• Journal of the Korea Concrete Institute
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• v.17 no.6 s.90
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• pp.955-962
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• 2005

Still no accurate theory exists for predicting ultimate shear strength of deep reinforced concrete beams because of the structural and material non-linearity after cracking. Currently, the load capacity assesment is performed for the upper structure of the bridges and containing non-reliability in the applications and results. The purpose in this study is to evaluate analytically the complex shear behaviors and normal strength for the reinforced concrete deep beams and to offer the accuracy load capacity assesment method based on the reliability theories. This paper presents a method for the load capacity assesment of reinforcement concrete deep beams using nonlinear finite element analysis. A computer program named RCAHEST (Reinforced Concrete Analysis in Higher Evaluation System Technology), for the analysis of reinforced concrete structures was used. Material non-linearity is taken Into account by comprising tensile, compressive and shear models of cracked concrete and a model of reinforcing steel. From the results, determine the reliability index for the failure base on the Euro Code. Then, calculate additional reduction coefficient to satisfy the goals from the reliability analysis. The proposed numerical method for the load capacity assesment of reinforced concrete deep beams is verified by comparison with the others methods.

• Journal of the Korea Concrete Institute
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• v.15 no.3
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• pp.400-408
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• 2003

Chloride ion inside concrete destroys the so-called passive film surrounding reinforcing bars inside concrete so that the so-called salt attack accelerates corrosion which is the most critical factor for durability as well as structural safety of reinforced concrete structures. Recently, as a solution of the salt attack, the ground granulated blast-furnace slag(GGBFS) have been used as binder or blended cement more extensively. In this paper, characteristics of chloride ion diffusion for the GGBFS concrete, which is known to possess better resistance to damage due to the chloride ion penetration than ordinary portland cement(OPC) concrete possesses, are analyzed and a chloride ion diffusion model for the GGBFS concrete is proposed by modifying an existing diffusion model for the OPC concrete. The proposed model is verified by comparing diffusion analysis results using the model accelerated chloride penetration test results for concrete specimens as well as field test results for an RC bridge pier. Then, an optimal resistance condition to chloride penetration for the GGBFS concrete is obtained according to degrees of fineness and replacement ratios of the GGBFS concrete. The result shows that the GGBFS concrete has better resistance to chloride ion penetration than OPC concrete has and the resistance is more affected by the replacement ratio than the degree of fineness of the GGBFS.

• The Journal of Engineering Geology
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• v.14 no.4 s.41
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• pp.443-450
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• 2004

This study developed a prediction model of debris flow to predict a landslide probability on natural terrain composed of the Tertiary sedimentary and volcanic rocks using a logistic regression analysis. The landslides data were collected around Pohang, Gyeongbuk province where more than 100 landslides were occurred in 1998. Considered with basic characteristics of the logistic regression analysis, field survey and laboratory soil tests were performed for both slided points and not-slided points. The final iufluential factors on landslides were selected as six factors by the logistic regression analysis. The six factors are composed of two topographic factors and four geologic factors. The developed landslide prediction model has more than $90\%$ of prediction accuracy. Therefore, it is possible to make probabilistic and quantitative prediction of landslide occurrence using the developed model in this study area as well as the previously developed model for metamorphic and granitic rocks.

• Journal of the Korean GEO-environmental Society
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• v.16 no.12
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• pp.23-35
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• 2015

Nonlinear soil behavior before failure under dynamic loading is often implemented in a numerical analysis code by a mathematical fitting function model with Masing's rule. However, the model may show different behavior with an experimental results obtained from laboratory test in damping ratio corresponding secant shear modulus for a certain shear strain rage. The difference may come from an unique soil characteristics which is unable to implement by using the existing mathematical fitting model. As of now, several fitting models have been suggested to overcome the difference between model and real soil behavior but consequence of the difference in dynamic analysis is not reviewed yet. In this paper, the effect of the difference on site response was examined through nonlinear response history analysis. The analysis was verified and calibrated with well defined dynamic geotechnical centrifuge test. Site response analyses were performed with three mathematical fitting function models and compared with the centrifuge test results in prototype scale. The errors on peak ground acceleration between analysis and experiment getting increased as increasing the intensity of the input motion. In practical point of view, the analysis results of accuracy with the fitting model is not significant in low to mid input motion intensity.

• Composites Research
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• v.36 no.1
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• pp.53-58
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• 2023

The PIC design method is assigning different stacking sequences for each shell element through the preliminary FE analysis. In previous study, machine learning was applied to the PIC design method in order to assign the region efficiently, and the training data is labeled by dividing each region into tension, compression, and shear through the preliminary FE analysis results value. However, since buckling is not considered, when buckling occurs, it can't be divided into appropriate loading type. In the present study, it was proposed PIC-NTL (PIC design using novel technique for analyzing load type) which is method for applying a novel technique for analyzing load type considering buckling to the conventional PIC design. The stress triaxiality for each ply were analyzed for buckling analysis, and the representative loading type was designated through the determined loading type within decision area divided into two regions of the same size in the thickness direction of the elements. The input value of the training data and label consisted in coordination of element and representative loading type of each decision area, respectively. A machine learning model was trained through the training data, and the hyperparameters that affect the performance of the machine learning model were tuned to optimal values through Bayesian algorithm. Among the tuned machine learning models, the SVM model showed the highest performance. Most effective stacking sequence were mapped into PIC tube based on trained SVM model. FE analysis results show the design method proposed in this study has superior external loading resistance and energy absorption compared to previous study.

• Economic and Environmental Geology
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• v.56 no.5
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• pp.515-532
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• 2023

Bentonite, predominantly consists of expandable clay minerals, is considered to be the suitable buffering material in high-level radioactive waste disposal repository due to its large swelling property and low permeability. Additionally, the bentonite has large cation exchange capacity and specific surface area, and thus, it effectively retards the transport of leaked radionuclides to surrounding environments. This study aims to review the thermodynamic sorption models for four radionuclides (U, Am, Se, and Eu) and eight bentonites. Then, the thermodynamic sorption models and optimized sorption parameters were precisely analyzed by considering the experimental conditions in previous study. Here, the optimized sorption parameters showed that thermodynamic sorption models were related to experimental conditions such as types and concentrations of radionuclides, ionic strength, major competing cation, temperature, solid-to-liquid ratio, carbonate species, and mineralogical properties of bentonite. These results implied that the thermodynamic sorption models suggested by the optimization at specific experimental conditions had large uncertainty for application to various environmental conditions.

• Journal of KIISE:Software and Applications
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• v.37 no.6
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• pp.430-445
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• 2010

Effective service description and modeling methodologies are essential for dynamic service composition to provide autonomous services for users in ubiquitous computing environments. In our previous research, we proposed a 'u-Service' as an abstract and structured concept for operations of devices in ubiquitous environments. In addition, we established the mechanism to structure u-Services as an ontology and the description specification to represent attributes of u-Services. However, it did not provide enough methods or standards to analyze and evaluate the effectiveness of the u-Service ontology in the design time. Since existing quality models for software products or computing systems cannot consider characteristics of ubiquitous services, they are not suitable for ubiquitous service ontology. Therefore, in this paper, we propose a quality evaluation model to design and modeling a good ubiquitous service ontology, based on our u-Service ontology building process. We extract modeling goals and evaluation indicators according to characteristics of ubiquitous service ontology, and establish quality metrics to quantify each quality sub-characteristics. The experiment result of the proposed quality evaluation model for u-Service ontologies which are constructed for our previous works shows that we can analyze the design of ubiquitous service ontology from various angles, and indicate recommendations for improvement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.683-688
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• 2018

Recently, the demand for electric energy has been increasing due to the spread of hybrid electric vehicles. In this study, to meet this demand, the ANSYS MAXWELL electromagnetic simulation system was used to compare the power generation characteristics of three types of suspension system that can generate electricity using energy harvesting technology. Next, the optimal design was determined for each model by using the commercial PIDO (Process Integration and Design Optimization) tool, PIANO (Process Integration, Automation and Optimization). We selected three design variables and constructed an approximate model based on the experimental design method through electromagnetic analysis for 18 experimental points derived from Orthogonal Arrays among the experimental design methods. Then, we determined the optimal design by applying the Evolutionary Algorithm. Finally, the optimal design results were verified by electromagnetic simulation of the optimum design result model using the same analysis conditions as those of the initial model. After comparing the power generation characteristics for the optimal structure for each linear generator model, the maximum power generation amounts in the 8pole-8slot, 12pole-12slot, and 16pole-16slot structures were 366.5W, 466.7W and 579.7W, respectively, and it was found that as the number of slots and poles increases, the power generation increases.

• Tunnel and Underground Space
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• v.30 no.4
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• pp.306-319
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• 2020

Characterizations of Excavation Damage Zone (EDZ), which is hydro-mechanical degrading the host rock, are the important issues on the geological repository for the spent nuclear fuel. In the DECOVALEX 2019 project, Task G aimed to model the fractured rock numerically, describe the hydro-mechanical behavior of EDZ, and predict the change of the hydraulic factor during the lifetime of the geological repository. Task G prepared two-dimensional fractured rock model to compare the characteristics of each simulation tools in Work Package 1, validated the extended three-dimensional model using the TAS04 in-situ interference tests from Äspö Hard Rock Laboratory in Work Package 2, and applied the thermal and glacial loads to monitor the long-term hydro-mechanical response on the fractured rock in Work Package 3. Each modelling team adopted both Finite Element Method (FEM) and Discrete Element Method (DEM) to simulate the hydro-mechanical behavior of the fracture rock, and added the various approaches to describe the EDZ and fracture geometry which are appropriate to each simulation method. Therefore, this research can introduce a variety of numerical approaches and considerations to model the geological repository for the spent nuclear fuel in the crystalline fractured rock.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.6
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• pp.373-381
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• 2012

An automatic flow and water quality monitoring system was applied to estimate pollutant loads to an urban stream during storm events in DTV (Daeduk Techno Valley), Daejeon, Korea. The monitoring system consists of rainfall gage, ultrasonic water level meter, water quality sensors for DO, temperature, pH, conductivity, turbidity and automatic water sampler for further laboratory analysis. All data are transmitted through on-line system and the monitoring system is designed to be controlled manually in the field and remotely from laboratory computer. Flow rates were verified with field measurements during storm events and showed good agreements. Automatic sampler was used to collect real time samples and analyzed for BOD, COD, TN, TP, SS and other pollutant concentrations in the laboratory. SWMM (Storm Water Management Model) urban watershed model was applied and calibrated using the observed flow and water quality data for the study area. While flow modeling results showed good agreement for all events, water quality modeling results showed variable levels of agreement. These results indicate that current options in the SWMM model to predict pollutant build up and wash-off effects are not sufficient to satisfy modeling of all the rainfall events under study and thus need further modification. This study showed the automatic monitoring system can be used to provide data to assist further refinement of modeling accuracy. This automatic stormwater monitoring and modeling system can be used to develop basin scale water quality management strategies of urban streams in storm events.