• Title/Summary/Keyword: Strength development model

검색결과 700건 처리시간 0.031초

Multilevel modeling of diametral creep in pressure tubes of Korean CANDU units

  • Lee, Gyeong-Geun;Ahn, Dong-Hyun;Jin, Hyung-Ha;Song, Myung-Ho;Jung, Jong Yeob
    • Nuclear Engineering and Technology
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    • 제53권12호
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    • pp.4042-4051
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    • 2021
  • In this work, we applied a multilevel modeling technique to estimate the diametral creep in the pressure tubes of Korean Canada Deuterium Uranium (CANDU) units. Data accumulated from in-service inspections were used to develop the model. To confirm the strength of the multilevel models, a 2-level multilevel model considering the relationship between channels for a CANDU unit was compared with existing linear models. The multilevel model exhibited a very robust prediction accuracy compared to the linear models with different data pooling methods. A 3-level multilevel model, which considered individual bundles, channels, and units, was also implemented. The influence of the channel installation direction was incorporated into the three-stage multilevel model. For channels that were previously measured, the developed 3-level multilevel model exhibited a very good predictive power, and the prediction interval was very narrow. However, for channels that had never been measured before, the prediction interval widened considerably. This model can be sufficiently improved by the accumulation of more data and can be applied to other CANDU units.

수중물체에 대한 음향 표적강도의 수치해석과 실험적 검증 (Numerical Modeling and Experimental Verification for Target Strength of Submerged Objects)

  • 최영호;신기철;유진수;김재수;주원호;김영현;박종현;최상문;김우식
    • 한국해양공학회지
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    • 제19권1호
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    • pp.64-70
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    • 2005
  • Target Strength(TS) is an important factor for the detection of the target in an active sonar system: thus the numerical model for the prediction of TS is widely being developed. For the frequency range of several kHz, the most important scattering mechanism is known to be specular reflection, which is largely affected by the geometrical shape of the target. In this paper, a numerical algorithm to predict TS is developed based on the Kirchhoff approximation which is computationally efficient. The developed algorithm is applied to the canonical targets of simple shapes, for which the analytical solutions exist. The numerical results show good agreement with the analytical solutions. Also, the algorithm is applied to more complex scatterers, and is compared with the experimental data obtained in the water tank experiment for the purpose of verifying the developed numerical model. Discussions on the effect of spatial sampling and other aspects of numerical m odeling are presented.

Intelligent prediction of engineered cementitious composites with limestone calcined clay cement (LC3-ECC) compressive strength based on novel machine learning techniques

  • Enming Li;Ning Zhang;Bin Xi;Vivian WY Tam;Jiajia Wang;Jian Zhou
    • Computers and Concrete
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    • 제32권6호
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    • pp.577-594
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    • 2023
  • Engineered cementitious composites with calcined clay limestone cement (LC3-ECC) as a kind of green, low-carbon and high toughness concrete, has recently received significant investigation. However, the complicated relationship between potential influential factors and LC3-ECC compressive strength makes the prediction of LC3-ECC compressive strength difficult. Regarding this, the machine learning-based prediction models for the compressive strength of LC3-ECC concrete is firstly proposed and developed. Models combine three novel meta-heuristic algorithms (golden jackal optimization algorithm, butterfly optimization algorithm and whale optimization algorithm) with support vector regression (SVR) to improve the accuracy of prediction. A new dataset about LC3-ECC compressive strength was integrated based on 156 data from previous studies and used to develop the SVR-based models. Thirteen potential factors affecting the compressive strength of LC3-ECC were comprehensively considered in the model. The results show all hybrid SVR prediction models can reach the Coefficient of determination (R2) above 0.95 for the testing set and 0.97 for the training set. Radar and Taylor plots also show better overall prediction performance of the hybrid SVR models than several traditional machine learning techniques, which confirms the superiority of the three proposed methods. The successful development of this predictive model can provide scientific guidance for LC3-ECC materials and further apply to such low-carbon, sustainable cement-based materials.

청소년 자녀와 부모 관계향상 프로그램 모형 (The Model of Parent-Child Relationship Program for the Adolescents' Parents)

  • 윤명선
    • 가정과삶의질연구
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    • 제15권1호
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    • pp.71-82
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    • 1997
  • This paper concerns with parent-child relationship program for the adolescents' parents(PCRP). The purpose of this paper is to develop a model for the strength of the relationship between parents and their children as well as to prevent adolescent's individual and social problems The contents of PCRP based on the theoretical background consist of our parts: understanding adolescent physical and psychological development understanding adolescent sexuality developing effective communication skills and developing conflict solving skills. Implicationsh for the program evaluation methods and further development of family life education are discussed.

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역전파 학습 알고리즘을 이용한 콘크리트와 부착된 FRP 판의 부착강도 모델 개발 (Development of Bond Strength Model for FRP Plates Using Back-Propagation Algorithm)

  • 박도경
    • 한국구조물진단유지관리공학회 논문집
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    • 제10권2호
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    • pp.133-144
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    • 2006
  • FRP 판은 외부 부착된 보강 판의 효과적인 부착강도의 증진으로 실질적으로 부착강도에 대한 많은 연구가 수행되어왔다. 선행연구자들은 이러한 부착강도를 알아보기 위하여 다양한 변수를 설정하여 실험을 통하여 FRP 판의 부착강도를 규명하였다. 그러나, 이러한 부착강도를 알아보기 위한 실험은 장비구축의 비용과 시간 소비가 많이 되고 수행하기 어렵기 때문에 국한적으로 수행되고 있다. 본 연구는 선행연구자들의 부착실험 데이터를 다양한 신경망 모형과 알고리즘을 적용하여 최적의 인공신경망 모형을 개발하는데 그 목적이 있다. 인공신경망 모형의 출력층은 부착강도, 입력층은 FRP 판의 두께, 폭, 부착 길이, 탄성계수, 인장강도와 콘크리트의 압축강도, 인장강도, 폭을 변수로 선정하여 학습을 수행하였다. 개발된 인공신경망 모형은 역전파 학습 알고리즘을 적용하였으며, 오차는 0.001범위에 수렴되도록 학습을 하였다. 또한, 일반화 과정은 Bayesian 기법을 도입함으로써 보다 일반화된 방법으로 과대적합의 문제를 해소하였다. 개발된 모형의 검증은 학습에 이용되지 않은 다른 선행연구자들의 부착강도 결과 값과 비교함으로서 실시하였다.

이형 GFRP 보강근의 기본정착길이에 대한 연구 (A Study on the Basic Development Length of GFRP Rebar With Ribs)

  • 문도영
    • 대한토목학회논문집
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    • 제30권5A호
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    • pp.485-493
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    • 2010
  • 국내에서 개발된 이형 GFRP 보강근은 표면에 구축된 이형의 전단강도가 콘크리트의 전단강도 보다 상대적으로 작아 이형철근과 달리 이형 자체가 전단파괴되는 파괴모드를 보이는 것으로 확인된바 있다. 본 논문에서는 이형을 갖는 GFRP 보강근의 기본정착길이를 인발실험과 설계모델식과 해석적 엄밀식을 통해 고찰하였다. 실험결과, 동일조건하에서 파괴모드가 변화되는 임계정착길이가 이형철근은 직경의 15배, 이형 GFRP 보강근은 20배인 것으로 나타났다. 또한 실험결과를 ACI440.1R-03 설계모델식에 적용하여 분석한 결과, 충분한 횡구속이 수반된 경우 직경 9 mm의 이형 GFRP 보강근의 기본정착길이는 직경의 21배인 것으로 나타났다. 반면, ACI440.1R-06에 제시된 기본정착길이 모델은 실험결과에 비하여 너무 과대한 기본정착길이를 요구하는 것으로 나타났다. Cosenza 등(2002)의 모델은 실험결과에 비하여 더 적은 기본 정착길이를 요구하므로, 설계목적의 사용은 제한적인 것으로 판단되었다.

Evaluating the bond strength of FRP in concrete samples using machine learning methods

  • Gao, Juncheng;Koopialipoor, Mohammadreza;Armaghani, Danial Jahed;Ghabussi, Aria;Baharom, Shahrizan;Morasaei, Armin;Shariati, Ali;Khorami, Majid;Zhou, Jian
    • Smart Structures and Systems
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    • 제26권4호
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    • pp.403-418
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    • 2020
  • In recent years, the use of Fiber Reinforced Polymers (FRPs) as one of the most common ways to increase the strength of concrete samples, has been introduced. Evaluation of the final strength of these specimens is performed with different experimental methods. In this research, due to the variety of models, the low accuracy and impact of different parameters, the use of new intelligence methods is considered. Therefore, using artificial intelligent-based models, a new solution for evaluating the bond strength of FRP is presented in this paper. 150 experimental samples were collected from previous studies, and then two new hybrid models of Imperialist Competitive Algorithm (ICA)-Artificial Neural Network (ANN) and Artificial Bee Colony (ABC)-ANN were developed. These models were evaluated using different performance indices and then, a comparison was made between the developed models. The results showed that the ICA-ANN model's ability to predict the bond strength of FRP is higher than the ABC-ANN model. Finally, to demonstrate the capabilities of this new model, a comparison was made between the five experimental models and the results were presented for all data. This comparison showed that the new model could offer better performance. It is concluded that the proposed hybrid models can be utilized in the field of this study as a suitable substitute for empirical models.

전단보강철근이 없는 RC보의 트러스 해석기법 연구 (Development of A New Truss Model for RC Beams without Web Reinforcement)

  • 김지훈;정제평;김우
    • 한국콘크리트학회:학술대회논문집
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    • 한국콘크리트학회 2001년도 가을 학술발표회 논문집
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    • pp.1109-1114
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    • 2001
  • This paper describes an attempt to develop a new truss model for reinforced concrete beams failing in shear based on a rational behavioral model. The key idea incorporated with truss model is the internal force state factor which is able to express global state of internal force flow in cracked reinforced concrete beams subjected to shear and bending. A new truss model using internal force state factor may provide a comprehensive result of shear strength in reinforced concrete beams without web reinforcement.

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활성화 확산 모형을 이용한 아이콘 평가 (Icon Evaluation Using Spreading Activation Model)

  • 이선정;명노해
    • 대한인간공학회지
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    • 제26권4호
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    • pp.135-142
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    • 2007
  • Icon conveys symbolic information which they have become ubiquitous as main element of GUI. However, users often cannot intuitively understand its functional meanings. Icon has to be designed for users to easily understand functional meanings. In order to evaluate icon, the spreading activation model can be used to effectively understand the process of information retrieval. In asymmetric spreading activation model is that in the two nodes the degree of spreading activation is different according to direction. Thus, asymmetric spreading activation theory was performed evaluating the strength of association when users see visual image to associate their verbal meaning (visual image - verbal meaning pair) and users see verbal meaning to associate their visual image (verbal meaning - visual image pair). According to the direction, this study hypothesizes that the well-designed icons have symmetric relationship rather than asymmetric relationship between the two pairs. The strength of association is measured through the reaction time and the accuracy rate. In performing SAT (spreading activation test), the ten icons were selected as word processing software icons. After first SAT, newly designed icons were developed based on Korean mental model, and second SAT was conducted using them. The results showed that the accuracy rate of newly designed icon has been improved. Also there is significant difference of reaction time between current icons and newly designed icons. Well-designed icon is confirmed that the strength of association relationship arises symmetrically rather than asymmetrically between the two pairs. User centered icons could be designed by improving the strength of association between the two pairs. Asymmetric SAT evaluates the strength of the association between the visual image and the verbal meanings to contribute to the development of icon which it related to human's association structure.