• Wind and Structures
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• v.10 no.6
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• pp.511-532
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• 2007

The present study aims to generate turbulent inflow data to more accurately represent the turbulent flow around a square cylinder when the inflow turbulence level is significant. The modified random flow generation (RFG) technique in conjunction with a previously developed LES code is successfully adopted into a finite element based fluid flow solver to generate the required inflow turbulence boundary conditions for the three-dimensional (3-D) LES computations of transitional turbulent flow around a square cylinder at Reynolds number of 22,000. The near wall region is modelled without using wall approximate conditions and a wall damping coefficient is introduced into the calculation of sub-grid length scale in the boundary layer of the cylinder wall. The numerical results obtained from simulations are compared with each other and with the experimental data for different inflow turbulence boundary conditions in order to discuss the issues such as the synthetic inflow turbulence effects on the 3-D transitional flow behaviour in the near wake and the free shear layer, the basic mechanism by which stream turbulence interacts with the mean flow over the cylinder body and the prediction of integral flow parameters. The comparison among the LES results with and without inflow turbulence and the experimental data emphasizes that the turbulent inflow data generated by the present RFG technique for the LES computation can be a viable approach in accurately predicting the effects of inflow turbulence on the near wake turbulent flow characteristics around a bluff body.

• Magazine of the Korean Society of Agricultural Engineers
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• v.31 no.4
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• pp.31-49
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• 1989

It is of the most urgent necessity to get hydrological time series of long duration for the establishment of rational design and operation criterion for the Agricultural hydraulic structures. This study was conducted to select best fitted frequency distribution for the monthly runoff and to simulate long series of generated flows by multi-season first order Markov model with comparison of statistical parameters which are derivated from observed and sy- nthetic flows in the five watersheds along Geum river basin. The results summarized through this study are as follows. 1. Both two parameter gamma and two parameter lognormal distribution were judged to be as good fitted distributions for monthly discharge by Kolmogorov-Smirnov method for goodness of fit test in all watersheds. 2. Statistical parameters were obtained from synthetic flows simulated by two parameter gamma distribution were closer to the results from observed flows than those of two para- meter lognormal distribution in all watersheds. 3. In general, fluctuation for the coefficient of variation based on two parameter gamma distribution was shown as more good agreement with the observed flow than that of two parameter lognormal distribution. Especially, coefficient of variation based on two parameter lognormal distribution was quite closer to that of observed flow during June and August in all years. 4. Monthly synthetic flows based on two parameter gamma distribution are considered to give more reasonably good results than those of two parameter lognormal distribution in the multi-season first order Markov model in all watersheds. 5. Synthetic monthly flows with 100 years for eack watershed were sjmulated by multi- season first order Markov model based on two parameter gamma distribution which is ack- nowledged to fit the actual distribution of monthly discharges of watersheds. Simulated sy- nthetic monthly flows may be considered to be contributed to the long series of discharges as an input data for the development of water resources. 6. It is to be desired that generation technique of synthetic flow in this study would be compared with other simulation techniques for the objective time series.

• Journal of Environmental Science International
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• v.24 no.4
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• pp.393-401
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• 2015

Rainfall-runoff model of Jeju Oedo Stream was used to compute the optimal unit hydrograph by HEC-HMS model that reflecting on watershed characteristics. Each rainfall event was comparatively analyzed with the actual flow measurement using Clark, Snyder and SCS synthetic methods for derived unit hydrograph. Subsequently, the null hypothesis was established as p-value for peak flow and peak time of each unit hydrograph by one-way ANOVA(Analysis of variance) was larger than significance level of 0.05. There was no significant difference in peak flow and peak time between different methods of unit hydrograph. As a result of comparing error rate with actual flow measurement data, Clark synthetic unit graph best reflected in Oedo Stream as compared to other methods, and error rate of Clark unit hydrograph was 0.02~1.93% and error rate at peak time was 0~2.74%.

• Journal of the Korean Society of Visualization
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• v.19 no.3
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• pp.92-98
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• 2021

Large Eddy Simulation (LES) has been popularly applied and used in the last several decades to simulate turbulent boundary layer in the numerical domain. A fully developed turbulent boundary layer has also been applied to predict the complicated wake flow behind bluff bodies. In this study we aimed to generate an artificial turbulent boundary layer, which is based on an exponential correlation function, and generates a series of realistic three-dimensional velocity data in two-dimensional inlet section which are correlated both in space and in time. The results suggest its excellent capability for high Reynolds number flows. To make an effective generation, a hexahedral mesh has been used and Cholesky decomposition was applied to possess suitable turbulent statistics such as the randomness and correlation of turbulent flow. As a result, the flow characteristics in the domain and fluctuating pressure near the wall are very close to those of fully developed turbulent boundary layers.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.3
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• pp.389-394
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• 2017

The limitation of flow control for a bistable fluidic valve has been investigated. The physical model of the fluidic valve includes two main flow outlets and two control flow inlets. The experiments were conducted with pressure regulators, mass flow meters, and piezo sensors to analyze flow switching characteristics of the fluidic valve. The experimental data such as pressure and mass flow rate of control flows and the switching time of the main flow was obtained with various operating conditions. The operation limit of the fluidic valve is identified, and a model equation for pre-estimating the minimum control pressure to switch the direction of the main flow has been proposed.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1181-1194
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• 2018

This study suggests a novel approach of estimating stream flow discharge using the Synthetic Aperture Radar (SAR) images taken from 2015 to 2017 by European Space Agency Sentinel-1 satellite. Fifteen small to medium sized rivers in the Han River basin were selected as study area, and the SAR satellite images and flow data from water level and flow observation system operated by the Korea Institute of Hydrological Survey were used for model construction. First, we apply the histogram matching technique to 12 SAR images that have undergone various preprocessing processes for error correction to make the brightness distribution of the images the same. Then, the flow estimation model was constructed by deriving the relationship between the area of the stream water body extracted using the threshold classification method and the in-situ flow data. As a result, we could construct a power function type flow estimation model at the fourteen study areas except for one station. The minimum, the mean, and the maximum coefficient of determination ($R^2$) of the models of at fourteen study areas were 0.30, 0.80, and 0.99, respectively.

• Wind and Structures
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• v.18 no.5
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• pp.567-598
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• 2014

In this paper, wind induced aerodynamic loads on a standard tall building have been evaluated through large-eddy simulation (LES) technique. The flow parameters of an open terrain were recorded from the downstream of an empty boundary layer wind tunnel (BLWT) and used to prescribe the transient inlet boundary of the LES simulations. Three different numerically generated inflow boundary conditions have been investigated to assess their suitability for LES. A high frequency pressure integration (HFPI) approach has been employed to obtain the wind load. A total of 280 pressure monitoring points have been systematically distributed on the surfaces of the LES model building. Similar BLWT experiments were also done to validate the numerical results. In addition, the effects of adjacent buildings were studied. Among the three wind field generation methods (synthetic, Simirnov's, and Lund's recycling method), LES with perturbation from the synthetic random flow approach showed better agreement with the BLWT data. In general, LES predicted peak wind loads comparable with the BLWT data, with a maximum difference of 15% and an average difference of 5%, for an isolated building case and however higher estimation errors were observed for cases where adjacent buildings were placed in the vicinity of the study building.

• Water for future
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• v.18 no.1
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• pp.75-83
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• 1985

The applicability of ARMA(1, 1) multiseason model, which is in the beginning stage of active researches in the field of synthetic generation is evaluated with the streamflow data at the Nakdong stage gauging station on the main stem of the Nakdong River. The method of parameter estimation for the modelis reviewed and the statistical analysis of the generated seasonal streamflows such as corrlogram analysis and the computation of moments is made. The results obtained by ARMA(1, 1) multiseason model are compared with the historical streamflow data and also with those by two other multiseason models, namely, Thomas-Fiering model and Matalas AR(1) multiseason model. The seasonal streamflows grnerated by three multiseason models were annually summed up to form respective annual flow series whose statistics were compared with those of the annual flow series generated by three annual models, namely, AR(1), Matalas AR(1), and ARMA(1, 1) annual models. The possibility of ARMA(1, 1) multiseason model for the simultaneous generation of seasonal and annual streamflows is also evaluated.

• Advances in aircraft and spacecraft science
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• v.8 no.4
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• pp.273-287
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• 2021

Model-based, data-driven and physics-based approaches represent the state-of-the-art techniques to estimate the aircraft flow angles, angle-of-attack and angle-of-sideslip, in avionics. Thanks to sensor fusion techniques, a synthetic sensor is able to provide estimation of flow angles without any dedicated physical sensors. The work deals with a physics-based scheme derived from flight mechanic theory that leads to a nonlinear flow angle model. Even though several solvers can be adopted, nonlinear models can be replaced with less accurate but straightforward ones in practical applications. The present work proposes a linearisation to obtain the flow angles' closed form solution that is verified using a flight simulator. The main objective of the paper, in fact, is to analyse the estimation degradation using the proposed closed form solutions with respect to the nonlinear scheme. Moreover, flight conditions, where the proposed closed form solutions are not applicable, are identified.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.135-142
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• 2021

Estimating the locations of workers in a shipyard is beneficial for a variety of applications such as selecting potential forwarders for transferring data in IoT services and quickly rescuing workers in the event of industrial disasters or accidents. In this work, we propose a human movement stream processing system for estimating worker locations in shipyards based on Apache Spark and TensorFlow serving. First, we use Apache Spark to process location data streams. Then, we design a worker location prediction model to estimate the locations of workers. TensorFlow serving manages and executes the worker location prediction model. When there are requirements from clients, Apache Spark extracts input data from the processed data for the prediction model and then sends it to TensorFlow serving for estimating workers' locations. The worker movement data is needed to evaluate the proposed system but there are no available worker movement traces in shipyards. Therefore, we also develop a mobility model for generating the workers' movements in shipyards. Based on synthetic data, the proposed system is evaluated. It obtains a high performance and could be used for a variety of tasksin shipyards.