• Computers and Concrete
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• 제12권4호
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• pp.377-392
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• 2013

This paper investigates prediction models estimating the hydration properties of concrete, such as the compressive strength, the splitting tensile strength, the elastic modulus,and the autogenous shrinkage. A prediction model is suggested on the basis of an equation that is formulated to predict the compressive strength. Based on the assumption that the apparent activation energy is a characteristic property of concrete, a prediction model for the compressive strength is applied to hydration-related properties. The hydration properties predicted by the model are compared with experimental results, and it is concluded that the prediction model properly estimates the splitting tensile strength, elastic modulus, and autogenous shrinkage as well as the compressive strength of concrete.

• Advances in concrete construction
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• 제13권5호
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• pp.395-410
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• 2022

This study collected the results of material tests and full-scale pumping tests using 127 types of concrete mixtures with compressive strength ranging from 24 to 200 MPa. The results of 242 material tests showed high correlations between the viscosity of the lubricating layer and concrete, between the slump and the yield stress of concrete, between the water-binder ratio and the viscosity of lubricating layer, and between the time required to reach 500 mm of slump flow and concrete viscosity. Based on these correlations, pumpability was predicted using 101 pumping test conditions, and their accuracy was compared to the actual test results. When the rheological properties of concrete and the lubricating layer were directly measured, the prediction result showed the highest accuracy. A high accuracy can be achieved when the measured viscosity of the lubricating layer, a key determinant of concrete pumpability, is reflected in the prediction of pumpability. When measuring rheological properties is difficult, the slump test can be used to quantitatively predict the pumpability despite the lower accuracy than those of other prediction methods.

• 한국농공학회논문집
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• 제65권3호
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• pp.15-28
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• 2023

The compaction properties of the soil change depending on the physical properties, and are also affected by crushing of the particles. Since the particle size distribution of soil affects the engineering properties of the soil, it is necessary to analyze the material properties to understand the compaction characteristics. In this study, the size of each sieve was classified into four in the particle size analysis as a material property, and the compaction characteristics were evaluated by multiple regression and maximum dry unit weight. As a result of maximum dry unit weight prediction, multiple regression analysis showed R² of 0.70 or more, and DNN analysis showed R² of 0.80 or more. The reliability of the prediction result analyzed by DNN was evaluated higher than that of multiple regression, and the analysis result of DNN-T showed improved prediction results by 1.87% than DNN. The prediction of maximum dry unit weight using particle size distribution seems to be applied to evaluate the compacting state by identifying the material characteristics of roads and embankments. In addition, the particle size distribution can be used as a parameter for predicting maximum dry unit weight, and it is expected to be of great help in terms of time and cost of applying it to the compaction state evaluation.

• 콘크리트학회논문집
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• 제12권1호
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• pp.33-44
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• 2000

Since the mechanism of chloride diffusion and its ratio in concrete depend on structural conditions and concrete as a micro-structure, if these are analyzed quantitatively, the long-term ageing of structures can be predicted. Although, a quantitative analysis of concrete micro-structure, in which the results are affected by various parameters, is very difficult, this can be done indirectly by the durability test of concrete. In this study, the compressive strength, void ratio and air permeability of concrete. In this study, the compressive strength, void ratio and air permeability of concrete are chosen as the parameters in concrete durability test, and these effects on test results are analysed according to changes of mixing properties. The relationships between parameters and chloride diffusion velocity is used for prediction models of chloride diffusion. The developed prediction models for the chloride diffusion according to mixing and physical properties, can be used to estimate the service life and corrosion initiation of reinforcing bars in marine structures.

• Journal of Welding and Joining
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• 제23권4호
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• pp.17-26
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• 2005

HAZ (Heat Affected Zone) which occurs during welding thermal cycle has an important effect on the mechanical properties of the weld metal. So there were many efforts to develop the model which is able to predict the microstructure and mechanical properties in weld HAZ and lots of metallurgical models have reported since early 1940. These models are justifiable based on the reasonable assumption and analytical approach, but they also have limitation by interesting alloying system and assumption in each literature. Therefore, this study summaries the previous models for prediction of properties in weld HAZ. Then several issues to solve for developing the more reliable model were proposed.

• 한국의류학회지
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• 제34권9호
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• pp.1567-1580
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• 2010

This study investigates the effects of visual texture on color emotion and establishes prediction models for color emotion by both physical color properties and visual texture characteristics. A variety of fabrics including silk, cotton, and flax were colored by digital textile printing according to chromatic hue and tone combinations that are evaluated in terms of color emotion. Subjective visual texture ratings are also obtained for gray-colored same fabrics to those used in color emotion tests. As a result, fabric clusters by visual texture factors showed significant differences in color emotion factors that are primarily affected by physical color properties. Finally prediction models for color emotion factors by both physical color properties and visual texture clusters were established, which has a potential to be used to explain color emotion according to the visual texture characteristics of fabrics.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2002년도 추계학술발표대회 논문집
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• pp.292-295
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• 2002

In this paper, an analytical model for the prediction of the elastic properties of multi-axial warp knit fabric (MWK) composites is proposed. The geometric limitation, effect of stitching fibers and design parameters of MWK composites are considered in the model. The elastic behavior of MWK composites was conducted by using an averaging method. The predicted elastic properties are in reasonably good agreement with experimental values. Finally the effect of stitching in the MWK composites are discussed.

• 한국지반환경공학회 논문집
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• 제19권5호
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• pp.13-22
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• 2018

The number of researches on the mechanical properties of cemented sand and gravel (CSG) materials and the application of the CSG Dam has been increased. In order to explain the technical scheme of strength prediction model about the artificial neural network, we obtained the sample data by orthogonal test using the PVA (Polyvinyl alcohol) fiber, different amount of cementing materials and age, and established the efficient evaluation and prediction system. Combined with the analysis about the importance of influence factors, the prediction accuracy was above 95%. This provides the scientific theory for the further application of CSG, and will also be the foundation to apply the artificial neural network theory further in water conservancy project for the future.

• 청정기술
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• 제18권3호
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• pp.265-271
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• 2012

화석연료에 대한 의존성을 줄이기 위한 대안으로서 재생에너지 사용이 요구되고 있다. 청정에너지원의 하나인 바이오매스는 그 물성치의 실시간 파악이 중요하기 때문에 다양한 종류의 바이오매스에 대해 널리 연구되어 왔으며, 방법론적인 측면에서는 비침투성이며 많은 정보를 가진 특징으로 인하여 근적외선 분광법이 성공적으로 적용되었다. 본 논문에서는 여러 바이오매스 종류에 대한 물성치의 빠른 예측을 위해 근적외선 데이터에 기반한 비선형 방법론의 적용성을 평가하였다. 다양한 방법론에 기반한 예측 모델들을 근적외선 데이터의 전처리방법과 조합하여 예측 성능을 평가하였다. 바이오매스 물성 예측 모델의 성능에서는 선형 모델보다는 비선형 모델에서 예측오차가 최소화되었으며 전처리 방법과 결합되었을 때 최적의 예측결과를 얻을 수 있었다.

• Geomechanics and Engineering
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• 제35권6호
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• pp.647-663
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• 2023

The investigation of the disc cutter wear prediction has an important guiding role in TBM equipment selection, project planning, and cost forecasting, especially when tunneling in a long-distance rock formations with high strength and high abrasivity. In this study, a comprehensive database of disc cutter wear data, geological properties, and tunneling parameters is obtained from a 1326 m excavated metro tunnel project in leptynite in Shenzhen, China. The failure forms and wear consumption of disc cutters on site are analyzed with emphasis. The results showed that 81% of disc cutters fail due to uniform wear, and other cutters are replaced owing to abnormal wear, especially flat wear of the cutter rings. In addition, it is found that there is a reasonable direct proportional relationship between the uniform wear rate (WR) and the installation radius (R), and the coefficient depends on geological characteristics and tunneling parameters. Thus, a preliminary prediction formula of the uniform wear rate, based on the installation radius of the cutterhead, was established. The correlation between some important geological properties (K_V and UCS) along with some tunneling parameters (F_n and p) and wear rate was discussed using regression analysis methods, and several prediction models for uniform wear rate were developed. Compared with a single variable, the multivariable model shows better prediction ability, and 89% of WR can be accurately estimated. The prediction model has reliability and provides a practical tool for wear prediction of disc cutter under similar hard rock projects with similar geological conditions.