• Wind and Structures
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• v.20 no.6
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• pp.763-791
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• 2015

"Wind and Ports" is a European project that has been carried out since 2009 to handle wind forecast in port areas through an integrated system made up of an extensive in-situ wind monitoring network, the numerical simulation of wind fields, the statistical analysis of wind climate, and algorithms for medium-term (1-3 days) and short term (0.5-2 hours) wind forecasting. The in-situ wind monitoring network, currently made up of 22 ultrasonic anemometers, provides a unique opportunity for detecting high resolution thunderstorm records and studying their dominant characteristics relevant to wind engineering with special concern for wind actions on structures. In such a framework, the wind velocity of thunderstorms is firstly decomposed into the sum of a slowly-varying mean part plus a residual fluctuation dealt with as a non-stationary random process. The fluctuation, in turn, is expressed as the product of its slowly-varying standard deviation by a reduced turbulence component dealt with as a rapidly-varying stationary Gaussian random process with zero mean and unit standard deviation. The extraction of the mean part of the wind velocity is carried out through a moving average filter, and the effect of the moving average period on the statistical properties of the decomposed signals is evaluated. Among other aspects, special attention is given to the thunderstorm duration, the turbulence intensity, the power spectral density and the integral length scale. Some noteworthy wind velocity ratios that play a crucial role in the thunderstorm loading and response of structures are also analyzed.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.10
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• pp.83-98
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• 2007

The handover between different radio access networks, especially where their coverage overlaps, suffers various complications since the different access networks provide different service characteristics. One way to reduce service interruptions and QoS (i.e., bandwidth, throughput, delay) degradations during the inter-technology handover is to reserve the required resource in advance. The resource reservation algorithm should minimize the handover latency and maximize the resource utilization based on the accurate estimation on mobile's location, velocity, movement pattern and service requirements. In this paper, we propose a resource reservation algorithm based on the mobile terminal velocity and the cell selection probability, which maximizes resource utilization ana reduces network overhead. We compare the proposed algorithm with PMS(Predictive Mobility Support) and VCDS(Velocity and Call Duration Support scheme) based on 3-layer network model under various scenarios.

• Journal of the Korean Geotechnical Society
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• v.40 no.4
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• pp.127-135
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• 2024

The purpose of this paper is to establish the relationship between compression wave velocity and porosity in unsaturated soil using a deep neural network (DNN) algorithm. Input parameters were examined using the error norm method to assess their impact on porosity. Compression wave velocity was conclusively found to have the most significant influence on porosity estimation. These parameters were derived through both field and laboratory experiments using a total of 266 numerical data points. The application of the DNN was evaluated by calculating the mean squared error loss for each iteration, which converged to nearly zero in the initial stages. The predicted porosity was analyzed by splitting the data into training and validation sets. Compared with actual data, the coefficients of determination were exceptionally high at 0.97 and 0.98, respectively. This study introduces a methodology for predicting dependent variables through error norm analysis by disregarding fewer sensitive factors and focusing on those with greater influence.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.5
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• pp.531-542
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• 2007

Simultaneous measurement technique for temperature and velocity fields near a heated solid body has been constructed. The measurement system consists of a 3-late CCD color camera, a color image grabber, a 1ighting system, a host computer and a software for the whole quantification process. Thermo Chromic Liquid Crystals (TCLC) was used as temperature sensors. A neural network was used to get a calibration curve between the temperature and the color change of the TCLC in order to enhance the dynamic range of temperature measurement. The velocity field measurement was attained by the use of the fray-level images taken for the flow field, and by introducing the cross-correlation technique. The temperature and the velocity fields of the forced and the natural convective flows neat the surface of a cartridge heater were measured simultaneously with the constructed measurement system.

• Journal of Biomedical Engineering Research
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• v.20 no.1
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• pp.91-97
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• 1999

We propose a new method for measuring the frequency characteristics of phase velocity along a bone for bending vibration modes to diagnose its mechanical characteristics. By introducing a simple model of a distributed-constant-network, the phase velocity is determined for each frequency from the spatial distribution of velocity along a radius bone surface which is measured by the ultrasonic Doppler method.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.10
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• pp.1341-1347
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• 2002

In order to improve efficiency of a system with three-dimensional flow characteristics, this paper presents a new method that overcomes three-dimensional effects by using two-dimensional CFD and neural network. The method was applied to shape optimization of cut-off in a multi-blade fan/scroll system. As the entrance conditions of two-dimensional CFD, the experimental values at the positions out of the inactive zone were used. The distributions of velocity and pressure obtained by two-dimensional CFD were compared with those of three-dimensional CFD and experimental results. It was found that the distributions of velocity and pressure have qualitative similarity. The results of two-dimensional CFD were used for teaming as target values of neural network. The optimal angle and radius of cut-off were determined as 71$^{\circ}$and 0.092 times the outer diameter of impeller, respectively. It is quantified in the previous report that the optimal angle and radius of cut-off are approximately 72$^{\circ}$and 0.08 times the outer diameter of impeller, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.4
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• pp.103-112
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• 1989

A numerical model for Steady state groundwater flow has been established to understand the groundwater flow phenomena near a radioactive waste repository. The integrated finite difference method based on a network composed of nodes and members was applied to investigate groundwater flow in homogeneous, heterogeneous and layered media. Its numerical solution was in good agreement with analytic solution. Physical phenomena associated in the groundwater flow depending on both hydraulic characteristics and effects of fractured zone were also investigated. A method by which feasible groundwater flow paths can be identified was developed. This method used the composite network for the geologic media near a repository and the direction of computed groudwater velocity. Groundwater velocity and travel time were predicted for the possible pathway form a repository to a biosphere.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.340-343
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• 1992

Fundamental positioning characteristics of a dual-axis Sawyer linear motor are described. The Sawyer motor is capable of high positional accuracy. An electronic control unit of the motor whose velocity is proportional to the frequency of the electric current was produced in our laboratory. The positioning system was constructed using two Sawyer motors, an air bearings suspension unit and an electronic control unit. The stable motion of the motor was confirmed on the open loop operation. The adjustable operating conditions were the live load of 1 kg, the maximum acceleration of 1.2G and the maximum velocity of 350 mm/s. Absolute positioning accuracy was improved within .+-.5.mu.m, on microstep operating conditions of dividing one pitch of 508.mu.m into 508 steps. The following two conclusions were obtained. An accelerating-cruising-decelerating control is effective for reduction in the travel time required. Also, microstep operation is effective for improving the resolution of position.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1871-1880
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• 2011

In this paper, a controller for two wheeled inverted pendulum robot, i.e., Segway type robot that is a convenient and easily handled vehicle is designed to have more stable balancing and faster velocity control compared to the conventional method. First, a widely used PID control structure is applied to the two wheeled inverted pendulum robot and proper PID control gains for some specified weights of users are obtained to get accurate balancing and velocity control by use of experimental trial-and-error method. Next, neural network is employed to generate appropriate PID control gains for arbitrarily selected weight. Here the PID gains based on the trial-and-error method are used as training data. Simulation study has been carried out to find that the performance of the designed controller using the neural network is more excellent than the conventional PID controller in terms of faster balancing and velocity control.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.133-138
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• 1993

This paper presents neural network based position estimation method in slippery environment as an approach to solve one of problems which are engaged in dead reckoning method. Position estimator is composed of slip detector and linear velocity estimator. Both of them are based on the fact that dynamic characteristic of mobile robot in slippery environment is different from the case without slip. To find out the dynamic relation among driving torque, angular acceleration of driving wheel and linear acceleration of mobile robot, accelerometer is used for measuring acceleration of mobile robot and neural network is used for dynamic system identifier in slippery environment.