Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.33
no.6
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pp.507-516
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2015
Debris flow is a representative natural disaster in Korea and occurs frequently every year. Recently, it has caused considerable damage to property and considerable loss of life in both mountainous and urban regions. Therefore, It is necessary to estimate the scope of damage for a large area in order to predict the debris flow. A response model such as the random walk model(RWM) can be used as a useful tool instead of a physics-based numerical model. RWM is a probability model that simplifies both debris flows and sedimentation characteristics as a factor of slopes for a subjective site and represents a relatively simple calculation method compared to other debris flow behavior calculation models. Although RWM can be used to analyzing and predicting the scope of damage caused by a debris flow, input variables for terrain conditions are yet to be determined. In this study, optimal input variables were estimated using DEM generated from the Aerial Photograph and LiDAR data of Mt. Umyeon, Seoul, where a large-scale debris flow occurred in 2011. Further, the deposition volume resulting from the debris flow was predicted using the input variables for a specific area in which the deposition volume could not be calculated because of work restoration and the passage of time even though a debris flow occurred there. The accuracy of the model was verified by comparing the result of predicting the deposition volume in the debris flow with the result obtained from a debris flow behavior analysis model, Debris 2D.
This study describes the damage effects modeling for a quantitative prediction about the hazardous distances from pressurized chlorine saturated liquid tank, which has two-phase leakage. The heavy gas, chlorine is an accidental substance that is used as a raw material and intermediate in chemical plants. Based on the evaluation method for damage prediction and accident effects assessment models, the operating conditions were set as the standard conditions to reveal the optimal variables on an accident due to the leakage of a liquid chlorine storage vessel. A model of the atmospheric diffusion model, ALOHA (V5.4.4) developed by USEPA and NOAA, which is used for a risk assessment of Off-site Risk Assessment (ORA), was used. The Yeosu National Industrial Complex is designated as a model site, which manufactures and handles large quantities of chemical substances. Weather-related variables and process variables for each scenario need to be modelled to derive the characteristics of leakage accidents. The estimated levels of concern (LOC) were calculated based on the Gaussian diffusion model. As a result of ALOHA modeling, the hazardous distance due to chlorine diffusion increased with increasing air temperature and the wind speed decreased and the atmospheric stability was stabilized.
This study aimed to assess the causality of different climate variables on the production of whole crop maize (Zea mays L.; WCM) in the central inland region of the Korea. Furthermore, the effect of these climate variables was also determined by looking at direct and indirect pathways during the stages before and after silking. The WCM metadata (n = 640) were collected from the Rural Development Administration's reports of new variety adaptability from 1985-2011 (27 years). The climate data was collected based on year and location from the Korean Meteorology Administration's weather information system. Causality, in this study, was defined by various cause-and-effect relationships between climatic factors, such as temperature, rainfall amount, sunshine duration, wind speed and relative humidity in the seeding to silking stage and the silking to harvesting stage. All climate variables except wind speed were different before and after the silking stage, which indicates the silking occurred during the period when the Korean season changed from spring to summer. Therefore, the structure of causality was constructed by taking account of the climate variables that were divided by the silking stage. In particular, the indirect effect of rainfall through the appropriate temperature range was different before and after the silking stage. The damage caused by heat-humidity was having effect before the silking stage while the damage caused by night-heat was not affecting WCM production. There was a large variation in soil surface temperature and rainfall before and after the silking stage. Over 350 mm of rainfall affected dry matter yield (DMY) when soil surface temperatures were less than 22℃ before the silking stage. Over 900 mm of rainfall also affected DMY when soil surface temperatures were over 27℃ after the silking stage. For the longitudinal effects of soil surface temperature and rainfall amount, less than 22℃ soil surface temperature and over 300 mm of rainfall before the silking stage affected yield through over 26℃ soil surface temperature and less than 900 mm rainfall after the silking stage, respectively.
Based on the experiment results, the damage and fracture behavior of concrete at the ages of 1d, 2d, 7d and 28d, in three-point bending and uniaxial tensile tests, were simulated with a finite element program, ABAQUS. The critical stress intensity factor $K_{IC}^s$ and the critical crack tip opening displacement ($CTOD_C$) of concrete were calculated with effective-elastic crack approach for the three-point bending test of grade C30 concrete. Based on the crack band model, a bilinear strain-softening curve was derived to simulate the LOAD-CMOD curves and LOAD-Displacement curves. In numerical analysis of the uniaxial tension test of concrete of grade C40, the damage and fracture mechanics were combined. The smeared cracking model coupling with damaged variable was adopted to evaluate the onset and development of microcracking of uniaxial tensile specimen. The uniaxial tension test was simulated by invoking the damage plastic model which took both damage and plasticity as inner variables with user subroutines. All the numerical simulated results show good agreement with the experimental results.
It is necessary to guarantee the safety, serviceability and durability of reinforced concrete structures over their service life. However, concrete structures represent a decrease in their durability due to the effects of external environments according to the passage of time, and such degradation in durability can cause structural degradation in materials. In concrete structures, some degradations in durability increase the corrosion of embedded rebars and also decrease the structural performance of materials. Thus, the structural condition assessment of RC materials damaged by corrosion of rebars becomes an important factor that judges needs to apply restoration. In order to detect the damage of reinforced concrete structures, a visual inspection, a nondestructive evaluation method(NDE) and a specific loading test have been employed. However, obscurities for visual inspection and inaccessible members raise difficulty in evaluating structure condition. For these reasons, detection of location and quantification of the damage in structures via structural response have been one of the very important topics in system identification research. The main objective of this project is to develope a methodologies for the damage identification via static responses of the members damaged by durability. Six reinforced concrete beams with variables of corrosion position and corrosion width were fabricated and the damage detections of corroded RC beams were performed by the optimization and the conjugate beam methods using static deflection. In results it is proved that the conjugate beam method could predict the damage of RC members practically.
Based on damage accumulation of multi-grid composite walls, a method of dynamic reliability estimations is proposed. The multi-grid composite wall is composed of edge frame beam, edge frame columns, grid beams, grid columns and filling blocks. The equations including stiffness, shear forces at filling blocks cracking and multi-grid composite walls yielding, ultimate displacement, and damage index are obtained through tests of 13 multi-grid composite wall specimens. Employing these equations in reliability calculations, procedures of dynamic reliability estimations based on damage accumulation of multi-grid composite walls subjected to random earthquake excitations are proposed. Finally the proposed method is applied to the typical composite wall specimen subjected to random earthquake excitations which can be specified by a finite number of input random variables. The dynamic reliability estimates, when filling blocks crack under earthquakes corresponding to 63% exceedance in 50 years and when the composite wall reach limit state under earthquakes corresponding to 2-3% exceedance in 50 years, are obtained using the proposed method by taking damage indexes as thresholds. The results from the proposed method which show good agreement with those from Monte-Carlo simulations demonstrate the proposed method is effective.
Extended Kalman Filter (EKF) has been widely used for structural identification and damage detection. However, conventional EKF approaches require that external excitations are measured. Also, in the conventional EKF, unknown structural parameters are included as an augmented vector in forming the extended state vector. Hence the sizes of extended state vector and state equation are quite large, which suffers from not only large computational effort but also convergence problem for the identification of a large number of unknown parameters. Moreover, such approaches are not suitable for intelligent structural damage detection due to the limited computational power and storage capacities of smart sensors. In this paper, a two-stage and two-step algorithm is proposed for the identification of structural damage as well as unknown external excitations. In stage-one, structural state vector and unknown structural parameters are recursively estimated in a two-step Kalman estimator approach. Then, the unknown external excitations are estimated sequentially by least-squares estimation in stage-two. Therefore, the number of unknown variables to be estimated in each step is reduced and the identification of structural system and unknown excitation are conducted sequentially, which simplify the identification problem and reduces computational efforts significantly. Both numerical simulation examples and lab experimental tests are used to validate the proposed algorithm for the identification of structural damage as well as unknown excitations for structural health monitoring.
Heat pipes located underground in urban areas and operated under high temperature and pressure conditions can cause large-scale human and economic damage if damaged. In order to predict damage in advance, damage and construction information of heat pipe are analyzed to derive independent variables that have a correlation with frequency of damage, and a simple regression analysis modified model using each variable is applied to the field. However, as the correlation between independent variables applied to the model increases, the independence between variables is harmed and the reliability of the model decreases. In this study, the independence of the pipe diameter, burial depth, insulation level of monitoring system, and disconnection or short circuit of the detection line, which are judged to be interrelated, was tested to derive a method for combining variables and setting categories necessary to apply to the frequency of damage estimation model. For the test of independence, the continuous variables pipe diameter and burial depth were each converted into three categories, insulation level of monitoring system was converted into two categories, and the categorical variable disconnection or short circuit of the detection line status was kept as two categories. As a result of the test of independence, p-value between pipe diameter and burial depth, level of monitoring system and disconnection or short circuit of the detection line was lower than the significance level (α = 0.05), indicating a large correlation between them. Therefore, the pipe diameter and burial depth were combined into one variable, and the categories of the combined variable were set to 9 considering the previously set categories. The insulation level of monitoring system and the disconnection or short circuit of the detection line were also combined into one variable. Since the insulation level is unreliable when the detection line status is disconnection or short circuit, the categories of the combined variable were set to 3.
Offshore structures are exposed to low- and high-frequency responses due to environmental loads, and fatigue damage models are used to calculate the fatigue damage from these. In this study, we tried to optimize the main parameters used in fatigue damage calculation to derive a new fatigue damage model. A total of 162 bi-modal spectra using the elliptic equation were defined to describe the response of offshore structures. To calculate the fatigue damage from the spectra, time series were generated from the spectra using the inverse Fourier transform, and the rain-flow counting method was applied. The considered optimization variables were the size of the frequency increments, ratio of the time increment, and number of repetitions of the time series. In order to obtain optimized values, the fatigue damage was calculated using the parameter values proposed in previous work, and the fatigue damage was calculated by increasing or decreasing the proposed values. The results were compared, and the error rate was checked. Based on the test results, new values were found for the size of the frequency increment and number of time series iterations. As a validation, the fatigue damage of an actual tension spectrum found using the new proposed values and fatigue damage found using the previously proposed method were compared. In conclusion, we propose a new optimized calculation process that is faster and more accurate than the existed method.
Journal of the Korean institute of surface engineering
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v.50
no.4
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pp.251-258
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2017
This study was carried out with solution temperature variables of $75^{\circ}C$ and $90^{\circ}C$ for STS 304, which is a nuclear equipment material, in order to determine the corrosion damage behavior in chemical decontamination process using permanganic acid and oxalic acid. Then electrochemical polarization experiment, weight loss measurement, surface morphology observation and surface damage depth were measured every cycle of the decontamination process to analyze the degree of corrosion damage. As a result, the corrosion current density, weight loss, and surface damage increased as the decontamination process cycle increased, and the corrosion damage of STS 304 tended to increase. Few ${\mu}m$ pitting damage was observed on the surface observation. In 5 cycle, the elongated wormhole-type pitting damage appeared, leading to relatively large surface damage. However, there was no significant difference in the degree of surface damage resulting from the increase in the temperature of the chemical decontamination solution.
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