• Journal of Aerospace System Engineering
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• v.13 no.3
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• pp.78-86
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• 2019

This paper describes the stiffness optimization of the torsion spring hinge of the large SAR antenna considering the deployment performance. A large SAR antenna is folded in a launch environment and then unfolded when performing a mission in orbit. Under these conditions, it is very important to find the proper stiffness of the torsion spring hinge so that the antenna panels can be deployed with minimal impact in a given time. If the torsion spring stiffness is high, a large impact load at the time of full deployment damages the structure. If it is weak, it cannot guarantee full deployment due to the deployment resistance. A multi-body dynamics analysis model was developed to solve this problem using RecurDyn and the development performance were predicted in terms of: development time, latching force, and torque margin through deployment analysis. In order to find the optimum torsion spring stiffness, the deployment performance was approximated by the response surface method (RSM) and the optimal design was performed to derive the appropriate stiffness value of the rotating springs.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.1
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• pp.17-27
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• 2019

In this paper, we study the applicability of Tuned Mass Damper(TMD) to improve seismic performance of piping system under earthquake loading. For this purpose, a mode analysis of the target pipeline is performed, and TMD installation locations are selected as important modes with relatively large mass participation ratio in each direction. In order to design the TMD at selected positions, each corresponding mode is replaced with a SDOF damped model, and accordingly the corresponding pipeline is converted into a 2-DOF system by considering the TMD as a SDOF damped model. Then, optimal design values of the TMD, which can minimize the dynamic amplification factor of the transformed 2-DOF system, are derived through GA optimization method. The proposed TMD design values are applied to the pipeline numerical model to analyze seismic performance with and without TMD installation. As a result of numerical analyses, it is confirmed that the directional acceleration responses, the maximum normal stresses and directional reaction forces of the pipeline system are reduced, quite a lot. The results of this study are expected to be used as basic information with respect to the improvement of the seismic performance of the piping system in the future.

• Applied Chemistry for Engineering
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• v.29 no.6
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• pp.746-752
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• 2018

In this study, an optimized process for the waste cooking oil based biodiesel production using microwave energy was designed by using Box-Behnken design model. The process variables were chosen as a mole ratio of the methanol to oil, microwave power, and reaction time. Fatty acid methyl ester (FAME) content was then measured. Through the results of basic experiments, the range of optimum operation variables for the Box-Behnken design model, such as the methanol/oil mole ratio and reaction time, were set as between 8 to 10 and between 4 to 6 min, respectively. Ranges of the microwave power were set as from 8 to 12 W/g for 1.30 mg of KOH/g, acid value, while from 10 to 14 W/g for 2.00 mg of KOH/g, acid value. The optimum methanol/oil mole ratio, microwave power, and reaction time were reduced to 7.58, 10.26 W/g, and 5.1 min, respectively, for 1.30 mg KOH/g of acid value. Also, the optimum methanol/oil mole ratio, microwave power, and reaction time were 7.78, 12.18 W/g, and 5.1 min, respectively, for 2.00 mg KOH/g of acid value. Predicted FAME contents were 98.4% and 96.3%, with error rates of less than 0.3%. Therefore, when the optimized process of biodiesel production using microwave energy was applied to the Box-Behnken design model, the low error rate could be obtained.

• Applied Chemistry for Engineering
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• v.30 no.3
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• pp.337-344
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• 2019

In this study, an antioxidant was extracted from Lonicera japonica and Sophora japonica L, which was optimized by using the central composite design (CDD) model of response surface methodology (RSM). The response value of CDC model establishes the extraction yield and the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity. The extraction time, volume ratio of ethanol/ultrapure water, and extraction temperature were selected as quantitative factors. According to the result of CDC, optimal extraction conditions of Lonicera japonica were as follows; the extraction time of 2.08 h, volume ratio of ethanol/ultrapure water of 41.53 vol.%, and extraction temperature of $55.08^{\circ}C$. At these conditions the expected results indicated that the yield and DPPH radical scavenging activity were estimated as 37.88 wt% and 40.37%, respectively. On the other hand, optimal extraction conditions of Sophora japonica L. could be found as the extraction time of 2.13 h, volume ratio of ethanol/ultrapure water of 62.89 vol.%, and temperature of $50.42^{\circ}C$. Under the conditions, the (possible) maximum values of yield and DPPH radical scavenging activity were found as 35.43 wt% and 55.7%, respectively.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.209-218
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• 2021

First principle-based modeling studies have been performed to improve the heat exchange efficiency of ORV and optimize operation, but the heat transfer coefficient of ORV is an irregular system according to time and location, and it undergoes a complex modeling process. In this study, FNN, LSTM, and AutoML-based modeling were performed to confirm the effectiveness of data-based modeling for complex systems. The prediction accuracy indicated high performance in the order of LSTM > AutoML > FNN in MSE. The performance of AutoML, an automatic design method for machine learning models, was superior to developed FNN, and the total time required for model development was 1/15 compared to LSTM, showing the possibility of using AutoML. The prediction of NG and seawater discharged temperatures using LSTM and AutoML showed an error of less than 0.5K. Using the predictive model, real-time optimization of the amount of LNG vaporized that can be processed using ORV in winter is performed, confirming that up to 23.5% of LNG can be additionally processed, and an ORV optimal operation guideline based on the developed dynamic prediction model was presented.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.25-33
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• 2021

With the development of machine learning techniques, various types of data such as vibration, temperature, and flow rate can be used to detect and diagnose abnormalities in machine conditions. In particular, in the field of the state monitoring of rotating machines, the fault diagnosis of machines using vibration data has long been carried out, and the methods are also very diverse. In this study, an experiment was conducted to collect vibration data from normal and abnormal compressors by installing accelerometers directly on rotary compressors used in household air conditioners. Data segmentation was performed to solve the data shortage problem, and the main features for the fault classification model were extracted through the chi-square test after statistical and physical features were extracted from the vibration data in the time domain. The support vector machine (SVM) model was developed to classify the normal or abnormal conditions of compressors and improve the classification accuracy through the hyperparameter optimization of the SVM.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.842-848
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• 2022

Parametric studies of heat transfer and fluid flow are very important research of interest because the design and operation of fluid flow and heat transfer systems are guided by these parametric studies. The safety of the system operation and system optimization can be determined by decreasing or increasing particular fluid flow and heat transfer parameter while keeping other parameters constant. The parameters that can be varied in order to determine safe and optimized system include system pressure, mass flow rate, heat flux and coolant inlet temperature among other parameters. The fluid flow and heat transfer systems can also be enhanced by the presence of or without the presence of particular effects including gravity effect among others. The advanced Generation IV reactors to be deployed for large electricity production, have proven to be more thermally efficient (approximately 45% thermal efficiency) than the current light water reactors with a thermal efficiency of approximately 33 ℃. SCWR is one of the Generation IV reactors intended for electricity generation. High Performance Light Water Reactor (HPLWR) is a SCWR type which is under consideration in this study. One-eighth of a proposed fuel assembly design for HPLWR consisting of 7 fuel/rod bundles with 9 coolant sub-channels was the geometry considered in this study to examine the effects of system pressure and mass flow rate on wall and fluid temperatures. Gravity effect on wall and fluid temperatures were also examined on this one-eighth fuel assembly geometry. Computational Fluid Dynamics (CFD) code, STAR-CCM+, was used to obtain the results of the numerical simulations. Based on the parametric analysis carried out, sub-channel 4 performed better in terms of heat transfer because temperatures predicted in sub-channel 9 (corner subchannel) were higher than the ones obtained in sub-channel 4 (central sub-channel). The influence of system mass flow rate, pressure and gravity seem similar in both sub-channels 4 and 9 with temperature distributions higher in sub-channel 9 than in sub-channel 4. In most of the cases considered, temperature distributions (for both fluid and wall) obtained at 25 MPa are higher than those obtained at 23 MPa, temperature distributions obtained at 601.2 kg/h are higher than those obtained at 561.2 kg/h, and temperature distributions obtained without gravity effect are higher than those obtained with gravity effect. The results show that effects of system pressure, mass flowrate and gravity on fluid flow and heat transfer are significant and therefore parametric studies need to be performed to determine safe and optimum operating conditions of fluid flow and heat transfer systems.

• Wind and Structures
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• v.34 no.1
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• pp.127-136
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• 2022

In this work a multi-fidelity non-intrusive polynomial chaos (MF-NIPC) has been applied to a structural wind engineering problem in architectural design for the first time. In architectural design it is important to design structures that are safe in a range of wind directions and speeds. For this reason, the computational models used to design buildings and bridges must account for the uncertainties associated with the interaction between the structure and wind. In order to use the numerical simulations for the design, the numerical models must be validated by experi-mental data, and uncertainties contained in the experiments should also be taken into account. Uncertainty Quantifi-cation has been increasingly used for CFD simulations to consider such uncertainties. Typically, CFD simulations are computationally expensive, motivating the increased interest in multi-fidelity methods due to their ability to lev-erage limited data sets of high-fidelity data with evaluations of more computationally inexpensive models. Previous-ly, the multi-fidelity framework has been applied to CFD simulations for the purposes of optimization, rather than for the statistical assessment of candidate design. In this paper MF-NIPC method is applied to flow around a rectan-gular 5:1 cylinder, which has been thoroughly investigated for architectural design. The purpose of UQ is validation of numerical simulation results with experimental data, therefore the radius of curvature of the rectangular cylinder corners and the angle of attack are considered to be random variables, which are known to contain uncertainties when wind tunnel tests are carried out. Computational Fluid Dynamics (CFD) simulations are solved by a solver that employs the Finite Element Method (FEM) for two turbulence modeling approaches of the incompressible Navier-Stokes equations: Unsteady Reynolds Averaged Navier Stokes (URANS) and the Large Eddy simulation (LES). The results of the uncertainty analysis with CFD are compared to experimental data in terms of time-averaged pressure coefficients and bulk parameters. In addition, the accuracy and efficiency of the multi-fidelity framework is demonstrated through a comparison with the results of the high-fidelity model.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.33 no.2
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• pp.54-60
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• 2023

In this study, microstructure and basic property analysis of DG (Desulfurization gypsum) and CCMs (Carbondioxide conversion capture materials) made by reacting CO₂ with DG were conducted to analyze applicability as a cement admixture. The main crystalline phases of DG were CaO and CaSO₄, and CCMs were CaSO₄, CaCO₃, Ca(OH)₂ and CaSO₄·H₂O. As a result of particle size analysis, the difference in average particle sizes between the two materials was about 7 ㎛. No major heavy metals were detected in the CCMs, and as a result o f TGA, the CO₂ decomposition of CCMs was more than twice as high as that of DG. Therefore, it was judged that CCMs could be used as a cement admixture through optimization of manufacturing conditions. As a results of measuring the strength behavior of DG and CCMs mixture ratios, the long-term strength of CCMs-mixed mortar was higher, and this is due to the filler effect of CaCO₃ in CCMs.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.11 no.2
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• pp.82-91
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• 2006

We investigated the possibility of using effluents from a municipal sewage treatment plant (STP) as tracers a tracer for hydrologic studies of rivers. The possibility was checked in a 12-km long reach downstream of Jeonju Municipal Sewage Treatment Plant (JSTP). Time-series monitoring of the water chemistry reveals that chemical compositions of the effluent from the JSTP are fluctuating within a relatively wide range during the sampling period. In addition, the signals from the plant were observed at the downstream stations consecutively with increasing time lags, especially in concentrations of the conservative chemical parameters (concentrations f3r chloride and sulfate, total concentration of major cations, and electric conductivity). Based on this observation, we could estimate the stream flow (Q), velocity (v), and dispersion coefficient (D). A 1-D nonreactive solute-transport model with automated optimization schemes was used for this study. The values of Q, v, and D estimated from this study varied from 6.4 to $9.0m^3/sec$ (at the downstream end of the reach), from 0.06 to 0.10 m/sec, and from 0.7 to $6.4m^2/sec$, respectively. The results show that the effluent from a large-scaled municipal STP frequently provides good, multiple natural tracers far hydrologic studies.