blocks. Circuit of buck type converter is constructed for simulation. Simulation includes not only the internal function of IC but also the various performance results such as LED array current control and dimming. Experiment results are also shown to prove the verification of its usage. This results show that the simulation approach is valid for a circuit optimization and a reduction of development time.

• Smart Structures and Systems
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• 제15권3호
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• pp.609-625
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• 2015

Management of infrastructure stock is essential in sustainability of society, and its analysis and optimization are studied in the light of control system modeling in this paper. At the first part of the paper, cost of stock management is analyzed based on macroscopic statistics on infrastructure stock and economical growth. Stock management burden relative to economy is observed to become larger at low economic growth periods in developed economies. Then, control system modeling of stock management is introduced and by augmenting maintenance actions as control input, dynamic behavior of stock is simulated and compared with existing time history statistics. Assuming steady state conditions, applicability of the model to cross sectional data is also demonstrated. The proposed model is enhanced so that both preventive and corrective maintenance can be included as system inputs, i.e., feedforward and feedback control inputs. Optimal management strategy to achieve specified deteriorated stock level with minimal cost, expressed in terms of preventive and corrective maintenance actions, is derived based on estimated parameter values for corrosion of steel bridges. Relative cost effectiveness of preventive maintenance is shown when target deteriorated stock level is lower.

• 제어로봇시스템학회논문지
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• 제7권12호
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• pp.985-992
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• 2001

This paper proposes a self-organizing fuzzy modeling(SOFUM)which an create a new hyperplane shaped cluster and adjust parameters of the fuzzy model in repetition. The suggested algorithm SOFUM is composed of four steps: coarse tuning. fine tuning cluster creation and optimization of learning rates. In the coarse tuning fuzzy C-regression model(FCRM) clustering and weighted recursive least squared (WRLS) algorithm are used and in the fine tuning gradient descent algorithm is used to adjust parameters of the fuzzy model precisely. In the cluster creation, a new hyperplane shaped cluster is created by applying multiple regression to input/output data with relatively large fuzzy entropy based on parameter tunings of fuzzy model. And learning rates are optimized by utilizing meiosis-genetic algorithm in the optimization of learning rates To check the effectiveness of the suggested algorithm two examples are examined and the performance of the identified fuzzy model is demonstrated via computer simulation.

• 항공우주시스템공학회지
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• 제8권4호
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• pp.18-23
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• 2014

In preliminary design phase, the wing geometry of the civil aircraft was determined using the empirical equation and historical data. To make wing geometry more aerodynamically efficient, an aerodynamic shape optimization was conducted. For this purpose the parametric modeling, high fidelity CFD analysis and metamodel-based optimal design technique were adopted. The parametric modeling got the design process to achieve the improvement by generating the configuration outputs easily for the major design variables. The optimal design equations were formularized as the type of the multi-objective functions considering low/high speed and lift/drag coefficient. The optimal solution was explored with the help of the kriging metamodel and the desirability function, therefore the optimal wing planform was sought to be excellent at both low and high speed region. Additionally the optimal wing planform was validated that it was excellent not only at the specific AOA, but also all over the range of AOA.

• 한국전기전자재료학회논문지
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• 제15권4호
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• pp.344-348
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• 2002

As microelectronics technology continues to progress, there is also a continuous demand on highly integration and miniaturization of systems. For example, it is desirable to package several integrated circuits together in multilayer structure, such as multichip modules, to achieve higher levels of compactness and higher performance. Passive components (i.e., capacitors, resistors, and inductors) are very important fort many MCM applications. In addition, the low-temperature co-fired ceramic (LTCC) process has considerable potential for embedding passive components in a small area at a low cost. In this paper, we investigate a method of statistically modeling integrated passive devices from just a small number of test structures. A set of LTCC inductors is fabricated and their scattering parameters (s-parameters) are measured for a range of frequencies from 50MHz to 5GHz. An accurate model for each test structure is obtained by using a building block based modeling methodology and circuit parameter optimization using the HSPICE circuit simulator.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2003년도 추계학술발표회 논문집
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• pp.341-345
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• 2003

This study develops modeling processes for alignment optimization considering characteristics of intersections using genetic algorithms and GIS for road alignment optimization. Since existing highway alignment optimization models have neglected the characteristics of intersections, they have shown serious weaknesses for real applications. In this paper, intersection costs include earthwork, right-of-way, pavement, accident, delay and fuel consumption costs that are sensitive and dominating to alignments. Also, local optimization of intersections for saving good alignment alternatives is developed and embedded. A highway alignment is described by parametric representation in space and vector manipulation is used to find the coordinates of intersections and other interesting points. The developed intersection cost estimation model is sufficiently precise for estimating intersection costs and eventually enhancing the performance of highway alignment optimization models. Also, local optimization of intersections can be used for improving search flexibility, thus allowing more effective intersections. It also provides a basis for extending the alignment optimization from single highways to networks. The presented two artificial examples show that the total intersection costs are substantial and sensitive to highway alignments.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.656-657
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• 2015

Recently, Multi-Objective Optimization of design elements is an important issue in building design. Design variables that considering the specificities of the different environments should use the appropriate algorithm on optimization process. The purpose of this study is to compare and analyze the optimal solution using three evolutionary algorithms and energy modeling simulation. This paper consists of three steps: i)Developing three evolutionary algorithm model for optimization of design elements ; ii) Conducting Multi-Objective Optimization based on the developed model ; iii) Conducting comparative analysis of the optimal solution from each of the algorithms. Including Non-dominated Sorted Genetic Algorithm (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO) and Random Search were used for optimization. Each algorithm showed similar range of result data. However, the execution speed of the optimization using the algorithm was shown a difference. NSGA-II showed the fastest execution speed. Moreover, the most optimal solution distribution is derived from NSGA-II.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2011년도 춘계학술대회 논문집
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• pp.1113-1114
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• 2011

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 추계학술대회
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• pp.870-875
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• 2004

Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, the robust design strategy is developed based on the DACE and the global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the system. The robustness is determined by the DACE model to reduce the real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.