• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.519-528
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• 2023

The aim of this study was to enhance the flow rate and noise performance of a centrifugal pump in dishwashers by designing an optimized impeller shape through numerical and experimental investigations. To evaluate the performance of the target centrifugal pump, experiment was conducted using a pump performance tester and noise experiment was carried out in a semi-anechoic chamber with microphones and a reflecting wall behind the dishwasher. Through the use of advanced computational fluid dynamics techniques, numerical simulations were performed to analyze the flow and aeroacoustics performance of our target centrifugal pump impeller. To achieve this, numerical simulations were carried out using the Reynolds-Average Navier-Stokes equations and Ffowcs-Willliams and Hawkings equations as governing equations. In order to ensure the validity of numerical methods, a thorough comparison of numerical results with experimental results. After having confirmed the reliability of the current numerical method of this study, the optimization of the target centrifugal pump impeller was conducted. An improvement in flow rate was confirmed numerically, and a manufactured proto-type of the optimized model was used for experimental investigation. Furthermore, it was observed that by applying the fan law, we could effectively reduce noise levels without reducing the flow rate.

• Smart Structures and Systems
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• v.32 no.4
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• pp.267-279
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• 2023

Data modelling and interpretation for structural health monitoring (SHM) field data are critical for evaluating structural performance and quantifying the vulnerability of infrastructure systems. In order to improve the data modelling accuracy, and extend the application range from data regression analysis to out-of-sample forecasting analysis, an improved most likely heteroscedastic Gaussian process (iMLHGP) methodology is proposed in this study by the incorporation of the outof-sample forecasting algorithm. The proposed iMLHGP method overcomes this limitation of constant variance of Gaussian process (GP), and can be used for estimating non-stationary typhoon-induced response statistics with high volatility. The first attempt at performing data regression and forecasting analysis on structural responses using the proposed iMLHGP method has been presented by applying it to real-world filed SHM data from an instrumented cable-stay bridge during typhoon events. Uncertainty quantification and correlation analysis were also carried out to investigate the influence of typhoons on bridge strain data. Results show that the iMLHGP method has high accuracy in both regression and out-of-sample forecasting. The iMLHGP framework takes both data heteroscedasticity and accurate analytical processing of noise variance (replace with a point estimation on the most likely value) into account to avoid the intensive computational effort. According to uncertainty quantification and correlation analysis results, the uncertainties of strain measurements are affected by both traffic and wind speed. The overall change of bridge strain is affected by temperature, and the local fluctuation is greatly affected by wind speed in typhoon conditions.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.641-653
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• 2023

As climate change and urbanization are causing unprecedented natural disasters in urban areas, it is crucial to have urban flood predictions with high fidelity and accuracy. However, conventional physically- and deep learning-based urban flood modeling methods have limitations that require a lot of computer resources or data for high-resolution flooding analysis. In this study, we propose and implement a method for improving the spatial resolution of urban flood analysis using a deep learning based super-resolution technique. The proposed approach converts low-resolution flood maps by physically based modeling into the high-resolution using a super-resolution deep learning model trained by high-resolution modeling data. When applied to two cases of retrospective flood analysis at part of City of Portland, Oregon, U.S., the results of the 4-m resolution physical simulation were successfully converted into 1-m resolution flood maps through super-resolution. High structural similarity between the super-solution image and the high-resolution original was found. The results show promising image quality loss within an acceptable limit of 22.80 dB (PSNR) and 0.73 (SSIM). The proposed super-resolution method can provide efficient model training with a limited number of flood scenarios, significantly reducing data acquisition efforts and computational costs.

• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.801-813
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• 2023

Recently, as studies about Artificial Neural Network (ANN) are actively progressing, studies for predicting water quality of rivers using ANN are being conducted. However, it is difficult to analyze the operation process inside ANN, because ANN is form of Black-box. Although eXplainable Artificial Intelligence (XAI) is used to analyze the computational process of ANN, research using XAI technology in the field of water resources is insufficient. This study analyzed Multi Layer Perceptron (MLP) to predict Water Temperature (WT), Dissolved Oxygen (DO), hydrogen ion concentration (pH) and Chlorophyll-a (Chl-a) at the Dasan water quality observatory in the Nakdong river using Layer-wise Relevance Propagation (LRP) among XAI technologies. The MLP that learned water quality was analyzed using LRP to select the optimal input data to predict water quality, and the prediction results of the MLP learned using the optimal input data were analyzed. As a result of selecting the optimal input data using LRP, the prediction accuracy of MLP, which learned the input data except daily precipitation in the surrounding area, was the highest. Looking at the analysis of MLP's DO prediction results, it was analyzed that the pH and DO a had large influence at the highest point, and the effect of WT was large at the lowest point.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.672-680
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• 2023

Weight is a critical factor in the ship design process given that it has a substantial impact on the hydrodynamic performance of ships. Typically, ships are optimally designed for specific conditions with a fixed draft and displacement. However, in reality, weight and draft can vary within a certain range owing to operational activities, such as fuel consumption, ballast adjustments, and loading conditions . Therefore, we investigated how resistance changes under three different loading conditions, namely overload, design-load, and lightship, for small craft, using both model experiments and numerical simulations. Additionally, we examined the sensitivity of weight changes to resistance to enhance the performance of ships, ultimately reducing power requirements in support of the International Maritime Organization's (IMO) goal of reducing CO2 emissions by 50% by 2050. We found that weight changes have a more significant impact at low Froude Numbers. Operating under overload conditions, which correspond to a 5% increase in draft and an 11.1% increase in displacement, can lead to a relatively substantial increase in total resistance, up to 15.97% and 14.31% in towing tests and CFD simulations, respectively.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.681-687
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• 2023

The selection technique for optimal operation position selection technique is used to present the initial bow and stern draft with minimum resistance, for achievingthat is, the optimal fuel consumption efficiency at a given operating displacement and speed. The main purpose of this studypaper is to develop a program to select the optimal operating position with maximum energy efficiency under given operating conditions based on the effective power data of the target ship. This program was written as a Python-based GUI (Graphic User Interface) usingbased on artificial intelligence techniques sucho that ship owners could easily use the GUIit. In the process, tThe introduction of the target ship, the collection of effective power data through computational fluid dynamics (CFD), the learning method of the effective power model using deep learning, and the program for presenting the optimal operation position using the deep neural network (DNN) model were specifically explained. Ships are loaded and unloaded for each operation, which changes the cargo load and changes the displacement. The shipowners wants to know the optimal operating position with minimum resistance, that is, maximum energy efficiency, according to the given speed of each displacement. The developed GUI can be installed on the ship's tablet PC and application and used to determineselect the optimal operating position.

• Korean Journal of Optics and Photonics
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• v.35 no.1
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• pp.9-17
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• 2024

A plenoptic optical system for microscopy comprises an objective lens, tube lens, microlens array (MLA), and an image sensor. Numerical aperture (NA) matching between the tube lens and MLA is used for optimal performance. This paper extends performance predictions from NA matching to unmatching cases and introduces a computational technique for plenoptic configurations using optical analysis software. Validation by fabricating and experimenting with two sample systems at 10× and 20× magnifications resulted in predicted spatial resolutions of 12.5 ㎛ and 6.2 ㎛ and depth of field (DOF) values of 530 ㎛ and 88 ㎛, respectively. The simulation showed resolutions of 11.5 ㎛ and 5.8 ㎛, with DOF values of 510 ㎛ and 70 ㎛, while experiments confirmed predictions with resolutions of 11.1 ㎛ and 5.8 ㎛ and DOF values of 470 ㎛ and 70 ㎛. Both formula-based prediction and simulations yielded similar results to experiments that were suitable for system design. However, regarding DOF values, simulations were closer to experimental values in accuracy, recommending reliance on simulation-based predictions before fabrication.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3874-3897
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• 2023

A high-fidelity computational fluid dynamics (CFD) analysis was performed using the Large Eddy Simulation (LES) model for the lower plenum of the High-Temperature Test Facility (HTTF), a ¼ scale test facility of the modular high temperature gas-cooled reactor (MHTGR) managed by Oregon State University. In most next-generation nuclear reactors, thermal stress due to thermal striping is one of the risks to be curiously considered. This is also true for HTGRs, especially since the exhaust helium gas temperature is high. In order to evaluate these risks and performance, organizations in the United States led by the OECD NEA are conducting a thermal hydraulic code benchmark for HTGR, and the test facility used for this benchmark is HTTF. HTTF can perform experiments in both normal and accident situations and provide high-quality experimental data. However, it is difficult to provide sufficient data for benchmarking through experiments, and there is a problem with the reliability of CFD analysis results based on Reynolds-averaged Navier-Stokes to analyze thermal hydraulic behavior without verification. To solve this problem, high-fidelity 3-D CFD analysis was performed using the LES model for HTTF. It was also verified that the LES model can properly simulate this jet mixing phenomenon via a unit cell test that provides experimental information. As a result of CFD analysis, the lower the dependency of the sub-grid scale model, the closer to the actual analysis result. In the case of unit cell test CFD analysis and HTTF CFD analysis, the volume-averaged sub-grid scale model dependency was calculated to be 13.0% and 9.16%, respectively. As a result of HTTF analysis, quantitative data of the fluid inside the HTTF lower plenum was provided in this paper. As a result of qualitative analysis, the temperature was highest at the center of the lower plenum, while the temperature fluctuation was highest near the edge of the lower plenum wall. The power spectral density of temperature was analyzed via fast Fourier transform (FFT) for specific points on the center and side of the lower plenum. FFT results did not reveal specific frequency-dominant temperature fluctuations in the center part. It was confirmed that the temperature power spectral density (PSD) at the top increased from the center to the wake. The vortex was visualized using the well-known scalar Q-criterion, and as a result, the closer to the outlet duct, the greater the influence of the mainstream, so that the inflow jet vortex was dissipated and mixed at the top of the lower plenum. Additionally, FFT analysis was performed on the support structure near the corner of the lower plenum with large temperature fluctuations, and as a result, it was confirmed that the temperature fluctuation of the flow did not have a significant effect near the corner wall. In addition, the vortices generated from the lower plenum to the outlet duct were identified in this paper. It is considered that the quantitative and qualitative results presented in this paper will serve as reference data for the benchmark.

• Journal of Korea Water Resources Association
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• v.56 no.spc1
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• pp.1059-1069
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• 2023

Dam-break flow occurs when an elevated dam suddenly collapses, resulting in the catastrophic release of rapid and uncontrolled impounded water. This study compares laminar and turbulent closure models for simulating three-dimensional dam-break flows using OpenFOAM. The Reynolds-Averaged Navier-Stokes (RANS) model, specifically the k-ε model, is employed to capture turbulent dissipation. Two scenarios are evaluated based on a laboratory experiment and a modified multi-layered block obstacle scenario. Both models effectively represent dam-break flows, with the turbulent closure model reducing oscillations. However, excessive dissipation in turbulent models can underestimate water surface profiles. Improving numerical schemes and grid resolution enhances flow recreation, particularly near structures and during turbulence. Model stability is more significantly influenced by numerical schemes and grid refinement than the use of turbulence closure. The k-ε model's reliance on time-averaging processes poses challenges in representing dam-break profiles with pronounced discontinuities and unsteadiness. While simulating turbulence models requires extensive computational efforts, the performance improvement compared to laminar models is marginal. To achieve better representation, more advanced turbulence models like Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) are recommended, necessitating small spatial and time scales. This research provides insights into the applicability of different modeling approaches for simulating dam-break flows, emphasizing the importance of accurate representation near structures and during turbulence.

• Advances in nano research
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• v.16 no.4
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• pp.325-340
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• 2024

There are several novel uses for dispersing many nanoparticles into a conventional fluid, including dynamic sealing, damping, heat dissipation, microfluidics, and more. Therefore, melting heat and mass transfer characteristics of a 3-D MHD Hybrid Nanofluid flow over a rotating disc with presenting dufour and soret effects are assessed numerically in this study. In this instance, we investigated both ferric sulfate and molybdenum disulfide as nanoparticles suspended within base fluid water. The governing partial differential equations are transformed into linked higher-order non-linear ordinary differential equations by the local similarity transformation. The collection of these deduced equations is then resolved using a Chebyshev spectral collocation-based algorithm built into the Mathematica software. To demonstrate how different instances of hybrid/ nanofluid are impacted by changes in temperature, velocity, and the distribution of nanoparticle concentration, examples of graphical and numerical data are given. For many values of the material parameters, the computational findings are shown. Simulations conducted for different physical parameters in the model show that adding hybrid nanoparticle to the fluid mixture increases heat transfer in comparison to simple nanofluids. It has been identified that hybrid nanoparticles, as opposed to single-type nanoparticles, need to be taken into consideration to create an effective thermal system. Furthermore, porosity lowers the velocities of simple and hybrid nanofluids in both cases. Additionally, results show that the drag force from skin friction causes the nanoparticle fluid to travel more slowly than the hybrid nanoparticle fluid. The findings also demonstrate that suction factors like magnetic and porosity parameters, as well as nanoparticles, raise the skin friction coefficient. Furthermore, It indicates that the outcomes from different flow scenarios correlate and are in strong agreement with the findings from the published literature. Bar chart depictions are altered by changes in flow rates. Moreover, the results confirm doctors' views to prescribe hybrid nanoparticle and particle nanoparticle contents for achalasia patients and also those who suffer from esophageal stricture and tumors. The results of this study can also be applied to the energy generated by the melting disc surface, which has a variety of industrial uses. These include, but are not limited to, the preparation of semiconductor materials, the solidification of magma, the melting of permafrost, and the refreezing of frozen land.