• 한국섬유공학회:학술대회논문집
• /
• 한국섬유공학회 2007년도 학술발표회 논문집
• /
• pp.201-202
• /
• 2007

• 반도체디스플레이기술학회지
• /
• 제19권4호
• /
• pp.88-93
• /
• 2020

Based on the capture-emission energy (CEE) maps of CMOS devices, a physics-informed machine learning model for the bias temperature instability (BTI)-induced threshold voltage shifts and low frequency noise is presented. In order to incorporate physics theories into the machine learning model, the integration of artificial neural network (IANN) is employed for the computation of the threshold voltage shifts and low frequency noise. The model combines the computational efficiency of IANN with the optimal estimation of Gaussian mixture model (GMM) with soft clustering. It enables full lifetime prediction of BTI under various stress and recovery conditions and provides accurate prediction of the dynamic behavior of the original measured data.

• 전자공학회논문지A
• /
• 제33A권7호
• /
• pp.162-170
• /
• 1996

A breakdown model of gate oxides under constant current stresses is proposed. This model directly relates the oxide lifetime to the stress current density, and includes statistical nature of oxide breakdown using the concept of "effective oxide thinning". It is shown tha this model can reliably predict the TDDB characteristics for any current stress levels and oxide areas.

• 한국신뢰성학회지:신뢰성응용연구
• /
• 제17권2호
• /
• pp.83-91
• /
• 2017

Purpose: The purpose of this study is to develop a quality assurance model and to determine appropriate warranty period for a guided missile using its field data. Methods: 10 years of actual firing data is collected from the defense industry company and military. Parametric maximum likelihood estimation for a reliability function is determined with the data. Results: The reliability function estimates average lifetime of the missile. That function shows a user requirement, 80% reliability (lifetime) is come up when 8 years have passed, which is longer than the estimates in the missile's development phase. Conclusion: Quality assurance warranty for a guided missile must be established with actual test data. It is necessary to update and modify the reliability prediction and the warranty period with actual field test data.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 2004년도 하계학술대회 논문집 Vol.5 No.1
• /
• pp.405-408
• /
• 2004

In this work, Analytical model for voltage and current characteristics of NPT(Non-PunchThrough) IGBT(Insulated Gate Bipolar Transistor) was represented. voltage and current characteristics models were based on prediction on power loss of NPT IGBT during transient condition. For Analytical current model, excess carrier concentration and accumulated charge in active base width was analyzed with time variance. Analytical models were simulated by varying lifetime of excess minority carrier.

• 한국안전학회지
• /
• 제31권3호
• /
• pp.75-81
• /
• 2016

Tendon corrosion reliability in KICT-ultra high performance concrete (K-UHPC) bridges is assessed and predicted considering uncertainties in flexural bending capacity and corrosion occurrence. In post-tensioning bridge systems, corrosion is a one of most critical failure mechanisms due to strength reduction by it. During the entire service life, those bridges may experience lifetime corrosion deterioration initiated and propagated in tendons which are embedded not only in normal concrete but also in K-UHPC. For this reason, the time-variant corrosion performance has to be assessed. In the absence of in-depth researches associated with K-UHPC tendon corrosion, a reliability-based prediction model is developed to evaluate lifetime corrosion performance of tendon in K-UHPC bridges. In 2015, KICT built a K-UHPC pilot bridge at 168/5~168/6 milestone on Yangon-Mandalay Expressway in Myanmar, by using locally produced tendons which post-tensioned in longitudinal and lateral ways of K-UHPC girders. For an illustrative purpose, this K-UHPC bridge is used to identify the time-variant corrosion performance.

• Journal of Communications and Networks
• /
• 제14권3호
• /
• pp.310-318
• /
• 2012

Detecting intrusion attacks accurately and rapidly in wireless networks is one of the most challenging security problems. Intrusion attacks of various types can be detected by the change in traffic flow that they induce. Wireless industrial networks based on the wireless networks for industrial automation-process automation (WIA-PA) standard use a superframe to schedule network communications. We propose an intrusion detection system for WIA-PA networks. After modeling and analyzing traffic flow data by time-sequence techniques, we propose a data traffic prediction model based on autoregressive moving average (ARMA) using the time series data. The model can quickly and precisely predict network traffic. We initialized the model with data traffic measurements taken by a 16-channel analyzer. Test results show that our scheme can effectively detect intrusion attacks, improve the overall network performance, and prolong the network lifetime.

• Nuclear Engineering and Technology
• /
• 제53권8호
• /
• pp.2547-2555
• /
• 2021

The frequency of reactor coolant leakage is expected to increase over the lifetime of a nuclear power plant owing to degradation mechanisms, such as flow-acceleration corrosion and stress corrosion cracking. When loss of coolant accidents (LOCAs) occur, several parameters change rapidly depending on the size and location of the cracks. In this study, leak flow during LOCAs is predicted using a deep fuzzy neural network (DFNN) model. The DFNN model is based on fuzzy neural network (FNN) modules and has a structure where the FNN modules are sequentially connected. Because the DFNN model is based on the FNN modules, the performance factors are the number of FNN modules and the parameters of the FNN module. These parameters are determined by a least-squares method combined with a genetic algorithm; the number of FNN modules is determined automatically by cross checking a fitness function using the verification dataset output to prevent an overfitting problem. To acquire the data of LOCAs, an optimized power reactor-1000 was simulated using a modular accident analysis program code. The predicted results of the DFNN model are found to be superior to those predicted in previous works. The leak flow prediction results obtained in this study will be useful to check the core integrity in nuclear power plant during LOCAs. This information is also expected to reduce the workload of the operators.

• 에너지공학
• /
• 제22권4호
• /
• pp.338-346
• /
• 2013

일반 납축전지는 차량의 시동 성능 위주로 최적 설계되어 있다. 최근 차량 전장 시스템과 납축전지를 활용한 연비기술 적용의 증가로 납축전지의 사용 빈도가 늘어나고 있다. 연비기술 적용은 납축전지의 잦은 충방전 반응을 일으켜 납축전지 내구 수명을 단축시키고 있다. 본 연구에서는 납축전지의 노화 수명 모델 구현을 통해 배터리 내구 수명을 예측하는 방법을 제시하고자 한다. 납축전지의 노화에 영향을 미치는 요인은 방전율, 충전 시간, 완충 시간, 온도 조건 등이 있다. 본 논문에서는 납축전지의 동적 거동을 예측하기 위하여 전기화학반응 속도론, 이온의 전달현상, 전극 공극률의 시간에 따른 변화를 고려하였다. 수명 예측을 위해서 노화 메커니즘 중 노화에 가장 큰 영향을 주는 극판 부식 현상과 활물질 탈락을 노화 모델링에 반영하였다. 개발된 납축전지의 노화 모델을 검증하기 위하여 납축전지의 가속 충방전 시험을 수행하였다.

• 한국신뢰성학회지:신뢰성응용연구
• /
• 제9권4호
• /
• pp.275-290
• /
• 2009

This paper considers accelerated thermal degradation tests which are performed for rubber seal materials used for undersea tunnels constructed by immersion method. Three types of rubber seals are tested; rubber expansion seal, omega seal, and shock absorber hose. Main ingredient of rubber expansion seal is EPDM(Ethylene Propylene Diene Monomer) and that of both omega seal and shock absorber hose is SBR(Styrene Butadiene Rubber). The accelerated stress is temperature and an Arrhenius model is introduced to describe the relationship between the lifetime and the stress. From the accelerated degradation tests, dominant failure mode of the rubber seals is found to be the loss of elongation. The lifetime distribution and the service life of the rubber seals at use condition are estimated from the test results. The acceleration factor for three types of rubber seals are also investigated.