• Geomechanics and Engineering
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• v.17 no.1
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• pp.11-18
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• 2019

The formulas offered so far on the settlement of raft footings provide only a rough estimate of the actual settlement. One of the best ways to make an accurate estimation is to conduct 3-dimensional finite element analyses. However, the required procedure for these analyses is comparatively cumbersome and expensive and needs a bit more expertise. In order to address this issue, in this study, a raft footing settlement formula was developed based on ninety finite element model configurations. The formula was derived using multi-parameter exponential regression analyses. The settlement formula incorporates the dimensions and the elastic modulus of a rectangular raft, vertical uniform pressure and soil moduli and Poisson's ratios up to 5 layers. In addition to this, an equation was offered for the estimation of average deflection of the raft. The proposed formula was checked against 3 well-documented case studies. The formula that is derived from 3D finite element analyses is useful in optimising the raft properties.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.2
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• pp.88-97
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• 2011

For Korean design provisions are not equipped for skewed steel box girder bridges, when American provisions are adopted, load distribution factors different from real behavior are determinated. Furthermore the possibility of over or under estimated bridge design involves. The aim of this study is to provide more rational load distribution factor formulas based on real behavior for shear at obtuse corner of skewed steel box girder bridges. In order to accomplish the aim finite element analysis for a variety of skewed steel box girder bridge structural models is carried out, and each parameters degree of influence on wheel load distribution factors of skewed steel box girder bridges are analyzed. Then multiple regression analysis is fulfilled in order to propose formulas for determinating shear force load distribution factor of skewed steel box girder bridges.

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.1
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• pp.90-97
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• 1996

In Korea, total sediment discharge of a river has been estimated simply by using certain sediment transport formulas including, among others, Einstein's formula. Those formular, however, are known not to be reliable enough for the result calculated by them to be used directly to river planning and management. Therefore, the study used the Modified Einstein Procedure to the estimation of total sediment discharge, because this method is reliable estimated by measurement. Here, measurement of sediment discharge used depth integrating method. The major results obtained from the study for estimation by depth integrating method of sediment discharge in Naeseong stream are as follow; 1 The sedeiment characteristics of Naeseong stream are; The distribution of sediment grain size shows that silt and clay are 55% and sand is 45%. and the bed load sediment grain size is constituted that sand contained with the grain size from O.062mm to 2.0mm is 80% 2. The sediment rating formulas derived from the regression analysis between the sediment discharge and flow discharge are; Seogpo-Gyo : Qs=$0.017 \times 10^{-4} Q^{2.352}$, where discharge is l0cms $0.074 \times 10^{-4} Q^{2.066}$, where discharge is l0cms

• Journal of Ocean Engineering and Technology
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• v.35 no.4
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• pp.257-265
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• 2021

Many studies have been performed to predict a reliable and accurate stress-range distribution and fatigue damage regarding the Gaussian wide-band stress response due to multi-peak waves and multiple dynamic loads. So far, most of the approximation models provide slightly inaccurate results in comparison with the rain-flow counting method as an exact solution. A step-by-step study was carried out to develop new approximate spectral moments that are close to the rain-flow counting moment, which can be used for the development of a fatigue damage model. Using the special parameters and bandwidth parameters, four kinds of parameter-based combinations were constructed and estimated using the R-squared values from regression analysis. Based on the results, four candidate empirical formulas were determined and compared with the rain-flow counting moment, probability density function, and root mean square (RMS) value for relative distance. The new approximate spectral moments were finally decided through comparison studies of eight response spectra. The new spectral moments presented in this study could play an important role in improving the accuracy of fatigue damage model development. The present study shows that the new approximate moment is a very important variable for the enhancement of Gaussian wide-band fatigue damage assessment.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.23-32
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• 2012

This paper deals with the bias and variance of regression coefficient estimators in a finite population. We derive approximate formulas for the bias, variance and mean square error of two estimators when we select a fixed-size inclusion probability proportional to the size sample and then estimate regression coefficients by the ordinary least square estimator as well as the weighted least square estimator based on the selected sample data. Necessary and sufficient conditions for the comparison of the two estimators in terms of variance and mean square error are suggested. In addition, a simple example is introduced to numerically compare the variance and mean square error of the two estimators.

• Computers and Concrete
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• v.12 no.2
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• pp.187-209
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• 2013

This paper presents a study on the prediction of transfer length of 13 mm seven-wire prestressing steel strand in pretensioned prestressed concrete members with rectangular cross-section including several material properties and design and manufacture parameters. To this end, a carefully selected database consisting of 207 different cases coming from 18 different sources spanning a variety of practical transfer length prediction situations was compiled. 16 single input features and 5 combined input features are analyzed. A widely used feedforward neural regression model was considered as a representative of several machine learning methods that have already been used in the engineering field. Classical multiple linear regression was also considered in order to comparatively assess performance and robustness in this context. The results show that the implemented model has good prediction and generalization capacity when it is used on large input data sets of practical interest from the engineering point of view. In particular, a neural model is proposed -using only 4 hidden units and 10 input variables-which significantly reduces in 30% and 60% the errors in transfer length prediction when using standard linear regression or fixed formulas, respectively.

• Geomechanics and Engineering
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• v.9 no.1
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• pp.101-113
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• 2015

Saturated soil hydraulic conductivity is a very important soil parameter in numerous practical engineering applications, especially rainfall infiltration and slope stability problems. This parameter is difficult to measure since it is very highly sensitive to various soil conditions. There have been many analytical and empirical formulas to predict saturated soil hydraulic conductivity based on experimental data. However, there have been few studies to investigate in-situ hydraulic conductivity of weathered granite soils, which constitute the majority of soil slopes in Korea. This paper introduces an estimation method to derive saturated hydraulic conductivity of Korean weathered granite soils using in-situ experimental data which were obtained from a variety of slope areas of South Korea. A robust regression analysis was performed using different physical soil properties and an empirical solution with an $R^2$ value of 0.9193 was suggested. Besides that this research validated the proposed model by conducting in-situ saturated soil hydraulic conductivity tests in two slope areas.

• Journal of the Korean Society of Propulsion Engineers
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• v.11 no.2
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• pp.71-78
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• 2007

An experimental investigation was conducted to clarify the combustion characteristics of Polyethylene-GOX(PE-GOX) hybrid motor using a single-port fuel grain configuration. Data from the experiments were analyzed to evaluate the length-averaged regression rate of PE-GOX propellants. Based on the existing theories, the empirical regression rate formulas provided from Marxman[3,4] and Altman[14] showed good concordance with the PE-GOX experiments. The accuracy of the regression rate was then evaluated and compared with the measured one. As a result, Marxman's model was somewhat more precise than Altman's model in these experiments. Moreover, the consideration of the empirical regression rate showed that O/F ratio has minor variation due to the quasi constant inflow of the fuel during motor firing.

• Tuberculosis and Respiratory Diseases
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• v.41 no.5
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• pp.521-530
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• 1994

Background : The past studies on prediction formulas of pulmonary function parameters in healthy nonsmoking Korean adults have been performed in relatively small number of subjects and the reported results were restricted on a few parameters. Also there was no systematic investigation into the effect of smoking on pulmonary function parameters in smokers who have no respiratory symptoms. Therefore we attempted to establish prediction formulas of pulmonary function parameters and examined the effect of smoking on pulmonary function parameters. Methods We analyzed the result of parameters derived from the forced expiratory spirogram in 1,067 nonsmoking subjects from June in 1990 to December in 1991. They consisted of 306 males and 761 females and had neither respitatory symptoms nor history of respiratory disease. We derived prediction formulas by multiple linear regression method from their age, heights, and weights in each sex. To examine the effect of smoking on pulmonary function parameters, we classified 383 smoking men into three groups according to the past amount of smoking as follows : i.e. group of smokers who have smoked below 10 pack-years, 10-20 pack-years and above 20 pack-years. Regarding each group of past smoking as an independent dummy variable, we analyzed pulmonary function parameters including nonsmoking men as a baseline by multiple linear regression. We evaluated the smoking effect on pulmonary function parameters according to estimated p-value. Result : 1) Prediction formulas for pulmonary function parameters in each sex were derived. 2) The past smoking less than 10 pack-years does not give any effect on pulmonary function parameters. The past smoking of 10~20 pack-years showed significant negative correlation with $FEV_1$/FVC and FEF 25~75%, and the smoking above 20 pack years showed negative correlation with $FEV_1$ and $FEV_1$/FVC. Conclusion : We have got prediction formulas of pulmonary function parameters which is driven from forced expiratory spirogram in nonsmoking Korean adults by multiple linear regression from age, heights and weights of subjects. The past smoking more than 10 pack-years showed negative correlation with some pulmonary function parameters of airflow obstruction.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.36 no.2
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• pp.37-49
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• 2024

To date, numerous empirical formulas have been proposed through hydraulic model experiments to predict the wave breaker index, including wave height and depth of wave breaking, due to the inherent complexity of generation mechanisms. Unfortunately, research on the characteristics of wave breaking and the prediction of the wave breaker index for gravel beaches has been limited. This study aims to forecast the wave breaker index for gravel beaches using representative linear-based machine learning techniques known for their high predictive performance in regression or classification problems across various research fields. Initially, the applicability of existing empirical formulas for wave breaker indices to gravel seabeds was assessed. Various linear-based machine learning algorithms were then employed to build prediction models, aiming to overcome the limitations of existing empirical formulas in predicting wave breaker indices for gravel seabeds. Among the developed machine learning models, a new calculation formula for easily computable wave breaker indices based on the model was proposed, demonstrating high predictive performance for wave height and depth of wave breaking on gravel beaches. The study validated the predictive capabilities of the proposed wave breaker indices through hydraulic model experiments and compared them with existing empirical formulas. Despite its simplicity as a polynomial, the newly proposed empirical formula for wave breaking indices in this study exhibited exceptional predictive performance for gravel beaches.