• 한국연소학회지
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• 제22권1호
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• pp.14-22
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• 2017

Co-firing of renewable fuel in coal fired boilers is an attractive option to mitigate $CO_2$ emissions, since it is a relatively low cost option for efficiently converting renewable fuel to electricity by adding biomass as partial substitute of coal. However, it would cause reducing plant efficiency and operational flexibility, and increasing operation and capital cost associated with handling and firing equipment of renewable fuels. The aim of this study is to investigate the effects of biomass co-firing on $CO_2$ emission and capital/operating cost. Wood pellet, PKS (palm kernel shell), EFB (empty fruit bunch) and sludge are considered as renewable fuels for co-firing with coal. Several approaches by the co-firing ratio are chosen from previous plant demonstrations and commercial co-firing operation, and they are evaluated and discussed for $CO_2$ reduction and cost estimation.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2000년도 하계학술대회 논문집
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• pp.115-118
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• 2000

In case of developing new motor, many examinations was tested to decide a motor efficiency and reliability. To give reliability judgment, traction motor winding insulation was tested by electrical method after appling electrical, heat, mechanical, environmental stress. In this study, stator form-wound winding of traction motor in urban transit E.M.U was tested by accelerative thermal degradation test. Stator form-wound winding was tested on the accelerative degradation composed of heat, vibration, moisture, overvoltage and researched insulation resistance, dielectric loss, partial discharge for insulation degradation properties, evaluated withstand voltage. Degradation temperature was $230[^\circ{C}]$, $250[^\circ{C}]$, $270[^\circ{C}]$, for stator form-wound winding respectively. On the test results of accelerative thermal degradation, insulation properties were relied all temperature until 10 times and expected life was evaluated by the rule of reducing $10[^\circ{C}]$ life into halves. Expected life was 31.8 years. It is guaranteed insulation reliability because of exceeding 25 years life times as considering.

• Bulletin of the Korean Chemical Society
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• 제20권1호
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• pp.35-41
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• 1999

Stability characteristics of hyperbolic reaction-diffusion equations with a reversible Brusselator model are investigated as an extension of the previous work. Intensive stability analysis is performed for three important parameters, Nrd, β and Dx, where Nrd is the reaction-diffusion number which is a measure of hyperbolicity, β is a measure of reversibility of autocatalytic reaction and Dx is a diffusion coefficient of intermediate X. Especially, the dependence on Nrd of stability exhibits some interesting features, such as hyperbolicity in the small Nrd region and parabolicity in the large Nrd region. The hyperbolic reaction-diffusion equations are solved numerically by a spectral method which is modified and adjusted to hyperbolic partial differential equations. The numerical method gives good accuracy and efficiency even in a stiff region in the case of small Nrd, and it can be extended to a two-dimensional system. Four types of solution, spatially homogeneous, spatially oscillatory, spatio-temporally oscillatory and chaotic can be obtained. Entropy productions for reaction are also calculated to get some crucial information related to the bifurcation of the system. At the bifurcation point, entropy production changes discontinuously and it shows that different structures of the system have different modes in the dissipative process required to maintain the structure of the system. But it appears that magnitude of entropy production in each structure give no important information related for states of system itself.

• Journal of the Korean Wood Science and Technology
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• 제49권5호
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• pp.491-503
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• 2021

Wood identification is regularly performed by observing the wood anatomy, such as colour, texture, fibre direction, and other characteristics. The manual process, however, could be time consuming, especially when identification work is required at high quantity. Considering this condition, a convolutional neural networks (CNN)-based program is applied to improve the image classification results. The research focuses on the algorithm accuracy and efficiency in dealing with the dataset limitations. For this, it is proposed to do the sample selection process or only take a small portion of the existing image. Still, it can be expected to represent the overall picture to maintain and improve the generalisation capabilities of the CNN method in the classification stages. The experiments yielded an incredible F1 score average up to 93.4% for medium sample area sizes (200 × 200 pixels) on each CNN architecture (VGG16, ResNet50, MobileNet, DenseNet121, and Xception based). Whereas DenseNet121-based architecture was found to be the best architecture in maintaining the generalisation of its model for each sample area size (100, 200, and 300 pixels). The experimental results showed that the proposed algorithm can be an accurate and reliable solution.

• 정보보호학회논문지
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• 제21권5호
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• pp.161-168
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• 2011

2009년에 전동호 등에 의해 경량의 강한 인증과 프라이버시를 제공하는 프로토콜이 제안되었다. 태그는 단지 간단한 비트연산들과 난수생성기를 필요로 한다. JK-RFID 인증 프로토콜은 도청, 재전송, 스푸핑, 위치추적, 서비스거부 공격, 전방향 안전성에 대한 강한 보안성을 제공한다. 하지만, 본 논문에서는 전방향 안전성에 대한 취약성을 지적하고 키 업데이트 과정에 대한 연산을 개선하였다. 본 논문은 전방향 안전성을 보장하는 개선된 JK-RFID 인증 프로토콜을 제안하고 전방향 안전성을 만족함을 검증하였다. 또한, 제안된 프로토콜의 안전성과 효율성을 분석하였다. 제안 프로토콜은 JK-RFID 인증 프로토콜에서 키 업데이트 부분의 연산을 수정하여 전방향 안전성을 개선하였다.

• 대한방사선기술학회지:방사선기술과학
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• 제43권6호
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• pp.461-467
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• 2020

In the field of nuclear medicine, errors are sometimes generated because the assessment of the uniformity of gamma cameras relies on the naked eye of the evaluator. To minimize these errors, we created an artificial intelligence model based on CNN algorithm and wanted to assess its usefulness. We produced 20,000 normal images and partial cold region images using Python, and conducted artificial intelligence training with Resnet18 models. The training results showed that accuracy, specificity and sensitivity were 95.01%, 92.30%, and 97.73%, respectively. According to the results of the evaluation of the confusion matrix of artificial intelligence and expert groups, artificial intelligence was accuracy, specificity and sensitivity of 94.00%, 91.50%, and 96.80%, respectively, and expert groups was accuracy, specificity and sensitivity of 69.00%, 64.00%, and 74.00%, respectively. The results showed that artificial intelligence was better than expert groups. In addition, by checking together with the radiological technologist and AI, errors that may occur during the quality control process can be reduced, providing a better examination environment for patients, providing convenience to radiologists, and improving work efficiency.

• 한국자기공명학회논문지
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• 제25권4호
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• pp.64-69
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• 2021

In the developed NMR hyperpolarization techniques, Signal amplification by reversible exchange (SABRE) technique is thought to be a promising method to overcome the low sensitivity of bio-NMR/MRI. Most experiments using SABRE have been done in methanol, which is biologically harmful solvent. Therefore, more biological friendly solvent, such as ethanol can be more appropriate solvent to be applicable in bio-NMR and MRI. As the proof of concept, successful hyperpolarization on pyridine via SABRE is carried out in ethanol and its enhancement factor is calculated to be more than 150 folds. To investigate more about its possibility of hyperpolarization in different alcohol solvents, methanol and propanol are used for SABRE in the same condition. The overall polarization trend in different external magnetic field is similar but its polarization number is decreased with higher molecular weight solvents (the order from methanol to propanol). This result indicates that the efficiency of SABRE is different from solvent system despite its same functional group and similar properties. Higher para-hydrogen concentration, higher partial pressure of para-hydrogen, and deuterated solvent can increase the hyperpolarization in any solvents. With these series of successful SABRE results, future studies on SABRE in more biofriendly environment, on more various solvent systems, and with more substrates are needed and it will be the firm basis for applying the SABRE system on the future bio-NMR/MRI.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.171-171
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• 2023

This study investigates the capability of Physics-Informed Neural Networks (PINNs) for solving the solution of partial differential equations. Particularly, the 1D Saint-Venant Equations (SVEs) were considered, which describe the movement of water in a domain with shallow depth compared to its horizontal extent, and are widely adopted in hydrodynamics, river, and coastal engineering. The core contribution of this work is to combine the robustness of neural networks with the physical constraints of the SVEs. The PINNs method utilized a neural network to approximate the solutions of SVEs, while also enforcing the underlying physical principles of the equations. This allows for a more effective and reliable solution, especially in areas with complex geometry and varying bathymetry. To validate the robustness of the PINNs method, numerical experiments were conducted on several benchmark problems. The results show that the PINNs could be achieved high accuracy when compared with the solution from the numerical solution. Overall, this study demonstrates the potential of using PINNs and highlights the benefits of integrating neural network and physics information for improved efficiency and accuracy in solving SVEs.

• Steel and Composite Structures
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• 제47권5호
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• pp.569-585
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• 2023

This paper proposes an efficient approach for the structural topology optimization of bi-directional functionally graded structures by incorporating popular radial basis functions (RBFs) into an implicit level set (ILS) method. Compared to traditional element density-based methods, a level set (LS) description of material boundaries produces a smoother boundary description of the design. The paper develops RBF implicit modeling with multiquadric (MQ) splines, thin-plate spline (TPS), exponential spline (ES), and Gaussians (GS) to define the ILS function with high accuracy and smoothness. The optimization problem is formulated by considering RBF-based nodal densities as design variables and minimizing the compliance objective function. A LS-RBF optimization method is proposed to transform a Hamilton-Jacobi partial differential equation (PDE) into a system of coupled non-linear ordinary differential equations (ODEs) over the entire design domain using a collocation formulation of the method of lines design variables. The paper presents detailed mathematical expressions for BiDFG beams topology optimization with two different material models: continuum functionally graded (CFG) and mechanical functionally graded (MFG). Several numerical examples are presented to verify the method's efficiency, reliability, and success in accuracy, convergence speed, and insensitivity to initial designs in the topology optimization of two-dimensional (2D) structures. Overall, the paper presents a novel and efficient approach to topology optimization that can handle bi-directional functionally graded structures with complex geometries.

• Ocean Systems Engineering
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• 제12권3호
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• pp.359-384
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• 2022

We develop in this work a new well-balanced preserving-positivity path-conservative central-upwind scheme for Saint-Venant-Exner (SVE) model. The SVE system (SVEs) under some considerations, is a nonconservative hyperbolic system of nonlinear partial differential equations. This model is widely used in coastal engineering to simulate the interaction of fluid flow with sediment beds. It is well known that SVEs requires a robust treatment of nonconservative terms. Some efficient numerical schemes have been proposed to overcome the difficulties related to these terms. However, the main drawbacks of these schemes are what follows: (i) Lack of robustness, (ii) Generation of non-physical diffusions, (iii) Presence of instabilities within numerical solutions. This collection of drawbacks weakens the efficiency of most numerical methods proposed in the literature. To overcome these drawbacks a reformulation of the central-upwind scheme for SVEs (CU-SVEs for short) in a path-conservative version is presented in this work. We first develop a finite-volume method of the first order and then extend it to the second order via the averaging essentially non oscillatory (AENO) framework. Our numerical approach is shown to be well-balanced positivity-preserving and shock-capturing. The resulting scheme could be seen as a predictor-corrector method. The accuracy and robustness of the proposed scheme are assessed through a carefully selected suite of tests.