• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.347-362
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• 2019

Underground excavation using TBM machines has been increasing to reduce complaints caused by noise, vibration, and traffic congestion resulted from the urban underground construction in Korea. However, TBM excavation design and construction still need improvement because those are based on standards of the technologically advanced countries (e.g., Japan, Germany) that do not consider geological environment in Korea at all. Above all, although TBM performance is a main factor determining the TBM machine type, duration and cost of the construction, it is estimated by only using UCS (uniaxial compressive strength) as the ground parameters and it often does not match the actual field conditions. This study was carried out as part of efforts to predict penetration rate suitable for Korean ground conditions. The effective parameters were defined through the correlation analysis between the penetration rate and the geotechnical parameters or TBM performance parameters. The effective parameters were then used as variables of the multiple regression analysis to derive a regression model for predicting TBM penetration rate. As a result, the regression model was estimated by UCS and joint spacing and showed a good agreement with field penetration rate measured during TBM excavation. However, when this model was applied to another site in Korea, the prediction accuracy was slightly reduced. Therefore, in order to overcome the limitation of the regression model, further studies are required to obtain a generalized prediction model which is not restricted by the field conditions.

• Journal of the Korea Concrete Institute
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• v.13 no.5
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• pp.447-456
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• 2001

Many investigators have tried to represent the nonlinear behavior of stress-strain relationship of concrete using mathematical curves. Most of empirical expressions for stress-strain relationship, however, have focused on old age concrete, and were not able to represent well the behavior of concrete at an early age. Where wide understanding on the behavior of concrete from early age to old age is very important in evaluating the durability and service life of concrete structures. In this paper, effect of 5 different strength levels and ages of from 12 hours to 28 days on compressive stress-strain relationship was observed experimentally and analytically. Tests were carried out on $\phi$100${\times}$200mm cylindrical specimens water-cured at 20${\pm}$3$^{\circ}C$. An analytical expression of stress-stain relationship with strength and age was developed using regression analyses on experimental results. For the verification of the proposed model, the model was compared with present and existing experimental data and some existing models. The analysis shows that the proposed model predicts well experimental data and describes well effect of strength and age on stress-strain relationship.

• Horticultural Science & Technology
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• v.29 no.6
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• pp.549-554
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• 2011

The effect of full bloom date and growing season weather on harvesting date of 'Niitaka' pear (Pyrus pyrifolia) in Naju province and the model of multiple linear regression for predicting the fruit growing days was studied. Earlier year in full bloom date, the harvesting date tended earlier but fruit growing days tended longer. Mean and coefficient of variation of fruit growing degree days (GDD) accumulated daily mean and maximum temperature at the base of $0^{\circ}C$ from full bloom date to harvesting date was 3,565, 2.9% and 4,463, 2.5%, respectively. Fruit growing days was not correlated with the fruit GDD accumulated daily mean and maximum temperature at the base of $0^{\circ}C$ in each month but highly correlated with GDD accumulated daily meteorological factors at days after full bloom date. Especially, it was highly negatively correlated with GDD accumulated daily mean and maximum temperature at the base of $0^{\circ}C$ from $1^{st}$ day after full bloom to $60^{th}$ day. The determination coefficient ($r^2$) of multiple linear regression model by full bloom date, GDD accumulated daily mean and maximum temperature from $1^{st}$ day after full bloom to $60^{th}$ day for predicting fruit growing days was 0.7212. As a result, the fruit growing days of 'Niitaka' pear in Naju province can predict with 72% accuracy by the model of multiple linear regression.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.33-44
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• 2005

Railroad crossing crashes are fewer than road crashes, but with regard to crash severity, they can be serious injury crashes. There should be, therefore, enormous efforts to increase the safety of railroad crossings. The objective of this paper is to identify and understand factors associated with railroad crossing crashes. Statistical models are used to examine the relationships between crossing accidents and geometric elements of crossings. The results show the Poisson model is the most appropriate method for the crossing accidents, because overdispersion was not observed. This study identifies seven significant factors associated with railroad crossing crashes through the main and variant models. With regard to explanatory factors on crossing safety, the total traffic volume, daily train volume, presence of commercial area around crossings, distance of train detector from crossings, time duration between the activation of warning signals and gates, crossing types, and speed hump were found to affect the safety of railroad crossings.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.135-147
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• 2017

We, for the first time, estimated daily and monthly surface nitrogen dioxide ($NO_2$) volume mixing ratio (VMR) using three regression models with $NO_2$ tropospheric vertical column density (OMIT-rop $NO_2$ VCD) data obtained from Ozone Monitoring Instrument (OMI) in Seoul in South Korea at OMI overpass time (13:45 local time). First linear regression model (M1) is a linear regression equation between OMI-Trop $NO_2$ VCD and in situ $NO_2$ VMR, whereas second linear regression model (M2) incorporates boundary layer height (BLH), temperature, and pressure obtained from Atmospheric Infrared Sounder (AIRS) and OMI-Trop $NO_2$ VCD. Last models (M3M & M3D) are a multiple linear regression equations which include OMI-Trop $NO_2$ VCD, BLH and various meteorological data. In this study, we determined three types of regression models for the training period between 2009 and 2011, and the performance of those regression models was evaluated via comparison with the surface $NO_2$ VMR data obtained from in situ measurements (in situ $NO_2$ VMR) in 2012. The monthly mean surface $NO_2$ VMRs estimated by M3M showed good agreements with those of in situ measurements(avg. R = 0.77). In terms of the daily (13:45LT) $NO_2$ estimation, the highest correlations were found between the daily surface $NO_2$ VMRs estimated by M3D and in-situ $NO_2$ VMRs (avg. R = 0.55). The estimated surface $NO_2$ VMRs by three modelstend to be underestimated. We also discussed the performance of these empirical modelsfor surface $NO_2$ VMR estimation with respect to otherstatistical data such asroot mean square error (RMSE), mean bias, mean absolute error (MAE), and percent difference. This present study shows a possibility of estimating surface $NO_2$ VMR using the satellite measurement.

• International Journal of Highway Engineering
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• v.6 no.4 s.22
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• pp.109-121
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• 2004

This study was performed to investigate the characteristics of drying shrinkage for concrete slabs as a project for Korean pavement design procedure. According to the volume-surface ratios and aggregate types, the experiments have been executed for 252 days. In order to simulate the volume-surface ratio of a real concrete pavement slab, three-layer epoxy coating and wrapping were used to prevent the evaporation at the part of specimen surfaces. As a result of preliminary test, coating and wrapping method was identified as reliable for three months. According to the volume-surface ratio, the drying shrinkage of the concrete specimen using sandstone was measured 1.32 to 1.8 times higher than that of the limestone specimen. Comparing to the measured drying shrinkage strains and established ACI and CEB-FIP model equations, it turned out that those model equations were underestimated. Finally, considering the age and volume-surface ratios, the prediction equations of the drying shrinkage of concrete specimen were proposed through a multiple nonlinear regression analysis.

• Radiation Oncology Journal
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• v.10 no.1
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• pp.115-120
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• 1992

A mathematical model is presented for the calculation of the depth absorbed dose in water Phantom irradiated by high energy Photon beam (10MV X-ray), based on transport theory. The parameters of this model are obtained from the experimental values which were simulated by non-linear regression process method. The calculated absorbed dose distribution is extended to 3-D by using trial function from beam profile field sizes, SSD and depth in water phantom irradiated by high energy Photon beam. The calculated values using this model are in good agreement with the measured values.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.5
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• pp.429-435
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• 2007

The present study proposed a method fer simulating reflective boundary conditions in Boussinesq wave propagation model by lining lateral boundaries like breakwaters and seawalls with artificial sponge layers. In order to find out the reflective characteristics of sponge layers, 1D numerical experiments were performed varying the relative sponge width (sponge width/wave length). The results showed that the reflection coefficient can be effectively realized from no reflection to full reflection simply by adjusting the relative sponge width. Based on the results, a multiple regression formula was proposed to delineate the relationship among the reflection coefficient and other dimensionless variables. Finally, the reflective sponge layer was applied to a semi-infinite breakwater, demonstrating that it can also be successfully employed in 2D applications.

• Proceedings of the Korea Concrete Institute Conference
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• 2009.05a
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• pp.125-126
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• 2009

Effective beam width model (EBWM) has been used for analysis of post-tensioned (PT) flat plate slab frames under lateral loads. For analyzing PT flat plate slab structure under lateral loads with good precision, reduction in slab stiffness has to be accurately estimated for Effective beam width model(EBWM). For this purpose, this study collected test results of PT flat plate system conducted by former researches. And this study reduced the width of slab so that the stiffness of the EBWM converged into the lateral stiffness of each test specimens by trial and error. By conducting nonlinear regression analysis, an equation for calculating stiffness reduction factor for the PT flat plate is proposed.

• Journal of Navigation and Port Research
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• v.32 no.1
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• pp.81-88
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• 2008

The forecast of a container traffic has been very important for port plan and development. Generally, statistic methods, such as regression analysis, ARIMA, have been much used for traffic forecasting. Recent research activities in forecasting with artificial neural networks(ANNs) suggest that ANNs can be a promising alternative to the traditional linear methods. In this paper, a hybrid methodology that combines both ARIMA and ANN models is proposed to take advantage of the unique strength of ARIMA and ANN models in linear and nonlinear modeling. The results with port traffic data indicate that effectiveness can differ according to the characteristics of ports.