• Atmosphere
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• v.26 no.1
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• pp.1-18
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• 2016

Eleven Tropical Cyclone (TC) intensity guidance models in the western North Pacific have been validated over 2008~2014 based on various analysis methods according to the lead time of forecast, year, month, intensity, rapid intensity change, track, and geographical area with an additional focus on TCs that influenced the Korean peninsula. From the evaluation using mean absolute error and correlation coefficients for maximum wind speed forecasts up to 72 h, we found that the Hurricane Weather Research and Forecasting model (HWRF) outperforms all others overall although the Global Forecast System (GFS), the Typhoon Ensemble Prediction System of Japan Meteorological Agency (TEPS), and the Korean version of Weather and Weather Research and Forecasting model (KWRF) also shows a good performance in some lead times of forecast. In particular, HWRF shows the highest performance in predicting the intensity of strong TCs above Category 3, which may be attributed to its highest spatial resolution (~3 km). The Navy Operational Global Prediction Model (NOGAPS) and GFS were the most improved model during 2008~2014. For initial intensity error, two Japanese models, Japan Meteorological Agency Global Spectral Model (JGSM) and TEPS, had the smallest error. In track forecast, the European Centre for Medium-Range Weather Forecasts (ECMWF) and recent GFS model outperformed others. The present results has significant implications for providing basic information for operational forecasters as well as developing ensemble or consensus prediction systems.

• Korean Journal of Community Nutrition
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• v.22 no.5
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• pp.413-425
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• 2017

Objectives: Accurate assessment of energy expenditure is important for estimation of energy requirements in athletic children. The objective of this study was to evaluate the accuracy of accelerometer for prediction of selected activities' energy expenditure and intensity in athletic elementary school children. Methods: The present study involved 31 soccer players (16 males and 15 females) from an elementary school (9-12 years). During the measurements, children performed eight selected activities while simultaneously wearing the accelerometer and carrying the portable indirect calorimeter. Five equations (Freedson/Trost, Treuth, Pate, Puyau, Mattocks) were assessed for the prediction of energy expenditure from accelerometer counts, while Evenson equation was added for prediction of activity intensity, making six equations in total. The accuracy of accelerometer for energy prediction was assessed by comparing measured and predicted values, using the paired t-test. The intensity classification accuracy was evaluated with kappa statistics and ROC-Curve. Results: For activities of lying down, television viewing and reading, Freedson/Trost, Treuth were accurate in predicting energy expenditure. Regarding Pate, it was accurate for vacuuming and slow treadmill walking energy prediction. Mattocks was accurate in treadmill running activities. Concerning activity intensity classification accuracy, Pate (kappa=0.72) had the best performance across the four intensities (sedentary, light, moderate, vigorous). In case of the sedentary activities, all equations had a good prediction accuracy, while with light activities and Vigorous activities, Pate had an excellent accuracy (ROC-AUC=0.91, 0.94). For Moderate activities, all equations showed a poor performance. Conclusions: In conclusion, none of the assessed equations was accurate in predicting energy expenditure across all assessed activities in athletic children. For activity intensity classification, Pate had the best prediction accuracy.

• Earthquakes and Structures
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• v.22 no.6
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• pp.609-623
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• 2022

To study the empirical seismic fragility of a reinforced concrete girder bridge, based on the theory of numerical analysis and probability modelling, a regression fragility method of a rapid fragility prediction model (Gaussian first-order regression probability model) considering empirical seismic damage is proposed. A total of 1,069 reinforced concrete girder bridges of 22 highways were used to verify the model, and the vulnerability function, plane, surface and curve model of reinforced concrete girder bridges (simple supported girder bridges and continuous girder bridges) considering the number of samples in multiple intensity regions were established. The new empirical seismic damage probability matrix and curve models of observation frequency and damage exceeding probability are developed in multiple intensity regions. A comparative vulnerability analysis between simple supported girder bridges and continuous girder bridges is provided. Depending on the theory of the regional mean seismic damage index matrix model, the empirical seismic damage prediction probability matrix is embedded in the multidimensional mean seismic damage index matrix model, and the regional rapid prediction matrix and curve of reinforced concrete girder bridges, simple supported girder bridges and continuous girder bridges in multiple intensity regions based on mean seismic damage index parameters are developed. The established multidimensional group bridge vulnerability model can be used to quantify and predict the fragility of bridges in multiple intensity regions and the fragility assessment of regional group reinforced concrete girder bridges in the future.

• Physical Therapy Korea
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• v.18 no.3
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• pp.76-84
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• 2011

The purpose of this study was to investigate the correlations between pain intensity, physical impairments, disability, and psychological factors according to the difference in duration of low back pain. This study was a cross-sectional survey of 102 participants with low back pain, divided into two groups equal in number: The first group consisted of patients with acute and subacute low back pain, while the second group consisted of patients suffering from chronic low back pain. The results showed that gender, age, pain intensity, physical impairment, disability and Fear-Avoidance Beliefs (FABs) for work activities were not significantly different between two groups. FABs for physical activities of the first group were significantly more prevalent than in the second group. More than moderate correlations were found between pain intensity, physical impairment, and disability in the first group. Less than moderate correlations were found between pain intensity, physical impairment, disability, FABs, and depression in the second group. These findings suggest that we must consider psychological factors in the treatment of patients with chronic low back pain. Regression analyses revealed that pain intensity and FABs for work activities significantly contributed to the prediction of disability in the first group. Also, pain intensity and FABs for physical activities significantly contributed to the prediction of disability in the second group. Pain intensity was most important predictor of disability in two groups.

• Physical Therapy Korea
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• v.16 no.3
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• pp.60-68
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• 2009

Psychsocial factors appear to play an important role in the maintenance and development of chronic disability from low back pain. Fear of pain may be more disabling than the pain itself in patients with nonacute low back pain. The purpose of this study was to identify the contribution of gender, age, depression and pain-related fear to pain intensity and disability in nonacute low back pain patients. This was a cross-sectional survey study of eighty four patients who had low back pain for at least 4 weeks. More than moderate correlations were found between pain intensity, disability, fear-avoidance beliefs and depression. Regression analyses revealed that disability ratings and fear-avoidance beliefs for work activities significantly contributed to the prediction of pain intensity, even when controlling for age, gender and pain duration. Also, fear-avoidance beliefs for physical activity, pain intensity, age and depression, significantly contributed to the prediction of disability, even when controlling for gender and pain duration. These findings suggest that disability scores and fear-avoidance beliefs for work activities are important determinants of pain intensity. They also suggest that fear-avoidance beliefs for physical activity, pain intensity, age and depression are important determinants of disability.

• Safety and Health at Work
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• v.11 no.3
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• pp.322-334
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• 2020

Background: Spontaneous combustion of coal is one of the factors which causes direct or indirect gas and dust explosion, mine fire, the release of toxic gases, loss of reserve, and loss of miners' life. To avoid these incidents, the prediction of spontaneous combustion is essential. The safety of miner's in the mining field can be assured if the prediction of a coal fire is carried out at an early stage. Method: Adularya Underground Coal Mine which is fully mechanized with longwall mining method was selected as a case study area. The data collected for 2017, by sensors from ten gas monitoring stations were used for the simulation and prediction of a coal fire. In this study, the fuzzy logic model is used because of the uncertainties, nonlinearity, and imprecise variables in the data. For coal fire prediction, CO, O₂, N₂, and temperature were used as input variables whereas fire intensity was considered as the output variable.The simulation of the model is carried out using the Mamdani inference system and run by the Fuzzy Logic Toolbox in MATLAB. Results: The results showed that the fuzzy logic system is more reliable in predicting fire intensity with respect to uncertainties and nonlinearities of the data. It also indicates that the 1409 and 610/2B gas station points have a greater chance of causing spontaneous combustion and therefore require a precautional measure. Conclusion: The fuzzy logic model shows higher probability in predicting fire intensity with the simultaneous application of many variables compared with Graham's index.

• Journal of the Society of Naval Architects of Korea
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• v.39 no.1
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• pp.90-99
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• 2002

The prediction of stress intensity factor(SIF) is one of the most important factors to analyse the propagation behavior of cracks in hull structural members. Up to now, however, simplified prediction method of SIF has not yet been established for the cracks experienced in large complex structures. As a first step to predict crack propagation behavior in a ship structure with very large structural redundancies, simplified SIF prediction formulas for various crack shapes were derived based on the results of the stress analysis under a non-crack condition in this study. The adequacy of the proposed method was then verified in comparison with other experimental and analysis results.

• Structural Engineering and Mechanics
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• v.72 no.1
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• pp.31-41
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• 2019

Structural integrity assessment of piping components is of paramount important for remaining life prediction, residual strength evaluation and for in-service inspection planning. For accurate prediction of these, a reliable fracture parameter is essential. One of the fracture parameters is stress intensity factor (SIF), which is generally preferred for high strength materials, can be evaluated by using linear elastic fracture mechanics principles. To employ available analytical and numerical procedures for fracture analysis of piping components, it takes considerable amount of time and effort. In view of this, an alternative approach to analytical and finite element analysis, a model based on relevance vector machine (RVM) is developed to predict SIF of part through crack of a piping component under fatigue loading. RVM is based on probabilistic approach and regression and it is established based on Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. Model for SIF prediction is developed by using MATLAB software wherein 70% of the data has been used for the development of RVM model and rest of the data is used for validation. The predicted SIF is found to be in good agreement with the corresponding analytical solution, and can be used for damage tolerant analysis of structural components.

• International Journal of Fluid Machinery and Systems
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• v.10 no.3
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• pp.254-263
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• 2017

The cavitation erosion remains an industrial issue for many applications. This paper deals with the cavitation intensity, which can be described as the fluid mechanical loading leading to cavitation damage. The estimation of this quantity is a challenging problem both in terms of modeling the cavitating flow and predicting the erosion due to cavitation. For this purpose, a numerical methodology was proposed to estimate cavitation intensity from 3D unsteady cavitating flow simulations. CFD calculations were carried out using Code_Saturne, which enables U-RANS equations resolution for a homogeneous fluid mixture using the Merkle's model, coupled to a $k-{\varepsilon}$ turbulence model with the Reboud's correction. A post-process cavitation intensity prediction model was developed based on pressure and void fraction derivatives. This model is applied on a flow around a hydrofoil using different physical (inlet velocities) and numerical (meshes and time steps) parameters. The article presents the cavitation intensity model as well as the comparison of this model with experimental results. The numerical predictions of cavitation damage are in good agreement with experimental results obtained by pitting test.

• Journal of the Korean Geophysical Society
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• v.7 no.2
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• pp.77-87
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• 2004