• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.358-361
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• 2010

A Reynolds-Averaged Navier-Stokes (RANS) code with transition prediction model is developed and the computational results on an oscillating airfoil are compared with the experimental data for OA209 airfoil. An approximated eN method that can predict transition onset points and the length of transition region is directly applied to the RANS code. The hysteresis loop in dynamic stall is compared for the computational results using transition prediction and fully turbulent models with the experimental data. Results with transition prediction show more correlation with the experimental data than the fully turbulent computation.

• Journal of computational fluids engineering
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• v.19 no.2
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• pp.8-16
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• 2014

Two-dimensional prediction capability of several analysis codes, such as XFOIL, MSES, and KFLOW, is compared and analyzed based on computational results of airfoil flows. To this end the transition transport equations are coupled with the Navier-Stokes equations for the prediction of the natural transition and the separation-induced transition. Experimental data of aerodynamic coefficients are used for comparison with numerical results for the transitional flows. Numerical predictions using the transition transport model show a good agreement with experimental data. Discrepancies have been found in the prediction of the pressure drag are mainly caused by the difference in the far-field circulation correction methods.

• 유체기계공업학회:학술대회논문집
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• 2006.08a
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• pp.235-238
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• 2006

This paper is about the code that realizes the $e^N$-Method for boundary-layer transition prediction. The $e^N$-Method based on the linear stability theory is applied to predicting boundary-layer transition frequently. This paper deals with the construction of code, stability analysis and the calculation of N-factor. The results of transition prediction using the $e^N$-Method for flat plate/cone compressible boundary-layers are presented.

• New & Renewable Energy
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• v.18 no.1
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• pp.17-28
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• 2022

This paper presents an effective Markov transition matrix (EMTM), which will be used to calculate the wind speed at the target site in a wind farm to accurately predict wind energy production. The existing MTS prediction method using a Markov transition matrix (MTM) exhibits a limitation where significant prediction variations are observed owing to random selection errors and its bin width. The proposed method selects the effective states of the MTM and refines its bin width to reduce the error of random selection during a gap filling procedure in MTS. The EMTM reduces the level of variation in the repeated prediction of wind speed by using the coefficient of variations and range of variations. In a case study, MTS exhibited better performance than other MCP models when EMTM was applied to estimate a one-day wind speed, by using mean relative and root mean square errors.

• 한국전산유체공학회:학술대회논문집
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• 2004.03a
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• pp.23-26
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• 2004

Drag prediction is sought for the aifoil having laminar and turbulent flow characteristics with CFD code being unable to predict transition to turbulent flow. Laminar flow simulation presents some insight to the transition position. Separate simulations with laminar and turbulent flow and their combination estimate the drag of the airfoil containing laminar and turbulent flow characteristics.

• Korean Journal of Materials Research
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• v.34 no.7
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• pp.363-369
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• 2024

In this study, the magnetocaloric effect and transition temperature of bulk metallic glass, an amorphous material, were predicted through machine learning based on the composition features. From the Python module 'Matminer', 174 compositional features were obtained, and prediction performance was compared while reducing the composition features to prevent overfitting. After optimization using RandomForest, an ensemble model, changes in prediction performance were analyzed according to the number of compositional features. The R2 score was used as a performance metric in the regression prediction, and the best prediction performance was found using only 90 features predicting transition temperature, and 20 features predicting magnetocaloric effects. The most important feature when predicting magnetocaloric effects was the 'Fe' compositional ratio. The feature importance method provided by 'scikit-learn' was applied to sort compositional features. The feature importance method was found to be appropriate by comparing the prediction performance of the Fe-contained dataset with the full dataset.

• International Journal of Fluid Machinery and Systems
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• v.4 no.1
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• pp.114-132
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• 2011

We have proposed a new approach based on energy gradient concept for the study of flow instability and turbulent transition in parallel flows in our previous works. It was shown that the disturbance amplitude required for turbulent transition is inversely proportional to Re, which is in agreement with the experiments for imposed transverse disturbance. In present study, the energy gradient theory is extended to the generalized curved flows which have much application in turbomachinery and other fluid delivery devices. Within the frame of the new theory, basic theorems for flow instability in general cases are provided in details. Examples of applications of the theory are given from our previous studies which show comparison of the theory with available experimental data. It is shown that excellent agreement has been achieved for several configurations. Finally, various prediction methods for turbulent transition are reviewed and commented.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2610-2615
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• 2021

The prediction of irradiation-induced transition temperature shift for RPV steels is an important method for long term operation of nuclear power plant. Based on the irradiation embrittlement data, an irradiation-induced transition temperature shift prediction model is developed with machine learning method XGBoost. Then the residual, standard deviation and predicted value vs. measured value analysis are conducted to analyze the accuracy of this model. At last, Cu content threshold and saturation values analysis, temperature dependence, Ni/Cu dependence and flux effect are given to verify the reliability. Those results show that the prediction model developed with XGBoost has high accuracy for predicting the irradiation embrittlement trend of RPV steel. The prediction results are consistent with the current understanding of RPV embrittlement mechanism.

• Journal of computational fluids engineering
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• v.17 no.1
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• pp.54-60
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• 2012

Transition prediction results are validated with experimental data obtained from a transonic wind tunnel for the KU109C airfoil. A Reynolds-Averaged Navier-Stokes code is simultaneously coupled with the transition transport model of Langtry and Menter and applied to the numerical prediction of aerodynamic performance of the KU109C airfoil. Drag coefficients from the experiment are better correlated to the numerical prediction results using a transition transport model rather than the fully turbulent simulation results. Maximum lift coefficient and drag divergence at the zero-lift condition with Mach number are investigated. Through the present validation procedure, the accuracy and usefulness of both the experiment and the numerical prediction are assessed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.5
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• pp.407-419
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• 2008

In this study, the transition Reynolds number of compressible axi-symmetric sharp cone boundary layer is predicted by using a linear stability theory and the -method. The compressible linear stability equation for sharp cone boundary layer was derived from the governing equations on the body-intrinsic axi-symmetric coordinate system. The numerical analysis code for the stability equation was developed based on a second-order accurate finite-difference method. Stability characteristics and amplification rate of two-dimensional second mode disturbance for the sharp cone boundary layer were calculated from the analysis code and the numerical code was validated by comparing the results with experimental data. Transition prediction was performed by application of the -method with N=10. From comparison with wind tunnel experiments and flight tests data, capability of the transition prediction of this study is confirmed for the sharp cone boundary layers which have an edge Mach number between 4 and 8. In addition, effect of wall cooling on the stability of disturbance in the boundary layer and transition position is investigated.