• Journal of Mechanical Science and Technology
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• v.15 no.9
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• pp.1292-1301
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• 2001

The mean-line method using empirical models is the most practical method of predicting off-design performance. To gain insight into the empirical models, the influence of empirical models on the performance prediction results is investigated. We found that, in the two-zone model, the secondary flow mass fraction has a considerable effect at high mass flow-rates on the performance prediction curves. In the TEIS model, the first element changes the slope of the performance curves as well as the stable operating range. The second element makes the performance curves move up and down as it increases or decreases. It is also discovered that the slip factor affects pressure ratio, but it has little effect on efficiency. Finally, this study reveals that the skin friction coefficient has significant effect on both the pressure ratio curve and the efficiency curve. These results show the limitations of the present empirical models, and more resonable empirical models are reeded.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.456-463
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• 2009

The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by in-situ test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network(NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network(CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.

• Journal of Mechanical Science and Technology
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• v.15 no.7
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• pp.889-894
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• 2001

In this study, the performances of various turbulence closure models are evaluated in the calculation of a transonic flow over axisymmetric bump. k-$\varepsilon$, explicit algebraic stress, and two Reynolds stress models, i.e., GL model proposed by Gibson & Launder and SSG model proposed by Speziale, Sarkar and Gatski, are chosen as turbulence closure models. SSG Reynolds stress model gives best predictions for pressure coefficients and the location of shock. The results with GL model also show quite accurate prediction of pressure coefficients down-stream of shock wave. However, in the predictions of mean velocities and turbulent stresses, the results are not so satisfactory as in the prediction of pressure coefficients.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.23 no.5
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• pp.610-620
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• 1999

Recently, numerous modifications of low Reynolds number $k-{\epsilon}$ model have boon carried out with the aid of DNS data. However, the previous models made in this way are too intricate to be used practically. To overcome this shortcoming, a new low Reynolds number $k-{\epsilon}$ model has boon developed by considering the distribution of turbulent properties near the wall. This study proposes the revised a turbulence model for prediction of turbulent flow with adverse pressure gradient and separation. Nondimensional distance $y^+$ in damping functions is changed to $y^*$ and some terms modeled for one dimensional flow in $\epsilon$ equations are expanded into two or three dimensional form. Predicted results by the revised model show an acceptable agreement with DNS data and experimental results. However, for a turbulent flow with severe adverse pressure gradient, an additive term reflecting an adverse pressure gradient effect will have to be considered.

• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.355-362
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• 2012

The aim of this study was to develop a bundle position-wise linear model (BPLM) to predict Pressure Tube (PT) diametral creep employing the previously measured PT diameters and operating conditions. There are twelve bundles in a fuel channel, and for each bundle a linear model was developed by using the dependent variables, such as the fast neutron fluences and the bundle coolant temperatures. The training data set was selected using the subtractive clustering method. The data of 39 channels that consist of 80 percent of a total of 49 measured channels from Units 2, 3, and 4 of the Wolsung nuclear plant in Korea were used to develop the BPLM. The data from the remaining 10 channels were used to test the developed BPLM. The BPLM was optimized by the maximum likelihood estimation method. The developed BPLM to predict PT diametral creep was verified using the operating data gathered from Units 2, 3, and 4. Two error components for the BPLM, which are the epistemic error and the aleatory error, were generated. The diametral creep prediction and two error components will be used for the generation of the regional overpower trip setpoint at the corresponding effective full power days. The root mean square (RMS) errors were also generated and compared to those from the current prediction method. The RMS errors were found to be less than the previous errors.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.101-104
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• 2007

All of noise prediction model have it's own features in the case of modeling conditions, so it is very important to know the features of each model case by case for a proper modeling, especially using at the Environmental Impact Assessment. For prediction of highway traffic noise and abating the noise by barriers, two kinds of prediction model, HW-NOISE, KHTN(Korea Highway Traffic Noise) has been mainly used in Korea. In this study, the features of these models were described at the same conditions. The properties of sound power from a road, diffraction characteristics from a barrier, sound pressure level decaying in each model were investigated. Using the results, it will be anticipated that the proper using of prediction models in the works of highway noise abating.

• 유체기계공업학회:학술대회논문집
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• 2001.11a
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• pp.30-34
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• 2001

In the present study, we studied the method of predicting the on-design and on-design point performance of axial flow fan with adjustable pitch blades. With the change of stagger angle of axial flow fan with adjustable pitch blade, flow rate and pressure can be changed. Because of this merit adjustable pitch fans are used in many industrial facility. When changing stagger angle or estimating the performance at a wide range of off-design condition, incidence angle changes greatly as the flow rate changes. Therefore, the deviation angle at the blade exit is estimated by the correlation considering the effects of blade design, incidence angle variation. In the loss model, we used known pressure loss model for blade boundary layer and wake, secondary flow, endwall boundary layer and tip leakage flow. The results of modified deviation angle model and experiment were compared for the usefulness of the modified model.

• Wind and Structures
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• v.30 no.3
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• pp.289-298
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• 2020

Gusts generated by downburst have caused a great variety of structural damages in many regions around the world. It is of great significance to accurately evaluate the downburst-induced wind load on high-rise building for the wind resistance design. The main objective of this paper is to propose a computational modeling approach which can satisfactorily predict the mean and fluctuating wind pressure coefficients induced by downburst on high-rise building surfaces. In this study, using an impinging jet to simulate downburst-like wind, and simultaneous pressure measurements are obtained on a high-rise building model at different radial locations. The model test data are used as the database for developing back propagation neural network (BPNN) models. Comparisons between the BPNN prediction results and those from impinging jet test demonstrate that the BPNN-based method can satisfactorily and efficiently predict the downburst-induced wind pressure coefficients on single and overall surfaces of high-rise building at various radial locations.

• Journal of Power System Engineering
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• v.18 no.6
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• pp.13-20
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• 2014

The steady-state, incompressible and three-dimensional numerical analysis was carried out to evaluate turbulent models on the aerodynamic performance of a small-size axial fan(SSAF). The prediction performance on the static pressure of all turbulent models is going downhill at the high static pressure and low flowrate region, but has improved at the axial flow region. In consequence, all turbulent models predict the static pressure coefficient with an error performance less than about 4% after the region of the flowrate coefficient of about 0.14. Especially, the turbulent model of SST $k-{\omega}$ shows the best prediction performance equivalent to an error performance less than about 2% on the static pressure.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.05a
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• pp.201-203
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• 2012

The establishment of the technology for evaluating friction resistance and pipe pressure and the relation of the fluid characteristics and pumpability of concrete is essential for the evaluation of concrete pumping performance for high speed construction of super-tall building. So, this study focuses on quantitative evaluation of concrete fluid characteristics and surface friction resistance under the change of concrete mix proportion and pumping condition. In this study, we measured the rheology of concrete and pipe pressure and surface friction characteristics when pumping. And, relations between the rheology characteristics of concrete and pumping performance was investigated by experiment. As the result of the experiment, high regression between the surface friction and pressure gradient was confirmed. And, prediction model to evaluate the friction resistance coefficient and pipe pressure reduction coefficient was suggested.