• 한국전자파학회논문지
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• 제11권3호
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• pp.345-351
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• 2000

본 논문에서는 Ka 대역 마이크로스트립 도파관 변환기를 설계하고, Expanding-cell 시간 영역 유한 차분법을 이용하여 변환기의 주파수 특성을 분석하였다. 마이크로스트립 도파관 변환기의 구조는 릿지(ridge)형 도파관, 마이크로스트립 라인, 그리고 $\lambda$/4 체비쉐프 도파관 임피던스 변환기로 이루어졌다 .. Expanding-cell 유한차분 방법을 마이크로스트립-도파관 변환기의 $\lambda$/4 체비쉐프 도파관 임피던스 변환기의 해석에 이용하여 계산의 정 확성과 효율성을 높였다. 계산 결과를 측정치와 비교하여 정확성을 입증하고, 균일한 크기의 미세 셀(fine cell) 과 성긴 셀(coarse cell)을 이용한 결과와 비교하여 효율성을 입증하였다 .. 4단과 3단 체비쉐프 도파관 임피던스 변환기의 주파수 특성을 비교하여 단의 수와 대역폭과의 관계를 분석하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.442-445
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• 1997

We present a hybrid self-tuning method of fuzzy inference systems with hyper elliptic Gaussian membership functions using genetic algorithm(GA) and back-propagation algorithm. The proposed self-tuning method has two phases : one is the coarse tuning process based on GA and the other is the fine tuning process based on back-propagation. But the parameters which is obtained by a GA are near optimal solutions. In order to solve the problem in GA applications, it uses a back-propagation algorithm, which is one of learning algorithms in neural networks, to finely tune the parameters obtained by a GA. We provide Box-Jenkins time series to evaluate the advantage and effectiveness of the proposed approach and compare with the conventional method.

• 산업공학
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• 제10권3호
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• pp.125-132
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• 1997

We proposed a 2-step neural network approach for estimating machining parameters of electric discharge wire cut. The first step net, which is described as a backward neuro-estimation, is designed for estimating coarse cutting parameters while the second phase net, as a polishing forward neuro-estimation, is utilized for determining fine parameters. Sequential estimation procedure, based on backward and forward net, is performed using the net's approximation capability which is M to 1 and 1 to M mapping property. Experimental results an given to evaluate the accuracy of the proposed 2-step neuro-estimation.

• 설비공학논문집
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• 제5권4호
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• pp.243-248
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• 1993

In this research, unsteady groundwater flow in unconfined and homogeneous three layer aquifers is studied theoretically and experimentally. Numerical solutions are obtained by Runge Kutta and Runge Kutta Gill method after transforming the governing nonlinear partial differential equations to nonlinear ordinary differential equations. Experimental apparatus includes a test section filled with fine, medium and coarse sands. Experimental results are compared with the numerical solutions and both experimental and numerical results correspond well with each other. This numerical approach may be also applied to the cases which have more aquifers.

• Wind and Structures
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• 제13권5호
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• pp.385-412
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• 2010

This article provides a time-resolved characterisation of the wind field in a recently-commissioned, downdraft outflow simulator at The University of Western Ontario. A large slot jet approach to physical simulation was used. The simulator performance was assessed against field observations from a 2002 downdraft outflow near Lubbock, Texas. Outflow wind speed records were decomposed according to classical time series analysis. Length scales, characterising the coarse and fine flow structure, were determined from the time-varying mean and residual components, respectively. The simulated downdraft outflow was approximately 1200 times smaller in spatial extent than the 2002 Lubbock event.

• 한국지하수토양환경학회지:지하수토양환경
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• 제15권2호
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• pp.47-54
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• 2010

Although the demands for the dredging work have been increasing due to social and industrial reasons including national plan for restoration of four major rivers, environmental standards or management guidelines for the dredged river sediment are limited. The suggested environmental standard for the beneficial use of dredged river sediment consists of two levels, recyclable and concern, and includes eight contaminants such as metals and organic contaminants. The systematic approach to remediate dredged river sediment is also suggested. The system consists of both washing and stabilization processes with continuous multi particle separation. In the early stage, the sediments are separated into two particle sizes. The coarse-grained sediment over 0.075 mm, generally decontaminated with less trouble, follows normal washing steps and is sent for recycling. The fine-grained sediments under 0.075 mm are separated again at 0.025 mm. The particles bigger than this second separation point are treated in two ways, advanced washing for highly contaminated sediments and stabilization for less. The lab test results show that birnessite and apatite are most effective stabilizing agents among tested for Cd and Pb. The most fine residues, down-sized by continuous particle separation, are finally sent for disposal. The system is tested for metals in this study, but is expected to be effective for organic contaminants included in the environmental standard, such as PAH and PCE. The feasibility test on the field site will be followed.

• 대한조선학회논문집
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• 제54권6호
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• pp.476-484
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• 2017

The purpose of this paper is to verify the structural integrity of a region with numerous penetration-holes in offshore structures such as semi-submersible rig and FPSO. In order to effectively check the yielding and buckling strength of plate members with penetration-holes, a screening analysis program was developed with the FE analysis tool to generate fine meshed model using the theoretical and analysis methods. When a hole is appeared in the plate structure members, the flow of stress is altered such that concentrations of stress form near the hole. Stress concentrations are of concern during both preliminary and detail design and need to be addressed from the perspectives of strength. To configure the geometrical shape, very fine meshed FE analysis is needed as the most accurate method. However, this method is practically impossible to apply for the strength verifications for all perforated plates. In this paper, screening analysis method was introduced to reduce analysis tasks prior to detailed FE analysis. This method is applied to not only the peak stress calculation combined stress concentration factor with nominal stress but also nominal equivalent stress calculation considering cutout effects. The areas investigated by very fine meshed analysis were to be chosen through screening analysis without any reinforcements for penetration-holes. If screening analysis results did not satisfy the acceptance criteria, direct FE analysis method as the 2nd step approach were applied with one of the coarse meshed model considering hole or with the very fine meshed model considering the hole shape and size. In order to effectively perform the local fine meshed analysis, automatic model generating program was developed based on the MSC/PATRAN which is pre-post FE analysis program. Buckling strength was also evaluated by Common Structure Rule (CSR) adopted by IACS as the stress obtained from very fine meshed FE analysis. Due to development of the screening analysis program and automatic FE modeling program, it was able to reduce the design periods and structural analysis costs.

• Structural Engineering and Mechanics
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• 제86권2호
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• pp.181-195
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• 2023

To predict the rheological behaviours along with the compressive strength of self-compacting concrete that incorporates environmentally friendly ingredients as cement substitutes, a comparative evaluation of machine learning methods is conducted. To model four parameters, slump flow diameter, L-box ratio, V-funnel time, as well as compressive strength at 28 days-a complete mix design dataset from available pieces of literature is gathered and used to construct the suggested machine learning standards, SVM, MARS, and Mp5-MT. Six input variables-the amount of binder, the percentage of SCMs, the proportion of water to the binder, the amount of fine and coarse aggregates, and the amount of superplasticizer are grouped in a particular pattern. For optimizing the hyper-parameters of the MARS model with the lowest possible prediction error, a gravitational search algorithm (GSA) is required. In terms of the correlation coefficient for modelling slump flow diameter, L-box ratio, V-funnel duration, and compressive strength, the prediction results showed that MARS combined with GSA could improve the accuracy of the solo MARS model with 1.35%, 11.1%, 2.3%, as well as 1.07%. By contrast, Mp5-MT often demonstrates greater identification capability and more accurate prediction in comparison to MARS-GSA, and it may be regarded as an efficient approach to forecasting the rheological behaviors and compressive strength of SCC in infrastructure practice.

• 대한의용생체공학회:의공학회지
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• 제29권2호
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• pp.122-131
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• 2008

For B-mode ultrasound images, we propose an image enhancement algorithm based on a multi-resolution approach, which consists of edge enhancing and noise reducing procedures. Edge enhancement processing is applied sequentially to coarse-to-fine resolution images obtained from wavelet-transformed data. In each resolution, the structural features of each pixel are examined through eigen analysis. Then, if a pixel belongs to an edge region, we perform two-step filtering: that is, directional smoothing is conducted along the tangential direction of the edge to improve continuity and directional sharpening is conducted along the normal direction to enhance the contrast. In addition, speckle noise is alleviated by proper attenuation of the wavelet coefficients of the homogeneous regions at each band. This region-based speckle-reduction scheme is differentiated from other methods that are based on the magnitude statistics of the wavelet coefficients. The proposed algorithm enhances edges regardless of changes in the resolution of an image, and the algorithm efficiently reduces speckle noise without affecting the sharpness of the edge. Hence, compared with existing algorithms, the proposed algorithm considerably improves the subjective image quality without providing any noticeable artifacts.

• Computers and Concrete
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• 제21권6호
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• pp.697-703
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• 2018

Compressive strength is one of the most important engineering properties of concrete, and testing of the compressive strength of concrete specimens is often costly and time consuming. In order to provide the time for concrete form removal, re-shoring to slab, project scheduling and quality control, it is necessary to predict the concrete strength based upon the early strength data. However, concrete compressive strength is affected by many factors, such as quality of raw materials, water cement ratio, ratio of fine aggregate to coarse aggregate, age of concrete, compaction of concrete, temperature, relative humidity and curing of concrete. The concrete compressive strength is a quite nonlinear function that changes depend on the materials used in the concrete and the time. This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for the prediction of concrete compressive strength. The training of fuzzy system was performed by a hybrid method of gradient descent method and least squares algorithm, and the subtractive clustering algorithm (SCA) was utilized for optimizing the number of fuzzy rules. Experimental data on concrete compressive strength in the literature were used to validate and evaluate the performance of the proposed ANFIS model. Further, predictions from three models (the back propagation neural network model, the statistics model, and the ANFIS model) were compared with the experimental data. The results show that the proposed ANFIS model is a feasible, efficient, and accurate tool for predicting the concrete compressive strength.