• Nuclear Engineering and Technology
• /
• v.53 no.12
• /
• pp.4042-4051
• /
• 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.

• Journal of Ocean Engineering and Technology
• /
• v.19 no.1 s.62
• /
• pp.64-70
• /
• 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.

• Computers and Concrete
• /
• v.32 no.6
• /
• pp.577-594
• /
• 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.

• Journal of Families and Better Life
• /
• v.15 no.1
• /
• pp.71-82
• /
• 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.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.10 no.2
• /
• pp.133-144
• /
• 2006

In order to catch out such Bond Strength, the preceding researchers had ever examined the Bond Strength of FRP Plate through their experimentations by setting up of various fluent. However, since the experiment for research on such Bond Strength takes much of expenditure for equipment structure and time-consuming, also difficult to carry out, it is conducting limitedly. This Study purposes to develop the most suitable Artificial Neural Network Model by application of various Neural Network Model and Algorithm to the adhering experiment data of the preceding researchers. Output Layer of Artificial Neural Network Model, and Input Layer of Bond Strength were performed the learning by selection as the variable of the thickness, width, adhered length, the modulus of elasticity, tensile strength, and the compressive strength of concrete, tensile strength, width, respectively. The developed Artificial Neural Network Model has applied Back-Propagation, and its error was learnt to be converged within the range of 0.001. Besides, the process for generalization has dissolved the problem of Over-Fitting in the way of more generalized method by introduction of Bayesian Technique. The verification on the developed Model was executed by comparison with the resulted value of Bond Strength made by the other preceding researchers which was never been utilized to the learning as yet.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.5A
• /
• pp.485-493
• /
• 2010

GFRP rebar with ribs resemble those of deformed steel rebar was developed in 2005. It was reported that ribs of the GFRP rebar were sheared off due to the lower shear strength of polymer. In this study, the basic development length of the GFRP rebar was investigated through pull-out tests, models specified in ACI440.1R-03 and -06, and empirical model derived by Cosenza et al. (2002). As a results of pull-out tests, the critical embeddment length, which is defined as the length when failure mode is changed from pull-out to bar fracture, was 20 times of bar diameter for GFRP rebar and was 15 times for steel rebar. It is believed that the basic development of the GFRP rebar is 21 times of bar diameter, which is determined from the application of average bond strength into the model equation specified in ACI440.1R-03. Compared to the model equation in ACI440.1R-06, that in ACI440.1R-03 is recommendable for design purpose. The Cosenza et al.'s model underestimates the basic development length of the GFRP rebar.

• Smart Structures and Systems
• /
• v.26 no.4
• /
• pp.403-418
• /
• 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.

• Proceedings of the KWS Conference
• /
• 2003.11a
• /
• pp.188-190
• /
• 2003

• Proceedings of the Korea Concrete Institute Conference
• /
• 2001.11a
• /
• pp.1109-1114
• /
• 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.

• Journal of the Ergonomics Society of Korea
• /
• v.26 no.4
• /
• pp.135-142
• /
• 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.