• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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• pp.218-224
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• 1996

The purpose of this syudy is to set up a proper repair plan and to extend the remaining lifetime of them by measuring the remaining lifetime of reinforced concrete structures quantitatively. This method is based on the actual research on age deterioration, carbonation depth and covering depth of the reinforced concrete structures. Also, it measure the remaining lifetime through quantitatively defining the probability of steel corrosion by the damage of steel corrosion. By doing that, we proceed the proper repair plan after reviewing the possibility of lifetime extension.

• Journal of Korean Society of Steel Construction
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• v.13 no.5
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• pp.467-476
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• 2001

The construction of highway bridges is almost complete in many countries including the United States. The government and highway agencies change the focus from constructing to maintaining To maintain the bridges effectively there is an urgent need to assess actual bridge loading carrying capacity and to predict their remaining life. The system reliability techniques have to be used for this purpose. Based on lifetime distribution (function) techniques this study illustrates how typical highway bridges can be modeled to predict their remaining life. The parameters of lifetime distribution are generated by Monte. The results can be used for optimization of planning interventions on existing bridges.

• Journal of Korean Society of Steel Construction
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• v.14 no.2
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• pp.365-373
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• 2002

In this paper, the system reliability concept was presented to predict the lifespan of bridges. Lifetime distribution functions (survivor functions) were used to model real bridges to predict their remaining life. Using the system reliability concept and lifetime distribution functions (survivor functions), a program called LIFETIME was developed. The survivor functions give the reliability of component at time t. The program was applied to an existing Colorado state highway bridge to predict the failure probability of the time-dependent system. The bridge was modeled as a system, with failure probability computed using time-dependent deteriorating models.

• International journal of advanced smart convergence
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• v.6 no.1
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• pp.57-67
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• 2017

In this paper, propose an algorithm to improve network lifetime by equally consuming energy of LEACH - Mobile sensor nodes. LEACH is one of energy efficient protocols. However, we did not consider the mobility of nodes. Therefore, the transmission reception success rate of the moving data is reduced. LEACH-Mobile is a protocol that has improved the drawbacks of these LEACH. However, since LEACH-Mobile has a larger number of data packets and consumes more energy than LEACH, it has a disadvantage that the lifetime of the network is short. In order to improvement these disadvantage, Based on the average of the remaining energy of the node, cluster heads are elected with a number of nodes whose energies are larger than the average of the remaining energy from the member nodes. After that, by trying to increase the lifetime of the network by equalizing the remaining energy. In to confirm whether improve the lifetime of the network, In this paper, the number of nodes and the position of all nodes are varied for each specific round, the rest energy is equalized, and the algorithm which uniformly selected the cluster head is compared with LEACH.

• Journal of the Korean Society for Railway
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• v.8 no.5
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• pp.439-443
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• 2005

The biggest challenge bridge agencies face is the maintenance of bridges, keeping them safe and serviceable, with limited funds. To maintain the bridges effectively, there is and urgent need to predict their remaining life from a system reliability viewpoint. In this paper, a model using lifetime functions to evaluate the overall system probability of survival of a rail road bridge is proposed. In this model, the rail load bridge is modeled as a system. Using the model, the lifetime of the rail road bridge is predicted.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.11A
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• pp.995-1003
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• 2005

Since the sensor network nodes have a small size and limited battery power, there have been many studies for reducing their energy consumption. Each sensor node can show different energy usage according to the frequency of event sensing and data transmission, and thus they have different lifetime. So, some nodes may run out of energy that causes disconnection of paths and reduction of network lifetime. In this paper, we propose a new energy-efficient routing algorithm for sensor networks that selects a least energy-consuming path among the paths formed by node with highest remaining energy and provides long network lifetime and somewhat uniform energy consumption by nodes. Simulation results show that our algorithm extends the network lifetime and enhances the network reliability by maintaining relatively uniform remaining energy distribution among sensor nodes.

• The KIPS Transactions:PartC
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• v.17C no.4
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• pp.371-378
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• 2010

In this paper, we propose a new energy-efficient routing algorithm for sensor networks that selects a least energy consuming path among the paths formed by node with highest remaining energy and provides long network lifetime and uniform energy consumption by nodes. The pair distribution of the energy consumption over all the possible routes to the base station is one of the design objectives. Also, an alternate route search mechanism is proposed to cope with the situation in which no routing information is available due to lack of remaining energy of the neighboring nodes. Simulation results show that our algorithm extends the network lifetime and enhances the network reliability by maintaining relatively uniform remaining energy distribution among sensor nodes.

• Magazine of the Korea Concrete Institute
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• v.6 no.3
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• pp.96-100
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• 1994

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.55-65
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• 2010

We present a method for increasing network lifetime without link failure due to lack of battery capacity of nodes in wireless ad-hoc networks with low mobility. In general, a node with larger remaining battery capacity represents the one with lesser traffic load. Thus, a modified AODV routing protocol is proposed to determine a possible route by considering a remaining battery capacity of a node. Besides, the total energy consumption of all nodes increase rapidly due to the huge amount of control packets which should be flooded into the network. To reduce such control packets efficiently, a source node can store information about alternative routes to the destination node into its routing table. When a link failure happens, the source node should retrieve the route first with the largest amount of the total remaining battery capacity from its table entries before initiating the route rediscovery process. To do so, the possibility of generating unnecessary AODV control packets should be reduced. The method proposed in this paper increases the network lifetime by 40% at most compared with the legacy AODV and MMBCR.

• Journal of Astronomy and Space Sciences
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• v.32 no.4
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• pp.367-377
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• 2015

Atmospheric drag force is an important source of perturbation of Low Earth Orbit (LEO) orbit satellites, and solar activity is a major factor for changes in atmospheric density. In particular, the orbital lifetime of a satellite varies with changes in solar activity, so care must be taken in predicting the remaining orbital lifetime during preparation for post-mission disposal. In this paper, the System Tool Kit (STK$^{(R)}$) Long-term Orbit Propagator is used to analyze the changes in orbital lifetime predictions with respect to solar activity. In addition, the STK$^{(R)}$ Lifetime tool is used to analyze the change in orbital lifetime with respect to solar flux data generation, which is needed for the orbital lifetime calculation, and its control on the drag coefficient control. Analysis showed that the application of the most recent solar flux file within the Lifetime tool gives a predicted trend that is closest to the actual orbit. We also examine the effect of the drag coefficient, by performing a comparative analysis between varying and constant coefficients in terms of solar activity intensities.