• Earthquakes and Structures
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• v.3 no.3_4
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• pp.473-494
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• 2012

The capacity of pipelines to resist collapse under external pressure and bending moment is a major aspect of deepwater pipeline design. Existing design codes present interaction equations that quantify pipeline capacities under such loadings, although reasonably accurate, are based on empirical data fitting of the bending strain, and assumed simplistic interaction with external pressure collapse. The rational model for collapse of deepwater pipelines, which are relatively thick with a diameter-to-thickness ratio less than 40, provides a unique theoretical basis since it is derived from first principles such as force equilibrium and compatibility equations. This paper presents the rational model methodology and compares predicted results and recently published full scale experimental data on the subject. Predictive capabilities of the rational model are shown to be excellent. The methodology is extended for the problem of pipeline collapse under point load, longitudinal bending and external pressure. Due to its rational derivation and excellent prediction capabilities, it is recommended that design codes adopt the rational model methodology.

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.2
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• pp.97-103
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• 1997

DO concentration in the aquatic system is important for the water quality management perspective. Water quality model uses available reaeration coefficient (K2) estimation equations in calculating DO, however, they might include inevitable uncertainty that the model output can be less reliable. In this study, the calibrated QUAL2E model for the Passaic River in New Jersey, U.S., was used to examine the effect of K2 estimation equation on the output DO concentration of the river. The model was run with six commonly used equations separately with all the other conditions remained same. The result showed that the output DO concentration profiles varied widely with different equations, and maximum difference was 4.96 mg/L for the same location which is unacceptably large. It implies that the development of reliable equation is required for proper water quality management. The unreliable model output can lead to a wrong decision in water quality management such as unnecessarily high or too low treatment of wastewater, which will cause serious effect on the community economically and socially in either case. Generating more reliable model output with slight investment to develop a site specific K$_2$ equation can improve the decision making process significantly and is highly recommended.

• Explosives and Blasting
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• v.22 no.1
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• pp.57-65
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• 2004

Explosive blasting in tunnel excavation produces ground vibration and air blast as its side effects, which may cause complaints from nearby residents. This study was intended to investigate the propagation characteristics of ground vibration induced by tunnel blasting and to evaluate its effects on the residential structures near the site. We have conducted field measurements for 6 blasts and acquired vibration data from 70 measuring points, some of which on positioned inside the tunnel for comparative reason. Various documentation was reviewed to determine an allowable level of peak particle velocity for the residential structures in the area and the allowable limit was set to 0.5 cm/sec. Propagation equations for peak particle velocities were derived from regression analyses using the data acquired at both the surface and the underground tunnel. Finally we proposed appropriate predictive equations for the two areas and a safe blasting criterion.

• Nutrition Research and Practice
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• v.11 no.4
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• pp.300-306
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• 2017

BACKGROUND/OBJECTIVES: The doubly labeled water (DLW) method is considered the gold standard for the measurement of total energy expenditure (TEE), which serves to estimate energy requirements. This study evaluated the accuracy of predictive dietary reference intake (DRI) equations for determining the estimated energy requirements (EER) of Korean adults by using the DLW as a reference method. SUBJECTS/METHODS: Seventy-one participants (35 men and 36 women) aged between 20 and 49 years were included in the study. The subjects' EER, calculated by using the DRI equation ($EER_{DRI}$), was compared with their TEE measured by the DLW method ($TEE_{DLW}$). RESULTS: The DRI equations for EER underestimated TEE by -36.3 kcal/day (-1.3%) in men and -104.5 kcal/day (-4.9%) in women. The percentages of accurate predictions among subjects were 77.1% in men and 62.9% in women. There was a strong linear correlation between $EER_{DRI}$ and $TEE_{DLW}$ (r = 0.783, P < 0.001 in men and r = 0.810, P < 0.001 in women). CONCLUSIONS: The present study supports the use of DRI prediction equations to determine EER in Korean adults. More studies are needed to confirm our results and to assess the validity of these equations in other population groups, including children, adolescents, and older adults.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.4
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• pp.554-559
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• 2004

The objective of the present study was to investigate the accuracy of mastitis diagnostic indicators for different dairy goat breeds. Biweekly milk samples were collected from individual half mammary gland of seven Saanen and seven Alpine dairy goats in the period of 40 to 120 days in milk. With threshold value set at 2.8 and 3.1 for Alpine and Saanen dairy goats, respectively, log (SPC) offered good sensitivity (0.89, 0.93), specificity (0.88, 0.95), positive predictive value (0.75, 0.85) and negative predictive value (0.95, 0.98) as a mastitis diagnostic tool. The correlations of log (SPC) with milk yield, log (SCC), ALP, LDH, $Na^{+}$, $K^{+}$ and EC were significant in Saanen dairy goats (p<0.05), with the highest correlation coefficient (0.653) existing between log (SPC) and log (SCC). The correlations of log (SPC) with milk yield, milk fat, milk protein, log (SCC), $Na^{+}$, $K^{+}$, EC were significant in Alpine dairy goats (p<0.05), with the highest correlation coefficient (0.416) existing between log (SPC) and log (SCC). There were different best-fit regression equations with different multiple diagnostic indicators for Saanen and Alpine dairy goats. In conclusion, different breeds of dairy goats may have to adapt different mastitis diagnostic parameters for a better diagnosis.

• Journal of Welding and Joining
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• v.28 no.4
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• pp.41-48
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• 2010

The purpose of this study is to establish the control method of the global bending distortion caused by fabrication process of hatch-cover in a container ship. In order to do it, the transitional behavior of global bending distortion in the deck of hatch-cover during fabrication process was measured by 3-dimensional measuring instrument. From the results, the principal factor controlling the global bending distortion was identified as the bending moment associated with the longitudinal shrinkage force and transverse shrinkage caused by welding and flame heating and the change of the centroid axis of hatch-cover in each fabrication process. Therefore, in this study, with the predictive equations of the longitudinal shrinkage force and transverse shrinkage caused by welding and flame heating and the simplified thermo elastic method, the predictive method for the global bending distortion was established and verified by comparing with the measured result. Based on the results, the amount of reverse bending distortion of main stiffeners was determined to prevent the global bending distortion of hatch-cover.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.2
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• pp.216-223
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• 1996

The active power factor control AC/DC converter needs a current loop compensator to obtain better dynamic characteristics and power factor performance, but the optimal design of a current loop compensator is difficult because the AC/DC converter is a nonlinear system having periodically varying poles and zeros. The predictive current control scheme generates a control input using the dynamic equations of the AC/DC converter so that the dynamic of the AC/DC converter is included in the controller and the necessary bandwidth and the gain characteristics of the current control loop are satisfied. And as a result, a compensator becomes unnecessary and the current loop shows the improved current loop characteristics. In this paper, a power factor controller without current loop compensator by adopting a predictive current control scheme is designed and the designed power factor controller is modelled by using a small signal perturbation modelling technique, and simulated to investigate its small signal characteristics. A 200 W power factor control AC/DC converter is built to verify the effectiveness of the proposed power factor controller.

• Journal of the Korean Society for Heat Treatment
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• v.37 no.3
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• pp.103-113
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• 2024

Martensite volume fraction significantly affects the mechanical properties of alloy steels. Martensite start temperature (M_s), transformation temperature for martensite 50 vol.% (M₅₀), and transformation temperature for martensite 90 vol.% (M₉₀) are important transformation temperatures to control the martensite phase fraction. Several researchers proposed empirical equations and machine learning models to predict the Ms temperature. These numerical approaches can easily predict the Ms temperature without additional experiment and cost. However, to control martensite phase fraction more precisely, we need to reduce prediction error of the Ms model and propose prediction models for other martensite transformation temperatures (M₅₀, M₉₀). In the present study, machine learning model was applied to suggest the predictive model for the Ms, M50, M90 temperatures. To explain prediction mechanisms and suggest feature importance on martensite transformation temperature of machine learning models, the explainable artificial intelligence (XAI) is employed. Random forest regression (RFR) showed the best performance for predicting the Ms, M50, M90 temperatures using different machine learning models. The feature importance was proposed and the prediction mechanisms were discussed by XAI.

• Food Science of Animal Resources
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• v.35 no.1
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• pp.108-113
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• 2015

The purpose of this study was to develop predictive models for the growth of Listeria monocytogenes in pork Bulgogi at various storage temperatures. A two-strain mixture of L. monocytogenes (ATCC 15313 and isolated from pork Bulgogi) was inoculated on pork Bulgogi at 3 Log CFU/g. L. monocytogenes strains were enumerated using general plating method on Listeria selective medium. The inoculated samples were stored at 5, 15, and $25^{\circ}C$ for primary models. Primary models were developed using the Baranyi model equations, and the maximum specific growth rate was shown to be dependent on storage temperature. A secondary model of growth rate as a function of storage temperature was also developed. As the storage temperature increased, the lag time (LT) values decreased dramatically and the specific growth rate of L. monocytogenes increased. The mathematically predicted growth parameters were evaluated based on the modified bias factor ($B_f$), accuracy factor ($A_f$), root mean square error (RMSE), coefficient of determination ($R^2$), and relative errors (RE). These values indicated that the developed models were reliably able to predict the growth of L. monocytogenes in pork Bulgogi. Hence, the predictive models may be used to assess microbiological hygiene in the meat supply chain as a function of storage temperature.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.1 no.1
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• pp.69-76
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• 1981

The predictive equations for reservoir sedimentation rate now in use are extensively reviewed, and the equation of multiple regression type, in which the reservoir sedimentation rate is related with the watershed area and the trap-efficiency, is proposed based on the 113 irrigation reservoir resurvey data. The predictive relation so obtained proved to be a reasonable measure for the estimation of reservoir sedimentation rate. The relationship of sediment yield with the watershed area and with the reservoir trap efficiency is also analyzed. The variations of sedimentation rate and of the annual reservoir capacity loss rate was shown to heavily depend on the trap-efficiency of a reservoir. Besides, the effect of sedimentation on stream channels is confirmed and quantified based on the predictive equation derived in the present study.