• Journal of Power System Engineering
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• v.19 no.4
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• pp.30-35
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• 2015

The purpose of this study is to identify the low temperature performance and strength characteristics of V-based extruded homogeneous SCR. The extruded catalyst and the coated catalyst showed 50% and 27% of NOx conversion performance respectively at about $210^{\circ}C$ of catalyst temperature, so the extruded SCR was higher in de-NOx performance than the coated SCR especially at a low temperature zone. The compressive strength of the Enhanced Extrusion #1, in which the content of promoters such as silica, clay, glass fiber and binder was optimized, was a 120% improvement compared to the Extrusion#1 catalyst, higher than the coated SCR.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.628-630
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• 2016

Compressive sensing can recover an original sparse signal from a few measurements. Its performance is affected by the number of non-zero elements in the signal. The knowledge of partial locations of non-zero elements can improve the recovery performance. In this paper, we apply the partial location knowledge to the multipath matching pursuit. The numerical results show it improves the signal recovery performance and the channel estimation performance in the ITU-VB channel.

• Computers and Concrete
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• v.11 no.2
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• pp.149-167
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• 2013

The complete stress-strain behavior of steel fiber reinforced concrete in compression is needed for the analysis and design of structures. An experimental investigation was carried out to generate the complete stress-strain curve of high-performance steel fiber reinforced concrete (HPSFRC) with a strength range of 52-80 MPa. The variation in concrete strength was achieved by varying the water-to-cementitious materials ratio of 0.40-0.25 and steel fiber content (Vf = 0.5, 1.0 and 1.5% with l/d = 80 and 55) in terms of fiber reinforcing parameter, at 10% silica fume replacement. The effects of these parameters on the shape of stress-strain curves are presented. Based on the test data, a simple model is proposed to generate the complete stress-strain relationship for HPSFRC. The proposed model has been found to give good correlation with the stress-strain curves generated experimentally. Inclusion of fibers into HPC improved the ductility considerably. Equations to quantify the effect of fibers on compressive strength, strain at peak stress and toughness of concrete in terms of fiber reinforcing index are also proposed, which predicted the test data quite accurately. Compressive strength prediction model was validated with the strength data of earlier researchers with an absolute variation of 2.1%.

• Smart Structures and Systems
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• v.16 no.5
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• pp.961-980
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• 2015

Magnetorheological (MR) fluids are capable of changing their rheological properties under the application of external fields. When MR fluids operate in the so-called squeeze mode, in which displacement levels are limited to a few millimetres but there are large forces, they have many potential applications in vibration isolation. This paper presents an experimental and a numerical investigation of the performance of an MR fluid under tensile and compressive loads and oscillatory squeeze-flow. The performance of the fluid was found to depend dramatically on the strain direction. The shape of the stress-strain hysteresis loops was affected by the strength of the applied field, particularly when the fluid was under tensile loading. In addition, the yield force of the fluid under the oscillatory squeeze-flow mode changed almost linearly with the applied electric or magnetic field. Finally, in order to shed further light on the mechanism of the MR fluid under squeeze operation, computational fluid dynamics analyses of non-Newtonian fluid behaviour using the Bingham-plastic model were carried out. The results confirmed superior fluid performance under compressive inputs.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.11a
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• pp.941-944
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• 2008

This study is aimed to investigate the residual strength of fire damaged high-performance concrete flexural and compressive members. The compressive strength of specimens is 55MPa and the main parameter for comparison is the exposure time to fire. In case of beams, the cover thickness made the differences in spalled section area, residual strength and serviceability. The exposure time to fire did not affect on the spalled section area in case of compressive members without loading. However, the residual strength and stiffness was reduced by the time exposed to fire. This study can be used to estimate the performance of fire damaged high-strength concrete structural members for reusing and to give the information for repairing and strengthening.

• Advances in concrete construction
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• v.10 no.5
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• pp.431-441
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• 2020

For the purpose of improving the properties of UHPC as well as the economic efficiency in production of the material, Availability of river sands as fine aggregate instead of micro silica sand were investigated. Four different sizes of river sands were considered. Using river sand instead of micro silica sand increased the flowability, and decreased the yield stress and plastic viscosity in rheological properties, and the effect was higher with larger particle size of river sand. It was demonstrated by analyses based on the packing density. In the results of compressive strength and elastic modulus, even though river sand was not as good as micro silica sand, it could provide high strength of over 170 MPa and elastic modulus greater than 40 GPa. The difference in compressive strength depending on the size of river sand was explained with the concept of maximum paste thickness based on the packing density of aggregate. The flexural performance with river sand also presented relatively lower resistance than micro silica sand, and the reduction was greater with larger particle size of river sand. The flexural performance was proven to be also influenced by the difference in the fiber orientation distribution due to the size of river sand.

• Computers and Concrete
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• v.21 no.5
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• pp.485-493
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• 2018

Statistical analysis has found useful application in the design of experiments (DOE) especially optimization of concrete ingredients however, to be able to apply the concept properly using computer aided applications there has to be an upper and lower limits of responses fed to the system. In this study, the production of high-performance steel fiber concrete (HPSFC) at five different fiber addition levels by volume with two aspect ratios of 60 and 83 were studied under two curing methods completely dry cured (DC) and moist cured (MC) conditions. In other words, this study was carried out for those limits based on material properties available in North Cyprus. Specimens utilized were cubes 100 mm size casted and cured for 28 days and tested for compressive strength. Minitab 18 statistical software was utilized for the analysis of results at a 5 per cent level of significance. Experimentally, it was observed that, there was fluctuation in compressive strength results for the two aspect ratios and curing regimes. On the other hand P-value hypothesis evaluation of the response showed that at the stated level of significance, there was a statistically significant difference between dry and moist curing conditions. Upper and lower limit values were proposed for the response to be utilized in DOE for future studies based on these material properties. It was also suggested that for a narrow confidence interval and accuracy of the system, future study should increase the sample size.

• Structural Engineering and Mechanics
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• v.49 no.6
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• pp.763-773
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• 2014

The recently developed Ultra High Performance Concrete (UHPC) displays outstanding compressive strength and ductility but is also subjected to very large autogenous shrinkage. In addition, the use of forms and reinforcement to confine this autogenous shrinkage increases the risk of shrinkage cracking. Accordingly, this study adopts a combination of shrinkage reducing admixture and expansive admixture as a solution to reduce the shrinkage of UHPC and estimates its appropriateness by evaluating the compressive and flexural strengths as well as the autogenous shrinkage according to the age. Moreover, the coefficient of thermal expansion known to experience sudden variations at early age is measured in order to evaluate exactly the autogenous shrinkage and the thermal expansion is compensated considering these measurements. The experimental results show that the compressive and flexural strengths decreased slightly at early age when mixing 7.5% of expansive admixture and 1% of shrinkage reducing admixture but that this decrease becomes insignificant after 7 days. The use of expansive admixture tended to premature the setting of UHPC and the start of sudden increase of autogenous shrinkage. Finally, the combined use of shrinkage reducing admixture and expansive admixture appeared to reduce effectively the autogenous shrinkage by about 47% at 15 days.

• Computers and Concrete
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• v.10 no.2
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• pp.197-217
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• 2012

This research deals with the prediction of compressive strength of normal and high strength concrete using neural networks. The compressive strength was modeled as a function of eight variables: quantities of cement, fine aggregate, coarse aggregate, micro-silica, water and super-plasticizer, maximum size of coarse aggregate, fineness modulus of fine aggregate. Two networks, one using raw variables and another using grouped dimensionless variables were constructed, trained and tested using available experimental data, covering a large range of concrete compressive strengths. The neural network models were compared with regression models. The neural networks based model gave high prediction accuracy and the results demonstrated that the use of neural networks in assessing compressive strength of concrete is both practical and beneficial. The performance of model using the grouped dimensionless variables is better than the prediction using raw variables.

• Advances in Computational Design
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• v.3 no.3
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• pp.289-302
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• 2018

The use of optimum content of supplementary cementing materials (SCMs) such as limestone filler (LF) to blend with Portland cement has been resulted in many environmental and technical advantages, such as increase in physical properties, enhancement of sustainability in concrete industry and reducing $CO_2$ emission are well known. Artificial neural networks (ANNs) have been already applied in civil engineering to solve a wide variety of problems such as the prediction of concrete compressive strength. The feed forward back propagation (FFBP) algorithm and Tan-sigmoid transfer function were used for the ANNs training in this study. The training, testing and validation of data during the backpropagation training process yielded good correlations exceeding 97%. A parametric study was conducted to study the sensitivity of the developed model to certain essential parameters affecting the compressive strength of concrete. The effects and benefits of limestone filler on hardened properties of the concrete such as compressive strength were well established endorsing previous results in the literature. The results of this study revealed that the proposed ANNs model showed a high performance as a feasible and highly efficient tool for simulating the LF concrete compressive strength prediction.