• Proceedings of the Korean Institute of Building Construction Conference
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• 2005.11a
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• pp.75-78
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• 2005

This raper investigates the effect of curing temperature on strength development of concrete incorporating cement kiln dust(CKD) and blast furnace slag (BS) quantitatively. Estimation of compressive strength of concrete was conducted using equivalent age equation and rate constant model. An increasing curing temperature results in an increase in strength at early age, but with the elapse of age, strength development at high curing temperature decreases compared with that at low curing temperature. Especially, the use of 35 has a remarkable strength development at early age and even at later age, high strength is maintained due to accelerated pozzolanic activity resulting from high temperature. Whereas, at low curing temperature, the use of BS leads to a decrease in compressive strength. Accordingly, much attention should be paid to prevent strength loss at low temperature. Based on the strength development estimation using equivalent age equation, good agreements between measured strength and calculated strength are obtained.

• Advances in environmental research
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• v.4 no.1
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• pp.49-68
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• 2015

Chemically activated and carbonized adsorbents were prepared from Moringa oleifera pod husks (MOP), characterized and evaluated for their ability to remove a common antibiotic - ofloxacin (OFX) from aqueous solution. The pulverized precursor was steeped in a saturated ammonium chloride solution for a day to give the chemically activated adsorbent (AMOP). A portion of AMOP was pyrolyzed in a muffle furnace at 623 K for 30 min to furnish its carbonized analogue (CMOP). The adsorbents showed favorable physicochemical attributes. The effects of operational parameters such as initial OFX solution pH and concentration, adsorbent dosage, temperature and contact time on OFX removal were investigated. At equilibrium, optimal removal efficiencies of 90.98% and 99.84% were achieved at solution pH 5 for AMOP and CMOP, respectively. The equilibrium adsorption data fitted into both the Langmuir and Freundlich isotherms. Gibbs free energy change (${\Delta}G^o$), enthalpy change (${\Delta}H^o$) and entropy change (${\Delta}S^o$) indicated that the adsorption of OFX was feasible, spontaneous, exothermic and occurred via the physisorption mode. Adsorption kinetics obeyed the Blanchard pseudo-second-order model. The results may find applications in the adsorptive removal of micro-contaminants of pharmaceutical origin from wastewater.

• Nuclear Engineering and Technology
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• v.45 no.2
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• pp.223-236
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• 2013

In the present study the behavior of fire and the residual strength of fire-ignited RC slabs are investigated by experimental tests and numerical simulations. The fire tests of RC slabs were carried out in a furnace using the ISO 834 standard fire. The load capacity of the cooled RC slabs that were not loaded during the fire tests was evaluated by additional 3 point bending tests. The influence of the proportion of PP (polypropylene) fibers in the RC slabs on the structural behavior of the RC slabs after the fire loading was investigated. The results of the fire tests showed that the maximum temperature of concrete with PP fiber was lower than that of concrete without PP fiber. As the concrete was heated, the ultimate compressive strength decreased and the ultimate strain increased. The load-deflection relations of RC slabs after fire loading were compared by using existing stress-strain-temperature models. The comparison between the numerical analysis and the experimental tests showed that some numerical analyses were reliable and therefore, can be applied to evaluate the ultimate load of RC slabs after fire loading. The ultimate load capacity after cooling down the RC slabs without PP fiber showed a considerable reduction from that of the RC slabs with PP fiber.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.551-560
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• 2004

In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) that is based on a genetically optimized multilayer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms (GAs). The proposed SOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, and a collection of the specific subset of input variables) and addresses specific aspects of parametric optimization. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized SOFPNN, the model is experimented with using two time series data(gas furnace and chaotic time series), A comparative analysis reveals that the proposed SOFPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literatures.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.13 no.5
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• pp.383-389
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• 2000

The relationship between the DC degradation characteristics of the ZnO varistor and the ambient sintering-process is investigated in this study. ZnO varistors made o matsuoka’s composition were fabricated by standard ceramic techniques. The ambient sintering-process is performed at the extraordinary electrical-furnace which is equipped with the vacuum system. Gases used in sintering process were oxygen nitrogen argon and air. Using XRD and SEM the phase and microstructure of samples were analyzed respectively. The conditions of DC degradation tests were conducted at 115$\pm$2$^{\circ}C$ for 13 h. Current-voltage analysis is used to determine nonlinear coefficients($\alpha$). Frequency analysis are performed to understand electrical properties as DC degradation test. From above analysis it is found that the ZnO varistor sintered in oxygen atmosphere showed superior properties at the DC degradation test and degradation phenomenon of ZnO varistor is caused by the change of electrical properties in grain boundary. These results are in accordance with Gupta’s degradation model.

• Journal of the Korean Society of Safety
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• v.8 no.4
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• pp.175-182
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• 1993

Volatilization of toxic heavy metals, especially, metal chlorides at elevated temperatures in oxidation conditions was observed using a thermogravimetric furnace since such metal chlorides used to be a cause for the disease of industrial workers by their toxicity and high volatile extent. Most of tested metal chloride compounds were evaporated or decomposed into gas phase at elevated temperatures ranged from 200~90$0^{\circ}C$, while CrCl$_3$ and NiC1$_2$became stable with converting into oxide forms. A kinetic model for evaporation/condensation could predict maximum evaporation flux and the calculated values were compared with real evaporation flux. The ratio of two fluxes could be explained as the fraction of impinging gas molecules to the condensing surface( $\alpha$ ) and obtained in the range of 10$^{-3}$ ~10$^{-9}$ for the experimented toxic heavy metal chlorides. This ratio might be used to define the volatile extent or toxicity of such toxic metal compounds. The schemes to avoid volatilization of toxic heavy metals Into the atmosphere were suggested as follows ; 1 ) controlling the compositions of metals and Chlorine produced substances( such as PVC ) in the treated materials using a reverse estimation from regulatory limit and characteristics of a processing facility, 2) Installation of wet type devices such as a scrubber for condensing the metal compounds.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.210-216
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• 2006

In the rule based modeling, data partitioning plays crucial role be cause partitioned sub data set implies particular information of the given data set or system. In this paper, we present an empirical study result of the data pattern estimation to find underlying data patterns of the given data. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). In each sequence, the average value of the sum of all inter-distance between centroid and data point. In the sequel, compute the derivation of the weighted average distance to observe a pattern distribution. For the final step, after overall clustering process is completed, weighted average distance value is applied to estimate range of the number of clusters in given dataset. The proposed estimation method and its result are considered with the use of FCM demo data set in MATLAB fuzzy logic toolbox and Box and Jenkins's gas furnace data.

• Journal of the Korean Society for Heat Treatment
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• v.34 no.5
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• pp.218-225
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• 2021

In this study, damping capacities were comparatively investigated for Mg-9%Al alloy with as-cast (AC) and fully discontinuous precipitates (DPs) microstructures, respectively. The DPs microstructure was obtained by solution treatment at 678 K for 24 h, followed by furnace cooling to RT. The AC microstructure was typically characterized by partially divorced eutectic β(Mg₁₇Al₁₂) phase particles distributed along the α-(Mg) matrix cell boundaries. The DPs microstructure showed lamellar morphology consisting of α and β thin layers with various interlamellar spacings. The DPs microstructure had better damping capacity than the AC microstructure in the strain-amplitude independent region, while in the strain-amplitude dependent region, the damping behavior was reversed. In view of the microstructural features of AC and DPs, the lower concentration of Al in the α-(Mg) phase for the DPs microstructure and the lower β phase number density for the AC microstructure would be responsible for the higher damping capacities in the strain-amplitude independent and strain-amplitude dependent regions, respectively.

• Structural Engineering and Mechanics
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• v.70 no.6
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• pp.671-681
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• 2019

This paper examines the applicability of artificial neural network (ANN) and multivariate adaptive regression splines (MARS) to predict the compressive strength of bacteria incorporated geopolymer concrete (GPC). The mix is composed of new bacterial strain, manufactured sand, ground granulated blast furnace slag, silica fume, metakaolin and fly ash. The concentration of sodium hydroxide (NaOH) is maintained at 8 Molar, sodium silicate ($Na_2SiO_3$) to NaOH weight ratio is 2.33 and the alkaline liquid to binder ratio of 0.35 and ambient curing temperature ($28^{\circ}C$) is maintained for all the mixtures. In ANN, back-propagation training technique was employed for updating the weights of each layer based on the error in the network output. Levenberg-Marquardt algorithm was used for feed-forward back-propagation. MARS model was developed by establishing a relationship between a set of predictors and dependent variables. MARS is based on a divide and conquers strategy partitioning the training data sets into separate regions; each gets its own regression line. Six models based on ANN and MARS were developed to predict the compressive strength of bacteria incorporated GPC for 1, 3, 7, 28, 56 and 90 days. About 70% of the total 84 data sets obtained from experiments were used for development of the models and remaining 30% data was utilized for testing. From the study, it is observed that the predicted values from the models are found to be in good agreement with the corresponding experimental values and the developed models are robust and reliable.

• Smart Structures and Systems
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• v.30 no.2
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• pp.195-207
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• 2022

Computational drawbacks associated with regular predictive models have motivated engineers to use hybrid techniques in dealing with complex engineering tasks like simulating the compressive strength of concrete (CSC). This study evaluates the efficiency of tree potential metaheuristic schemes, namely shuffled complex evolution (SCE), multi-verse optimizer (MVO), and beetle antennae search (BAS) for optimizing the performance of a multi-layer perceptron (MLP) system. The models are fed by the information of 1030 concrete specimens (where the amount of cement, blast furnace slag (BFS), fly ash (FA1), water, superplasticizer (SP), coarse aggregate (CA), and fine aggregate (FA2) are taken as independent factors). The results of the ensembles are compared to unreinforced MLP to examine improvements resulted from the incorporation of the SCE, MVO, and BAS. It was shown that these algorithms can considerably enhance the training and prediction accuracy of the MLP. Overall, the proposed models are capable of presenting an early, inexpensive, and reliable prediction of the CSC. Due to the higher accuracy of the BAS-based model, a predictive formula is extracted from this algorithm.