• Title/Summary/Keyword: Verification and validation

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Education program development for early childhood character through Nuri curriculum (누리과정 중심의 그림책 활용 유아인성교육 프로그램 개발)

  • Bae, Soo-Min;Youn, Jeong-Jin
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.6
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    • pp.55-62
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    • 2017
  • This research analyzes the character factor in picture book, so the purpose is to develop the early childhood character program through Nuri curriculum. Picture book is the most familiar media for childhoods, and we are available it naturally in our lives. For this first, we analyze 6 elements(consideration, respect, cooperation, sharing, order, filial duty) in teacher's guide of the Nuri curriculum. Next, consulting the analyzed factors, the 12 picture books which will be utilized this program are chosen by the standard like literary, artistic, educational value. The chosen picture book devised total 12 times education plan to design each 2 times education plan in the factors for teacher's guide of Nuri curriculum. Lastly, it was finally developed through validation process by 2 teachers and 2 the professors of early childhood education. The developed program is needed later field application and It is required of the effectiveness verification after we apply 12 times activities on each age of childhoods for 3 to 5 years od in education field, so it may improve elements like consideration, respect, cooperaion, sharing, order, filial duty as childhoods experience this program personally. Also, this can provide it to teachers in childhood eucation field as study guidance plan.

A Two-Stage Learning Method of CNN and K-means RGB Cluster for Sentiment Classification of Images (이미지 감성분류를 위한 CNN과 K-means RGB Cluster 이-단계 학습 방안)

  • Kim, Jeongtae;Park, Eunbi;Han, Kiwoong;Lee, Junghyun;Lee, Hong Joo
    • Journal of Intelligence and Information Systems
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    • v.27 no.3
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    • pp.139-156
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    • 2021
  • The biggest reason for using a deep learning model in image classification is that it is possible to consider the relationship between each region by extracting each region's features from the overall information of the image. However, the CNN model may not be suitable for emotional image data without the image's regional features. To solve the difficulty of classifying emotion images, many researchers each year propose a CNN-based architecture suitable for emotion images. Studies on the relationship between color and human emotion were also conducted, and results were derived that different emotions are induced according to color. In studies using deep learning, there have been studies that apply color information to image subtraction classification. The case where the image's color information is additionally used than the case where the classification model is trained with only the image improves the accuracy of classifying image emotions. This study proposes two ways to increase the accuracy by incorporating the result value after the model classifies an image's emotion. Both methods improve accuracy by modifying the result value based on statistics using the color of the picture. When performing the test by finding the two-color combinations most distributed for all training data, the two-color combinations most distributed for each test data image were found. The result values were corrected according to the color combination distribution. This method weights the result value obtained after the model classifies an image's emotion by creating an expression based on the log function and the exponential function. Emotion6, classified into six emotions, and Artphoto classified into eight categories were used for the image data. Densenet169, Mnasnet, Resnet101, Resnet152, and Vgg19 architectures were used for the CNN model, and the performance evaluation was compared before and after applying the two-stage learning to the CNN model. Inspired by color psychology, which deals with the relationship between colors and emotions, when creating a model that classifies an image's sentiment, we studied how to improve accuracy by modifying the result values based on color. Sixteen colors were used: red, orange, yellow, green, blue, indigo, purple, turquoise, pink, magenta, brown, gray, silver, gold, white, and black. It has meaning. Using Scikit-learn's Clustering, the seven colors that are primarily distributed in the image are checked. Then, the RGB coordinate values of the colors from the image are compared with the RGB coordinate values of the 16 colors presented in the above data. That is, it was converted to the closest color. Suppose three or more color combinations are selected. In that case, too many color combinations occur, resulting in a problem in which the distribution is scattered, so a situation fewer influences the result value. Therefore, to solve this problem, two-color combinations were found and weighted to the model. Before training, the most distributed color combinations were found for all training data images. The distribution of color combinations for each class was stored in a Python dictionary format to be used during testing. During the test, the two-color combinations that are most distributed for each test data image are found. After that, we checked how the color combinations were distributed in the training data and corrected the result. We devised several equations to weight the result value from the model based on the extracted color as described above. The data set was randomly divided by 80:20, and the model was verified using 20% of the data as a test set. After splitting the remaining 80% of the data into five divisions to perform 5-fold cross-validation, the model was trained five times using different verification datasets. Finally, the performance was checked using the test dataset that was previously separated. Adam was used as the activation function, and the learning rate was set to 0.01. The training was performed as much as 20 epochs, and if the validation loss value did not decrease during five epochs of learning, the experiment was stopped. Early tapping was set to load the model with the best validation loss value. The classification accuracy was better when the extracted information using color properties was used together than the case using only the CNN architecture.

The Alignment Evaluation for Patient Positioning System(PPS) of Gamma Knife PerfexionTM (감마나이프 퍼펙션의 자동환자이송장치에 대한 정렬됨 평가)

  • Jin, Seong Jin;Kim, Gyeong Rip;Hur, Beong Ik
    • Journal of the Korean Society of Radiology
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    • v.14 no.3
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    • pp.203-209
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    • 2020
  • The purpose of this study is to assess the mechanical stability and alignment of the patient positioning system (PPS) of Leksell Gamma Knife Perfexion(LGK PFX). The alignment of the PPS of the LGK PFX was evaluated through measurements of the deviation of the coincidence of the Radiological Focus Point(RFP) and the PPS Calibration Center Point(CCP) applying different weights on the couch(0, 50, 60, 70, 80, and 90 kg). In measurements, a service diode test tool with three diode detectors being used biannually at the time of the routine preventive maintenance was used. The test conducted with varying weights on the PPS using the service diode test tool measured the radial deviations for all three collimators 4, 8, and 16 mm and also for three different positions of the PPS. In order to evaluate the alignment of the PPS, the radial deviations of the correspondence of the radiation focus and the LGK calibration center point of multiple beams were averaged using the calibrated service diode test tool at three university hospitals in Busan and Gyeongnam. Looking at the center diode for all collimators 4, 8, and 16 mm without weight on the PPS, and examining the short and long diodes for the 4 mm collimator, the means of the validation difference, i.e., the radial deviation for the setting of 4, 8, and 16 mm collimators for the center diode were respectively measured to 0.058 ± 0.023, 0.079 ± 0.023, and 0.097 ± 0.049 mm, and when the 4 mm collimator was applied to the center diode, the short diode, and the long diode, the average of the radial deviation was respectively 0.058 ± 0.023, 0.078 ± 0.01 and 0.070 ± 0.023 mm. The average of the radial deviations when irradiating 8 and 16 mm collimators on short and long diodes without weight are measured to 0.07 ± 0.003(8 mm sd), 0.153 ± 0.002 mm(16 mm sd) and 0.031 ± 0.014(8 mm ld), 0.175 ± 0.01 mm(16 mm ld) respectively. When various weights of 50 to 90 kg are placed on the PPS, the average of radial deviation when irradiated to the center diode for 4, 8, and 16 mm is 0.061 ± 0.041 to 0.075 ± 0.015, 0.023 ± 0.004 to 0.034 ± 0.003, and 0.158 ± 0.08 to 0.17 ± 0.043 mm, respectively. In addition, in the same situation, when the short diode for 4, 8, and 16 mm was irradiated, the averages of radial deviations were 0.063 ± 0.024 to 0.07 ± 0.017, 0.037 ± 0.006 to 0.059 ± 0.001, and 0.154 ± 0.03 to 0.165 ± 0.07 mm, respectively. In addition, when irradiated on long diode for 4, 8, and 16 mm, the averages of radial deviations were measured to be 0.102 ± 0.029 to 0.124 ± 0.036, 0.035 ± 0.004 to 0.054 ± 0.02, and 0.183 ± 0.092 to 0.202 ± 0.012 mm, respectively. It was confirmed that all the verification results performed were in accordance with the manufacturer's allowable deviation criteria. It was found that weight dependence was negligible as a result of measuring the alignment according to various weights placed on the PPS that mimics the actual treatment environment. In particular, no further adjustment or recalibration of the PPS was required during the verification. It has been confirmed that the verification test of the PPS according to various weights is suitable for normal Quality Assurance of LGK PFX.

Improvements for Atmospheric Motion Vectors Algorithm Using First Guess by Optical Flow Method (옵티컬 플로우 방법으로 계산된 초기 바람 추정치에 따른 대기운동벡터 알고리즘 개선 연구)

  • Oh, Yurim;Park, Hyungmin;Kim, Jae Hwan;Kim, Somyoung
    • Korean Journal of Remote Sensing
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    • v.36 no.5_1
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    • pp.763-774
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    • 2020
  • Wind data forecasted from the numerical weather prediction (NWP) model is generally used as the first-guess of the target tracking process to obtain the atmospheric motion vectors(AMVs) because it increases tracking accuracy and reduce computational time. However, there is a contradiction that the NWP model used as the first-guess is used again as the reference in the AMVs verification process. To overcome this problem, model-independent first guesses are required. In this study, we propose the AMVs derivation from Lucas and Kanade optical flow method and then using it as the first guess. To retrieve AMVs, Himawari-8/AHI geostationary satellite level-1B data were used at 00, 06, 12, and 18 UTC from August 19 to September 5, 2015. To evaluate the impact of applying the optical flow method on the AMV derivation, cross-validation has been conducted in three ways as follows. (1) Without the first-guess, (2) NWP (KMA/UM) forecasted wind as the first-guess, and (3) Optical flow method based wind as the first-guess. As the results of verification using ECMWF ERA-Interim reanalysis data, the highest precision (RMSVD: 5.296-5.804 ms-1) was obtained using optical flow based winds as the first-guess. In addition, the computation speed for AMVs derivation was the slowest without the first-guess test, but the other two had similar performance. Thus, applying the optical flow method in the target tracking process of AMVs algorithm, this study showed that the optical flow method is very effective as a first guess for model-independent AMVs derivation.

울진 3&4호기 CFMS 화면설계의 인간공학적 검토

  • 정광태;이용희
    • Proceedings of the ESK Conference
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    • 1996.10a
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    • pp.171-178
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    • 1996
  • CFMS(Critical Function Monitoring System)는 원자력발전소의 비상시에 운전원에게 보조장보를 제공하는 지원시스템이다. 본 연구에서는 원자력발전소 울진 3&4호기 CFMS의 화면설계에 대한 인간 공학적 검토를 수행하였다. CFMS에 대한 규제 및 법규를 만족시키는 것과 CFMS 화면설계가 운전원에게 편의성을 제공할 수 있는지에 대한 인간공학적 타당성 평가의 사례를 제시하고자 한다. 본 연구에서는 인간공학적 검토의 공식적인 체계를 설정하기 위하여, CFMS 설계에서 필요한 인간공학 업무를 규정하고 수행절차를 기술하는 인간공학 프로그램 계획 (Human Factors Engineering Program Plan; HFEPP)과 설계평가의 방법과 업무 내용을 기술하는 확인 및 검증 프로그램 계획(Human Factors Engineerign Verification and Validation Plan; HFE V&V Plan)을 개발하였다. CFMS 설계에 대한 인간공학적 확인 및 검증을 위하여 CFMS의 정보 가용성 (information availability)과 화면 적합성 (display suitability)을 확인하였다. 정보 가용성의 확인은 CFMS 설계 요건서에서 정의된 정보를 중심으로 한 필요정보의 목록과 CFMS 화면상에서 제공되는 정보의 목록을 비교함으로써 수행되었다. 화면 적합성의 확인은 검토항목 선정, 검토양식 개발, 전문가 검토, 실험검토 등의 과정을 통하여 수행되었다. 관련 규제 문건으로 부터 규제요건상 만족해야할 최소한의 검토항목을 선정하고 검토양식을 개발하였으며, 인간공학 전문가들의 주관적 평가를 통하 여 수행되었다. 또한 화면의 조작방식에 대한 상세검토를 수행하였다. 검토결과로부터 발견된 문제점들은 HED (Human Engineerign Discrepance) 목록으로 정리하여 설계에 반영하도록 하였다.로 마음의 안정감, 몸의 긴장 이완에 따른 건강 상태 유지, 수업 집중도 향상 등이 나타났다. 위와 같은 종합 적 분석 결과에 따라, 본 연구는 제조 현장의 생산성 향상 및 품질 향상과 연계하여 작업자의 작업 집중도 향상, 작업자의 육체적, 심리적 변화에 따른 생산성 및 품질 향상 변화 정도 등의 산업공학(인간공학) 제 분야의 여러 측면에서 연구 및 적용이 가능하리라 사료된다.l, 시험군:25.90$\pm$7.16mg/d1, 47% 감소)를 나타내었으며, 시험군의 AUC는 대조군에 비해 39% 감소하였고, 혈중 아세트알데히드의 농도는 투여 60분후 시험군(3.96$\pm$0.07nmo1/$m\ell$)이 대조군(6.45$\pm$0,64nmo1/$m\ell$)에 비해 유의성 있는 감소(39%)를 나타내었으며, 시험군의 AUC는 대조군에 비해 48% 감소하였다 한편, 시험관내 에탄올 대사 효소에 대한 바이오짐의 효과를 검색해본 결과 바이오짐(2.0 $\mu\textrm{g}$/assay)에 의해 Aldehyde dehydrogenase(1.5unit/assay)의 활성이 14% 증가되었다. 본 연구의 결과로 볼 때, 비지니스 및 바이오짐은 음주 후 상승된 혈중 에탄을 농도 및 아세트알데히드의 농도를 현저히 감소시키는 효과가 있었다.량 보호 관리, 도시 소공원 개발, 역사 문화 공원 조성, 하천 공간 복원, 공원 시설 기능 개선, 이용 프로그램 개발, 공원 관리 개선, 환경 피해 녹지의 회복, 도시 환경 림 조성, 녹지 기능 증진, 도시 자연 경관 보전, 공원 녹지체계 구성, 공원 녹지 공급 균형, 주변 환경 녹화, 가로 녹화의 17개 시책을 제안하였다. 이러한 정책사업의 원활한 추진을 위해서는 기존의 관주도의 일방적인 공원 녹지 행정이 아닌 시민의 참여를 통

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Development of case-based learning and co-teaching clinical practice education model for pre-service nurses (예비간호사를 위한 사례기반학습 및 코티칭 임상실습 교육모형 개발)

  • Hyunjeong Kim;Heekyoung Hyoung;Hyunwoo Kim;Seryeong Kim
    • Journal of Christian Education in Korea
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    • v.72
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    • pp.245-271
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    • 2022
  • The purpose of this study is to develop a nursing clinical practice education model that applies case-based learning and co-teaching to nursing students, and to secure the validity of the developed model. To verify the validity of the nursing clinical practice education model, it was applied to the subject of 'Health Response and Nursing VI (Perception/ Cognition) Practice' in the 2nd semester of 2021 at J University in Jeonju, and the instructor's response to the model was evaluated. Surveys and focus group interviews were conducted on confidence in clinical practice and teaching and learning models. After deriving the case-based learning stage and co-teaching elements through a review of precedent literature and case studies, an initial model was devised after expert review, and the devised model was reviewed for internal validity by nursing education experts, and then modified and supplemented. As a result of the learner response evaluation conducted after applying the model to the clinical practice subject for external validation verification, the confidence in clinical performance was 4.22 points and the satisfaction with the teaching-learning model was 4.68 points. Summarizing the results of the focus group interview, the importance of prior learning and the learning of selected cases based on actual cases, learning terminology and professional knowledge, eliminated fear of the practice field, felt familiar, and learned various cases. He said that he was able to think critically through the time to organize the knowledge learned in the practice field. In addition, through co-teaching, it was found that field leaders and advisors taught the theoretical and practical aspects at the same time through examples, thereby experiencing practical education closer to practice. It is expected that the nursing clinical practice education model developed through this study, applying case-based learning and co-teaching, will be an effective teaching and learning model that can reduce the gap between theory and practice and improve the clinical performance of nursing students.

A Study on the Influence of Workers' Aspiration for Academic Needs on Participation in University Education (근로자의 학업욕구 열망이 대학교육 참여에 미치는 영향에 관한 연구)

  • Lee, Ji-Hun;Mun, Bok-Hyun
    • Journal of Korea Entertainment Industry Association
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    • v.15 no.3
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    • pp.231-241
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    • 2021
  • This study intended to present strategies and implications for attracting new students and customized education to university officials through research on the participation of workers' academic aspirations in university education. Thus, variables were derived by analyzing prior data, and causal settings between variables and questionnaires were developed. Subject to the survey, 331 workers interested in participating in university education were collected through interpersonal interviews. The collected data were dataized, and reliability and feasibility verification and frequency analysis were conducted. Finally, we validate the fit of the structural equation model and the causal relationship for each concept. Therefore, the results of the validation show the following implications. First, university officials should be motivated by a mentor and mentee system with experienced people who have switched to a suitable vocational group through university education. It will also be necessary to develop and disseminate programs so that they can continue to develop themselves for the future. To this end, it will be necessary to help them understand their aptitude and strengths through consultation with experts. Second, university officials should strengthen public relations so that prospective students can know the cases and information of the job transformation of the admitted workers through recommendations. It will also be necessary to develop university education programs that can self-develop, accept various ideas through "public contest", and provide accurate information about university education to workers through re-processing. Third, university officials should provide workers with a program that allows them to catch two rabbits: job transformation and self-improvement through university education. In other words, it is necessary to stimulate the motivation of workers by providing various information such as visiting advanced overseas companies, obtaining various certificates, moving between departments of blue-collar and white-collar, and transfer opportunities. Fourth, university officials should actively promote university education programs related to this by participating in university education and receiving systematic education and the flow of social environment. Finally, university officials will need to consult and promote workers so that they can self-develop when they participate in college education, and they will have to figure out what they need for self-development through demand surveys and analysis.

Verification of Gated Radiation Therapy: Dosimetric Impact of Residual Motion (여닫이형 방사선 치료의 검증: 잔여 움직임의 선량적 영향)

  • Yeo, Inhwan;Jung, Jae Won
    • Progress in Medical Physics
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    • v.25 no.3
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    • pp.128-138
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    • 2014
  • In gated radiation therapy (gRT), due to residual motion, beam delivery is intended to irradiate not only the true extent of disease, but also neighboring normal tissues. It is desired that the delivery covers the true extent (i.e. clinical target volume or CTV) as a minimum, although target moves under dose delivery. The objectives of our study are to validate if the intended dose is surely delivered to the true target in gRT and to quantitatively understand the trend of dose delivery on it and neighboring normal tissues when gating window (GW), motion amplitude (MA), and CTV size changes. To fulfill the objectives, experimental and computational studies have been designed and performed. A custom-made phantom with rectangle- and pyramid-shaped targets (CTVs) on a moving platform was scanned for four-dimensional imaging. Various GWs were selected and image integration was performed to generate targets (internal target volume or ITV) for planning that included the CTVs and internal margins (IM). The planning was done conventionally for the rectangle target and IMRT optimization was done for the pyramid target. Dose evaluation was then performed on a diode array aligned perpendicularly to the gated beams through measurements and computational modeling of dose delivery under motion. This study has quantitatively demonstrated and analytically interpreted the impact of residual motion including penumbral broadening for both targets, perturbed but secured dose coverage on the CTV, and significant doses delivered in the neighboring normal tissues. Dose volume histogram analyses also demonstrated and interpreted the trend of dose coverage: for ITV, it increased as GW or MA decreased or CTV size increased; for IM, it increased as GW or MA decreased; for the neighboring normal tissue, opposite trend to that of IM was observed. This study has provided a clear understanding on the impact of the residual motion and proved that if breathing is reproducible gRT is secure despite discontinuous delivery and target motion. The procedures and computational model can be used for commissioning, routine quality assurance, and patient-specific validation of gRT. More work needs to be done for patient-specific dose reconstruction on CT images.

A Comparative Study on the Effective Deep Learning for Fingerprint Recognition with Scar and Wrinkle (상처와 주름이 있는 지문 판별에 효율적인 심층 학습 비교연구)

  • Kim, JunSeob;Rim, BeanBonyka;Sung, Nak-Jun;Hong, Min
    • Journal of Internet Computing and Services
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    • v.21 no.4
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    • pp.17-23
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    • 2020
  • Biometric information indicating measurement items related to human characteristics has attracted great attention as security technology with high reliability since there is no fear of theft or loss. Among these biometric information, fingerprints are mainly used in fields such as identity verification and identification. If there is a problem such as a wound, wrinkle, or moisture that is difficult to authenticate to the fingerprint image when identifying the identity, the fingerprint expert can identify the problem with the fingerprint directly through the preprocessing step, and apply the image processing algorithm appropriate to the problem. Solve the problem. In this case, by implementing artificial intelligence software that distinguishes fingerprint images with cuts and wrinkles on the fingerprint, it is easy to check whether there are cuts or wrinkles, and by selecting an appropriate algorithm, the fingerprint image can be easily improved. In this study, we developed a total of 17,080 fingerprint databases by acquiring all finger prints of 1,010 students from the Royal University of Cambodia, 600 Sokoto open data sets, and 98 Korean students. In order to determine if there are any injuries or wrinkles in the built database, criteria were established, and the data were validated by experts. The training and test datasets consisted of Cambodian data and Sokoto data, and the ratio was set to 8: 2. The data of 98 Korean students were set up as a validation data set. Using the constructed data set, five CNN-based architectures such as Classic CNN, AlexNet, VGG-16, Resnet50, and Yolo v3 were implemented. A study was conducted to find the model that performed best on the readings. Among the five architectures, ResNet50 showed the best performance with 81.51%.

Numerical Modelling for the Dilation Flow of Gas in a Bentonite Buffer Material: DECOVALEX-2019 Task A (벤토나이트 완충재에서의 기체 팽창 흐름 수치 모델링: DECOVALEX-2019 Task A)

  • Lee, Jaewon;Lee, Changsoo;Kim, Geon Young
    • Tunnel and Underground Space
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    • v.30 no.4
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    • pp.382-393
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    • 2020
  • The engineered barrier system of high-level radioactive waste disposal must maintain its performance in the long term, because it must play a role in slowing the rate of leakage to the surrounding rock mass even if a radionuclide leak occurs from the canister. In particular, it is very important to clarify gas dilation flow phenomenon clearly, that occurs only in a medium containing a large amount of clay material such as a bentonite buffer, which can affect the long-term performance of the bentonite buffer. Accordingly, DECOVALEX-2019 Task A was conducted to identify the hydraulic-mechanical mechanism for the dilation flow, and to develop and verify a new numerical analysis technique for quantitative evaluation of gas migration phenomena. In this study, based on the conventional two-phase flow and mechanical behavior with effective stresses in the porous medium, the hydraulic-mechanical model was developed considering the concept of damage to simulate the formation of micro-cracks and expansion of the medium and the corresponding change in the hydraulic properties. Model verification and validation were conducted through comparison with the results of 1D and 3D gas injection tests. As a result of the numerical analysis, it was possible to model the sudden increase in pore water pressure, stress, gas inflow and outflow rate due to the dilation flow induced by gas pressure, however, the influence of the hydraulic-mechanical interaction was underestimated. Nevertheless, this study can provide a preliminary model for the dilation flow and a basis for developing an advanced model. It is believed that it can be used not only for analyzing data from laboratory and field tests, but also for long-term performance evaluation of the high-level radioactive waste disposal system.