Journal of the Korea Institute of Building Construction
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v.9
no.5
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pp.119-125
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2009
In this paper, the engineering properties and estimation of drying shrinkage of concrete incorporating fly ash (FA), blast furnace slag (BS) and cement kiln dust (CKD) were discussed. FA, BS and CKD contents ranged from 0% to 20%. Water to binder ratio (W/B) also ranged from 40 to 50 %, with a 5% interval. For estimating drying shrinkage, an exponential model proposed by the author was applied, According to results, the use of FA, BS and CKD resulted in a decrease of flowability and air contents. As expected, the use of admixtures also decreases the early age strength of concrete, while at later age, due to a pozzolanic reaction of FA and BS, the compressive strength was recovered to a value comparable with that of plain concrete. For drying shrinkage, the use of admixtures led to an increase in the drying shrinkage of concrete. The exponential model suggested by the author showed good agreement between the calculated and experimental values both at early age and at later age.
In this study, in order to propose an efficient model to predict the torque capacity of steel fiber reinforced concrete (SFRC) beams, the existing experimental data related to torsional response of beams is reviewed. It is observed that existing data neglects the effects of some parameters on the variation of torque capacity. Thus, an experimental research was also conducted to obtain the effects of neglected parameters. In the experimental study, a total of seventeen SFRC beams are tested against torsion. The parameters considered in the experiments are concrete compressive strength, steel fiber aspect ratio, volumetric ratio of steel fibers and longitudinal reinforcement ratio. The effect of each parameter is discussed in terms of torque versus unit angle of twist graphs. The data obtained from this experimental research is also combined with the data got from previous studies and employed in artificial neural network (ANN) analysis to estimate the ultimate torque capacity of SFRC beams. In addition to parameters considered in the experiments, aspect ratio of beam cross-section, yield strengths of both transverse and longitudinal reinforcements, and transverse reinforcement ratio are also defined as parameters in ANN analysis due to their significant effects observed in previous studies. Assessment of the accuracy of ANN analysis in estimating the ultimate torque capacity of SFRC beams is performed by comparing the analytical and experimental results. Comparisons are conducted in terms of root mean square error (RMSE), mean absolute error (MAE) and coefficient of efficiency ($E_f$). The results of this study revealed that addition of steel fibers increases the ultimate torque capacity of reinforced concrete beams. It is also found that ANN is a powerful method and a feasible tool to estimate ultimate torque capacity of both normal and high strength concrete beams within the range of input parameters considered.
Journal of the Korean Society of Hazard Mitigation
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v.3
no.4
s.11
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pp.119-129
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2003
Concrete and steel are essential structural materials in the construction. But, concrete, different from steel, consists of many materials and is affected by many factors such as properties of materials, site environmental situations, and skill of constructors. Concrete have two kinds of properties, immediately knowing properties such as slump, air contents and time dependent one like strength. Therefore, concrete mixes depend on experiences of experts. However, at point of time using High Performance Concrete, new method is wanted because of more ingredients like mineral and chemical admixtures and lack of data. Artificial Neural Networks(ANN) are a mimic models of human brain to solve a complex nonlinear problem. They are powerful pattern recognizers and classifiers, also their computing abilities have been proven in the fields of prediction, estimation and pattern recognition. Here, among them, the back propagation network and radial basis function network ate used. Compositions of high-performance concrete mixes are eight components(water, cement, fine aggregate, coarse aggregate, fly ash, silica fume, superplasticizer and air-entrainer). Compressive strength, slump, and air contents are measured. The results show that neural networks are proper tools to minimize the uncertainties of the design of concrete mixtures.
Journal of the Korean Recycled Construction Resources Institute
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v.3
no.4
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pp.301-306
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2015
For the purpose of developing high performance marine concrete with improved crack resistance and durability, this analytical study aimed to estimate strength, hydration heat characteristics, and chloride attack resistance of concrete with mineral admixture. Ground granulated furnace slag and fly ash were considered for mineral admixture. The replacement of ground granulated furnace slag and fly ash considered in the analysis was in the range of 0~70% and 0~40 %, respectively. The analysis results indicated that both ground granulated furnace slag and fly ash decreased compressive strength, and the effect of adding ground granulated furnace slag on mitigation of hydration heat was limited whereas fly ash had an noticeable influence on it. It was also found that the replacement with ground granulated furnace slag enhanced the chloride attack resistance but fly ash deteriorated the resistance. From the analytical studies, It could be expected that a ternary blended cement composition with proper amount of ground granulated furnace slag and fly ash might be effective to control crack resistance as well as chloride attack resistance of marine concrete.
Park, Chul-Whan;Synn, Joong-Ho;park, Chan;Kim, Min-Kyu;Chung, So-Keul;Kim, Hwa-Soo
Tunnel and Underground Space
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v.10
no.4
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pp.526-532
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2000
The uniaxial compressive strength of rock mass is known as the major factor in the assessment of drillability and the optimum excavation design in full-face tunnel excavation by TBM. Referring to worldwide cases, TBM has been applied mostly to the rock mass within the strength range of 80~250 MPa. Recently, a water way tunnel has been constructed as a part of Milyang dam project by TBM within the rock masses where the rock type is mainly granite with some granophyre, hornfels and andesite. Their uniaxial compressive strengths in extended area are estimated higher than 260 MPa. In this paper, the relation between the penetration rate and the rock mass properties is analyzed and TBM application to the very hard rocks is discussed. As a result that three suggestions to predict the TBM net penetration rate are analyzed, NTH method seems a better approach than other methods in the extremely hard rocks. NTH prediction matches with the results of actual values with the variations of 2~20%. Hardness measurement by Schmidt hammer and RMR estimation are carried out along the L = 5.3 km entire TBM tunnel alignment. The net penetration rate measured monthly is shown to be reciprocally proportional to Schmidt rebound hardness and RMR where coefficients of correlation, $R^2$are 0.705 and 0.777 respectively. As a result, they are good quantitative indices for the prediction of TBM net penetration rate in the extremely hard rocks. Magnitude of in-situ stress has a certain effect on TBM performance, and it is required to measure the in-situ stresses in TBM excavation design.
The rebound hardness test using the SilverSchmidt hammer was performed for diorite, granodiorite, and andesite exposed around the King Sejong Station, Barton peninsula. Then, the R-value and uniaxial compressive strength (UCS) of these rocks were estimated from the Q-values which were obtained from the SilverSchmidt hammer. The Q-value of diorite was distributed in the range from 67.0 to 89.5, granodiorite of the range from 57.5 to 89.0, and andesite of the range from 58.0 to 76.5. The average Q-values of diorite, granodiorite, and andesite were 76.0, 72.0, and 67.0, respectively. The converted UCS of diorite was distributed in the range from 118 to 195 MPa, granodiorite of the range from 91 to 193 MPa, and andesite of the range from 92 to 148 MPa. The average UCS of diorite, granodiorite, and andesite were 147, 136, and 117 MPa, respectively. The converted R-value of diorite was distributed in the range from 53.0 to 72.2, granodiorite of the range from 45.4 to 71.8, and andesite of the range from 45.8 to 60.9. The average Q-values of diorite, granodiorite, and andesite were 60.0, 58.0, and 53.0, respectively. The R-value was represented approximately 20% lower than the Q-value. In conclusion, it will be possibile that the R-value and UCS of rocks under the extreme area from the SilverSchmidt Q-value are evaluated.
Mechanical properties and microleakage of two composites [conventional hybrid type DenFil (VERICOM Co., Anyang, Korea) / micro matrix hybrid type Esthet X (Dentsply Caulk, Milford, DE, U.S.A.)] were evaluated to assess whether variable light intensity curing is better than conventional curing technique. Curing was done for 40 seconds in two ways of 2 step soft-start technique and 5 step ramping technique. Three kinds of light intensities of 50, 100, $200{\;}mW/\textrm{cm}^2$ were initially used for 10, 20, 30 seconds each and the maximum intensity of $600 {\;}mW/\textrm{cm}^2$ was used for the rest of curing time in a soft-start curing tech nique. In a ramping technique, curing was done with the same initial intensities and the light intensity was increased 5 times with the same rate to the maximum intensity of $600{\;}mW/\textrm{cm}^2$. After determining conditions that showed no different mechanical properties with conventional technique, Esthet X composite was filled in a class V cavity, which dimension was $4{\times}3{\times}1.5{\;}mm$ and cured under those conditions. Microleakage was evaluated in two ways of dye penetration and maximum gap estimation through SEM observation. ANOVA and Spearman's rho test were used to confirm any statistical significance among groups. The results were as follows : 1 Several curing conditions of variable light intensities resulted in the similar mechanical properties with a conventional continuous curing technique, except conditions that start curing with an initial light intensity of $50{\;}mW/\textrm{cm}^2$. 2. Conventional and ramping techniques were better than soft-start technique in mechanical properties of microhardness and compressive strength. 3. Soft-start group that started curing with an initial light intensity of $100{\;}mW/\textrm{cm}^2$ for 10 seconds showed the least dye penetration. Soft-start group that started curing with an initial light intensity of $200{\;}mW/\textrm{cm}^2$ for 10 seconds showed the smallest marginal gap, if there was no difference among groups. 4. Soft-start technique resulted in better dye-proof margin than conventional technique(p=0.014) and ramping technique(p = 0.002). 5. There was a very low relationship(p=0.157) between the methods of dye penetration and marginal gap determination through SEM evaluation. From the results of this study, it was revealed that ramping technique would be better than conventional technique in mechanical properties, however, soft-start technique might be better than conventional one in microleakage. It was concluded that much endeavor should be made to find out the curing conditions, which have advantages of both aspects or to solve these kinds of problems through a novel idea of polymerization.
Park, Sung Chul;Park, Sang Gu;Kim, Sung Tae;Kim, Jae Hwan;Jwa, Yong-Joo
Journal of the Korean earth science society
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v.40
no.1
/
pp.46-55
/
2019
In this study, we investigated the stone materials used in the Woldae of Kwanghwamun gate to estimate their provenances. The Woldae was partly reconstructed in 2010 using red-colored original stone and greyish new stone. We carried out geological survey in Mt. Bukhan (Bukhansan) and Mt. Surak (Suraksan) to estimate the source of stone, where red-colored granitic rocks are widely distributed. Though the petrographical features of the granitic rocks from the surveyed area are quite similar, there exists a slight variation of magnetic susceptibility and color index of the rocks: the granitic rocks from Mt. Surak have higher value of magnetic susceptibility and clearer reddish feature. A series of evidence, such as historical records, stone cutting traces and petrographical features, for the source of stone materials used in the Woldae tells that Mt. Surak would have been the provenance for the stone materials used in the Woldae. We also conducted a nondestructive test to examine the physical property of the rocks. The original stone shows low compressive strength (147 MPa) due to the weathering, whereas the rock in Mt. Surak has higher compressive strength (244 MPa) capable of being used as building materials. If there were any difficulties to use the granitic rocks in Mt. Surak, some granitic rocks that have similar petrological characteristics, such as Changsu stone and Yeongjung stone from the Pocheon area, could be used as building material instead.
Journal of the Korea institute for structural maintenance and inspection
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v.21
no.6
/
pp.106-112
/
2017
This paper presents a mathematical model derived from the upper-bound theorem of concrete plasticity to rationally evaluate the shear friction strength of concrete interfaces with a construction joint. The upper limit of the shear friction strength was formulated from the limit state of concrete crushing failure on the strut-and-tie action along the construction joints to avoid overestimating the shear transfer capacity of a transverse reinforcement with a high clamping force. The present model approach proposed that the cohesion and coefficient of friction of concrete can be set to be $0.27(f_{ck})^{0.65}$ and 0.95, respectively, for rough construction joints and $0.11(f_{ck})^{0.65}$ and 0.64, respectively, for smooth ones, where $f_{ck}$ is the compressive strength of concrete. From the comparisons with 155 data compiled from the available literature, the proposed model gave lower values of standard deviation and coefficient of variation of the ratios between predictions and experiments than AASHTO and fib 2010 equations, indicating that the proposed model has consistent trends with test results, unlike the significant underestimation results of such code equations in evaluating the shear friction strength.
The extensive utilization of concrete has given rise to environmental concerns, specifically concerning the depletion of river sand. To address this issue, waste deposits can provide manufactured-sand (MS) as a substitute for river sand. The objective of this study is to explore the application of machine learning techniques to facilitate the production of manufactured-sand concrete (MSC) containing stone nano-powder through estimating the splitting tensile strength (STS) containing compressive strength of cement (CSC), tensile strength of cement (TSC), curing age (CA), maximum size of the crushed stone (Dmax), stone nano-powder content (SNC), fineness modulus of sand (FMS), water to cement ratio (W/C), sand ratio (SR), and slump (S). To achieve this goal, a total of 310 data points, encompassing nine influential factors affecting the mechanical properties of MSC, are collected through laboratory tests. Subsequently, the gathered dataset is divided into two subsets, one for training and the other for testing; comprising 90% (280 samples) and 10% (30 samples) of the total data, respectively. By employing the generated dataset, novel models were developed for evaluating the STS of MSC in relation to the nine input features. The analysis results revealed significant correlations between the CSC and the curing age CA with STS. Moreover, when delving into sensitivity analysis using an empirical model, it becomes apparent that parameters such as the FMS and the W/C exert minimal influence on the STS. We employed various loss functions to gauge the effectiveness and precision of our methodologies. Impressively, the outcomes of our devised models exhibited commendable accuracy and reliability, with all models displaying an R-squared value surpassing 0.75 and loss function values approaching insignificance. To further refine the estimation of STS for engineering endeavors, we also developed a user-friendly graphical interface for our machine learning models. These proposed models present a practical alternative to laborious, expensive, and complex laboratory techniques, thereby simplifying the production of mortar specimens.
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