• Journal of Bio-Environment Control
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• v.27 no.4
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• pp.424-430
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• 2018

This study was carried out to estimate growth characteristics of hot pepper and to develop predicted models for the production yield based on the growth parameters and climatic elements. Sigmoid regressions for the prediction of growth parameters in terms of fresh and dry weight, plant height, and leaf area were designed with growing degree days (GDD). The biomass and leaf expansion of hot pepper plants were rapidly increased when 1,000 and 941 GDD. The relative growth rate (RGR) of hot pepper based on dry weight was formulated by Gaussian's equation RGR $(dry\;weight)=0.0562+0.0004{\times}DAT-0.00000557{\times}DAT^2$ and the yields of fresh and dry hot pepper at the 112 days after transplanting were estimated 1,387 and 291 kg/10a, respectively. Results indicated that the growth and yield of hot pepper were predicted by potential growth model under plastic tunnel cultivation. Thus, those models need to calibration and validation to estimate the efficacy of prediction yield in hot pepper using supplement a predicting model, which was based on the parameters and climatic elements.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.432-438
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• 2011

The purpose of the present thesis is to develop bankruptcy prediction models capable of being applied to the Korean construction industry and to deduce an optimal model through comparative evaluation of final developed models. A study population was selected as general contractors in the Korean construction industry. In order to ease the sample securing and reliability of data, it was limited to general contractors receiving external audit from the government. The study samples are divided into a bankrupt company group and a non-bankrupt company group. The bankruptcy, insolvency, declaration of insolvency, workout and corporate reorganization were used as selection criteria of a bankrupt company. A company that is not included in the selection criteria of the bankrupt company group was selected as a non-bankrupt company. Accordingly, the study sample is composed of a total of 112 samples and is composed of 48 bankrupt companies and 64 non-bankrupt companies. A financial ratio was used as early predictors for development of an estimation model. A total of 90 financial ratios were used and were divided into growth, profitability, productivity and added value. The MDA (Multivariate Discriminant Analysis) model and BLRA (Binary Logistic Regression Analysis) model were used for development of bankruptcy prediction models. The MDA model is an analysis method often used in the past bankruptcy prediction literature, and the BLRA is an analysis method capable of avoiding equal variance assumption. The stepwise (MDA) and forward stepwise method (BLRA) were used for selection of predictor variables in case of model construction. Twenty two variables were finally used in MDA and BLRA models according to timing of bankruptcy. The ROC-Curve Analysis and Classification Analysis were used for analysis of prediction performance of estimation models. The correct classification rate of an individual bankruptcy prediction model is as follows: 1) one year ago before the event of bankruptcy (MDA: 83.04%, BLRA: 93.75%); 2) two years ago before the event of bankruptcy (MDA: 77.68%, BLRA: 78.57%); 3) 3 years ago before the event of bankruptcy (MDA: 84.82%, BLRA: 91.96%). The AUC (Area Under Curve) of an individual bankruptcy prediction model is as follows. : 1) one year ago before the event of bankruptcy (MDA: 0.933, BLRA: 0.978); 2) two years ago before the event of bankruptcy (MDA: 0.852, BLRA: 0.875); 3) 3 years ago before the event of bankruptcy (MDA: 0.938, BLRA: 0.975). As a result of the present research, accuracy of the BLRA model is higher than the MDA model and its prediction performance is improved.

• Journal of the Society of Disaster Information
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• v.8 no.3
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• pp.234-241
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• 2012

The main objective of this research is to calibrate the performance prediction models for the growth of fatigue cracking in multi-layered asphalt concrete pavement systems. However, the calibration factors are dependent upon the prediction model, testing method, and the laboratory loading history. A detailed study on the field data has revealed that the performance of flexible pavements is affected by both the traffic loading and the environmental cycling which is related to the age of the pavements. Thus, a composite indicator was developed in this study which utilizes both the traffic and the age information with appropriate weighting factors. Using the proposed fatigue performance model the calibration factors were also estimated through the comparisons between the field performances on fatigue cracking and the laboratory-based fatigue life.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.132-144
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• 2023

European and American countries are actively promoting eco-friendly cars to reduce exhaust emissions from internal combustion engines. In Korea, the "4th Basic Plan for Eco-Friendly Vehicles" aims to promote eco-friendly cars by improving charging infrastructure, expanding incentive systems, and targeting the supply of 1.13 million eco-friendly cars by 2025. As rapid growth in the number of electric vehicles sold is expected, estimates are required of this growth and corresponding power demands. In this study, the authors used a growth model to predict future growth in the electric vehicle market and a previously derived electricity generation model to estimate corresponding power demands up to 2036, the target year of the "10th Basic Plan for Power Supply and Demand". The results obtained provide useful basic research data for future electric vehicle infrastructure planning.

• Journal of Korean Society of Forest Science
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• v.101 no.2
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• pp.266-278
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• 2012

The objective of this study was developing dynamic stand growth model to predict diameter at breast height (DBH) growth by thinning intensity and cycle for major tree species of South Korea. The yield table, one of static stand growth models, constructed by Korea Forest Service was employed to prepare dynamic stand growth models for 8 tree species. In the process of model development, the thinning type was designated to thinning from below and equations for predicting the DBH change after thinning by different intensities was generated. In addition, stand density (N/ha), age and site index were adopted as explanatory variables for DBH prediction model. Thereafter, using the model, DBH growth under various silvicuture through integrating such equations considering thinning intensities, and cycles. The dynamic stand growth model of DBH developed in this study can provide understanding of effectiveness in forest growth and growing stock when thinning practice is performed in forest. Furthermore, results of this study is also applicable to quantitatively assess the carbon storage sequestration capability.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.8 s.179
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• pp.2074-2082
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• 2000

In this study, to investigate and to predict the crack growth behavior under variable amplitude loading, crack growth tests are conducted on 7075-T6 aluminum alloy. The loading wave forms are generated by normal random number generator. All wave forms have same average and RMS(root mean square) value, but different standard deviation, which is to vary the maximum load in each wave. The modified Forman's equation is used as crack growth equation. Using the retardation coefficient D defined in previous study, the load interaction effect is considered. The variability in crack growth process is described by the random variable Z which was obtained from crack growth tests under constant amplitude loading in previous work. From these, a statistical model is developed. The curves predicted by the proposed model well describe the crack growth behavior under variable amplitude loading and agree with experimental data. In addition, this model well predicts the variability in crack growth process under variable amplitude loading.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.8
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• pp.818-823
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• 2012

In order to predict necking behaviour of aluminium sheets, a crystal plasticity model is introduced in the finite element analysis of tensile test. Due to the computational limits of time and memory, only a small part of tensile specimen is subjected to the analysis. Grains having different orientations are subjected to numerical tensile tests and each grain is discretized by many elements. In order to predict the sudden drop of load carrying capacity after necking, a well-known Cockcroft-Latham damage model is introduced. The mismatch of grain orientation causes stress concentration at several points and damage is evolved at these points. This phenomenon is similar to void nucleation. In the same way, void growth and void coalescence behaviours are well predicted in the analysis. For the comparison of prediction capability of necking, same model is subjected to finite element analysis using uniform material properties of polycrystal with and without damage. As a result, it is shown that the crystal plasticity model can be used in prediction of necking and fracture behavior of materials accurately.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.3
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• pp.165-175
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• 2006

To analyze the deformation and failure of slopes, generally, two types of model, Polynomial model and Growth model, are applied. These two models are focused on the behavior of the slope by time. Therefore, this research is more focused on predicting of slope failure than analyzing the slope behavior by time. Generally, Growth model is used to analyze the soil slope, to the contrary, Polynomial model is used for rock slope. However, 3-degree polynomial($y=ax^3+bx^2+cx+d$) is suggested to combine two models in this research. The main trait of this model is having an asymptote. The fields to adopt this model are Gosujae Danyang(soil slope) and Youngduk slope(rock slope), which are the cut-slope near national road. Data from Gosujae are shown the failure traits of soil slope, to the contrary, those of Youngduk slope are shown the traits of rock slope. From the real-time monitoring data of the slope, 3-degree polynomial is proved as excellent system to analyze the failure and behavior of slope. In case of Polynomial model, even if the order of polynomials is increased, the $R^2$ value and shape of the curve-fitted graph is almost the same.

• Atmosphere
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• v.25 no.1
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• pp.1-18
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• 2015

The most objective way to overcome the limitation of numerical weather prediction model is to represent the uncertainty of prediction by introducing probabilistic forecast. The uncertainty of the numerical weather prediction system developed due to the parameterization of unresolved scale motions and the energy losses from the sub-scale physical processes. In this study, we focused on the growth of model errors. We performed ensemble forecast to represent model uncertainty. By employing the multi-physics scheme (PHYS) and the stochastic kinetic energy backscatter scheme (SKEBS) in simulating typhoon Rusa (2002), we assessed the performance level of the two schemes. The both schemes produced better results than the control run did in the ensemble mean forecast of the track. The results using PHYS improved by 28% and those based on SKEBS did by 7%. Both of the ensemble mean errors of the both schemes increased rapidly at the forecast time 84 hrs. The both ensemble spreads increased gradually during integration. The results based on SKEBS represented model errors very well during the forecast time of 96 hrs. After the period, it produced an under-dispersive pattern. The simulation based on PHYS overestimated the ensemble mean error during integration and represented the real situation well at the forecast time of 120 hrs. The displacement speed of the typhoon based on PHYS was closest to the best track, especially after landfall. In the sensitivity tests of the model uncertainty of SKEBS, ensemble mean forecast was sensitive to the physics parameterization. By adjusting the forcing parameter of SKEBS, the default experiment improved in the ensemble spread, ensemble mean errors, and moving speed.

• Journal of computational fluids engineering
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• v.21 no.2
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• pp.12-24
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• 2016

The standard ${\kappa}-{\varepsilon}$ and realizable ${\kappa}-{\varepsilon}$ models are adopted to improve the prediction performance on the recirculating flow. In this paper, the backward facing step flows are used to assess the prediction performance of the recirculation zone. The model constants of turbulence model are obtained by the experimental results and they have a different value according to the flow. In the case of an isotropic flow situation, decaying of turbulent kinetic energy should follow a power law behavior. In accordance with the power law, the coefficients for the dissipation rate of turbulent kinetic energy are not universal. Also, the other coefficients as well as the dissipation coefficient are not constant. As a result, a suitable coefficients can be varied according to each of the flow. The changes of flow over the backward facing step in accordance with model constants of the ${\kappa}-{\varepsilon}$ models show that the reattachment length is dependent on the growth rate(${\lambda}$) and the ${\kappa}-{\varepsilon}$ models can be improved the prediction performance by changing the model constants about the recirculating flow. In addition, it was investigated for the curvature correction effect of the ${\kappa}-{\varepsilon}$ models in the recirculating flow. Overall, the curvature corrected ${\kappa}-{\varepsilon}$ models showed an excellent prediction performance.