• Structural Engineering and Mechanics
• /
• v.25 no.1
• /
• pp.53-73
• /
• 2007

In this study, an effective load increment method for multi modal adaptive non-linear static (pushover) analysis (NSA) for building type structures is presented. In the method, lumped plastisicity approach is adopted and geometrical non-linearties (second-order effects) are included. Non-linear yield conditions of column elements and geometrical non-linearity effects between successive plastic sections are linearized. Thus, load increment needed for formation of plastic sections can be determined directly (without applying iteration or step-by-step techniques) by using linearized yield conditions. After formation of each plastic section, the higher mode effects are considered by utilizing the essentials of traditional response spectrum analysis at linearized regions between plastic sections. Changing dynamic properties due to plastification in the system are used on the calculation of modal lateral loads. Thus, the effects of stiffness changes and local mechanism at the system on lateral load distribution are included. By using the proposed method, solution can be obtained effectively for multi-mode whereby the properties change due to plastifications in the system. In the study, a new procedure for determination of modal lateral loads is also proposed. In order to evaluate the proposed method, a 20 story RC frame building is analyzed and compared with Non-linear Dynamic Analysis (NDA) results and FEMA 356 Non-linear Static Analysis (NSA) procedures using fixed loads distributions (first mode, SRSS and uniform distribution) in terms of different parameters. Second-order effects on response quantities and periods are also investigated. When the NDA results are taken as reference, it is seen that proposed method yield generally better results than all FEMA 356 procedures for all investigated response quantities.

• KIPS Transactions on Computer and Communication Systems
• /
• v.10 no.5
• /
• pp.155-162
• /
• 2021

n-step TD learning is a combination of Monte Carlo method and one-step TD learning. If appropriate n is selected, n-step TD learning is known as an algorithm that performs better than Monte Carlo method and 1-step TD learning, but it is difficult to select the best values of n. In order to solve the difficulty of selecting the values of n in n-step TD learning, in this paper, using the characteristic that overestimation of Q can improve the performance of initial learning and that all n-step returns have similar values for Q ≈ Q^*, we propose a new learning target, which is composed of the maximum and the mean of all k-step returns for 1 ≤ k ≤ n. Finally, in OpenAI Gym's Atari game environment, we compare the proposed algorithm with n-step TD learning and proved that the proposed algorithm is superior to n-step TD learning algorithm.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2000.10a
• /
• pp.443-448
• /
• 2000

In this paper, multiphase optimization of machine structure is presented. The goal of first step is to obtain (i) light weight, (ii) rigidity statically. In this step, multiple optimization problem with two objective functions is treated using Pareto Genetic Algorithm. Where two objective functions are weight of the structure, and static compliance. The method is applied to a new machine structure design.

• KIEE International Transactions on Electrophysics and Applications
• /
• v.4C no.2
• /
• pp.55-59
• /
• 2004

Throughout manufacturing processes, pulse shaping is required for material processing and it is regarded as an important (actor according to the specific characteristics of materials. Therefore, this study suggests a highly appropriate pulse shaping technique using a multi-switching method. This is a pulse superposition method in which one flash lamp can consecutively turn on by the double switching of the discharging system. It is possible to construct a variety of pulse shapes and pulse widths by the consecutive trigger of the silicon-controlled rectifiers (SCR) of a PIC (program integrated circuit) one-chip microprocessor. The use of this technique can provide a number of advantages to people who require suitable pulse shaping for particular applications such as welding, cutting, and drilling.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2007.11a
• /
• pp.121-129
• /
• 2007

Recently a multi-attribute structure analysis method is one of the evident areas of important points in the decision support system analysis. This research developed an internet/intranet-based solution builder for a three-step decision support system using fuzzy-AHP in the view of 1) brainstorming far the idea generation, 2) fuzzy-AHP (fuzzy analytic hierarchy process) as a multi-attribute structured analysis method and 3) aggregation logic model to integrate the results of individual analysis. We applied this decision support system to the make-or-buy decision problem for school foodservice system considering the multi-attributes in the decision making. A computer program is developed and demonstrated it internet/intranet-based decision problem. It was known that this solution builder provides decision makers a good tool for mate-of-buy group decision making.

• Transactions of Materials Processing
• /
• v.30 no.1
• /
• pp.27-34
• /
• 2021

In this study, response surface method (RSM) was used in modeling and multi-objective optimization of the parameters of AA5052-H32 in incremental sheet forming (ISF). The goals of optimization were the maximum forming angle, minimum thickness reduction, and minimum surface roughness, with varying values in response to changes in production process parameters, such as tool diameter, tool spindle speed, step depth, and tool feed rate. A Box-Behnken experimental design (BBD) was used to develop an RSM model for modeling the variations in the forming angle, thickness reduction, and surface roughness in response to variations in process parameters. Subsequently, the RSM model was used as the fitness function for multi-objective optimization of the ISF process based on experimental design. The results showed that RSM can be effectively used to control the forming angle, thickness reduction, and surface roughness.

• Journal of the Korean Society for Precision Engineering
• /
• v.17 no.10
• /
• pp.192-199
• /
• 2000

The design of multi-stage gear drives is a time-consuming process because it includes more complicated problems, which are not considered in the design of single-stage gear drives. The designer has no determine the number of reduction stages and the gear ratios of each reduction stage. In addition, the design problems include not only dimensional design but also configuration design of gear drive elements. There is no definite rule or principle for these types of design problems. Thus the design practices largely depend on the sense and the experiences of the designer, and consequently result in undesirable design solution. A new and generalized design algorithm has been proposed to support the designer at the preliminary phase of the design of multi-stage gear drives. The proposed design algorithm automates the design process by integrating the dimensional design and the configuration design process. The algorithm consists of four steps. In the first step, the user determines the number of reduction stages. In the second step, gear ratios of every stage are chosen using the random search method. The values of the basic design parameters of a gear are chose in the third step by using the generate and test method. Then the values of the dimensions, such as pitch diameter, outer diameter and face width, are calculated for the configuration design in the next step. The strength and durability of each gear is guaranteed by the bending strength and the pitting resistance rating practices by using AGMA rating formulas. In the final step, the configuration design is carried out using simulated annealing algorithm. The positions of gears and shafts are determined to minimize the geometrical volume (size) of a gearbox while avoiding interferences between them. These steps are carried out iteratively until a desirable solution is acquired. The proposed design algorithm is applied to the preliminary design of four-stage gear drives in order to validate the availability. The design solution has considerably good results in both aspects of the dimensional and the configuration design.

• The Journal of the Acoustical Society of Korea
• /
• v.22 no.4
• /
• pp.315-322
• /
• 2003

We propose a channel-attentive Mel frequency cepstral coefficient (CAMFCC) extraction method to improve the recognition performance of speech that is partially corrupted in the frequency domain. This method introduces weighting terms both at the filter bank analysis step and at the output probability calculation of decoding step. The weights are obtained for each frequency channel of filter bank such that the more reliable channel is emphasized by a higher weight value. Experimental results on TIDIGITS database corrupted by various frequency-selective noises indicated that the proposed CAMFCC method utilizes the uncorrupted speech information well, improving the recognition performance by 11.2% on average in comparison to a multi-band speech recognition system.

• Smart Structures and Systems
• /
• v.12 no.3_4
• /
• pp.345-361
• /
• 2013

Locating and assessing the severity of damage in large or complex structures is one of the most challenging problems in the field of civil engineering. Considering that the wavelet packet transform (WPT) has the ability to clearly reflect the damage characteristics of structural response signals and the artificial neural network (ANN) is capable of learning in an unsupervised manner and of forming new classes when the structural exhibits change, this paper investigates a multi-stage structural damage diagnosis method by using the WPT and ANN based on "energy-damage" theory, in which, the wavelet packet component energies are first extracted to be damage sensitive feature and then adopted as input into an improved back propagation (BP) neural network model for damage diagnosis in a step by step mode. To validate the efficacy of the presented approach of the damage diagnosis, the benchmark structure of the American Society of Civil Engineers (ASCE) is employed in the case study. The results of damage diagnosis indicate that the method herein is computationally efficient and is able to detect the existence of different damage patterns in the simulated experiment where minor, moderate and severe damages corresponds to involving in the loss of stiffness on braces or the removal bracing in various combinations.

• Smart Structures and Systems
• /
• v.11 no.4
• /
• pp.331-348
• /
• 2013

Effective monitoring, reliable data analysis, and rational data interpretations are challenges for engineers who are specialized in bridge health monitoring. This paper demonstrates how to use the Global Positioning System (GPS) and accelerometer data to accurately extract static and quasi-static displacements of the bridge induced by ambient effects. To eliminate the disadvantages of the two separate units, based on the characteristics of the bias terms derived from the GPS and accelerometer respectively, a wavelet based multi-step filtering method by combining the merits of the continuous wavelet transform (CWT) with the discrete stationary wavelet transform (SWT) is proposed so as to address the GPS deformation monitoring application more efficiently. The field measurements are carried out on an existing suspension bridge under the normal operation without any traffic interference. Experimental results showed that the frequencies and absolute displacements of the bridge can be accurate extracted by the proposed method. The integration of GPS and accelerometer can be used as a reliable tool to characterize the dynamic behavior of large structures such as suspension bridges undergoing environmental loads.