• Journal of Biosystems Engineering
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• v.37 no.5
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• pp.279-286
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• 2012

Purpose: This study has been conducted to investigate the applicability of motion analysis of tillage blade for estimation of tillage characteristics of crank-type and rotary-type rotavators. Methods: The interrelation between tillage traces from motion analysis and field test results including rotavating depth, pulverizing ratio and inversion ratio at the same work conditions were analyzed for both crank-type and rotary-type rotavators. The work conditions include working speed of prime mover tractor and PTO speed of rotavators. For the motion analysis, joint conditions of main connecting component were specified considering the actual working mechanism of rotavator. Results: There were important correlations for the trend between motion analysis and field test results. Conclusions: Although further study is needed for applying motion analysis to estimate the accurate tillage related parameters such as rotavating depth, the soil pulverizing ratio and inversion ratio, it could be used to compare the tillage characteristics of various rotavators quickly and simply.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.10 s.175
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• pp.137-143
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• 2005

The integrity of steam generator tubes in nuclear power plant should be maintained sufficiently during operation. For sake of this, complicated assessment procedures are required such as fracture mechanics analysis, etc. The integrity assessment of tubes has been performed by using conventional deterministic approaches while there are many uncertainties to carry out a rational evaluation. In this respect, probabilistic integrity assessment is considered as an alternative method for integrity assessment. The objectives of this study are to develop an integrity assessment system based on probabilistic fracture mechanics and to predict the failure probability of steam generator tubes containing an axial through-wall crack. The developed integrity assessment system consists of three evaluation modules, which apply first order reliability method, second order reliability method and Monte Carlo simulation method, respectively. The system has been applied to predict failure probability of steam generator tubes and the estimation results showed a promising applicability of the probabilistic integrity assessment system.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.2
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• pp.88-95
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• 1994

This paper is to evaluate the applicability of neural networks to the estimation of evapotranspiration. Two neural networks were developed to forecast daily evapotranspiration of the rice crop with back-propagation and counter-propagation algorithm. The neural network trained by back-propagation algorithm with delta learning rule is a three-layer network with input, hidden, and output layers. The other network with counter-propagation algorithm is a four-layer network with input, normalizing, competitive, and output layers. Training neural networks was conducted using daily actual evapotranspiration of rice crop and daily climatic data such as mean temperature, sunshine hours, solar radiation, relative humidity, and pan evaporation. During the training, neural network parameters were calibrated. The trained networks were applied to a set of field data not used in the training. The created response of the back-propagation network was in good agreement with desired values and showed better performances than the counter-propagation network did. Evaluating the neural network performance indicates that the back-propagation neural network may be applied to the estimation of evapotranspiration of the rice crop. This study does not provide with a conclusive statement as to the ability of a neural network to evapotranspiration estimating. More detailed study is required for better understanding and evaluating the behavior of neural networks.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.4
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• pp.299-309
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• 2019

Waterworks facilities inevitably experience some amount of leakage even if there is a lot of investment or state-of-the-art technology that is applied such as DMA(District Metered Area) system construction, leakage detection, repair, pipe rehabilitation, etc. The primary reason is the leakage is naturally restored over time. In the UK, this restoration characteristic is defined as NRR(Natural rate of rise of leakage) and used to decision making for prioritizing active leakage control of DMAs. However, this restoration characteristic is well recognized, but researches on NRR in the water distribution system are insufficient in Korea. In this study, the estimation method of NRR was developed suitable for applicating in Korea considering of SCADA data, water infrastructure, and water usage patterns by modification of the UK's NRR method. The proposed method was applied to 9 DMAs and verified it's applicability by comparing with the other water loss performance indicators. It is expected that the proposed method can be used to support decision making for sustainable NRW(Nor-revenue water) management in the water distribution system.

• Journal of Soil and Groundwater Environment
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• v.24 no.5
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• pp.31-41
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• 2019

In 2013, the Ministry of Environment in South Korea promulgated a new regulatory bulletin that contained revised enforcement ordinance on soil management protocols. The bulletin recommends the use of Universal Soil Loss Equation (USLE) for the soil erosion estimation, but USLE has limited applicability in prediction of soil erosion because it does not allow direct estimation of actual mass of soil erosion. Therefore, there is a great need of revising the protocol to allow direct comparison between the measured and estimated values of soil erosion. The Korean Soil Loss Equation (KORSLE) was developed recently and used to estimate soil loss in two fields as an alternative to existing USLE model. KORSLE was applied to estimate monthly rainfall erosivity indices as well as temporal variation in potential soil loss. The estimated potential soil loss by KORSLE was adjusted with correction factor for direct comparison with measured soil erosion. The result was reasonable since Nash-Stucliff efficiency were 0.8020 in calibration and 0.5089 in validation. The results suggest that KORSLE is an appropriate model as an alternative to USLE to predict soil erosion at field scale.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.81-100
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• 2020

The purpose of this study was to propose applicability of spatial data and quality check criteria for estimating damage from storm and flood. Using the data from the National Disaster Management System and National Spatial Data Infrastructure, spatial database for estimation of storm and flood damage has been mapped to each type of damage. This was proposed as the quality check criteria for damage analysis. Through this study, it is possible to utilize the spatial database for estimating storm and flood damage. The reliability of analysis results are ensured through the quality check criteria.

• Geomechanics and Engineering
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• v.30 no.5
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• pp.449-460
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• 2022

Safe underground construction in a rock mass requires adequate ground investigation and effective determination of rock conditions. The estimation of rock mass behavior is difficult, because rock masses are innately anisotropic and heterogeneous at different scales and are affected by various environmental factors. Quantitative rock mass classification systems, such as the Q-system and rock mass rating, are widely used for characterization and engineering design. The measurement of rock classification parameters is subjective and can vary among observers, resulting in questionable accuracy. Geophysical investigation methods, such as seismic surveys, have also been used for ground characterization. Torsional shear wave propagation characteristics in cylindrical rods are equal to that in an infinite media. A probabilistic quantitative relationship between the Q-value and shear wave velocity is thus investigated considering long-wavelength wave propagation in equivalent continuum jointed rock masses. Individual Q-system parameters are correlated with stress-dependent shear wave velocities in jointed rocks using experimental and numerical methods. The relationship between the Q-value and the shear wave velocity is normalized using a defined reference condition. This relationship is further improved using probabilistic analysis to remove unrealistic data and to suggest a range of Q-values for a given wave velocity. The proposed probabilistic Q-value estimation is then compared with field measurements and cross-hole seismic test data to verify its applicability.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.6
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• pp.567-576
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• 2017

The object of this research is an establishment of BIM-based quantity takeoff(QTO) and cost estimation guidelines for reinforcement concrete structures focused on improvement of field applicability in transition period from 2D drawing-based environment to 3D BIM-based environment. Preliminary studies on existing guidelines and standards for BIM modeling, QTO and cost estimation of reinforcement concrete structures are performed, and then a standardization of BIM-based cost estimation process is proposed through comparative analysis between 2D drawing-based cost estimation process and 3D BIM-based. In addition, modeling, QTO, and cost estimation processes of cost-BIM model for RC structures are conducted. The contributions of this research and the guidelines suggested by this research are 1) lowering barriers to entity to the new BIM-based environment for small size companies, 2) reducing construction cost by a close estimate, 3) establishing the foundation for integrated management of informations through construction project life cycle, 4) and ultimately, developing the BIM ecosystems.

• Journal of Korean Society of Forest Science
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• v.107 no.4
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• pp.402-411
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• 2018

This study was conducted to develop ingrowth estimation equations on Pinus densiflora found in Gangwon Province and in the center of Korean Peninsula, based on the National Forest Inventory (NFI)'s permanent sampling plot data. For this study, identical sampling plots in $5^{th}$ and $6^{th}$ NFI data were collected in order to identify ingrowth amounts for the last 5 years. Following two-stage approaches in developing the ingrowth estimation equations, the logistic regression model was used in the first stage to estimate the ingrowth probability. In the second stage, regression analysis on sampling plots with ingrowth occurrence was used to estimate the ingrowth amount. A candidate model was finally selected as an optimal model after a verification based on three evaluation statistics which include mean difference (MD), standard deviation of difference (SDD) and standard error of difference (SED). In results, a logistic regression model based on the number of sampling plot which did not result in ingrowth (model VI), was selected for an ingrowth probability estimation equation and exponential function including the species composition (SC) variable was optimal for an ingrowth estimation equation (model VII). The ingrowth estimation equations developed in this study also evaluated the estimation ability in various forest stand conditions, and no particular issue in fitness or applicability was observed.

• Journal of Korean Society on Water Environment
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• v.25 no.2
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• pp.212-220
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• 2009

In many studies, the Numeric Integration (NI) method has been widely used to calculate pollutant loads from the watershed because it is easy to apply. However, there have been many needs for more accurate pollutant loads estimation method with the restricted number of water quality samples. However, the ESTIMATOR model does not allow the users to define the regression model to explain the measured flow and water quality relationship, indicating the ESTIMATOR model is not flexible. The LOADEST model allows the user to choose the model type from 11 predefined general forms of regression equations. Annual loads of T-N and T-P with the LOADEST model were 0.70 times and 0.84 times of those by NI method, respectively. The coefficient of determination ($R^2$) of the LOADEST regression for the T-N and T-P were 0.92 and 0.72, respectively. This indicates that the load estimation regression model with the LOADEST for the study watershed explains the relationship between the observed flow and water quality data well reasonably well. Based on these findings, we suggest that the LOADEST model estimated regression equation could be used to estimate pollutant loads using the measured flow data for the study watershed.