• 전산구조공학
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• 제8권4호
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• pp.117-127
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• 1995

이 연구의 목적은 단조하중과 반복하중을 받는 철근콘크리트 면부재 해석에 대한 이방향성 회전 직교축 모델의 성능을 검토하기 위함이다. 여기서 다루는 구조부재는 철근에 의하여 적절히 보강된 보, 기둥, 보-기둥 접합부, 그리고 전단벽등으로 부재의 파괴가 인장균열후 압축파괴에 의하여 일어나는 부재이다. 보통 단조하중에 대하여 사용도는 이방향성 회전 직교축 모델을 반복하중에 대하여 확장하며, 철근과 부착의 기존 재료모델과 함꼐 유한요소해석에 사용한다. 단조하중에 대하여 이방향성 회전 직교축 모델을 사용한 해석 결과는 취성파괴를 나타내는 철근콘크리트보의 실험결과와 비교된다. 또한 반복하중을 받는 전단벽의 극한하중, 비선형 변형, 핀칭 현상 등에 대하여 실험결과와 비교된다.

• 한국수소및신에너지학회논문집
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• 제26권3호
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• pp.294-299
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• 2015

Free piston linear engine (FPLE) is a promising concept being explored in the mid-20th century. On the other hand, Arficial neural networks (ANNs) are non-linear computer algorithms and can model the behavior of complicated non-linear processes. Some researchers already studied this method to predict internal combustion engine characteristics. However, no investigation to predict the performance of a FPLE using ANN approach appears to have been published in the literature to date. In this study, the ability of an artificial neural network model, using a back propagation learning algorithm has been used to predict the in-cylinder pressure, frequency, maximum stroke length of a free piston linear engine. It is advised that, well-trained neural network models can provide fast and consistent results, making it an easy-to-use tool in preliminary studies for such thermal engineering problems.

• 한국지능시스템학회논문지
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• 제14권5호
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• pp.660-665
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• 2004

In this study, a new architecture and comprehensive design methodology of genetically optimized Multi-layer Fuzzy Neural Networks (gMFNN) are introduced and a series of numeric experiments are carried out. The gMFNN architecture results from a synergistic usage of the hybrid system generated by combining Fuzzy Neural Networks (FNN) with Polynomial Neural Networks (PNN). FNN contributes to the formation of the premise part of the overall network structure of the gMFNN. The consequence part of the gMFNN is designed using PNN. The optimization of the FNN is realized with the aid of a standard back-propagation learning algorithm and genetic optimization. The development of the PNN dwells on the extended Group Method of Data Handling (GMDH) method and Genetic Algorithms (GAs). To evaluate the performance of the gMFNN, the models are experimented with the use of a numerical example.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2006년도 6th International Meeting on Information Display
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• pp.733-738
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• 2006

As the film transistor-liquid crystal display (TFTLCD) panels become larger and provide higher resolution, the propagation delay of row and column lines, the voltage modulation of Vcom, and the response time of liquid crystal affect the display images now more than in the past. It is more important to understand the electrical characteristic of TFT-LCD panels these days. This paper describes the electrical model of a 15-inch XGA ($1024{\times}768$) TFT-LCD panel. The parasitic resistance and capacitance of its panel are obtained by 3D simulation of a sub pixel. The accuracy of these data is verified by the measured values in an actual panel [1]. The developed panel simulation platform, the equivalent circuit of a 15-inch XGA panel, is simulated by HSPICE. The results of simulation are compared with those of experiment, according to changing the width of signal. Especially, the proposed simulation platform for modeling TFTLCD panels can be applied to large size LCD TVs. It can help panel and circuit designers to verify their ideas without making actual panels and circuits.

• Journal of Communications and Networks
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• 제7권4호
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• pp.450-461
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• 2005

In this paper, we derive analytical expressions for the exact pairwise error probability (PEP) of a space-time coded system operating over spatially correlated fast (constant over the duration of a symbol) and slow (constant over the length of a code word) fad­ing channels using a moment-generating function-based approach. We discuss two analytical techniques that can be used to evaluate the exact-PEPs (and therefore, approximate the average bit error probability (BEP)) in closed form. These analytical expressions are more realistic than previously published PEP expressions as they fully account for antenna spacing, antenna geometries (uniform linear array, uniform grid array, uniform circular array, etc.) and scattering models (uniform, Gaussian, Laplacian, Von-mises, etc.). Inclusion of spatial information in these expressions provides valuable insights into the physical factors determining the performance of a space-time code. Using these new PEP expressions, we investigate the effect of antenna spacing, antenna geometries and azimuth power distribution parameters (angle of arrival/departure and angular spread) on the performance of a four-state QPSK space-time trellis code proposed by Tarokh et al. for two transmit antennas.

• International Journal of Ocean System Engineering
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• 제4권1호
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• pp.29-42
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• 2014

The objective of this paper is to present the implementation of a joint modeling system able to evaluate the propagation of the polluting agents in the marine environment. The system is composed by circulation model (Mohid) and a spectral wave model (SWAN). The results coming from the circulation model are provided as input to the SWAN simulations. Following this target the Mohid water circulation model was implemented and calibrated in the Black Sea basin. The current simulations were run for one year (2010) with a time step of 24 hours, using wind fields from ECMWF. The results concerning the current fields were introduced into SWAN, and the difference between the results of the SWAN simulations with and without the current input from Mohid was assessed. In this regard, 10 points where the significant wave height difference is higher were considered and analyzed. The conclusion of the work is that such a joint system provides more reliable results concerning the wave and current conditions in the Black Sea as it is very useful in providing the support in the case of the environmental alerts that may occur in marine environments.

• 한국주조공학회지
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• 제34권3호
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• pp.107-111
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• 2014

Permeability is the ability of a material to transmit fluid/gases. It is an important material property and it depends on mould parameters such as grain fineness number, clay, moisture, mulling time, and hardness. Modeling the relationships among these variable and interactions by mathematical models is complex. Hence a biologically inspired artificial neural-network technique with a back-propagation-learning algorithm was developed to estimate the permeability of green sand. The developed model was used to perform a sensitivity analysis to estimate permeability. The individual as well as the combined influence of mould parameters on permeability were simulated. The model was able to describe the complex relationships in the system. The optimum process window for maximum permeability was obtained as 8.75-10.5% clay and 3.9-9.5% moisture. The developed model is very useful in understanding various interactions between inputs and their effects on permeability.

• 한국정밀공학회지
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• 제21권10호
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• pp.78-85
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• 2004

The particle amount monitoring technique using ultrasound is proposed to determine the proper maintenance time of the filter in the supply process of pure gas in the unit of oxygen plant. There are advantages that it is adaptable in high temperature and high pressure, and it is not disturbed by being exposed in the gas flow, and it can be implemented very economically. The applicability of the ultrasonic technique is pre-studied through the theoretical analysis for the dependency of attenuation of ultrasonic wave on the particles in the gas flow. For the purpose, absorption, scattering and dispersion models are considered, and the attenuation by absorption and the change rate of the propagation speed are calculated fur the specific range of particle size and the ultrasonic wave frequency. It was expected by simulation that the absorptive attenuation by particles was the most sensitive to the change of particle amount. The experimental result showed high correspondence with the theoretical expectation so that this ultrasound attenuation measurement was proved to be highly effective for monitoring the amount of floating particles in the gas flow.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계 학술대회논문집(수송기계편)
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• pp.190-193
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• 2005

The air filter in engine intake system filters the dirt in the breathing air but also it attenuates the noise although the phenomenon has been regarded negligible. For the analysis of the acoustical performance of air filter, an acoustical model is suggested in this paper. The air filter consists of a porous filter element, which catches the particulate dirt, and a plastic filter box, which supports the filter element. Fibrous structure of the filter element is modeled as a micro-perforated panel using the flow resistivity and porosity. The pleated geometry of the filter element is modeled as two coupled ducts and a mathematical model is developed for the analysis of sound propagation. The filter box Is modeled as a rigid rectangular box. By combining two models, a 4-pole transfer matrix for the air filter is derived. The transmission loss calculated using the transfer matrix of the suggested model is compared with the measured data. Reasonably good agreement is observed. The result can be improved by considering the visco-thermal effect in modeling, in particular at a frequency range near the troughs of TL curve.

• Smart Structures and Systems
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• 제20권2호
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• pp.207-217
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• 2017

Because of the inevitable uncertainties such as structural parameters, external excitations and measurement noises, the effects of uncertainties should be taken into consideration in structural damage detection. In this paper, two probabilistic structural damage detection approaches are proposed to account for the underlying uncertainties in structural parameters and external excitation. The first approach adopts the statistical moment-based structural damage detection (SMBDD) algorithm together with the sensitivity analysis of the damage vector to the uncertain parameters. The approach takes the advantage of the strength SMBDD, so it is robust to measurement noise. However, it requests the number of measured responses is not less than that of unknown structural parameters. To reduce the number of measurements requested by the SMBDD algorithm, another probabilistic structural damage detection approach is proposed. It is based on the integration of structural damage detection using temporal moments in each time segment of measured response time history with the sensitivity analysis of the damage vector to the uncertain parameters. In both approaches, probability distribution of damage vector is estimated from those of uncertain parameters based on stochastic finite element model updating and probabilistic propagation. By comparing the two probability distribution characteristics for the undamaged and damaged models, probability of damage existence and damage extent at structural element level can be detected. Some numerical examples are used to demonstrate the performances of the two proposed approaches, respectively.