• Geomechanics and Engineering
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• v.20 no.5
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• pp.385-397
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• 2020

This paper presents an application of artificial neural networks (ANNs) in settlement prediction of a foundation on sandy soil. In order to train the ANN model, a wide experimental database about settlement of foundations acquired from available literatures was collected. The data used in the ANNs model were arranged using the following five-input parameters that covered both geometrical foundation and sandy soil properties: breadth of foundation B, length to width L/B, embedment ratio D_f/B, foundation net applied pressure q_net, and average SPT blow count N. The backpropagation algorithm was implemented to develop an explicit predicting formulation. The settlement results are compared with the results of previous studies. The accuracy of the proposed formula proves that the ANNs method has a huge potential for predicting the settlement of foundations on sandy soils.

• Nuclear Engineering and Technology
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• v.43 no.3
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• pp.301-308
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• 2011

The diametral creep of pressure tubes (PTs) in CANDU (CANada Deuterium Uranium) reactors is one of the principal aging mechanisms governing the heat transfer and hydraulic degradation of the heat transport system (HTS). PT diametral creep leads to diametral expansion, which affects the thermal hydraulic characteristics of the coolant channels and the critical heat flux (CHF). The CHF is a major parameter determining the critical channel power (CCP), which is used in the trip setpoint calculations of regional overpower protection (ROP) systems. Therefore, it is essential to predict PT diametral creep in CANDU reactors. PT diametral creep is caused mainly by fast neutron irradiation, temperature and applied stress. The objective of this study was to develop a bundle position-wise linear model (BPLM) to predict PT diametral creep employing previously measured PT diameters and HTS operating conditions. The linear model was optimized using a genetic algorithm and was devised based on a bundle position because it is expected that each bundle position in a PT channel has inherent characteristics. The proposed BPLM for predicting PT diametral creep was confirmed using the operating data of the Wolsung nuclear power plant in Korea. The linear model was able to predict PT diametral creep accurately.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.320-325
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• 2010

A multiphase CFD analysis is performed to investigate the effect of near-wall grid for simulating a subcooled boiling flow in vertical tube. The multiphase flow model used in this CFD analysis is the two-fluid model in which liquid(water) and vapor(steam) are considered as continuous and dispersed fluids, respectively. A wall boiling model is also used to simulate the subcooled boiling heat transfer at the heated wall boundary. The diameter and heated length of tube are 0.0154 m and 2 m, respectively. The system pressure in tube is 4.5 MPa and the inlet subcooling is 60 K. The near-wall grid size in the non-dimensional wall unit ($y_{w}^{+}$) was examined from 64 to 172 at the outlet boundary. The CFD calculations predicted the void distributions as well as the liquid and wall temperatures in tube. The predicted axial variations of the void fraction and the wall temperature are compared with the measured ones. The CFD prediction of the wall temperature is shown to slightly depend on the near-wall grid size but the axial void prediction has somewhat large dependency. The CFD prediction was found to show a better agreement with the measured one for the large near-wall grid, e.g., $y_{w}^{+}$ > 100.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.6
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• pp.757-770
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• 1998

A Navier-Stokes code with a low Reynolds number k-.epsilon. turbulence model was tested to investigate its predictability for the unsteady transitional boundary layer flow due to rotor-stator interaction. A preliminary calculation with three different numbers of time steps 300, 600, and 1000 for a rotor wake passing period was carried out to see the effects of time steps on the unsteady flow and pressure fields due to rotor-stator interaction. Numerical solutions showed that unsteady pressure was much more sensitive to the number of time steps and over 600 time steps should be used to get a numerical solution independent of the number of time steps for a rotor wake passing period. The original low Reynolds number k-.epsilon. turbulence model showed very poor prediction of the unsteady transitional boundary layer flow due to rotor-stator interaction. This was due to the excessive production of turbulent kinetic energy near the leading edge. A modification suggested by Launder was incorporated and the modified model captured well the wake induced transitional strip. Present solutions also showed improved prediction over previous Euler/boundary layer solution in terms of the onset of unsteady transition and its extent.

• Journal of ILASS-Korea
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• v.1 no.3
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• pp.37-50
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• 1996

Computational fluid dynamics was used to optimize an A/C duct. Three dimensional flow analysis in an automotive A/C duct was performed computationally using various turbulence models and compared numerical predictions such as outlet flow split, surface pressure distribution along the duct to experimental data. Additionally, we studied the effect of location variation of 2nd branch on exit flow ratio and could find optimal location of 2nd branch. The design of an A/C duct was modeled and calculated to enhance the airflow distribution in each outlet using the STAR-CD computational fluid dynamics software. In results, modified $k-\varepsilon$ turbulence model allows a successful prediction of static pressure distribution particulary at around strong curvature but little improvement flow split. In the future, adoption of CFD to design an A/C duct with modified $k-\varepsilon$ model will bring benefits of producing more accurate prediction, and also give designers more detail information much more than now.

• Korean Journal of Food Science and Technology
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• v.23 no.5
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• pp.605-609
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• 1991

The physical properties which must be considered as engineering factors affecting on the evaporation process of fruit juices are boiling point rise, density, viscosity, thermal conductivity and specific heat. These factors are varied with food ingredients, soluble solids, pressure and temperature. In the reserch, it has been worked to obtain the data and to develop prediction model for the boiling point rise as a faction of soluble solid and pressure by the regression of SPSS package program. For the prediction model of density, it was developed as a fuction of soluble solid content on apple and pear juices. For the viscosity model, it was establised by the factors of temperature and content of soluble solid through the optimization program.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.4
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• pp.118-129
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• 1996

In this study, three dimensional flow analysis in a HVAC duct was performed computationally using various turbulence models and compared numerical predictions such as outlet flow split, surface pressure distribution along the duct to experimental data. It's well known that accuracy of computational predictions of flow heavily dependent on turbulent models and discritization method. Therefore, in this work, to assess the ability of turbulent models to predict characteristics of duct flow, three kinds of models, namely standard $k-\varepsilon$, RNG $k-\varepsilon$ and modified $k-\varepsilon$, containing parameter for the effect of streamline curvature were employed and validated one another by comparing with experimental data. In results, modified $k-\varepsilon$ turbulence model allows a successful prediction of static pressure distribution particulary at around strong curvature but little improvement flow split. In the futrue, adoption of CFD to design HVAC duct with modified $k-\varepsilon$ model will bring benefits of producing more accurate prediction, and also give designers more detail information much more than now.

• Nuclear Engineering and Technology
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• v.41 no.7
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• pp.907-920
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• 2009

This study was performed to evaluate the prediction capability of a commercial CFD code and to investigate the effects of different geometries such as a 4.4 mm tube and an 8/10 mm annular channel on the detailed flow structures. A numerical simulation was performed for the conditions, at which the experimental data was produced by the test facility SPHINX. A 2-dimensional axisymmetric steady flow was assumed for computational simplicity. The RNG $\kappa-\varepsilon$ turbulence model (RNG) with an enhanced wall treatment option, SST $\kappa-\omega$ (SST) and low Reynolds Abid turbulence model (ABD) were employed and the numerical predictions were compared with the experimental data generated from the experiment. The effects of the geometry on heat transfer were investigated. The flow and temperature fields were also examined in order to investigate the mechanism of heat transfer near the wall. The local heat transfer coefficient predicted by the RNG model is very close to the measurement result for the tube. In contrast, the local heat transfer coefficient predicted by the SST and ABD models is closer to the measurement for the annular channel.

• The KSFM Journal of Fluid Machinery
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• v.20 no.2
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• pp.63-68
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• 2017

This paper predicts the rotordynamic force coefficients of tilting pad journal bearings (TPJBs) with ball-socket pivot and compares the predictions to the published test data obtained under load-between-pad (LBP) configuration. The present TPJB model considers the pivot stiffness calculated based on the Hertzian contact stress theory. Due to the compliance of the pivot, the predicted journal eccentricity agree well with the measured journal center trajectory for increasing static loads, while the early prediction without pivot model consideration underestimates it largely. The predicted pressure profile shows the significant pressure development even on the unloaded pads along the direction opposite to the loading direction. The predicted stiffness coefficients increase as the static load and the rotor speed increase. They agree excellently with test data from open literature. The predicted damping coefficients increase as the static load increases and the rotor speed decreases. The prediction underestimates the test data slightly. In general, the current predictive model including the pivot stiffness improves the accuracy of the rotordynamic performance predictions when compared to the previously published predictions.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.19 no.2
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• pp.93-101
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• 2023

In this study, a deep learning algorithm was used to diagnose electric potential signals obtained through CIPS and DCVG, used indirect inspection methods to confirm the soundness of buried pipes. The deep learning algorithm consisted of CNN(Convolutional Neural Network) model for diagnosing the electric potential signal and Grad CAM(Gradient-weighted Class Activation Mapping) for showing the flaw prediction point. The CNN model for diagnosing electric potential signals classifies input data as normal/abnormal according to the presence or absence of flaw in the buried pipe, and for abnormal data, Grad CAM generates a heat map that visualizes the flaw prediction part of the buried pipe. The CIPS/DCVG signal and piping layout obtained from the 3D finite element model were used as input data for learning the CNN. The trained CNN classified the normal/abnormal data with 93% accuracy, and the Grad-CAM predicted flaws point with an average error of 2m. As a result, it confirmed that the electric potential signal of buried pipe can be diagnosed using a CNN-based deep learning algorithm.