• Journal of Welding and Joining
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• v.18 no.5
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• pp.33-40
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• 2000

Fatigue crack propagation life of weld toe crack through residual stress field was estimated with Elber's crack concept. Propagation of weld toe crack is heavily influenced by residual stress caused by welding process, so it is essential to take into account the effect of residual stress on the propagation life of weld toe crack. Fatigue crack at transverse and longitudinal weld toe was studied respectively, which represent typical weld joint in ship structure. Numerical and experimental studies are performed for both cases. Residual stress near weldment was estimated through nonlinear thermo-elasto-plastic finite element method, and residual stress intensity factor with Glinka's weight function method. Effective stress intensity factor was calculated with Newman-Forman-de Koning-Henriksen equation which is based on Dugdale strip yield model in estimating crack closure level U at different stress ratio. Calculated crack propagation life coincided well with experimental results.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_2
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• pp.949-956
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• 2020

It's important to measure fuel consumption of vehicles. It's possible to monitor green house gas from vehicles for various traffic conditions with the measured data. It's effective to eco-drive for drivers with fuel consumption data also. There's a display of fuel consumption in the modern vehicles, but it's not useful to get the data from the display. An estimating method for fuel consumption of a vehicle is suggested in the study. It's a simple but an effective method using GPS data. The GPS data(speed, acceleration, road slope) and vehicle data(weight, frontal area, model year, certified fuel economy) is necessary to estimate the fuel consumption for the method. It calculates driving resistance force to estimate engine power. Then it estimates the necessary fuel consumption to maintain the engine power with fuel-power conversion factor. The conversion factor is corrected with certified fuel economy, model year and rated power. The precision of the methods is checked with road test data. The test driving data was measured with GPS and OBD. The error of the estimated fuel consumption for the measured one is about 1.8%. But the error is large for the 1000 and 100 data number from the total data number of about 10,000. The error is from the larger change range of the GPS data than the one of the measured fuel consumption data. But the proposed estimating method is useful to percept the fuel consumption change for better fuel economy with simple gadget like smart phone or other GPS instruments.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.309-315
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• 2014

Summer cabbages in an alpine area are very sensitive to the fluctuations in supply and demand. Yield variability due to weather conditions dictates the market fluctuations of cabbage price. This study reports an empirical relationship based on weather conditions to estimate the growth and harvestable biomass of cabbages, factors that are critical for supply of summer cabbages. Based on experimental results testing sowing date effects over the two years from 1997 to 1998, a logistic equation was parameterized to predict leaf area expansion of summer cabbages. This logistic model for leaf area expansion was then combined with an empirical allometric relationship to predict total biomass. The final equation for estimating fresh weight accumulation of Chinese cabbage is given by: $$Fresh\;weight=3500/(1+{\exp}(5.175-1.153{\times}(6/(1+{\exp}(6.367-0.0064{\times}PHU)))))$$ Where PHU is potential heat units ($^{\circ}C$). The model performance was tested using weather data from 2003 to 2006 to predict fresh harvestable biomass. Overall the model performance was satisfactory with the correlation efficient ranging between 0.89 and 0.94 for each year.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.1043-1052
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• 2009

To derive easily the coefficient of permeability from several other soil properties, the estimation model of coefficient of permeability was proposed using linear regression analysis. The coefficient of permeability is one of the major factors to evaluate the soil characteristics. The study area is located in Kangwon-do Pyeongchang-gun Jinbu-Myeon. Soil samples of 45 spots were taken from the study area and various soil tests were carried out in laboratory. After selecting the soil factor influenced by the coefficient of permeability through the correlation analysis, the estimation model of coefficient of permeability was developed using the linear regression analysis between the selected soil factor and the coefficient of permeability from permeability test. Also, the estimation model of coefficient of permeability was compared with the results from permeability test and empirical equation, and the suitability of proposed model was proved. As the result of correlation analysis between various soil factors and the coefficient of permeability using SPSS(statistical package for the social sciences), the largest influence factor of coefficient of permeability were the effective grain size, porosity and dry unit weight. The coefficient of permeability calculated from the proposed model was similar to that resulted from permeability test. Therefore, the proposed model can be used in case of estimating the coefficient of permeability at the same soil condition like study area.

• Steel and Composite Structures
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• v.2 no.1
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• pp.1-20
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• 2002

Fiber-Reinforced Plastics (FRP) have received significant attention for use in civil infrastructure due to their unique properties, such as the high strength-to-weight ratio and stiffness-to-weight ratio, corrosion and fatigue resistance, and tailorability. It is well known that FRP wraps increase the load-carrying capacity and the ductility of reinforced concrete columns. A number of researchers have explored their use for seismic components. The application of concern in the present research is on the use of FRP for corrosion protection of reinforced concrete columns, which is very important in cold-weather and coastal regions. More specifically, this work is intended to give practicing engineers with a more practical procedure for estimating the strength of a deficient column rehabilitated using FRP wrapped columns than those currently available. To achieve this goal, a stress-strain model for FRP wrapped concrete is proposed, which is subsequently used in the development of the moment-curvature relations for FRP wrapped reinforced concrete column sections. A comparison of the proposed stress-strain model to the test results shows good agreement. It has also been found that based on the moment-curvature relations, the balanced moment is no longer a critical moment in the interaction diagram. Besides, the enhancement in the loading capacity in terms of the interaction diagram due to the confinement provided by FRP wraps is also confirmed in this work.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.3
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• pp.90-96
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• 2004

The objective of this study was to develop a model for safe work load based on a physiological model of metabolic energy of manual material handling tasks. Fifteen male subjects voluntarily participated in this study. Lifting activities with four different weights, 0, 8, 16, 24kg, and four different working frequencies (2, 5, 8, 11 lifts/min) for a lifting range from floor to the knuckle height of 76cm were considered. Oxygen consumption rates and heart rates were measured during the performance of sixteen different lifting activities. Simplified predictive equations for estimating the oxygen consumption rate and the heart rate were developed. The oxygen consumption rate and the heart rate could be expressed as a function of task variables; frequency and the weight of the load, and a personal variable, body weight, and their interactions. The coefficients of determination ($r^2$) of the model were 0.9777 and 0.9784, respectively, for the oxygen consumption rate and the heart rate. The model of oxygen consumption rate was modified to estimate the work load for the given oxygen consumption rate. The overall absolute percent errors of the validation of this equation for work load with the original data set was 39.03%. The overall absolute percent errors were much larger than this for the two models based on the US population. The models for the oxygen consumption rate and for the work load developed in this study work better than the two models based on the US population. However, without considering the biomechanical approach, the developed model for the work load and the two US models are not recommended to estimate the work loads for low frequent lifting activities.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.328-331
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• 2008

A literature survey has been reported of the systems analysis on the liquid rocket engines. The analysis tools are mainly about the calculation of the rocket engine performance at the early days. However recent trend shows that researchers try to develop an integrated environment of distributed analysis tools for faster and cheaper analysis. This article presents the systems analysis results of the liquid rocket engine of gas generator cycle using the published mass estimating model. The specific impulse change for various thrust to weight ratio agrees qualitatively well with the published data.

• Geomechanics and Engineering
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• v.14 no.4
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• pp.315-324
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• 2018

With rapid economic growth, numerous deep excavation projects for high-rise buildings and subway transportation networks have been constructed in the past two decades. Deep excavations particularly in thick deposits of soft clay may cause excessive ground movements and thus result in potential damage to adjacent buildings and supporting utilities. Extensive plane strain finite element analyses considering small strain effect have been carried out to examine the wall deflections for excavations in soft clay deposits supported by diaphragm walls and bracings. The excavation geometrical parameters, soil strength and stiffness properties, soil unit weight, the strut stiffness and wall stiffness were varied to study the wall deflection behaviour. Based on these results, a multivariate adaptive regression splines model was developed for estimating the maximum wall deflection. Parametric analyses were also performed to investigate the influence of the various design variables on wall deflections.

• Journal of muscle and joint health
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• v.5 no.1
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• pp.83-109
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• 1998

This study was carried out to identify the Important modifiable risk factors for reduced bone mass and to construct prediction model which can classify women with either low or high bone mass. Through the literature review, individual characteristics such as age, body weight, height, education level, family history, age of menarche, postmenopausal period, gravity, parity, menopausal status, and breast feeding period were identified and factors of life style such as past milk consumption, past physical activity, present daily activity, present calcium intake, alcohol intake, cigarette smoking, coffee consumption were identified as influencing factors of reduced bone mass in women. Four hundred and eighty women aged between 28 and 76 who had given measurement bone mineral density by dual energy x-ray absortiometry in lumbar vertebrae and femur from July to October, 1997 at 4 general hospitals in Seoul and Pusan were selected for this study. Women were excluded if they had a history of any chronic illness such as rheumatoid arthritis, diabetes mellitus, hyperthroidism, & gastrointestinal disorder and any medication such as calcium supplements, calcitonin, estrogen, thyroxine, antacids, & corticosteroids known affect bone. As a result of these exclusion criteria, four hundred and seventeen women were used for analysis. Multiple logistic regression model was developed for estimating the likelihood of the presence or absence of reduced bone mass. A SAS procedure was used to estimate risk factor coefficient. The results are as follows For lumbar spine, the variables significant were age, body weight, menopause status, daily activity, past milk consumption, and past physical activity(p<0.01), while for femoral Ward's triangle, age, body weight, level of education, past milk consumption, past physical activity(p<0.001). Past physical activity, present daily activity and past milk consumption are the most powerful modifiable predictors in vertebrae and femur among the predictors. When the model performance was evaluated by comparing the observed outcome with predicted outcome, the model correctly identified 74.1% of persons with reduced bone mass and 84.5% of persons with normal bone mass in the lumbar vertebrae and 82.9% of persons with reduced bone mass and 75.0% of persons with normal bone mass in the femoral Ward's triangle. On the basis of these results, a number of recommendations for the management of reduced bone mass may be made : First, those woman who are classified as high risk group of the reduced bone mass in the prediction model should examine the bone mineral density to further examine the usefulness of this model. Second, the optimal amount of milk consumption and a regular weight bearing exercise in childhood, adolescence, and early adult should be ensured.

• The Korean Journal of Applied Statistics
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• v.36 no.4
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• pp.323-335
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• 2023

In causal analysis of high dimensional data, it is important to reduce the dimension of covariates and transform them appropriately to control confounders that affect treatment and potential outcomes. The augmented inverse probability weighting (AIPW) method is mainly used for estimation of average treatment effect (ATE). AIPW estimator can be obtained by using estimated propensity score and outcome model. ATE estimator can be inconsistent or have large asymptotic variance when using estimated propensity score and outcome model obtained by parametric methods that includes all covariates, especially for high dimensional data. For this reason, an ATE estimation using an appropriate dimension reduction method and semiparametric model for high dimensional data is attracting attention. Semiparametric method or sparse sufficient dimensionality reduction method can be uesd for dimension reduction for the estimation of propensity score and outcome model. Recently, another method has been proposed that does not use propensity score and outcome regression. After reducing dimension of covariates, ATE estimation can be performed using matching. Among the studies on ATE estimation methods for high dimensional data, four recently proposed studies will be introduced, and how to interpret the estimated ATE will be discussed.