• Tunnel and Underground Space
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• v.9 no.1
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• pp.48-55
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• 1999

One of the major roles of concrete lining is the supplementary support of ground load. Therefore, if there are cracks or deformation found in the lining, the causes should be carefully examined. Tunnel Soundness Evaluation System (DW-TSES) was developed to meet such requirements. Main facility of the system was intended to find the probable causes on the basis of the apparent changes in lining and the environmental conditions. It also includes facilities for evaluating the soundness of a tunnel and indicating the method for repair or reinforcement. The characteristic feature of damages is used for reasoning in case of deterioration and leakage, and artificial neural network is used in external pressure. This process depends on the results of the case analyses and FDM, which have a collection of the typical features of different types of damages as well as the unusual changes caused by the external pressure. The comparison of the outputs of this system with those of expert's diagnoses draws the following conclusions. 1) Artificial neural network was a suitable tool to find to causes of damages by external pressure. 2) The environmental conditions improved the accuracy in reasoning. 3) The result of finding causes and evaluating soundness was helpful to suggest effective methods concerning tunnel maintenance.

• Explosives and Blasting
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• v.17 no.4
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• pp.67-88
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• 1999

Ground settlements induced by tunnel excavation cause the foundations of the neighboring superstructures to deform. An expert system called NESASS was developed to analyze the structural safety of such superstructures. NESASS predicts the trend of ground settlements to be resulted from tunnel excavation and carries out a safety analysis for superstructures on the basis of the predicted ground settlements. Using neural network techniques, NESASS learns a data base consisting of the measured ground settlements collected from numerous actual fields and infers a settlement trend at the field of interest. NESASS calculates the magnitudes of angular distortion, deflection ratio, and differential settlement of the structure and, in turn, determines the safety of the structure. In addition, NESASS predicts the patterns of cracks to be formed on the structure using Dulacskas model for crack evaluation. In this study, the ground settlements measured from the Seoul subway construction sites were collected and sorted with respect to the major factors influencing ground settlement. Subsequently, a database of ground settlement due to tunnel excavation was built. A parametric study was performed to verify the reliability of the proposed neural network structure. A comparison of the ground settlement trends predicted by NESASS with the measured ones indicates that NESASS leads to reasonable predictions. An examples is presented in this paper where NESASS is used to evaluate the safety of a structure subject to deformation due to tunnel excavation near to the structure.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.101-106
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• 2020

This research is related to a development of the ultrasonic detector for an internal defect detection of various assembly part's welding zone. In this research, measurement S/Ws including system's motion control, S/W ultrasonic transmitter/receiver control, defect judgment standard setting, etc. have been designed for ultrasonic detection, and welding defects sample network, etc. were also designed for comparison between products in good condition and defective products. Through this kind of system, automatic detection function can be performed for the depth and the defect location of the assembly parts welding zone, and the system is able to make a judgment of internal defect detection which is used to be performed by an expert in the past.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.05a
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• pp.608-611
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• 2004

As the use of various electronic equipments has been increased recently according to industrialization and information network establishment, concern about electromagnetic wave exposed environment has also been increased. Therefore, this study aims to verify electromagnetic wave absorbing effects of inorganic paint that is made of carbon, electro-conductive materials with regard to its physical characteristics, its electromagnetic wave absorbing rate through a mock-up test for proving its effects in the indoor condition. The results are as follows: The results of running tests on electromagnetic wave absorbing inorganic paints for checking their requirements as painting material such as adherence degree, resistance to fine crack, resistance to washing, alkali-resistance, discoloration-resistance, etc. show that inorganic paints have the physical characteristics meeting the requirements for painting materials. In addition, it shows that the electromagnetic wave absorbing effect, in line with the number of paintings and the thickness of paintings, secures $75\~89\%$ of efficiency. And the mock-up test shows that the electromagnetic wave absorbing effect inside building is directly proportional to the distance from the source of electromagnetic wave such as electronic equipments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.393-396
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• 1995

In this syudy, the researches classifying the artificial and natural flaws in welding parts are performed using the smart pattern recognition technology. For this purpose the smart signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing,feature extraction , feature selection and classifier selection is treated by bulk. Specially it is composed with and discussed using the statistical classifier such as the linear disciminant function classifier, the empirical Bayesian classifier. Also, the smart pattern recognition technology is applied to classification problem of natural flaw(i.e multiple classification problem-crack,lack of penetration,lack of fusion,porosity,and slag inclusion, the planar and volumetric flaw classification problem). According to this results, if appropriately learned the neural network classifier is better than ststistical classifier in the classification problem of natural flaw. And it is possible to acquire the recognition rate of 80% above through it is different a little according to domain extracting the feature and the classifier.

• Journal of Korea Foundry Society
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• v.22 no.4
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• pp.174-183
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• 2002

Twin-roll process is a relatively new continuous casting process which can produce high-quality strip products directly, and solidification rate can reach $10^3$ to $10^4$ K/s, leading to fine and uniform microstructures with enhanced mechanical properties. The strip casting condition for producing fine Al-Sn alloy strip was obtained experimentally, and defects appearing on the strip was examined. Crack formation and surface quality of the strip was found to depend mainly on process parameters such as melt temperature, roller gap and rolling speed. Sn structure of network type was observed in Al-20Sn and Al-40Sn alloy strips, and cell spacing of Al-40Sn alloy was smaller than that of Al-20Sn. Banding strength of the heat treated specimens increased with increasing of soaking time and temperature, and bonding strength of Al-20Sn alloy was more superior than that of Al-40Sn alloy. However wear resistance of Al-40Sn alloy contained large amount of soft Sn which possess good anti-friction characteristics was superior than that of Al-20Sn alloy.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1343-1346
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• 2005

In the cold rolling mill, coil breakage that generated in rolling process makes the various types of troubles such as the degradation of productivity and the damage of equipment. Recent researches were done by the mechanical analysis such as the analysis of roll chattering or strip inclining and the prevention of breakage that detects the crack of coil. But they could cover some kind of breakages. The prediction of Coil breakage was very complicated and occurred rarely. We propose to build effective prediction modes for coil breakage in rolling process, based on data mining model. We proposed three prediction models for coil breakage: (1) decision tree based model, (2) regression based model and (3) neural network based model. To reduce model parameters, we selected important variables related to the occurrence of coil breakage from the attributes of coil setup by using the methods such as decision tree, variable selection and the choice of domain experts. We developed these prediction models and chose the best model among them using SEMMA process that proposed in SAS E-miner environment. We estimated model accuracy by scoring the prediction model with the posterior probability. We also have developed a software tool to analyze the data and generate the proposed prediction models either automatically and in a user-driven manner. It also has an effective visualization feature that is based on PCA (Principle Component Analysis).

• Journal of the Korean Ceramic Society
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• v.31 no.2
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• pp.220-226
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• 1994

The hydrolysis and condensation reactions in the mixed alkoxide solutions of Si(OC2H5)4 and Zr(O-nC3H7)4 with various water contents (1, 2, 4, and 8 in molar ratio to alkoxide, r) and catalysts were examined by rheological measurements and the number average molecular weight in order to explain the shape of the polymer in the mixed alkoxide solutions. It was found that fibers could be drawn in the viscosity range of 1∼100P from the acid-catalyzed solutions with lower water contents of the mole ratio H2O/alkoxide, r 2. On the other hand, crack free bulk gel was formed from the acid-catalyzed solutions including a large amount of water (r 4), and the base-catalyzed solutions. The relation between the intrinsic viscosity [{{{{ eta }}] and the number average molecular weight n, namely [{{{{ eta }}]=Knα, has shown that the acid-catalyzed spinnable solutions (r=1 and 2) have linear polymers and the exponent α's are about 0.56 and 0.81, whereas non-spinnable solutions (r=4 and 8) have three dimensional network polymers or spherical particles and the exponent α's are 0.41∼0.51 and 0.35.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.365-368
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• 2006

RBSN Method, Rigid-Body-Spring Network Method, is a structural analysis method that overcomes the problems faced in FEM analysis of concrete or crack forming structures. In RBSN, irregular lattices are used to model structural components consisting of bulk material, curvilinear reinforcements, and their interfaces. Because reinforcements and their interfaces in the bulk material are freely positioned, meshing is irrespective of the geometry of the representing bulk material. In this paper, RBSN method of 3D is applied in simulating the pull-out test of FRP (Fiber Reinforced Polymer) embedded in concrete. The comparison of analysis results to experimental results shows that RBSN method simulates the shear-slip behavior very precisely. From the analysis results, 3D RBSN method is proven to be an effective and accurate analysis method for concrete structural analysis. Also, the results show that RBSN method can be a potential analysis method for concrete structures that can replace the current FEM analysis.

• Advances in concrete construction
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• v.11 no.3
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• pp.261-270
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• 2021

In this study, a new understanding is presented on the microcracking behavior of high strength concrete (HSC) with steel fiber addition having prior compressive loading history. Microcracking behavior at critical stress (σcr) region, using seven fiber addition volume of 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, and 2.0% was evaluated, at two aspect ratios (60 and 75). The specimens were loaded up to a specified compressive stress levels (0.70fc-0.96fc), and subsequently subjected to split tensile tests. This was followed by microscopic analyses afterwards. Four compressive stress levels as percentage of fc were selected according to the linearity end point based on stress-time (σ-t) diagram under uniaxial compression. It was seen that pre-compression has an effect on the linearity end point as well as fiber addition where it lies within 85-91% of fc. Tensile strength gain was observed in some cases with respect to the 'maiden' tensile strength as oppose to tensile strength loss due to the fiber addition with teething effect. Aggregate cracking was the dominant failure mode instead of bond cracks due to improved matrix quality. The presence of the steel fiber improved the extensive failure pattern of cracks where it changes from 'macrocracks' to a branched network of microcracks especially at higher fiber dosages. The applied pre-compression resulted in hardening effect, but the cracking process is similar to that in concrete without fiber addition.