• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 2005년도 하계학술대회 논문집 Vol.6
• /
• pp.57-58
• /
• 2005

The properties such as capacitance and resonant frequency are important in embedded capacitors. Accurate equivalent model is required to find these properties of embedded capacitor. In this paper, we investigate to analyze the properties of high-K embedded capacitor which was fabricated by Low Temperature Co-fired Ceramic (LTCC). Modeling based on partial element equivalent circuit (PEEC) method is performed using HSPICE circuit simulation. This modeling methodology can provide the good inspection of embedded capacitor to device engineer.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 2006년도 하계학술대회 논문집 Vol.7
• /
• pp.426-427
• /
• 2006

In this paper, the neural network model of the pretilt angle in the nematic liquid crystal on the homogeneous polyimide surface with different surface treatments is investigated. The pretilt angle is one of the main factors to determine the alignment of the liquid crystal display. The pretilt angle is measured to analyze the variation of the characteristics on the various process conditions. The rubbing strength and the hard baking temperature are considered as input factors. Latin hypercube sampling was used to generate initial weights and biases.

• Nuclear Engineering and Technology
• /
• 제30권6호
• /
• pp.496-506
• /
• 1998

This paper deals with the computational modeling of buoyancy-driven turbulent heat transfer involving spatially uniform volumetric heat sources in semicircular geometry. The Launder & Sharma low-Reynolds number k-$\varepsilon$ turbulence model without any modifications and the SIMPLER computational algorithm were used for the numerical modeling, which was incorporated into the new computer code CORE-TNC. This computer code was subsequently benchmarked with the Mini-ACOPO experimental data in the modified Rayleigh number range of 2$\times$10$^{13}$ $\times$10$^{14}$ . The general trends of the velocity and temperature fields were well predicted by the model used, and the calculated isotherm patterns were found to be very similiar to those observed in previous experimental investigations. The deviation between the Mini-ACOPO experimental data and the corresponding numerical results obtained with CORE-TNC for the average Nusselt number was less than 30% using fine grid in the near-wall region and the three-point difference formula for the wall temperature gradient. With isothermal pool boundaries, heat was convected predominantly to the upper and adjacent lateral surfaces, and the bottom surface received smaller heat fluxes.

• Advances in nano research
• /
• 제7권3호
• /
• pp.181-190
• /
• 2019

The thermal buckling temperature values of the graded carbon nanotube reinforced composite shell structure is explored using higher-order mid-plane kinematics and multiscale constituent modeling under two different thermal fields. The critical values of buckling temperature including the effect of in-plane thermal loading are computed numerically by minimizing the final energy expression through a linear isoparametric finite element technique. The governing equation of the multiscale nanocomposite is derived via the variational principle including the geometrical distortion through Green-Lagrange strain. Additionally, the model includes different grading patterns of nanotube through the panel thickness to improve the structural strength. The reliability and accuracy of the developed finite element model are varified by comparison and convergence studies. Finally, the applicability of present developed model was highlight by enlighten several numerical examples for various type shell geometries and design parameters.

• 반도체디스플레이기술학회지
• /
• 제21권4호
• /
• pp.110-115
• /
• 2022

Accurate current-voltage modeling of solar cell systems plays an important role in power prediction. Solar cells have nonlinear characteristics that are sensitive to environmental conditions such as temperature and irradiance. In this paper, the output characteristics of photovoltaic module are accurately predicted by combining the artificial neural network and physical model. In order to estimate the performance of PV module under varying environments, the artificial neural network model is trained with randomly generated temperature and irradiance data. With the use of proposed model, the current-voltage and power-voltage characteristics under real environments can be predicted with high accuracy.

• Structural Engineering and Mechanics
• /
• 제81권5호
• /
• pp.647-664
• /
• 2022

The powerful data mapping capability of computational deep learning methods has been recently explored in academic works to develop strategies for structural health monitoring through appropriate characterization of dynamic responses. In many cases, these studies concern laboratory prototypes and finite element models to validate the proposed methodologies. Therefore, the present work aims to investigate the capability of a deep learning algorithm called Sparse Autoencoder (SAE) specifically focused on detecting structural alterations in real-case studies. The idea is to characterize the dynamic responses via SAE models and, subsequently, to detect the onset of abnormal behavior through the Shewhart T control chart, calculated with SAE extracted features. The anomaly detection approach is exemplified using data from the Z24 bridge, a classical benchmark, and data from the continuous monitoring of the San Vittore bell-tower, Italy. In both cases, the influence of temperature is also evaluated. The proposed approach achieved good performance, detecting structural changes even under temperature variations.

• 센서학회지
• /
• 제32권3호
• /
• pp.164-168
• /
• 2023

Accurate and reliable weather forecasts for temperature, relative humidity, and precipitation using advanced transformer models and IoT are essential in various fields related to global climate change. We propose a novel weather prediction device that integrates state-of-the-art transformer models and IoT techniques to improve prediction accuracy and real-time processing. The proposed system demonstrated high reliability and performance, offering valuable insights for industries and sectors that rely on accurate weather information, including agriculture, transportation, and emergency response planning. The integration of transformer models with the IoT signifies a substantial advancement in weather and climate modeling.

• Applied Science and Convergence Technology
• /
• 제24권4호
• /
• pp.102-110
• /
• 2015

Fluid model based numerical analysis is done to simulate a plasma processing system with electrodes at floating potential. $V_f$ is a function of electron temperature, electron mass and ion mass. Commercial plasma fluid simulation softwares do not provide options for floating electrode boundary value condition. We developed a user subroutine in CFD-ACE+ and compared four different cases: grounded, dielectric, zero normal electric field and floating electric potential for a 2D-CCP (capacitively coupled plasma) with a ring electrode.

• 대한기계학회논문집A
• /
• 제31권12호
• /
• pp.1208-1213
• /
• 2007

Some structural problems and temperature difference of the pyrolysis equipment were improved by using the structure analysis and the optimal design of torch. The pyrolysis equipment developed in this study is expected to the excellent pyrolysis effect. To modify user-friendly the dimension of a part, we developed the feature modeling system that all of the related parts automatically change applying to the three-dimensional modeling method.

• 한국콘크리트학회:학술대회논문집
• /
• 한국콘크리트학회 2010년도 춘계 학술대회 제22권1호
• /
• pp.471-472
• /
• 2010

In this study, a new modeling framework for predicting temperature and structural behaviors of structures under fire condition is proposed. The proposed modeling framework including fire simulation, heat transfer and structural analysis is applied to simulate fire tests performed on the steel-concrete composite structures in Cardington, UK, for model validations. Good predictions are shown for spatial-temporal temperatures and deflections of fire-damaged steel-concrete structures.