• 한국생산제조학회지
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• 제21권2호
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• pp.225-231
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• 2012

Drop simulations of the board level in the flip chips with solder joints have been highlighted for years, recently. Also, through the study on the life prediction of thermal fatigue in the flip chips considering underfill, its importance has been issued greatly. In this paper, dynamic analysis using the implicit method in the Finite Element Analysis (FEA) is carried out to assess the factors effecting on flip chips considering underfill. The design parameters are size and thickness of chip, and size, pitch and array of solder ball with composition of Sn1.0Ag0.5Cu. The board systems by JEDEC standard is modeled with various design parameter combinations, and through these simulations, maximum yield stress and strain at each chip are shown at the solder balls. Modal analysis is simulated to find out the relation between drop impact and vibration of the board system.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.997-1000
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• 2005

Dynamic job shop environment requires not only more flexible capabilities of a CAPP system but higher utility of the generated process plans. In order to meet the requirements, this paper develops an algorithm that can select machines for the machining operations to be performed by predicting the machine loads. The developed algorithm is based on the multiple objective genetic algorithm that gives rise to a set of optimal solutions (in general, known as Pareto-optimal solutions). The objective shows a combination of the minimization of part movement and the maximization of machine utility balance. The algorithm is characterized by a new and efficient method for nondominated sorting, which can speed up the running time, as well as a method of two stages for genetic operations, which can maintain a diverse set of solutions. The performance of the algorithm is evaluated by comparing with another multiple objective genetic algorithm, called NSGA-II.

• 한국멀티미디어학회논문지
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• 제9권12호
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• pp.1709-1718
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• 2006

Users are able to use the information and service more free than previous wire network due to development of wireless network and device. For this reason, various studies on ubiquitous networks have been conducted. Various contexts brought in this ubiquitous environment, have recognized user's action through sensors. This results in the provision of better services. Because services exist in various places in ubiquitous networks, the application has the time of services searching. In addition, user's context is very dynamic, so a method needs to be found to recommend services to user by context. Therefore, techniques for reducing the time of service and increasing accuracy of recommendation are being studied. But it is difficult to quickly and appropriately provide large numbers of services, because only basic context information is stored. For this reason, we suggest DUPS(Dimension User Profile System), which stores location, time, and frequency information of often used services. Because previous technique used to simple information for recommending service without predicting services which is going to use on future, we can provide better service, and improve accuracy over previous techniques.

• 한국정밀공학회지
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• 제30권2호
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• pp.231-235
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• 2013

The purpose of this paper is to compare with estimation of equivalent fatigue load in time domain and frequency domain and estimate the fatigue life of structure with multi-axial vibration loading. The fatigue analysis with two methods is implemented with various signals like random, sinusoidal signals. Also an equivalent fatigue life estimated by rainflow cycle counting in time domain is compared with results estimated with probability density function of each signal in frequency domain. In case of frequency domain, equivalent fatigue life can estimate through Dirlik's method with probability density function. And the work proposed in this paper compared the fatigue damage accumulated under uni-axial loading to that induced by multi-axial loading. The comparison is preformed for a simple cantilever beam, which is exposed to vibrations of several directions. For verification of estimation performance of fatigue life, results are compared to those of FEM analysis (ANSYS).

• 전기학회논문지P
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• 제51권4호
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• pp.175-185
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• 2002

In this paper, a new fully digital current control method of UPS inverter, which is based on an internal model control, is proposed. In the proposed control system, overshoots and oscillations due to the computation time-delay are compensated by explicit incorporation of the time-delay in the current control loop transfer function. The internal model controller is adopted to a second order deadbeat reference-to-output response which means that its response reaches the reference in two sampling time including computational time-delays. That is, the average current of filter capacitor is been exactly equal to the reference current with a time lag of two sampling intervals. Therefore, this method has an essentially overshoot free reference-to-output response with a minimum possible rise time. The effectiveness of the proposed control system has been verified by the simulation and experimental respectively. From the simulation and experimental results, the proposed system is achieved the robust characteristics to the calculation time delay and parameter variation as well as very fast dynamic performance, thus it can be effectively applied to the power supply for the critical load.

• Earthquakes and Structures
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• 제8권4호
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• pp.915-934
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• 2015

Within the context of Structural Health Monitoring (SHM), it is often the case that structural systems are described by uncertainty, both with respect to their parameters and the characteristics of the input loads. For the purposes of system identification, efficient modeling procedures are of the essence for a fast and reliable computation of structural response while taking these uncertainties into account. In this work, a reduced order metamodeling framework is introduced for the challenging case of nonlinear structural systems subjected to earthquake excitation. The introduced metamodeling method is based on Nonlinear AutoRegressive models with eXogenous input (NARX), able to describe nonlinear dynamics, which are moreover characterized by random parameters utilized for the description of the uncertainty propagation. These random parameters, which include characteristics of the input excitation, are expanded onto a suitably defined finite-dimensional Polynomial Chaos (PC) basis and thus the resulting representation is fully described through a small number of deterministic coefficients of projection. The effectiveness of the proposed PC-NARX method is illustrated through its implementation on the metamodeling of a five-storey shear frame model paradigm for response in the region of plasticity, i.e., outside the commonly addressed linear elastic region. The added contribution of the introduced scheme is the ability of the proposed methodology to incorporate uncertainty into the simulation. The results demonstrate the efficiency of the proposed methodology for accurate prediction and simulation of the numerical model dynamics with a vast reduction of the required computational toll.

• Smart Structures and Systems
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• 제24권6호
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• pp.733-744
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• 2019

Wind speed forecasting is critical for a variety of engineering tasks, such as wind energy harvesting, scheduling of a wind power system, and dynamic control of structures (e.g., wind turbine, bridge, and building). Wind speed, which has characteristics of random, nonlinear and uncertainty, is difficult to forecast. Nowadays, machine learning approaches (generalized regression neural network (GRNN), back propagation neural network (BPNN), and extreme learning machine (ELM)) are widely used for wind speed forecasting. In this study, two schemes are proposed to improve the forecasting performance of machine learning approaches. One is that optimization algorithms, i.e., cross validation (CV), genetic algorithm (GA), and particle swarm optimization (PSO), are used to automatically find the optimal model parameters. The other is that the combination of different machine learning methods is proposed by finite mixture (FM) method. Specifically, CV-GRNN, GA-BPNN, PSO-ELM belong to optimization algorithm-assisted machine learning approaches, and FM is a hybrid machine learning approach consisting of GRNN, BPNN, and ELM. The effectiveness of these machine learning methods in wind speed forecasting are fully investigated by one-year field monitoring data, and their performance is comprehensively compared.

• 대한방사선기술학회지:방사선기술과학
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• 제44권2호
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• pp.109-115
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• 2021

In this study, a physical evaluation of internal radiation exposure in children was conducted using nuclear medicine test(Renal DTPA Dynamic Study) to simulate the distribution and effects of the radiation throughout the tracer kinetics over time. Monte Carlo simulations were performed to determine the internal medical radiation exposure during the tests and to provide basic data for medical radiation exposure management. Specifically, dose variability based on changes in the tracer kinetic was simulated over time. The internal exposure to the target organ (kidney) and other surrounding organs was then quantitatively evaluated and presented. When kidney function was normal, the dose to the target organ(kidney) was approximately 0.433 mGy/mCi, and the dose to the surrounding organs was approximately 0.138-0.266 mGy/mCi. When kidney function was abnormal, the dose to the surrounding organs was 0.228-0.419 mGy/mCi. This study achieved detailed radiation dose measurements in highly sensitive pediatric patients and enabled the prediction of radiation doses according to kidney function values. The proposed method can provide useful insights for medical radiation exposure management, which is particularly important and necessary for pediatric patients.

• 한국수자원학회논문집
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• 제39권7호
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• pp.593-603
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• 2006

강우로부터 유출현상은 고유적으로 비선형성이다. 더욱이 실제적으로 이와 같은 비선형성의 해석은 많은 어려움을 내포하고 있다. 또한, 부정류효과의 동적작용을 고려한 저류개념은 매개변수의 유역특성상 추정하기가 상당히 복잡하기 때문에 피해오고 있는 실정이다. 본 연구에서는 이와 같은 동적효과를 고려한 비선형의 저류함수에 대한 매개변수의 최적치를 얻고자 시도한다. 이를 위한 수치해법은 금강의 보청천유역의 관측치와 계산치의 오차를 최소로 하는 최소자승법에 의거 준선형화, Runge-Kutta 및 pattern-search 법들을 적용한다. 본 연구의 동적효과를 고려한 비선형 개념적모형의 적용성은 비선형성만을 고려한 저류함수모형 및 기존의 Nash 모형과 비교하여 검토하였다. 그 결과 2계모형이 l계모형보다 강우로부터 유출예측치를 보다 더 잘 재현하는 것을 알 수 있었으며, Nash 모형과는 대등함을 보여주었다. 여기서 획득된 매개변수들은 물리적 의미뿐만 아니라 본 모형의 국내 적용성도 제공한다.

• 대한인간공학회지
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• 제24권1호
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• pp.9-17
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• 2005

81.1% of traffic accidents is attributed to the drivers. In this regard, D/E model is a practical and effective method in terms of the cost and time in evaluating the road hazardousness. To examine the validity of the threshold values by the levels of demand We selected 10 subjects and collected their physiological signals while they were driving on Honam Highway (Jeonju ${\leftrighttarro}$ Hoideog section). Based on the collected data, the hazardous road condition was evaluated using the new threshold values of the effort level determined by cluster analysis. In applying the D/E model, a decision method based on the demand level was suggested, using a traffic accident prediction model. Additionally, the limit value of the effort level was determined using the drivers' physiological signal data collected at the highway. A comparison analysis of the two D/E models revealed no significant difference: The existing method and the clustering method determined 9 and 7 hazardous road zones, respectively, while actual traffic accidents were reported in 6 and 4 zones, respectively among the predicted road hazardous zones. However, the latter method suggested a more scientific and rational basis in determining the limit value of the Effort level. In conclusion, although D/E model has a great merit as a pioneering method to reflect human factors in evaluating the road hazardousness, it is believed that this method could be improved by a more dynamic method that considers the traffic conditions and the individual physiological signal of the drivers simultaneously in determining a better limit.