• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.53-61
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• 2021

This paper is a preliminary study for the development of a drone for inspection inside a boiler in a thermal power plant, which is a high-temperature environment, and validated whether the drone can fly normally through a high-temperature environment simulation using AirSim. In a high-temperature flight environment, the aerodynamic characteristics of the air density and viscosity are different from room temperature, and the flight performance of the drone is also changed accordingly. Therefore, in order to confirm the change of the aerodynamic characteristics of the propeller according to the temperature change, the propeller analysis and thrust test through JBLADE, and the operation characteristics prediction through the electric propulsion system performance prediction model were performed. In addition, the analysis and performance prediction results were applied to AirSim for simulation, and the aircraft redesigned through the analysis of the results. As a result of the redesign, it was confirmed that about 65% of the maximum power used before the redesign was reduced to 52% to obtain the necessary thrust when hovering in an environment of 80℃.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4102-4111
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• 2023

In order to better perform thermal hydraulic calculation and analysis of supercritical water reactor, based on the experimental data of supercritical water, the model training and predictive analysis of the heat transfer coefficient of supercritical water were carried out by using the support vector machine (SVM) algorithm. The changes in the prediction accuracy of the supercritical water heat transfer coefficient are analyzed by the changes of the regularization penalty parameter C, the slack variable epsilon and the Gaussian kernel function parameter gamma. The predicted value of the SVM model obtained after parameter optimization and the actual experimental test data are analyzed for data verification. The research results show that: the normalization of the data has a great influence on the prediction results. The slack variable has a relatively small influence on the accuracy change range of the predicted heat transfer coefficient. The change of gamma has the greatest impact on the accuracy of the heat transfer coefficient. Compared with the calculation results of traditional empirical formula methods, the trained algorithm model using SVM has smaller average error and standard deviations. Using the SVM trained algorithm model, the heat transfer coefficient of supercritical water can be effectively predicted and analyzed.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.2
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• pp.71-76
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• 2003

A virtual machine tool (VMT) is presented in this two-part paper. In Part 1, the analytical foundation for a virtual machining system is developed, which is envisioned as the foundation for a comprehensive simulation environment capable of predicting the outcome of cutting processes. The VHT system undergoes "pseudo-real machining", before actual cutting with a CNC machine tool takes place, to provide the proper cutting conditions for process planners and to compensate or control the machining process in terms of the productivity and attributes of the products. The attributes can be characterized by the machined surface error, dimensional accuracy, roughness, integrity, and so forth. The main components of the VMT are the cutting process, application, thermal behavior, and feed drive modules. In Part 1, the cutting process module is presented. When verified experimentally, the proposed models gave significantly better prediction results than any other methods. In Part 2 of this paper, the thermal behavior and feed drive modules are developed, and the models are integrated into a comprehensive software environment.vironment.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.74-79
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• 2001

In this two-part paper, a virtual machine tool (VMT) is presented. In part 1, the analytical foundation of a virtual machining system, envisioned as the foundation for a comprehensive simulation environment capable of predicting the outcome of cutting processes, is developed. The VMT system purposes to experience the pseudo-real machining before real cutting with a CNC machine tool, to provide the proper cutting conditions for process planners, and to compensate or control the machining process in terms of the productivity and attributes of products. The attributes can be characterized with the machined surface error, dimensional accuracy, roughness, integrity and so forth. The main components of the VMT are cutting process, application, thermal behavior and feed drive modules. In part 1, the cutting process module is presented. The proposed models were verified experimentally and gave significantly better prediction results than any other method. The thermal behavior and feed drive modules are developed in part 2 paper. The developed models are integrated as a comprehensive software environment in part 2 paper.

• KIEAE Journal
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• v.17 no.4
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• pp.83-88
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• 2017

Purpose: The objective of this study is to develop a predictive model for calculating the amount of cooling load for the different setback temperatures during the setback period. An artificial neural network (ANN) is applied as a predictive model. The predictive model is designed to be employed in the control algorithm, in which the amount of cooling load for the different setback temperature is compared and works as a determinant for finding the most energy-efficient optimal setback temperature. Method: Three major steps were conducted for proposing the ANN-based predictive model - i) initial model development, ii) model optimization, and iii) performance evaluation. Result:The proposed model proved its prediction accuracy with the lower coefficient of variation of the root mean square errors (CVRMSEs) of the simulated results (Mi) and the predicted results (Si) under generally accepted levels. In conclusion, the ANN model presented its applicability to the thermal control algorithm for setting up the most energy-efficient setback temperature.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.3
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• pp.334-343
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• 2019

The Al-Zour coastal area, located in southern Kuwait, is a region of concentrated industrial water use, seawater intake, and the outfall of existing power plants. The Al-Zour LNG import facility project is ongoing and there are two issues regarding the seawater temperature in this area that must be considered: variations in water temperature under local meteorology and an increase in water temperature due to the expansion of the thermal discharge of expanded power plant. MIKE 3 model was applied to simulate the water temperature from June to July, based on re-analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and the thermal discharge input from adjacent power plants. The annual water temperatures of two candidate locations of the seawater intake for the Al-Zour LNG re-gasification facility were measured in 2017 and compared to the numerical results. It was determined that the daily seawater temperature is mainly affected by thermal plume dispersion oscillating with the phase of the tidal currents. The regional meteorological conditions such as air temperature and tidal currents, also contributed a great deal to the prediction of seawater temperature.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.5 s.176
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• pp.1343-1351
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• 2000

Thermally induced errors have been significant factors affecting the machine tool accuracy. In this paper, the spindle thermal error has been focused, where the 5 degree of freedom thermal error components are considered. An effective measurement system has been devised for the 5 DOF thermal errors, consisting of gap sensors and thermocouples around the micro-computer interfaced environment. Several thermal error modeling techniques are also implemented for the thermal error prediction: multiple linear regression, neural network and system identification methods, etc. The performance of the thermal error modeling techniques is evaluated and compared, giving the system identification method as the optimum model having the least deviation. The developed system for the thermal error measurement and modeling was practically applied to a CNC machining center, and the spindle thermal errors were effectively compensated around the micro computer-machine tool interfaced networks. The machine tool accuracy was improved about 4-5 times typically.

• KIEAE Journal
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• v.15 no.4
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• pp.105-110
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• 2015

Purpose: This study aimed at finding the optimal input variables of the artificial neural network-based predictive model for the optimal controls of the indoor temperature environment. By applying the optimal input variables to the predictive model, the required time for restoring the current indoor temperature during the setback period to the normal setpoint temperature can be more precisely calculated for the cooling season. The precise prediction results will support the advanced operation of the cooling system to condition the indoor temperature comfortably in a more energy-efficient manner. Method: Two major steps employing the numerical computer simulation method were conducted for developing an ANN model and finding the optimal input variables. In the first process, the initial ANN model was intuitively determined to have input neurons that seemed to have a relationship with the output neuron. The second process was conducted for finding the statistical relationship between the initial input variables and output variable. Result: Based on the statistical analysis, the optimal input variables were determined.

• Journal of the Ergonomics Society of Korea
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• v.19 no.2
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• pp.63-74
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• 2000

This paper is to clarify a thermal physiological index that can account for the effects of local thermal environment. For this purpose two young female subjects exposing themselves to the above while sitting on a chair, sitting on the floor and lying on the floor were measured. These three representative postures accompanied the different contact surface areas, thereby the heat conduction rate between the floor and subject was quantitatively measured for each posture. It made the present study deal with the effect of heat conduction concerning the modified mean skin temperature and finally propose new weighting coefficients for the mean skin temperature calculation based on the Hardy & DuBois' formulas. In order to verify the proposed model, the experiment was carried out using a floor heating system. The comparison between the experimental result and prediction revealed that the proposed model should be about 10% more accurate than the conventional one in the case of lying on the floor which the heat conduction effect becomes important.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.81-98
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• 2024

This study analyzed the impact of urban spatial factors on the thermal environment. The personal thermal sensation was set as the unit of thermal environment to analyze its correlation with environmental factors. To collect data on personal thermal sensation, Living Lab was applied, allowing citizens to record their thermal sensation and measure the temperature. Based on the input points of the collected personal thermal sensation, nearby urban spatial elements were collected to build a dataset for statistical analysis. Logistic regression analysis was conducted to analyze the impact of each factor on personal thermal sensation. The analysis results indicate that the temperature is influenced by the surrounding spatial environment, showing a negative correlation with building height, greenery rate, and road rate, and a positive correlation with sky view factor. Furthermore, the road rate, sky view factor, and greenery rate, in that order, had a strong impact on perceived heat. The results of this study are expected to be utilized as basic data for assessing the thermal environment to prepare local thermal environment measures in response to climate change.