• Composites Research
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• v.34 no.2
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• pp.123-128
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• 2021

This paper dealt with multi-scale natural frequency characteristics of wavy CNT (carbon nanotube) reinforced composites by applying the Mori-Tanaka method, rule of mixture, and Halpin-Tsai equation. By compelling benefit of an ad-hoc Eshelby tensor, the load-transfer characteristics of CNT with a waviness implanted in the polymer matrix was determined. The numerical results obtained are in good agreement with those reported by other investigators. Furthermore, the new results reported in this paper show the interactions between CNT weight, waviness ratios and layup sequences of laminated composites. Key observation points are discussed and significant considerations are given in practical designing of CNT reinforced composites.

• Advances in concrete construction
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• v.11 no.4
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• pp.307-314
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• 2021

Activated hwangtoh (ACT) is a natural resource abundant in South Korea, approximately 15.0% of soil. It is an efficient mineral admixture that has activated pozzolanic properties through high-temperature heating and rapid cooling. The purpose of this study is to improve a curb mixture that can reduce NOx outside and investigate durability performance. To this end, mortar curb specimens were manufactured by replacing OPC with ACT. The ACT substitution ratios of 0.0, 10.0, and 25.0% were considered, and mechanical and durability tests on the curb specimens were conducted at 28 and 91 days of age. Steam curing was carried out for three days for the production of curbs, which was very effective to strength development at early ages. The reduction in strength at early ages could be compensated through this process, and no significant performance degradation was evaluated in the tests on chloride attack, carbonation, and freezing and thawing. The mortar curb with an ACT of 10.0~25.0% replacement ratio exhibited clear NOx reduction through photocatalytic (TiO2) treatment. This is due to the increase in physical absorption through surface absorption and the photocatalyst-containing TiO2 coating. In this study, the reasonable range of the ACT replacement ratio for NOx reduction was quantitatively evaluated through a comprehensive analysis of each test.

• Advances in nano research
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• v.7 no.2
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• pp.109-123
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• 2019

In this article, the free vibration analysis of annular sandwich plates with various functionally graded (FG) porous cores and carbon nanotubes reinforced composite (CNTRC) facesheets is investigated based on modified couple stress theory (MCST) and first order shear deformation theories (FSDT). The annular sandwich plate is composed of two face layers and a functionally graded porous core layer which contains different porosity distributions. Various approaches such as extended mixture rule (EMR), Eshelby-Mori-Tanaka (E-M-T), and Halpin-Tsai (H-T) are used to determine the effective material properties of microcomposite circular sandwich plate. The governing equations of motion are extracted by using Hamilton's principle and FSDT. A Ritz method has been utilized to calculate the natural frequency of an annular sandwich plate. The effects of material length scale parameters, boundary conditions, aspect and inner-outer radius ratios, FG porous distributions, pore compressibility and volume fractions of CNTs are considered. The results are obtained by Ritz solutions that can be served as benchmark data to validate their numerical and analytical methods in the future work and also in solid-state physics, materials science, and micro-electro-mechanical devices.

• Advances in concrete construction
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• v.11 no.1
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• pp.11-18
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• 2021

The present study fabricated polyvinyl alcohol (PVA) fiber-reinforced alkali-activated slag/fly ash (AASF) composites with varying mixture ratios of slag and fly ash. The thermomechanical behaviors of the AASF composites exposed to 200, 400, 600, or 800℃ were evaluated by means of compressive strength test, visual observation, and fire resistance tests. X-ray diffractometry, mercury intrusion porosimetry, and thermogravimetry tests were performed to analyze the microstructure change of the AASF composites upon exposure to high temperatures. Specimens exhibited a gradual strength loss up to 600℃, while also showing a significant decrease in the strength above 600℃. The fire resistance test revealed the occurrence of an inflection point as indicated by an increase in the internal temperature at around 200℃. In addition, specimens showed the dehydration of C-S-H gel, the presence of åkermanite, gehlenite, and anorthite upon exposure to 800℃, which is associated with the formation of macropore population with pores having diameters of 1-3 ㎛ and 20-40 ㎛. Visual observation indicated that the PVA fibers mitigated the cracking and/or spalling of the specimens upon exposure to 800℃.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.310-317
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• 2022

The mass attenuation coefficient is the primary physical parameter to model narrow beam gamma-ray attenuation. A new machine learning based approach is proposed to model gamma-ray shielding behavior of composites alternative to theoretical calculations. Two fuzzy logic algorithms and a neural network algorithm were trained and tested with different mixture ratios of vanadium slag/epoxy resin/antimony in the 0.05 MeV-2 MeV energy range. Two of the algorithms showed excellent agreement with testing data after optimizing adjustable parameters, with root mean squared error (RMSE) values down to 0.0001. Those results are remarkable because mass attenuation coefficients are often presented with four significant figures. Different training data sizes were tried to determine the least number of data points required to train sufficient models. Data set size more than 1000 is seen to be required to model in above 0.05 MeV energy. Below this energy, more data points with finer energy resolution might be required. Neuro-fuzzy models were three times faster to train than neural network models, while neural network models depicted low RMSE. Fuzzy logic algorithms are overlooked in complex function approximation, yet grid partitioned fuzzy algorithms showed excellent calculation efficiency and good convergence in predicting mass attenuation coefficient.

• Steel and Composite Structures
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• v.43 no.6
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• pp.797-808
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• 2022

This paper presents an investigation on the free vibration characteristics of functionally graded nanocomposite double-beams reinforced by single-walled carbon nanotubes (SWCNTs). The double-beams coupled by an interlayer spring, resting on the elastic foundation with a linear layer and shear layer, and is simply supported in thermal environments. The SWCNTs gradient distributed in the thickness direction of the beam forms different reinforcement patterns. The materials properties of the functionally graded carbon nanotube-reinforced composites (FG-CNTRC) are estimated by rule of mixture. The first order shear deformation theory and Euler-Lagrange variational principle are employed to derive the motion equations incorporating the thermal effects. The vibration characteristics under several patterns of reinforcement are presented and discussed. We conducted a series of studies aimed at revealing the effects of the spring stiffness, environment temperature, thickness ratios and carbon nanotube volume fraction on the nature frequency.

• Computers and Concrete
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• v.28 no.6
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• pp.567-583
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• 2021

The use of waste materials as a binder or aggregate in the concrete mixture is a great step towards sustainability in the construction industry. Waste rubber (WR) can be used as coarse and fine aggregates in concrete and improves the crack resistance, impact resistance, and fatigue life of the produced concrete. However, the mechanical properties of rubberized concrete degrade significantly by replacing the natural aggregate with WR. To have accurate estimations of the mechanical properties of rubberized concrete, two machine learning methods consisting of artificial neural network (ANN) and neuro-fuzzy system (NFS) were served in this study. To do this, a comprehensive dataset was collected from reliable literature, and two scenarios were addressed for the selection of input variables. In the first scenario, the critical ratios of the rubberized concrete and the concrete age were considered as the input variables. In contrast, the mechanical properties of concrete without WR and the percentage of aggregate volume replaced by WR were assumed as the input variables in the second scenario. The results show that the first scenario models outperform the models proposed by the second scenario. Moreover, the developed ANN models are more reliable than the proposed NFS models in most cases.

• Computers and Concrete
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• v.29 no.6
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• pp.433-444
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• 2022

Concrete's compressive strength is widely studied in order to understand many qualities and the grade of the concrete mixture. Conventional civil engineering tests involve time and resources consuming laboratory operations which results in the deterioration of concrete samples. Proposing efficient non-destructive models for the prediction of concrete compressive strength will certainly yield advancements in concrete studies. In this study, the efficiency of using radial basis function neural network (RBFNN) which is not common in this field, is studied for the concrete compressive strength prediction. Complementary studies with back propagation neural network (BPNN), which is commonly used in this field, have also been carried out in order to verify the efficiency of RBFNN for compressive strength prediction. A total of 13 input parameters, including novel ones such as cement's and fly ash's compositional information, have been employed in the prediction models with RBFNN and BPNN since all these parameters are known to influence concrete strength. Three different train: test ratios were tested with both models, while different hidden neurons, epochs, and spread values were introduced to determine the optimum parameters for yielding the best prediction results. Prediction results obtained by RBFNN are observed to yield satisfactory high correlation coefficients and satisfactory low mean square error values when compared to the results in the previous studies, indicating the efficiency of the proposed model.

• Journal of Korean Association for Spatial Structures
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• v.23 no.2
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• pp.69-78
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• 2023

This paper investigates the effects of aspect ratio and volume fraction of hooked-end normal-strength steel fibers on the compressive and flexural properties of high-strength concrete with specified compressive strength of 60 MPa. Three types of hooked-end steel fibers with aspect ratios of 64, 67 and 80 were considered and three volume fractions of 0.25%, 0.50% and 0.75% for each steel fiber were respectively added into each high-strength concrete mixture. The test results indicated that the addition of normal-strength steel fibers is effective to improve compressive and flexural properties of high-strength concrete but fiber aspect ratio had little effect on the modulus of elasticity and compressive strength. As steel fiber content and aspect ratio increased, flexural beahvior of notched high-strength concrete beams was effectively improved.

• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.322-327
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• 2023

A design of experiments was evaluated in optimizing MOF-5 synthesis for acetylene adsorption. At first, mixture design was used to optimize precursor concentration, terephthalic acid, zinc acetate dihydrate and N,N-dimethylformamide. More specifically, 13 conditions with various molar ratios were designed by extreme vertices design method. After preparing the samples, XRD, N₂ physisorption and SEM analysis were performed for their characterization. Moreover, acetylene adsorption experiments were carried out over the samples under identical conditions. The optimal precursor composition for MOF-5 synthesis was predicted on a molar basis as follows: terephthalic acid : acetate dihydrate : dimethylformamide = 0.1 : 0.4 : 0.5. Thereafter, multi-level factorial design was designated to investigate the effect of synthesis reaction conditions such as temperature, time and stirring speed. By the statistical analysis of 18 samples designed, 4 reaction parameters were determined for additional adsorption experiments. Therefore, MOF-5 prepared under the synthesis time and temperature of 100 ℃ and 12 h, respectively, showed the maximum adsorption capacity of 15.1 mmol/g.