• Nuclear Engineering and Technology
• /
• v.55 no.10
• /
• pp.3860-3865
• /
• 2023

A metallic microcell UO₂ pellet has a microstructure where a metal wall is connected to overcome the low thermal conductivity of the UO₂ fuel pellet. It has been verified that metallic microcell fuel pellets provide an impressive reduction of the fuel centerline temperature through a Halden irradiation test. However, it is difficult to predict the effective thermal conductivity of these pellets and researchers have had to rely on measurement and use of the finite element method. In this study, we designed a unit microcell model using a thermal resistance circuit to calculate the effective thermal conductivity on the basis of the microstructure characteristics by using the aspect ratio and compared the results with those of reported metallic UO₂ microcell pellets. In particular, using the thermal conductivity calculated by our model, the fuel centerline temperature of Cr microcell pellets on the 5th day of the Halden irradiation test was predicted within 6% error from the measured value.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.11 no.6
• /
• pp.904-912
• /
• 1987

The main mode of heat transfer of combustion gases at high temperature is thermal radiation of nonluminous gases, CO$_{2}$ and H$_{2}$O. Therefore the information of the emissivities of CO$_{2}$ and H$_{2}$O would be very important in the thermal performance analysis of furnace. In this study, an exponential model for the emissivities of CO$_{2}$ and H$_{2}$O was derived as function of P$_{g}$L and polynomial of reciprocal of temperature. Error analysis between the calculated values from present model and the valued of Hottel Chart was performed over temperature range of 1000-5000 R and a partial-pressure-length product range of 0.003 to 20 ft-atm. For CO$_{2}$ gray gas, the error percent between the calculated values and the values from Hottel Chart was distributed within 2.5% in case of using a polynomial in 1/T of degree 4. For H$_{2}$O gray gas, the model has an error range of 0 to 2.5% in case of using a polynomial in 1/T of degree 3.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.12 no.5
• /
• pp.9-15
• /
• 2013

Roll-to-roll printing technology has lately become a subject of special interests in the field of printed electronics. Since this technology has the advantage that continuous and mass production is possible. And for high precision register control is required in multi-layer printing to produce the electronic devices, this is one of the most important technologies in roll-to-roll printing technology. Register error could be generated by various reasons like eccentricity of roll and thermal deformation due to temperature variation in drying section. In this study, the effect of tension variation on the register was analyzed. The results of these analyses show that it is essential to consider the tension disturbance which is generated by the change of temperature in drying section, and conventional register model has limitation to estimate the register error. In order to overcome the limitation of the register model, advanced register model based on the SI process was developed. Also, the performance of the developed model was verified experimentally.

• Nuclear Engineering and Technology
• /
• v.54 no.11
• /
• pp.4322-4328
• /
• 2022

The two-fluid model is widely used to describe two-phase flows in complex systems such as nuclear reactors. Although the two-phase flow was successfully simulated, the standard two-fluid model suffers from an ill-posed nature. There are several remedies for the ill-posedness of the one-dimensional (1D) two-fluid model; among those, artificial viscosity is the focus of this study. Some previous works added artificial diffusion terms to both mass and momentum equations to render the two-fluid model well-posed and demonstrated that this method provided a numerically converging model. However, they did not consider mass conservation, which is crucial for analyzing a closed reactor system. In fact, the total mass is not conserved in the previous models. This study improves the artificial viscosity model such that the 1D incompressible two-fluid model is well-posed, and the total mass is conserved. The water faucet and Kelvin-Helmholtz instability flows were simulated to test the effect of the proposed artificial viscosity model. The results indicate that the proposed artificial viscosity model effectively remedies the ill-posedness of the two-fluid model while maintaining a negligible total mass error.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.2 s.95
• /
• pp.201-210
• /
• 1999

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric and thermal errors of the machine tools. Therefore, a key requirement for improving te machining accuracy and product quality is to reduce the geometric and thermal errors of machine tools. This study models geometric error for error analysis and develops on-machine measurement system by which the volumetric erors are measured. The geometric error is modeled using form shaping function(FSF) which is defined as the mathematical relationship between form shaping motion of machine tool and machined surface. The constant terms included in the error model are found from the measurement results of on-machine measurement system. The developed on-machine measurement system consists of the spherical ball artifact (SBA), the touch probe unit with a star type stylus, the thermal data logger and the personal computer. Experiments, performed with the developed measurement system, show that the system provides a high measuring accuracy, with repeatability of ${\pm}2{\mu}m$ in X, Y and Z directions.

• Journal of Korean Association for Spatial Structures
• /
• v.23 no.4
• /
• pp.81-88
• /
• 2023

Numerous factors contribute to the deterioration of reinforced concrete structures. Elevated temperatures significantly alter the composition of the concrete ingredients, consequently diminishing the concrete's strength properties. With the escalation of global CO2 levels, the carbonation of concrete structures has emerged as a critical challenge, substantially affecting concrete durability research. Assessing and predicting concrete degradation due to thermal effects and carbonation are crucial yet intricate tasks. To address this, multiple prediction models for concrete carbonation and compressive strength under thermal impact have been developed. This study employs seven machine learning algorithms-specifically, multiple linear regression, decision trees, random forest, support vector machines, k-nearest neighbors, artificial neural networks, and extreme gradient boosting algorithms-to formulate predictive models for concrete carbonation and thermal impact. Two distinct datasets, derived from reported experimental studies, were utilized for training these predictive models. Performance evaluation relied on metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analytical outcomes demonstrate that neural networks and extreme gradient boosting algorithms outshine the remaining five machine learning approaches, showcasing outstanding predictive performance for concrete carbonation and thermal effect modeling.

• 한국신재생에너지학회:학술대회논문집
• /
• 2007.11a
• /
• pp.550-554
• /
• 2007

A one-dimensional heat transfer model coupled with parameter estimation is developed in this study to predict the effective thermal conductivities of soil formation and borehole resistances from in situ field test data. In this application a new method of using initial ignoring time(IIT) obtained from error estimation is tried and turned out to be successful in determining soil thermal conductivities. The validity of this model is accomplished through comparison of the predicted temperature profiles of the model with the data from laboratory scale experimental setting. Eleven test boreholes were constructed in Ochang, Chungcheong Buk Do, and thermal response test was carried out with each borehole. The results of the in situ tests were analyzed with our 1-D numerical model and compared with the results of line source method. The comparison shows that the thermal properties from line source method is a little lower (${\sim}95%$)than those from numerical method. The reason of such result seems to be the lower thermal conductivity of grout material, which is not counted in line source method.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.24 no.6
• /
• pp.428-437
• /
• 2019

Analytical thermal models based on average convection heat transfer are frequently used for the design and selection of forced air-cooled plate fin heat sinks. In this paper, a convection heat transfer model within a ±10% margin of error was presented through experimental investigation. Five types of heat sinks with inlet widths of 1.7-6.8 mm were tested at 50-160 W heat sources to derive and verify the model. Causes of error between the experiment and analytical thermal model were analyzed and listed to design the heat sink. Using proposed method and the lists to be considered in the paper, a quick and accurate heat sink design of the power-conversion system is expected.

• Geomechanics and Engineering
• /
• v.10 no.1
• /
• pp.49-57
• /
• 2016

The high permeability-high strength concrete belongs to the typical of porous materials. It is mainly used in underground engineering for cold area, it can act the role of heat preservation, also to be the bailing and buffer layer. In order to establish a suitable model to predict the thermal conductivity and directly applied for engineering, according to the structure characteristics, the thermal conductivity predicting model was built by resistance network model of parallel three-phase medium. For the selected geometric and physical cell model, the thermal conductivity forecast model can be set up with aggregate particle size and mixture ratio directly. Comparing with the experimental data and classic model, the prediction model could reflect the mixture ratio intuitively. When the experimental and calculating data are contrasted, the value of experiment is slightly higher than predicting, and the average relative error is about 6.6%. If the material can be used in underground engineering instead by the commonly insulation material, it can achieve the basic requirements to be the heat insulation material as well.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.3 no.1
• /
• pp.7-14
• /
• 2004

Machining error is defined the normal distance between designed surface and actual tool path with tool deflection. This is inevitably caused by the tool deflection, tool wear, thermal effect and machine tool errors and so on. Among these factors, tool deflection is usually known as the most significant factor of machining error. Tool deflection problem is analyzed using Instantaneous horizontal cutting forces. The high quality and precision of machining products are required in finishing. In order to achieve these purposes, it is necessary work that decrease the machining error. This paper presents a study on the machining error caused by the tool deflection in ball end milling of 2 dimensional surface. Tool deflection model and simple machining error prediction model are described. This model is checked the validity with machining experiments of 2 dimensional surface. These results may be used to decrease machining error and tool path decision.