• Economic and Environmental Geology
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• v.44 no.2
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• pp.153-159
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• 2011

A comprehensive mechanistic model has been used to determine the flow pattern for gas-oil two-phase flow in pipes of petroleum production system. Depending on operational parameters, geometrical variables, and physical properties of the two phases, the two phases shows a specific flow patterns. For different parameters of the system, How pattern were compared for wide range of superficial velocities of oil and gas. In a variety of parameters, the inclinational angle and superficial velocities of oil and gas are the most dominant factors in determining the flow patterns for two-phase flow in pipelines. Other parameters such as pipe diameter and fluid properties have a limited effect on the change of flow patterns except for near transition. The mechanistic model is shown to be useful to determine the flow pattern in situations where either an experimental evaluation in a laboratory or reliable correlations are not available.

• Nuclear Engineering and Technology
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• v.28 no.3
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• pp.229-246
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• 1996

A mechanistic model has been developed to predict the release behavior of fission gas during steady-state irradiation of LWR UO$_2$ fuel. Under the assumption that UO$_2$ grain surface is composed of fourteen identical circular faces and grain edge bubble can be represented by a triangulated tube around the circumference of three circular grain faces, it introduces the concept of continuous formation of open grain edges tunnels that is proportional to grain edge swelling. In addition, it takes into account the interaction between the gas release from matrix to grain boundary and the reintroduction of gas atoms into the matrix by the irradiation-induced re-solution of grain face bubbles. It also treats analytically the behavior of intragranular, intergranular, and grain edge bubbles under the assumption that both intragranular and intergranular bubbles are uniform in both radius and number density. Comparison of the present model with experimental data shows that the model's prediction produces reasonable agreement for fuel with centerline temperatures of 1000 to 140$0^{\circ}C$, wide scatter band for fuel with centerline temperatures lower than 100$0^{\circ}C$, and underprediction for fuel with centerline temperatures higher than 140$0^{\circ}C$.

• Journal of Biosystems Engineering
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• v.37 no.4
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• pp.258-264
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• 2012

Purpose: This review aims at introducing 3 modeling approaches classified into 3 categories based on the purpose (estimation or prediction), structure (linear or non-linear) and phase (steady-state or dynamic-state); 1) statistical approaches, 2) kinetic modeling and 3) mechanistic modeling. We hope that this review can be a useful guide in the model-based approach of calcium metabolism as well as illustrates an application of engineering tools in studying biosystems. Background: The meaning of biosystems has been expanded, including agricultural/food system as well as biological systems like genes, cells and metabolisms. This expansion has required a useful tool for assessing the biosystems and modeling has arisen as a method that satisfies the current inquiry. To suit for the flow of the era, examining the system which is a little bit far from the traditional biosystems may be interesting issue, which can enlarge our insights and provide new ideas for prospective biosystem-researches. Herein, calcium metabolic models reviewed as an example of application of modeling approaches into the biosystems. Review: Calcium is an essential nutrient widely involved in animal and human metabolism including bone mineralization and signaling pathways. For this reason, the calcium metabolic system has been studied in various research fields of academia and industries. To study calcium metabolism, model-based system analyses have been utilized according to the purpose, subject characteristics, metabolic sites of interest, and experimental design. Either individual metabolic pathways or a whole homeostasis has been modeled in a number of studies.

• Asian-Australasian Journal of Animal Sciences
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• v.1 no.3
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• pp.149-152
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• 1988

Postweaning performances of steer from 11 to 18 months of age under intensive feedlot condition were examined in Brahman and Santa Gertudis cattle breeds which have been established in Paraguay. Fitting of growth data in each breed to an empirical growth model with non-linear least square analysis resulted in the following age(t; months) - weight(w; kg) function made out each breed: w=638.26($1-2.341e^{-0.010965t}$) for Brahman and w=716.38($1-2.365e^{-0.10741t}$) for Santa Gertrudis. The estimated mature size of Brahman steers(638 kg) was 11% lower than that of Santa Gertrudis steers(716 kg). However, slightly larger k value (rate of maturing) of Brahman steer in the mechanistic model suggested relatively earlier maturing tendency in the breed. No significant differences in dressing percentage (Brahman, 59.3%; Santa Gertrudis, 58.8%) of chilled carcass weight to live-weight were observed between breed.

• Nuclear Engineering and Technology
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• v.51 no.8
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• pp.1916-1938
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• 2019

The objective of this paper is to discuss the modeling principles of phenomena governing core degradation/melting and in-vessel melt relocation during severe accidents in light water reactors. The proposed modeling approach has been applied in the development of a new accident simulation package, COMPASS (COre Meltdown Progression Accident Simulation Software). COMPASS can be used either as a stand-alone tool to simulate in-vessel meltdown progression up to and including RPV failure, or as a component of an integrated simulation package being developed in Korea for the APR1400 reactor. Interestingly, since the emphasis in the development of COMPASS modeling framework has been on capturing generic mechanistic aspects of accident progression in light water reactors, several parts of the overall model should be useful for future accident studies of other reactor designs, both PWRs and BWRs. The issues discussed in the paper include the overall structure of the model, the rationale behind the formulation of the governing equations and the associated simplifying assumptions, as well as the methodology used to verify both the physical and numerical consistencies of the overall solver. Furthermore, the results of COMPASS validation against two experimental data sets (CORA and PHEBUS) are shown, as well as of the predicted accident progression at TMI-2 reactor.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.3
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• pp.9-19
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• 2015

Internal air temperature of greenhouse is an important variable that can be influenced by the complex interaction between outside weather and greenhouse inside climate. This paper focuses on a data-based model approach to predict internal air temperature of the greenhouse. External air temperature, solar radiation, wind speed and wind direction were measured next to an experimental greenhouse supported by the Electronics and Telecommunications Research Institute and used as input variables for the model. Internal air temperature was measured at the center of three sections of the greenhouse and used as an output variable. The proposed model consisted of a transfer function including the four input variables and tested the prediction accuracy according to the sampling interval of the input variables, the orders of model polynomials and the time delay variable. As a result, a second-order model was suitable to predict the internal air temperature having the predictable time of 20-30 minutes and average errors of less than ${\pm}1K$. Afterwards mechanistic interpretation was conducted based on the energy balance equation, and it was found that the resulting model was considered physically acceptable and satisfied the physical reality of the heat transfer phenomena in a greenhouse. The proposed data-based model approach is applicable to any input variables and is expected to be useful for predicting complex greenhouse microclimate involving environmental control systems.

• International Journal of Highway Engineering
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• v.19 no.5
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• pp.49-58
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• 2017

PURPOSES : The objective of this study is to develop a simple regression model in designing the asphalt concrete (AC) overlay thickness using the Mechanistic-empirical pavement design guide (MEPDG) program. METHODS : To establish the AC overlay design equation, multiple regression analyses were performed based on the synthetic database for AC thickness design, which was generated using the MEPDG program. The climate in Seoul city, a modified Hirsh model for determining dynamic modulus of asphalt material, and a new damaged master curve approach were used in this study. Meanwhile, the proposed rutting model developed in Seoul city was then used to calibrate the rutting model in the MEPDG program. The AC overlay design equation is a function of the total AC thickness, the ratio of AC overlay thickness and existing AC thickness, the ratio of existing AC modulus and AC overlay modulus, the subgrade condition, and the annual average daily truck traffic (AADTT). RESULTS : The regression model was verified by comparing the predicted AC thickness, the AADTT from the model and the MEPDG. The regression model shows a correlation coefficient of 0.98 in determining the AC thickness and 0.97 in determining AADTT. In addition, the data in Seoul city was used to validate the regression model. The result shows that correlation coefficient between the predicted and measured AADTT is 0.64. This indicates that the current model is more accuracy than the previous study which showed a correlation coefficient of 0.427. CONCLUSIONS:The high correlation coefficient values indicate that the regression equations can predict the AC thickness accurately.

• Molecules and Cells
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• v.44 no.7
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• pp.425-432
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• 2021

Aging is associated with functional and structural declines in organisms over time. Organisms as diverse as the nematode Caenorhabditis elegans and mammals share signaling pathways that regulate aging and lifespan. In this review, we discuss recent combinatorial approach to aging research employing C. elegans and mammalian systems that have contributed to our understanding of evolutionarily conserved aging-regulating pathways. The topics covered here include insulin/IGF-1, mechanistic target of rapamycin (mTOR), and sirtuin signaling pathways; dietary restriction; autophagy; mitochondria; and the nervous system. A combinatorial approach employing high-throughput, rapid C. elegans systems, and human model mammalian systems is likely to continue providing mechanistic insights into aging biology and will help develop therapeutics against age-associated disorders.

• Geomechanics and Engineering
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• v.17 no.4
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• pp.405-411
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• 2019

A significant influence of the particle size distribution on the resilient behaviour of granular aggregates was usually observed in laboratory tests. However, the mechanisms underlying this phenomenon were rarely reached. In this study, a mechanistic model considering particle breakage is proposed. It is found to be the combined effects of the coefficient of uniformity and the size range between maximum and minimum particle sizes that influences the resilient modulus of granular aggregates. The resilient modulus is found to undergo reduction with evolution of particle breakage by shifting the initial particle size distribution to a broader one.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.79-89
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• 2008

The pavement performance model is the most important factor to determine the pavement life in the mechanistic-empirical pavement design guide (MEPDG). As part of Korean Pavement Research Program (KPRP), the Korean Pavement Design Guide (KPDG) is currently being developed based on mechanistic-empirical principle. In this paper, the rutting prediction model of asphalt mixtures, one of the pavement performance model, has been developed using triaxial repeated loading testing data. This test was conducted on various types of asphalt mixtures for investigating the rutting characteristics by varying with the temperature and air void. The calibration process was made for the coefficients of rutting prediction model using the accelerated pavement testing data. The accuracy of prediction model can be increased when by considering the effect of individual rutting properties of materials rather than shear stresses with depths.