• Title/Summary/Keyword: Multi-Propagation

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Shear Capacity of Reinforced Concrete Beams Using Neural Network

  • Yang, Keun-Hyeok;Ashour, Ashraf F.;Song, Jin-Kyu
    • International Journal of Concrete Structures and Materials
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    • v.1 no.1
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    • pp.63-73
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    • 2007
  • Optimum multi-layered feed-forward neural network (NN) models using a resilient back-propagation algorithm and early stopping technique are built to predict the shear capacity of reinforced concrete deep and slender beams. The input layer neurons represent geometrical and material properties of reinforced concrete beams and the output layer produces the beam shear capacity. Training, validation and testing of the developed neural network have been achieved using 50%, 25%, and 25%, respectively, of a comprehensive database compiled from 631 deep and 549 slender beam specimens. The predictions obtained from the developed neural network models are in much better agreement with test results than those determined from shear provisions of different codes, such as KBCS, ACI 318-05, and EC2. The mean and standard deviation of the ratio between predicted using the neural network models and measured shear capacities are 1.02 and 0.18, respectively, for deep beams, and 1.04 and 0.17, respectively, for slender beams. In addition, the influence of different parameters on the shear capacity of reinforced concrete beams predicted by the developed neural network shows consistent agreement with those experimentally observed.

An Efficient Code Assignment Algorithm in Wireless Mesh Networks (무선 메쉬 네트워크에서의 효율적인 코드할당 알고리즘에 대한 연구)

  • Yeo, Jae-Hyun
    • Journal of Information Technology Applications and Management
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    • v.15 no.1
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    • pp.261-270
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    • 2008
  • Wireless Mesh Networks (WMNs) have emerged as one of the new hot topics in wireless communications. WMNs have been suggested for use in situations in which some or all of the users are mobile or are located in inaccessible environments. Unconstrained transmission in a WMN may lead to the time overlap of two or more packet receptions, called collisions or interferences, resulting in damaged useless packets at the destination. There are two types of collisions; primary collision, due to the transmission of the stations which can hear each other, and hidden terminal collision, when stations outside the hearing range of each other transmit to the same receiving stations. For a WMN, direct collisions can be minimized by short propagation and carrier sense times. Thus, in this paper we only consider hidden terminal collision while neglecting direct collisions. To reduce or eliminate hidden terminal collision, code division multiple access (CDMA) protocols have been introduced. The collision-free property is guaranteed by the use of spread spectrum communication techniques and the proper assignment of orthogonal codes. Such codes share the fixed channel capacity allocated to the network in the design stage. Thus, it is very important to minimize the number of codes while achieving a proper transmission quality level in CDMA WMNs. In this paper, an efficient heuristic code assignment algorithm for eliminating hidden terminal collision in CDMA WMNs with general topology.

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A Study on the PTP Motion of Robot Manipulators by Neural Networks (신경 회로망에 의한 로보트 매니퓰레이터의 PTP 운동에 관한 연구)

  • Kyung, Kye-Hyun;Ko, Myoung-Sam;Lee, Bum-Hee
    • Proceedings of the KIEE Conference
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    • 1989.07a
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    • pp.679-684
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    • 1989
  • In this paper, we describe the PTP notion of robot manipulators by neural networks. The PTP motion requires the inverse kinematic redline and the joint trajectory generation algorithm. We use the multi-layered Perceptron neural networks and the Error Back Propagation(EBP) learning rule for inverse kinematic problems. Varying the number of hidden layers and the neurons of each hidden layer, we investigate the performance of the neural networks. Increasing the number of learning sweeps, we also discuss the performance of the neural networks. We propose a method for solving the inverse kinematic problems by adding the error compensation neural networks(ECNN). And, we implement the neural networks proposed by Grossberg et al. for automatic trajectory generation and discuss the problems in detail. Applying the neural networks to the current trajectory generation problems, we can refute the computation time for trajectory generation.

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FREE SURFACE FLOW ANALYSIS BY SOROBAN GRID BASED CIP MEHTOD (Soroban grid 기반 CIP법을 이용한 자유표면 유동해석)

  • Im, H.N.
    • 한국전산유체공학회:학술대회논문집
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    • 2010.05a
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    • pp.326-334
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    • 2010
  • In this study, we provide a comprehensive review of the CIP(Constrained Interpolation Pro file/Cubic Interpolated Propagation) method with a pressure-based algorithm that is known as a general numerical solver for soled liquid, gas and plasmas. And also we introduce a body-fitted grid system(Soroban grid) for computation of strongly nonlinear marine hydrodynamic problems such as slamming water on deck, wave impact by green water. This grid system can keep the third-order accuracy in time and space with the help of the CIP method. The grid system consists of the straight lines and grid points. In the 2-dimensional grid case, each grid points moving in these lines like abacus - Soroban in Japanese. The length of each line can be different and the number of grid points in each line can be different. Mesh generation and searching of upstream departure point are very simple and possible to mesh-free treatment. To optimize computation of free-surface and multi-fluid flows, We adopt the C-CUP method. In most of the earlier computations, the C-CUP method was used with a staggered-grid approach. Here, because of the mesh free nature of the Soroban grid, we use the C-CUP method with a collocated-grid approach.

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Study on Surface Crack Propagation Behaviour of Mild Steel Weldment in Synthetic Sea Water (인공해수중에서 연강 용접부의 표면구열 성장거동)

  • 이종기;정세희
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.14 no.2
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    • pp.492-501
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    • 1990
  • It was known that the fracture incidences of offshore structure were mostly originated from the surface defects. Especially, in the case of the welded structures, since the welded region has some defects and incomplete beads which are apt to behave like the surface cracks, it has been necessary to evaluate the environmental effects on crack growth at HAZ for the design crack growth behaviour at multi-pall HAZ for SWS41 steel under free corrosion and cathodic protection(-0.9V vs Ag/Agcl) conditions. The results are summarized as follows ; (1) Crack growth rate of the as weld in air was faster than that of the parent and PWHT specimens over all .DELTA.K rang. (2) In free corrosion test, surface crack growth rate of the as welded was decreased in comparison with that of the parents. (3) In fatigue test under cathodic protection, cathodic electric potential(-0.9V vs Ag/Agcl) for the SWS41 steel parent was effective, while for the as welded ineffective. (4) There was a tendency that the exponent(m) of the Paris' equation was decreased in order of microhardness magnititude in air and under cathodic protection conditions and vise versa in free corrosion. (5) Fracture surface has dimples and ductile striations in air test, but transgranular cracks and brittle striations under cathodic protection test.

Development of Bond Strength Model for FRP-Plates Using Multi-layer Perceptron (다층 인식자 신경망 모형을 이용한 FRP 판의 부착강도 예측 모형 개발)

  • Kwak Kae-Hwan;Seok In-Soo;Hwang Hae-Sung;Sung Bai-Kyung;Jang Hwa-Sup
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2006.04a
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    • pp.1009-1014
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    • 2006
  • Synthetic materials with excellent thermodynamic characteristics and the merit of anti-corrosion are frequently used in buildings and constructions for enforcement of bent in stead of steel plates. Among them, many practical studies have been conducted on bond strength because of increased bond strength of FRP plates. Previous investigators identified the bond strength of FRP plates through experiments with settlement of various variables to identify the bond strength. However, the experiments to identify the bond force are difficult to be conducted because they requires large expenses and long time for equipment arrangement, thus, are conducted with limitation. In this study, for bond experiment, optimum neural network model was developed with use of Back-propagation and Conjugate gradient technique of previous investigators. Learning was performed with use of the variables of previous investigators in developed neural network model so as to identify the bond strength of FRP plates. for verification of developed model, credibility and excellence was proven by comparing with the models of previous investigators.

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Structure & Fatigue Behavior of TiCN and TiN/TiCN Thin Films (TiCN 및 TiN/TiCN 박막의 구조와 피로거동)

  • Baeg, C.H.;Hong, J.W.;Wey, M.Y.;Kang, H.J.
    • Journal of the Korean Society for Heat Treatment
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    • v.13 no.5
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    • pp.324-329
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    • 2000
  • Microstructure, mechanical and fatigue behaviors of TiCN and TiN/TiCN thin films, deposited on quenched and tempered STD61 tool steel, were investigated by using XRD, XPS, hardness, adhesion and fatigue tests. The TiCN thin film is grown along the (100), (111) orientation, whereas the TiN/TiCN thin film is grown along the (111) orientation. The preferred orientation of TiN/TiCN thin film strongly depends on the TiN buffer layer whose orientation is (111), as is well-known. The TiN/TiCN thin film showed the higher adhesion compared with TiCN single layer because the TiN buffer layer, having good toughness, reduces the effects of the lower hardness of substrate. In the high cycle tension-tension fatigue test, the fatigue life of the TiCN and the TiN/TiCN coated steel increased approximately two to four times and five to nine times respectively compared with uncoated specimens. The TiN buffer layer in multilayer thin films plays an important role in reducing residual stress and fatigue crack initiation, and then in restraining the fatigue propagation.

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Optimum Welding Position between Shell and Cylinder based on SEA (SEA를 이용한 셸과 실린더의 최적 용접 조건)

  • 이장우;양보석;안병하
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.14 no.5
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    • pp.370-376
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    • 2004
  • The overall aim of this paper is to determine coupling loss factor of welding point between shell and cylinder using loss factor and structural loss factor. For this purpose, two kinds of loss factor were adopted. One is loss factor of each sub structure, another is structural loss factor based on the complex welded or assembled structure. Using these two parameters, it ispossible to derive the coupling loss factor which represent characteristic condition of SEA theory. Coupling loss factor of conjunction in complex structure was expressed as power balance equation. The derived equation for a coupling loss factor has been simplified on the assumption of one way (uni-directional) power flow between multi-sub structures. Using these conditions, it is possible to find the equation of coupling loss factor expressed as above two loss factors. To check the effectiveness of above equation, this paper used two-stage application. The first approach was application between simple cylinder and shell. The next was adopted rotary compressor. Rotary compressor has three main conjunctions between shell and internal vibration part. This equation was applied to find out the optimum welding point with respect to reduce the noise propagation. It shows the effective tool to evaluate the coupling loss factor in complex structure

Application of Multi-Class AdaBoost Algorithm to Terrain Classification of Satellite Images

  • Nguyen, Ngoc-Hoa;Woo, Dong-Min
    • Journal of IKEEE
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    • v.18 no.4
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    • pp.536-543
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    • 2014
  • Terrain classification is still a challenging issue in image processing, especially with high resolution satellite images. The well-known obstacles include low accuracy in the detection of targets, especially for the case of man-made structures, such as buildings and roads. In this paper, we present an efficient approach to classify and detect building footprints, foliage, grass and road from high resolution grayscale satellite images. Our contribution is to build a strong classifier using AdaBoost based on a combination of co-occurrence and Haar-like features. We expect that the inclusion of Harr-like feature improves the classification performance of the man-made structures, since Haar-like feature is extracted from corner features and rectangle features. Also, the AdaBoost algorithm selects only critical features and generates an extremely efficient classifier. Experimental result indicates that the classification accuracy of AdaBoost classifier is much higher than that of the conventional classifier using back propagation algorithm. Also, the inclusion of Harr-like feature significantly improves the classification accuracy. The accuracy of the proposed method is 98.4% for the target detection and 92.8% for the classification on high resolution satellite images.

A pre-stack migration method for damage identification in composite structures

  • Zhou, L.;Yuan, F.G.;Meng, W.J.
    • Smart Structures and Systems
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    • v.3 no.4
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    • pp.439-454
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    • 2007
  • In this paper a damage imaging technique using pre-stack migration is developed using Lamb (guided) wave propagation in composite structures for imaging multi damages by both numerical simulations and experimental studies. In particular, the paper focuses on the experimental study using a finite number of sensors for future practical applications. A composite laminate with a surface-mounted linear piezoelectric ceramic (PZT) disk array is illustrated as an example. Two types of damages, one straight-crack damage and two simulated circular-shaped delamination damage, have been studied. First, Mindlin plate theory is used to model Lamb waves propagating in laminates. The group velocities of flexural waves in the composite laminate are also derived from dispersion relations and validated by experiments. Then the pre-stack migration technique is performed by using a two-dimensional explicit finite difference algorithm to back-propagate the scattered energy to the damages and damages are imaged together with the excitation-time imaging conditions. Stacking these images together deduces the resulting image of damages. Both simulations and experimental results show that the pre-stack migration method is a promising method for damage identification in composite structures.