• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.467-472
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• 2006

The purpose of this paper is to check the structural safety of the network equipments by performing the static and dynamic finite element analysis. The stress and displacement of structures under static loading condition are evaluated to check whether satisfying the design requirement conditions. Since the computed natural frequencies are similar to the results of experiment. the model could be used for the response spectrum analysis where experimental acceleration value at each frequency are used as seismic input excitation. It is shown that the analysis results are a little bit larger than that of the experimental values. Also sensitivity analysis and optimization for the natural frequency are performed and it is found that the first natural frequency is very sensitive to the stiffness of the equipment.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.149-158
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• 2002

For the purpose of preciously describing real time traffic pattern in urban road network, dynamic network loading(DNL) models able to simulate traffic behavior are required. A number of different methods are available, including macroscopic, microscopic dynamic network models, as well as analytical model. Equivalency minimization problem and Variation inequality problem are the analytical models, which include explicit mathematical travel cost function for describing traffic behaviors on the network. While microscopic simulation models move vehicles according to behavioral car-following and cell-transmission. However, DNL models embedding such travel time function have some limitations ; analytical model has lacking of describing traffic characteristics such as relations between flow and speed, between speed and density Microscopic simulation models are the most detailed and realistic, but they are difficult to calibrate and may not be the most practical tools for large-scale networks. To cope with such problems, this paper develops a new DNL model appropriate for dynamic traffic assignment(DTA), The model is combined with vertical queue model representing vehicles as vertical queues at the end of links. In order to compare and to assess the model, we use a contrived example network. From the numerical results, we found that the DNL model presented in the paper were able to describe traffic characteristics with reasonable amount of computing time. The model also showed good relationship between travel time and traffic flow and expressed the feature of backward turn at near capacity.

• Geomechanics and Engineering
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• v.10 no.1
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• pp.109-124
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• 2016

In this paper, process of dynamic powder compaction is investigated experimentally using impact of drop hammer and die tube. A series of test is performed using aluminum powder with different grain size. The energy of compaction of powder is determined by measuring height of hammer and the results presented in term of compact density and rupture stress. This paper also presents a mathematical modeling using experimental data and neural network. The purpose of this modeling is to display how the variations of the significant parameters changes with the compact density and rupture stress. The closed-form obtained model shows very good agreement with experimental results and it provides a way of studying and understanding the mechanics of dynamic powder compaction process. In the considered energy level (from 733 to 3580 J), the relative density is varied from 63.89% to 87.41%, 63.93% to 91.52%, 64.15% to 95.11% for powder A, B and C respectively. Also, the maximum rupture stress are obtained for different types of powder and the results shown that the rupture stress increases with increasing energy level and grain size.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.3
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• pp.1-15
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• 1993

In this paper, we propose over-reporting avoidance scheme which avoids congestion of network traffics by adjusting managed system's over-reporting, on the OSI network management model which reports events from managed system to managing system. In case of reporting events from managed system to managing system, management traffic concentration occurs, and it causes over-loading on the managing system and congestion on the network. This scheme takes advantage of feedback from managing system to managed system. Managed system transmits event reports as much as maximum event pertime allocated to itself to managing system, and it sets it's management variables to LOCK state and stops event reports as Threshold time is reached. At the time, managing system directs event reports again by using M-set primitive with referring it's status. With this scheme, distributed processing, dynamic network adaptation, convergence of optimal operation point is possible. In addition to it, a fairness is assured. In order to detect characteristics of the Unary feedback over-reporting avoidance scheme. It is observed a control capability of the event reporting and fairness of each nodes through measuring. ThresholdTime value. It is measured a number of mean activating nodes and maintained time of LOCK state according to event reporting load, and also measured lost ratio of management packet, queuing delay in managing system, and goodput to observe effects of general packet load. Binary feedback scheme. Unary feedback overreporting avoidance scheme and raw scheme on the OSI network management system each are compared and analyzed, and finally proved that the scheme proposed in this study performs better.

• Journal of the Korea institute for structural maintenance and inspection
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• v.2 no.4
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• pp.137-147
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• 1998

The neural net application was tried to develop the technique for monitoring the health status of a steel truss bridge which was scaled down to 1/15 of the real bridge for the laboratory experiments. The damage scenarios were chosen as 7 cases. The dynamic behavior, which was changed due to the breakage of the members, of the bridge was investigated by finite element analysis. The bridge consists of single spam, and eight (8) main structural subsystems. The loading vehicle, which weighs as 100 kgf, was operated by the servo-motor controller. The accelerometers were bonded on the surface of 7 cross-beams to measure the dynamic behavior induced by the abnormal structural condition. Artificial neural network technique was used to determine the severity of the damage. At first, the neural net was learnt by the results of finite element analysis, and also, the maximum detection error was 3.65 percents. Another neural net was also learnt, and verified by the experimental results, and in this case, the maximum detection error was 1.05 percents. In future study, neural net is necessary to be learnt and verified by various data from the real bridge.

• Journal of the Ergonomics Society of Korea
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• v.19 no.2
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• pp.87-99
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• 2000

This study aims to examine a fuzzy logic-based human expert EMG prediction model (FLHEPM) for predicting electromyographic responses of trunk muscles due to manual lifting based on two task (control) variables. The FLHEPM utilizes two variables as inputs and ten muscle activities as outputs. As the results, the lifting task variables could be represented with the fuzzy membership functions. This provides flexibility to combine different scales of model variables in order to design the EMG prediction system. In model development, it was possible to generate the initial fuzzy rules using the neural network, but not all the rules were appropriate (87% correct ratio). With regard to the model precision, the EMG signals could be predicted with reasonable accuracy that the model shows mean absolute error of 8.43% ranging from 4.97% to 13.16% and mean absolute difference of 6.4% ranging from 2.88% to 11.59%. However, the model prediction accuracy is limited by use of only two task variables which were available for this study (out of five proposed task variables). Ultimately, the neuro-fuzzy approach utilizing all five variables to predict either the EMG activities or the spinal loading due to dynamic lifting tasks should be developed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.5
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• pp.329-331
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• 2014

JavaScript is widely used to offer interactive web service and dynamic content. However, the number and size of JavaScript constituting the web page has been increasing steadily, and this circumstance leads to falling web performance. In this paper, we suggest a scheme for acceleration of JavaScript transmission considering software module reusability. We perform network simulation for the performance evaluation and analysis about the suggested scheme, and then confirm that the suggested scheme offers better performance in term of page loading time and the amount of traffic generated in the network than the transmission method using Gzip.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.9-17
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• 2013

This paper presents the design of the educational router system. This system is designed and implemented to support network configuration and embedded programming technology of the user on Internet. Not only Static routing protocol but also a kind of dynamic routing protocols such as OSPF and RIP and firewall have been programmed for education based on ethernet interface. ADS 1.2 as debugging environment, uC/OS-ii as RTOS and C language as development language are used. The educational procedures is compile, loading of static routing protocol, a kind of dynamic routing protocols such as OSPF and RIP and firewall program already supplied. Thereafter the verification is checked by using "ping" test to allow for demo operation such as hands-on training procedure. Finally programming procedure similar with demo operation of static routing protocol, a kind of dynamic routing protocols such as OSPF and RIP and packet filtering function is educated step by step.

• Steel and Composite Structures
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• v.41 no.5
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• pp.761-773
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• 2021

This study presents a 3D non-linear finite element (FE) assessment of dynamic soil-structure interaction (SSI). The numerical investigation has been performed on the time domain through a Finite Element (FE) system, while considering the nonlinear behavior of soil and the multi-directional nature of genuine seismic events. Later, the FE outcomes are analyzed to the recorded in-situ free-field and structural movements, emphasizing the numerical model's great result in duplicating the observed response. In this work, the soil response is simulated using an isotropic hardening elastic-plastic hysteretic model utilizing HSsmall. It is feasible to define the non-linear cycle response from small to large strain amplitudes through this model as well as for the shift in beginning stiffness with depth that happens during cyclic loading. One of the most difficult and unexpected tasks in resolving soil-structure interaction concerns is picking an appropriate ground motion predicted across an earthquake or assessing the geometrical abnormalities in the soil waves. Furthermore, an artificial neural network (ANN) has been utilized to properly forecast the non-linear behavior of soil and its multi-directional character, which demonstrated the accuracy of the ANN based on the RMSE and R² values. The total result of this research demonstrates that complicated dynamic soil-structure interaction processes may be addressed directly by passing the significant simplifications of well-established substructure techniques.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.1-8
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• 2006

This paper describes the procedures developing the algorithm for analyzing signals acquired from the Bridge Weigh-in-Motion (BWIM) system installed in Seohae Bridge as a part of the bridge monitoring system. Through the analysis procedure, information about heavy traffics such as weight, speed, and number of axles are attempted to be extracted from time domain strain data of the BWIM system. One of numerous pattern recognition techniques, artificial neural network (ANN) is employed since it can effectively include dynamic effects, bridge-vehicle interaction, etc. A number of vehicle running experiments with sufficient load cases are executed to acquire training and/or test set of ANN. Extracted traffic information can be utilized for developing quantitative database of loading effect. Also, it can contribute to estimate fatigue lift or current health condition, and design truck can be revised based on the database reflecting recent trend of traffic.