• International Journal of Concrete Structures and Materials
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• v.6 no.3
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• pp.155-163
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• 2012

In order to predict the neutralization of concrete which is the reaction of carbonation dioxide from the outside and cement hydration product, such as calcium hydroxide and C-S-H, it was studied the numerical analysis method considering change of the pore structure and relative humidity during the neutralization reaction. Diffusion-reaction neutralization model was developed to predict the neutralization depth of concrete with coating finishing material. In order to build numerical analysis models considering outdoor environment and finishing materials, the adaption of proposed model was shown the results of existing outdoor exposure test results and accelerated carbonation test.

• Journal of Korean Society of Forest Science
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• v.90 no.1
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• pp.133-138
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• 2001

Increased base cation loss and Al mobilization, a consequence of soil acid neutralization responses, are common in air polluted areas showing forest decline. The prediction models of acid neutralization responses were developed by using indicators of soil acidification level(pH, and base saturation) in order to assess the forest soil sensitivity to acidification. The soil acidification level was greatest in Namsan followed by Kanghwa, Ulsan, and Hongcheon, being contrary to regional total $ANC_H$ pattern through soil columns leached with additional acid ($16.7mmol_c\;H^+/kg$), Both base exchange and Al dissolution were main acid neutralization processes in all study regions. There were low base exchange and high Al dissolution in the regions of the low total $ANC_H$. The $ANC_M$ by sulfate adsorption was greatest in Hongcheon compared with other regions even though the AN rate was very low as 6.4%. Coefficients of adjusted determination of simple and multiple regression models between soil acidification level indicators and the acid neutralization responses were more than 0.52(p<0.04) and 0.89(p<0.01), respectively. The result suggests that soil pH and base saturation are available indicators for predicting the acid neutralization responses. These prediction models could be used as an useful method to measure forest soil sensitivity to acidification.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.11a
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• pp.511-514
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• 2005

In this study, LCC(Life Cycle Cost) evaluation technique is used for the purpose of accumulation of basic data required for such integrative system construction. We predicted the degradation time of concrete and repair material by neutralization through FEM analysis, and utilized the result for LCC evaluation It turned out that the repair method of construction in the most economical initial measure against degradation and a durable period can be chosen through the LCC evaluation in consideration of the degradation prediction using FEM analysis and the initial construction expense in a durable period and repair expense, and the number of repair times.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.11a
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• pp.188-189
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• 2020

In the field of architecture, concrete and steel bars are the most common and popular combinations. The relationship between the two in a structure is a complementary good that increases in utility when consuming both materials at the same time. However, the combination of the two, which has been perceived as semi-permanent, often faces repairs or reconstruction without its lifespan reaching decades. There are a number of deterioration factors at work for the reason for this phenomenon. Among them, the neutralization of concrete in particular refers to the process in which calcium hydroxide inside concrete reacts with carbon dioxide and loses alkalinity, which creates a corrosive environment for rebars inside concrete, causing serious damage to concrete. In this study, we intend to use a multi-physical analysis program using finite element analysis method to analyze the degree of carbonation according to the internal temperature and concentration of carbon dioxide in concrete, thereby contributing to the prediction of long-term neutralization of concrete and the research related to measures for neutralization of concrete.

• Journal of the Society of Disaster Information
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• v.13 no.3
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• pp.332-339
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• 2017

In the case of aged structures, the information of the structure is often lost after the completion of construction, and there is a great difficulty in predicting the durability life of the structure due to the lack of information on concrete formulations. In this study, the durability of concrete specimens was evaluated by various field and indoor test methods based on the core specimens collected from the field, and the durability life of the concrete structures was predicted by using the FEM analysis technique.As a result, the neutralization rate coefficient was $5.38E-6(cm^2/day)$ and the rate of progress was low. And the possibility of complex deterioration due to carbonation and salting was found to be very low.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.3
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• pp.145-156
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• 2000

In this paper, we propose a new methodology which includes the optimal design procedure of Polynomial Neural Networks(PNN) structure for model identification of complex and nonlinear system. The proposed PNN algorithm is based on GMDA(Group Method of Data handling) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and can be generated. The each node of PNN structure uses several types of high-order polynomial such as linear, quadratic and cubic, and is connected as various kinds of multi-variable inputs. In other words, the PNN uses high-order polynomial as extended type besides quadratic polynomial used in GMDH, and the number of input of its node in each layer depends on that of variables used in the polynomial. The design procedure to obtain an optimal model structure utilizing PNN algorithm is shown in each stage. The study is illustrated with the aid of pH neutralization process data besides representative time series data for gas furnace process used widely for performance comparison, and shows that the proposed PNN algorithm can produce the model with higher accuracy than previous other works. And performance index related to approximation and prediction capabilities of model is evaluated and also discussed.

• Journal of the Mineralogical Society of Korea
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• v.19 no.2 s.48
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• pp.71-80
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• 2006

We examined the mineralogical composition of pyrite-bearing rocks by quantitative powder X-ray diffraction analysis using the matrix-flushing method and ROCKJOCK (a full pattern fitting computer program). The neutralization potential (NP) and acid generating potential (AP) were calculated on the basis of mineralogical compositions. The mineralogical AP was compared with the conventional AP calculated from bulk sulfur concentration to assess the applicability to the prediction of acid rock drainage(ARD). The pyrite content calculated by matrix-flushing method showed a high positive correlation($r^2$=0.95) with those by ROCKJOCK. The pyrite contents by matrix-flushing method was 1.45 times larger than those by ROCKJOCK. The pyrite content and mineralogical AP obtained by the matrix-flushing method had a better correlation($r^2$=0.98) with those by the total sulfur concentrations in the all samples except KB sample. The mineralogical NPs of YJ sample were 23.0 and 34.0(kg $CaCO_3$ equivalent per tonne) by matrix-flushing method and ROCKJOCK, respectively. The AP calculated by matrix-flushing method and ROCKJOCK program were 47% and 72% of those by the conventional ABA test. We hereby suggested that the quantitative analysis using XRD data can be applied to prediction of ARD. For more reliable calculation of the mineralogical NP and AP, other sulfide and carbonate minerals such as pyrrhotite, dolomite, ankerite, siderite, rhodochrosite which can affact the mineralogical NP and AP should be considered.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.1025-1028
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• 2008

Using of maintenance system for gate bridge algorism, We made out algorism and engine for prediction of life cycle by neutralization, freezing-thawing and damage from sea wind. To objective of this system, user can use easily with maintenance system for gate bridge. Also, to improve of maintenance efficiency, web-program made out by superannuated evaluation and analysis of field exposure data. To develope web-program, we framing structure design of database, which is adapted to method of maintenance, repair, and reinforcing

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.149-158
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• 2023

As data utilization is becoming more important recently, the importance of data centers is also increasing. However, the data center is a problem in terms of environment and economy because it is a massive power-consuming facility that runs 24 hours a day. Recently, studies using deep learning techniques to reduce power used in data centers or servers or predict traffic have been conducted from various perspectives. However, the amount of traffic data processed by the server is anomalous, which makes it difficult to manage the server. In addition, many studies on dynamic server management techniques are still required. Therefore, in this paper, we propose a dynamic server management technique based on Long-Term Short Memory (LSTM), which is robust to time series data prediction. The proposed model allows servers to be managed more reliably and efficiently in the field environment than before, and reduces power used by servers more effectively. For verification of the proposed model, we collect transmission and reception traffic data from six of Wikipedia's data centers, and then analyze and experiment with statistical-based analysis on the relationship of each traffic data. Experimental results show that the proposed model is helpful for reliably and efficiently running servers.

• Composites Research
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• v.23 no.4
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• pp.44-51
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• 2010

Recently, to solve the problems associated with the neutralization and corrosion of reinforced concrete compression members, the structural configurations such as CFFT (Concrete Filled GFRP Tube) and RCFFT (Reinforced Concrete Filled GFRR Tube) have been developed and applied to main members of civil engineering structure. These members can increase structural performance in terms of structural stability, ductility as well as chemical resistance compared with conventional concrete structural members. Many researches in numerous institutions to predict the load carrying capacity of the concrete compression member strengthened with FRP materials have been conducted and they have been suggested an equation for the prediction of the load carrying capacity of the members. Through the review of the research results, it was found that their results are similar each other. Moreover, it was also found that the results are not directly applicable to our specimens since the results are largely depended upon the member configurations. Also, since the accurate design criteria for the RC members strengthened with FRP such as RCFFT have not been established properly, relevant theoretical and experimental investigations must be conducted for the application to the practical structures. In this study, structural behavior of RCFFT was evaluated through compressive and quasi-static flexural tests in order to formulate design criteria for the structural design. In addition, the RCFFT members were also investigated to examine their confinement effect and the equations capable of estimating the compressive ultimate strength and flexural stiffness of the RCFFT members were proposed.