• Earthquakes and Structures
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• v.20 no.2
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• pp.225-238
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• 2021

Supplemental passive dampers are widely employed to improve the structural performance of buildings under seismic excitations. Nevertheless, the added damping could be counter-productive if the axial forces induced by the damper reaction forces are not routed properly in the columns. A few researchers engaged to optimize the width-wise damper arrangement to improve the delivered path of the axial column forces. However, most of these studies are limited under the design-based seismic level and few of them has evaluated the collapse performance of buildings under strong earthquakes. In this paper, the strategic width-wise placement method of viscous dampers is explored regarding the building performance under collapse state. Two realistic steel buildings with different storeys are modelled and compared to explore higher mode effects. Each building is designed with four different damper arrangement scenarios based on a classic damper distribution method. Both a far-fault and a near-fault seismic environment are considered for the buildings. Incremental Dynamic Analysis (IDA) is performed to evaluate the probability of collapse and the plastic mechanism of the retrofitted steel buildings.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.10
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• pp.1223-1228
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• 2011

A moving-coil type linear actuator has been widely used in the system reciprocating short stroke because of its several advantages, such as the structural simplicity, low weight and a fast control response speed. This paper presents a design approach for improving the actuating performance with a clear expression of optimal configuration represented by a level set function. The optimization problem is formulated to minimize the variation of magnetic force at every moving displacement of the mover for fast and easy control. To consider the manufacturability of actuator, the concept of phase-field model is incorporated to control the complexity of structural boundaries. To verify the usefulness of the proposed method, the core design example of cylindrical linear actuator is performed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2356-2363
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• 2015

This study deals the optimization design with the simulation based design of a coil spring inserted into the lock nut for preventing the screw thread from loosening at the bolted joint when the high-strength steel bolt with the property class of 10.9 is used and the screw torque of 640 to 800 (Nm) is applied. In this study, structural analysis of assembly composed of bolt, nut and coil spring is carried out to evaluate its safety factors on the basis of the equivalent stress with commercial finite element analysis software. And the design strategy to extract the design improvement from these simulation results is established. An iterative process performed with the proposed design strategy is also proposed for improving the performance of the existing design. At the proposed procedure, the feasible design parameters using response surface method are found, and then these parameters are verified to be optimal or not by comparing with the response values and the simulation results obtained from the feasible parameters.

• Computers and Concrete
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• v.9 no.5
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• pp.327-340
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• 2012

The search for a design that meets both performance and safety, with minimal cost and lesser environmental impact was always the goal of structural engineers. In general, the design of conventional reinforced concrete structures is an iterative process based on rules of thumb established from the personal experience and intuition of the designer. However, such procedure makes the design process exhaustive and only occasionally leads to the best solution. In such context, this work presents the development and implementation of a mathematical formulation for obtaining optimal sections of reinforced concrete columns subjected to uniaxial flexural compression, based on the verification of strength proposed by the Brazilian standard NBR 6118 (ABNT 2007). To minimize the cost of the reinforced concrete columns, the Simulated Annealing optimization method was used, in which the amount and diameters of the reinforcement bars and the dimensions of the columns cross sections were considered as discrete variables. The results obtained were compared to those obtained from the conventional design procedure and other optimization methods, in an attempt to verify the influence of resistance class, variations in the magnitudes of bending moment and axial force, and material costs on the optimal design of reinforced concrete columns subjected to uniaxial flexural compression.

• Structural Engineering and Mechanics
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• v.49 no.1
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• pp.65-80
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• 2014

This paper reports on the development of a minimum cost design model and its application for obtaining economic designs for reinforced High Strength Concrete (HSC) T-sections in bending under ultimate limit state conditions. Cost objective functions, behavior constraint including material nonlinearities of steel and HSC, conditions on strain compatibility in steel and concrete and geometric design variable constraints are derived and implemented within the Conjugate Gradient optimization algorithm. Particular attention is paid to problem formulation, solution behavior and economic considerations. A typical example problem is considered to illustrate the applicability of the minimum cost design model and solution methodology. Results are confronted to design solutions derived from conventional design office methods to evaluate the performance of the cost model and its sensitivity to a wide range of unit cost ratios of construction materials and various classes of HSC described in Eurocode2. It is shown, among others that optimal solutions achieved using the present approach can lead to substantial savings in the amount of construction materials to be used. In addition, the proposed approach is practically simple, reliable and computationally effective compared to standard design procedures used in current engineering practice.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.12-14
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• 2005

In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks(SOFPNN) by means of genetically optimized fuzzy polynomial neuron(FPN) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms(GAs). The conventional SOFPNNs hinges on an extended Group Method of Data Handling(GMDH) and exploits a fixed fuzzy inference type in each FPN of the SOFPNN as well as considers a fixed number of input nodes located in each layer. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, a collection of the specific subset of input variables, and the number of membership function) and addresses specific aspects of parametric optimization. Therefore, the proposed SOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. To evaluate the performance of the genetically optimized SOFPNN, the model is experimented with using two time series data(gas furnace and chaotic time series).

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.3
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• pp.55-61
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• 2012

The structure of winch brake disk was successfully designed and developed based on sizing optimization. In this research, static analysis was performed by commercial software ANSYS v12.0. To simulate the working process of disk brake, the real properties of materials and working conditions were considered. Based on the results of the static structural analysis, the existing designs of the brake discs were optimized. Among existing designs, there are three cases that have achieved an efficient light weight around 200g. As a result, the optimized weight of each case was 3.41kg, 3.42kg, and 3.44kg, respectively. Finally, through prototyping and performance testing, the stability of the optimized brake disc was verified. Although, this free-fall winch brake disk had been developed in design and evaluation techniques, more detailed plans for developing the disk brake structure were also proposed as a further study based on this research.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.207-209
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• 2007

In this paper, we introduce a genetic optimization of fuzzy set-fuzzy model using successive tuning method to carry out the model identification of complex and nonlinear systems. To identity we use genetic alrogithrt1 (GA) sand C-Means clustering. GA is used for determination the number of input, the seleced input variables, the number of membership function, and the conclusion inference type. Information Granules (IG) with the aid of C-Means clustering algorithm help determine the initial paramters of fuzzy model such as the initial apexes of the, membership functions in the premise part and the initial values of polyminial functions in the consequence part of the fuzzy rules. The overall design arises as a hybrid structural and parametric optimization. Genetic algorithms and C-Means clustering are used to generate the structurally as well as parametrically optimized fuzzy model. To identify the structure and estimate parameters of the fuzzy model we introduce the successive tuning method with variant generation-based evolution by means of GA. Numerical example is included to evaluate the performance of the proposed model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.10 s.241
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• pp.1369-1376
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• 2005

In structural design, the design variables are frequently selected from certain discrete values. Various optimization algorithms have been developed fDr discrete design. It is well known that many function evaluations are needed in such optimization. Recently, sequential algorithm with orthogonal arrays (SOA), which is a search algorithm for a local minimum in a discrete space, has been developed. It considerably reduces the number of function evaluations. However, it only finds a local minimum and the final solution depends on the initial values of the design variables. A new algorithm is proposed to adopt a genetic algorithm (GA) in SOA. The GA can find a solution in a global sense. The solution from the GA is used as the initial design of SOA. A sequential usage of the GA and SOA is carried out in an iterative manner until the convergence criteria are satisfied. The performance of the algorithm is evaluated by various examples.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.127-136
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• 2005

In this paper, a new architecture and comprehensive design methodology of genetically optimized Rule-based Fuzzy Polynomial Neural Networks(gRFPNN) are introduced and a series of numeric experiments are carried out. The architecture of the resulting gRFPNN results from asynergistic usage of the hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks (PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the gRFPNN. The consequence part of the gRFPNN is designed using PNNs. At the premise part of the gRFPNN, FNN exploits fuzzy set based approach designed by using space partitioning in terms of individual variables and comes in two fuzzy inference forms: simplified and linear. As the consequence part of the gRFPNN, the development of the genetically optimized PNN dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the gRFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed gRFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.