• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.16 no.3
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• pp.281-290
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• 2018

In order to understand the long-term behavior of radionuclides in granite environments, geochemical behavior characteristics of uranium in granitic host rock of KURT (KAERI Underground Research Tunnel) were investigated by dissolution experiment with different reaction time and solutions. In the dissolution experiment, significantly increased dissolution levels of uranium from granite powder samples were identified during the reaction time of 0~10 days for reaction solutions ($UD-CO_3$ and UD-Bg) containing a large amount of $CO_3{^{2-}}$. On the other hand, significantly increased dissolution levels of uranium were also identified for reaction solutions containing Na and Ca after 60 days. Dissolution of uranium continuously increased in reaction solutions of $UD-CO_3$ ($44.61{\mu}g{\cdot}L^{-1}$), UD-Bg ($41.01{\mu}g{\cdot}L^{-1}$), UD-Na ($26.87{\mu}g{\cdot}L^{-1}$), UD-Ca ($20.26{\mu}g{\cdot}L^{-1}$), UD-CaSi ($17.03{\mu}g{\cdot}L^{-1}$), and UD-Si ($10.47{\mu}g{\cdot}L^{-1}$) in the experimental period of ~270 days. However, after day 270, dissolution of uranium showed a decreasing tendency. This is thought to have occurred because existing uranium in granite samples reached the limit of dissolution by interaction with reaction solutions. Concentrations of dissolved uranium and points of maximum concentration value were found to differ depending on the $CO_3{^{2-}}$ presence in the mixed reaction solution and on the geochemical type of the water. It is estimated that differences in the reaction rate between the granite sample and the reaction solution are due to the influence of dissolved ions in the reaction solution.

• International Journal of Concrete Structures and Materials
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• v.9 no.2
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• pp.241-254
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• 2015

A lot of reinforced concrete (RC) structures in Syria went out of service after a few years of construction. This was mainly due to reinforcement corrosion or chemical attack on concrete. The use of blended cements is growing rapidly in the construction industry due to economical, ecological and technical benefits. Syria is relatively rich in scoria. In the study, mortar/concrete specimens were produced with seven types of cement: one plain Portland cement (control) and six blended cements with replacement levels ranging from 10 to 35 %. Rapid chloride penetration test was carried in accordance with ASTM C 1202 after two curing times of 28 and 90 days. The effect on the resistance of concrete against damage caused by corrosion of the embedded steel has been investigated using an accelerated corrosion test by impressing a constant anodic potential. The variation of current with time and time to failure of RC specimens were determined at 28 and 90 days curing. In addition, effects of aggressive acidic environments on mortars were investigated through 100 days of exposure to 5 % $H_2SO_4$, 10 % HCl, 5 % $HNO_3$ and 10 % $CH_3COOH$ solutions. Evaluation of sulfate resistance of mortars was also performed by immersing in 5 % $Na_2SO_4$ solution for 52 weeks. Test results reveal that the resistance to chloride penetration of concrete improves substantially with the increase of replacement level, and the concretes containing scoria based-blended cements, especially CEM II/B-P, exhibited corrosion initiation periods several times longer than the control mix. Further, an increase in scoria addition improves the acid resistance of mortar, especially in the early days of exposure, whereas after a long period of continuous exposure all specimens show the same behavior against the acid attack. According to results of sulfate resistance, CEM II/B-P can be used instead of SRPC in sulfate-bearing environments.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.301-309
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• 2005

Learning program's behavior using machine learning techniques based on system call audit data is an effective intrusion detection method. Rule teaming, neural network, statistical technique, and hidden Markov model are representative methods for intrusion detection. Among them neural networks are known for its good performance in teaming system call sequences. In order to apply it to real world problems successfully, it is important to determine their structure. However, finding appropriate structure requires very long time because there are no formal solutions for determining the structure of networks. In this paper, a novel intrusion detection technique using evolutionary neural networks is proposed. Evolutionary neural networks have the advantage that superior neural networks can be obtained in shorter time than the conventional neural networks because it leams the structure and weights of neural network simultaneously Experimental results against 1999 DARPA IDEVAL data confirm that evolutionary neural networks are effective for intrusion detection.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.6
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• pp.109-118
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• 2008

Carbon fiber reinforced polymer(CFRP) can be bonded to the soffit of a concrete beam as a means of repairing and strengthening the beam. In such beams, materials, concrete and carbon fiber sheets, are different in coefficient of thermal expansion. Consequently, interfacial shear stresses can be increased and debonding failure may occur at the plate ends due to temperature rising. This paper presents a method of approximate closed-form solutions for the interfacial shear stresses and conducts a beam test to compare the numerical results. In case of temperature rising over $30^{\circ}C$, interfacial stress of 0.91MPa is occurred at the end of sheet. Therefore, using carbon fiber sheet for strengthening the concrete beam, it is necessary to consider the thermal effects and to evaluate the long time behavior of the concrete beam by temperature change.