• Title/Summary/Keyword: Thermal Modeling

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Geomechanical Stability of Underground Lined Rock Caverns (LRC) for Compressed Air Energy Storage (CAES) using Coupled Thermal-Hydraulic-Mechanical Analysis (열-수리-역학적 연계해석을 이용한 복공식 지하 압축공기에너지 저장공동의 역학적 안정성 평가)

  • Kim, Hyung-Mok;Rutqvist, Jonny;Ryu, Dong-Woo;Synn, Joong-Ho;Song, Won-Kyong
    • Tunnel and Underground Space
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    • v.21 no.5
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    • pp.394-405
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    • 2011
  • In this paper, we applied coupled non-isothermal, multiphase fluid flow and geomechanical numerical modeling using TOUGH-FLAC coupled analysis to study the complex thermodynamic and geomechanical performance of underground lined rock caverns (LRC) for compressed air energy storage (CAES). Mechanical stress in concrete linings as well as pressure and temperature within a storage cavern were examined during initial and long-term operation of the storage cavern for CAES. Our geomechanical analysis showed that effective stresses could decrease due to air penetration pressure, and tangential tensile stress could develop in the linings as a result of the air pressure exerted on the inner surface of the lining, which would result in tensile fracturing. According to the simulation in which the tensile tangential stresses resulted in radial cracks, increment of linings' permeability and air leakage though the linings, tensile fracturing occurred at the top and at the side wall of the cavern, and the permeability could increase to $5.0{\times}10^{-13}m^2$ from initially prescribed $10{\times}10^{-20}m^2$. However, this air leakage was minor (about 0.02% of the daily air injection rate) and did not significantly impact the overall storage pressure that was kept constant thanks to sufficiently air tight surrounding rocks, which supports the validity of the concrete-lined underground caverns for CAES.

Study of a Recurring Anticyclonic Eddy off Wonsan Coast in Northern Korea Using Satellite Tracking Drifter, Satellite Ocean Color and Sea Surface Temperature Imagery (위성원격탐사를 이용한 동해 원산연안의 재발생 와동류 연구)

  • 서영상;장이현;김정희
    • Korean Journal of Remote Sensing
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    • v.16 no.3
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    • pp.211-220
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    • 2000
  • Even though recurring eddies at the terminal end of the East Korean Warm Current have been identified in the thermal infrared imagery from the NOAA/AVHRR sensor and ocean color data from Orbview-2/SeaWiFS sensor, it is difficult to make observation in the field regarding recurring eddies located around the Wonsan coastal area in North Korea. But we could get in situ data related to an eddy from an ARGOS satellite tracking drifter trapped in the eddy on January 4th, 1999. An ARGOS drifter, a NOAA satellite tracked buoy was trapped by the eddy during January 4th.March 18, 1999. The ARGOS drifter rotated 10 times per 72 days on the edge of the eddy located at $39^{\circ}N$, $129^{\circ}E$. The diameter of the eddy was about 100 km. The horizontal rotation velocity of the recurring cold-core anti-cyclonic eddy was 1.53 km/h(42 cm/sec). The sea surface temperatures of the eddy varied from $14.7^{\circ}C$ on January 5, 1999 to $9.6^{\circ}C$ on March 18,1999. To study the mechanism of the recurring eddy. we tried to find out the relationship between the vector of the drifter moving in the eddy and the wind vector in Sokcho and Ulleung Island located near the eddy in southern Korea, and the difference in sea level between Ulleung Island and Mukho. We hope the results of this study would be useful for calibration and validation data of simulation and numerical modeling studies of the recurring eddy.

A Study on the GHG Reduction Newest Technology and Reduction Effect in Power Generation·Energy Sector (발전 에너지 업종의 온실가스 감축 신기술 조사 및 감축효과 분석)

  • Kim, Joo-Cheong;Shim, So-Jung
    • Journal of Climate Change Research
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    • v.4 no.4
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    • pp.349-358
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    • 2013
  • In this study, the newest technology available to reduce GHG emissions, which can be applicable in energy industries of the future that has large reduction obligations by energy target management and large intensity of GHG emissions, has been investigated by searching the technical characteristics of each technology. The newest technology to reduce GHG emissions in the field of power generation and energy can be mainly classified into the improvement of efficiency, CCS, and gas combined-cycle technology. In order to improve the reliability of the GHG emission factor obtained from the investigation process, it has been compared to the technology-specific GHG emission factor derived from the estimated amount of emissions. Then the GHG abatement measures, using the derived estimation of factor, by using the newest technology to reduce GHG emissions have been predicted. As a result, the GHG reduction rate by technology of CCS development has been expected to be the largest more than 30%, and the abatement rate by technology of coal gasified fuel cell and pressurized fluidized-bed thermal power generation has been showed more than 20%. If the effective introduction of the newest technology and the study of its characteristics is continued, and properly applied for future GHG emissions, it can be prospected that the national GHG reduction targets can be achieved in cost-efficient way.

Improved Performance of Image Semantic Segmentation using NASNet (NASNet을 이용한 이미지 시맨틱 분할 성능 개선)

  • Kim, Hyoung Seok;Yoo, Kee-Youn;Kim, Lae Hyun
    • Korean Chemical Engineering Research
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    • v.57 no.2
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    • pp.274-282
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    • 2019
  • In recent years, big data analysis has been expanded to include automatic control through reinforcement learning as well as prediction through modeling. Research on the utilization of image data is actively carried out in various industrial fields such as chemical, manufacturing, agriculture, and bio-industry. In this paper, we applied NASNet, which is an AutoML reinforced learning algorithm, to DeepU-Net neural network that modified U-Net to improve image semantic segmentation performance. We used BRATS2015 MRI data for performance verification. Simulation results show that DeepU-Net has more performance than the U-Net neural network. In order to improve the image segmentation performance, remove dropouts that are typically applied to neural networks, when the number of kernels and filters obtained through reinforcement learning in DeepU-Net was selected as a hyperparameter of neural network. The results show that the training accuracy is 0.5% and the verification accuracy is 0.3% better than DeepU-Net. The results of this study can be applied to various fields such as MRI brain imaging diagnosis, thermal imaging camera abnormality diagnosis, Nondestructive inspection diagnosis, chemical leakage monitoring, and monitoring forest fire through CCTV.

Introduction to Tasks in the International Cooperation Project, DECOVALEX-2023 for the Simulation of Coupled Thermohydro-mechanical-chemical Behavior in a Deep Geological Disposal of High-level Radioactive Waste (고준위방사성폐기물 처분장 내 열-수리-역학-화학적 복합거동 해석을 위한 국제공동연구 DECOVALEX-2023에서 수행 중인 연구 과제 소개)

  • Kim, Taehyun;Lee, Changsoo;Kim, Jung-Woo;Kang, Sinhang;Kwon, Saeha;Kim, Kwang-Il;Park, Jung-Wook;Park, Chan-Hee;Kim, Jin-Seop
    • Tunnel and Underground Space
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    • v.31 no.3
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    • pp.167-183
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    • 2021
  • It is essential to understand the complex thermo-hydro-mechanical-chemical (THMC) coupled behavior in the engineered barrier system and natural barrier system to secure the high-level radioactive waste repository's long-term safety. The heat from the high-level radioactive waste induces thermal pressurization and vaporization of groundwater in the repository system. Groundwater inflow affects the saturation variation in the engineered barrier system, and the saturation change influences the heat transfer and multi-phase flow characteristics in the buffer. Due to the complexity of the coupled behavior, a numerical simulation is a valuable tool to predict and evaluate the THMC interaction effect on the disposal system and safety assessment. To enhance the knowledge of THMC coupled interaction and validate modeling techniques in geological systems. DECOVALEX, an international cooperation project, was initiated in 1992, and KAERI has participated in the projects since 2008 in Korea. In this study, we introduced the main contents of all tasks in the DECOVALEX-2023, the current DECOVALEX phase, to the rock mechanics and geotechnical researchers in Korea.

Learning Method for Regression Model by Analysis of Relationship Between Input and Output Data with Periodicity (주기성을 갖는 입출력 데이터의 연관성 분석을 통한 회귀 모델 학습 방법)

  • Kim, Hye-Jin;Park, Ye-Seul;Lee, Jung-Won
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.7
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    • pp.299-306
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    • 2022
  • In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

Development of Three-dimensional Inversion Algorithm of Complex Resistivity Method (복소 전기비저항 3차원 역산 알고리듬 개발)

  • Son, Jeong-Sul;Shin, Seungwook;Park, Sam-Gyu
    • Geophysics and Geophysical Exploration
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    • v.24 no.4
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    • pp.180-193
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    • 2021
  • The complex resistivity method is an exploration technique that can obtain various characteristic information of underground media by measuring resistivity and phase in the frequency domain, and its utilization has recently increased. In this paper, a three-dimensional inversion algorithm for the CR data was developed to increase the utilization of this method. The Poisson equation, which can be applied when the electromagnetic coupling effect is ignored, was applied to the modeling, and the inversion algorithm was developed by modifying the existing algorithm by adopting comlex variables. In order to increase the stability of the inversion, a technique was introduced to automatically adjust the Lagrangian multiplier according to the ratio of the error vector and the model update vector. Furthermore, to compensate for the loss of data due to noisy phase data, a two-step inversion method that conducts inversion iterations using only resistivity data in the beginning and both of resistivity and phase data in the second half was developed. As a result of the experiment for the synthetic data, stable inversion results were obtained, and the validity to real data was also confirmed by applying the developed 3D inversion algorithm to the analysis of field data acquired near a hydrothermal mine.

TGC-based Fish Growth Estimation Model using Gaussian Process Regression Approach (가우시안 프로세스 회귀를 통한 열 성장 계수 기반의 어류 성장 예측 모델)

  • Juhyoung Sung;Sungyoon Cho;Da-Eun Jung;Jongwon Kim;Jeonghwan Park;Kiwon Kwon;Young Myoung Ko
    • Journal of Internet Computing and Services
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    • v.24 no.1
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    • pp.61-69
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    • 2023
  • Recently, as the fishery resources are depleted, expectations for productivity improvement by 'rearing fishery' in land farms are greatly rising. In the case of land farms, unlike ocean environments, it is easy to control and manage environmental and breeding factors, and has the advantage of being able to adjust production according to the production plan. On the other hand, unlike in the natural environment, there is a disadvantage in that operation costs may significantly increase due to the artificial management for fish growth. Therefore, profit maximization can be pursued by efficiently operating the farm in accordance with the planned target shipment. In order to operate such an efficient farm and nurture fish, an accurate growth prediction model according to the target fish species is absolutely required. Most of the growth prediction models are mainly numerical results based on statistical analysis using farm data. In this paper, we present a growth prediction model from a stochastic point of view to overcome the difficulties in securing data and the difficulty in providing quantitative expected values for inaccuracies that existing growth prediction models from a statistical point of view may have. For a stochastic approach, modeling is performed by introducing a Gaussian process regression method based on water temperature, which is the most important factor in positive growth. From the corresponding results, it is expected that it will be able to provide reference values for more efficient farm operation by simultaneously providing the average value of the predicted growth value at a specific point in time and the confidence interval for that value.

Improving Lifetime Prediction Modeling for SiON Dielectric nMOSFETs with Time-Dependent Dielectric Breakdown Degradation (SiON 절연층 nMOSFET의 Time Dependent Dielectric Breakdown 열화 수명 예측 모델링 개선)

  • Yeohyeok Yun
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.4
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    • pp.173-179
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    • 2023
  • This paper analyzes the time-dependent dielectric breakdown(TDDB) degradation mechanism for each stress region of Peri devices manufactured by 4th generation VNAND process, and presents a complementary lifetime prediction model that improves speed and accuracy in a wider reliability evaluation region compared to the conventional model presented. SiON dielectric nMOSFETs were measured 10 times each under 5 constant voltage stress(CVS) conditions. The analysis of stress-induced leakage current(SILC) confirmed the significance of the field-based degradation mechanism in the low electric field region and the current-based degradation mechanism in the high field region. Time-to-failure(TF) was extracted from Weibull distribution to ascertain the lifetime prediction limitations of the conventional E-model and 1/E-model, and a parallel complementary model including both electric field and current based degradation mechanisms was proposed by extracting and combining the thermal bond breakage rate constant(k) of each model. Finally, when predicting the lifetime of the measured TDDB data, the proposed complementary model predicts lifetime faster and more accurately, even in the wider electric field region, compared to the conventional E-model and 1/E-model.

Evaluation and Weathering Depth Modeling of Thermally Altered Pelitic Rocks based on Chemical Weathering and Variations: Ulju Cheonjeon-ri Petroglyph (화학적 풍화작용과 조성변화에 따른 열변질 이질암의 풍화심도 모델링 및 평가: 울주 천전리 각석)

  • LEE Chan Hee;CHUN Yu Gun
    • Korean Journal of Heritage: History & Science
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    • v.56 no.4
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    • pp.160-189
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    • 2023
  • The Cheonjeon-ri petroglyph is inscribed with shale formation belonging to the Daegu Formation of the Gyeongsang Supergroup in the Cretaceous of the Mesozoic Era. This rock undergoes thermal alteration to become hornfels, and has a high hardness and dense texture. Rock-forming minerals have almost the same composition as quartz, alkali felspar, plagioclase, calcite, mica, chlorite and opaque minerals, but calcite is rarely detected in the weathered zone. The petroglyph forms a weathered zone with a certain depth, and there is a difference in mineral and chemical composition between weathered and unweathered zones, respectively. The CaO contents of the weathered zone were reduced by more than 90% compared to that of the unweathered zone, because calcite reacted with water and dissolved. As a result of calculating the surface weathering depth for the petroglyph with the transmission characteristics of X-rays, depth of the parts in falling off and exfoliation showed a depth of about 0.5 to 1 mm, but the weathering depth in most areas was calculated to be about 3 to 4 mm. This can be proved by the contents and changes of Ca and Sr. The surface discolorations of the petroglyph are distributed with different color density, and the yellowish brown discoloration is alternated with a thin biofilm layer, showing a coverage of 79.6%. Therefore, periodic preservation managements and preventive conservation monitoring that can effectively control the physicochemical and biological damages of the Cheonjeonri petroglyph will be necessary.