• Steel and Composite Structures
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• v.44 no.5
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• pp.651-676
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• 2022

Most of the experimental, theoretical, and numerical studies on the stability of functionally graded composites are deterministic, while there are full of complex interactions of variables with an inherently probabilistic nature, this paper presents a non-intrusive framework to investigate the stochastic nonlinear buckling behaviors of porous functionally graded cylindrical shells exposed to inevitable source-uncertainties. Euler-Lagrange equations are theoretically derived based on the three variable refined shear deformation theory. Closed-form solutions for the shell buckling loads are achieved by solving the deterministic eigenvalue problems. The analytical results are verified with numerical results obtained from finite element analyses that are conducted in the commercial software ABAQUS. The non-intrusive framework is completed by integrating the Monte Carlo simulation with the verified closed-form solutions. The convergence studies are performed to determine the effective pseudorandom draws of the simulation. The accuracy and efficiency of the framework are verified with statistical results that are obtained from the first and second-order perturbation techniques. Eleven cases of individual and compound uncertainties are investigated. Sensitivity analyses are conducted to figure out the five cases that have profound perturbative effects on the shell buckling loads. Complete probability distributions of the first three critical buckling loads are completely presented for each profound uncertainty case. The effects of the shell thickness, volume fraction index, and stochasticity degree on the shell buckling load under compound uncertainties are studied. There is a high probability that the shell has non-unique buckling modes in stochastic environments, which should be known for reliable analysis and design of engineering structures.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.06a
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• pp.103-116
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• 2003

Rockfall Protection fence is one of the most common rockfall Protection methods in Korea. If rockfall protection fences are required along the road or railway, their location, height and capacity, in terms of the maximum kinetic energy that they can absorb, should be specified. Within this paper, the best practice of rockfall barrier is introduced. Modern rockfall simulations as a means to define risks, protection requirements, dynamic loading and height of potential structures and selection of appropriate placement is presented. Technical possibilities of rockfall barriers and their actual limits are presented. Safety concepts based on probabilistic approaches are proposed. Recent studies peformed in other countries show that Flexible Barriers are also a feasible system to stop and retain debris flows. Finally an outlook onto further development is given.

• Computers and Concrete
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• v.26 no.4
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• pp.351-365
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• 2020

This work presents numerical and experimental analyses of the behavior of reinforced-concrete deep beams with unconventional geometries. The main goal here is to experimentally and numerically study these geometries to find possible new behaviors due to the material nonlinearity of reinforced concrete with complex geometries. Usually, unconventional geometries result from innovative designs; in general, studies of reinforced concrete structures are performed only on conventional members such as beams, columns, and labs. To achieve the goal, four reinforced-concrete deep beams with geometries not addressed in the literature were tested. The models were numerically analyzed with the Adaptive Micro Truss Model (AMTM), which is the proposed method, to address new geometries. This work also studied the main parameters of the constitutive model of concrete based on a statistical analysis of the finite element (FE) results. To estimate the ultimate loads, FE simulations were performed using the Monte Carlo method. Based on the obtained ultimate loads, a probabilistic distribution was created, and the final ultimate loads were computed.

• Structural Engineering and Mechanics
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• v.53 no.4
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• pp.819-831
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• 2015

In this paper, we propose a new method for taking into account uncertainties based on the projection on polynomial chaos. The new approach is used to determine the dynamic response of a spur gear system with uncertainty associated to gear system parameters and this uncertainty must be considered in the analysis of the dynamic behavior of this system. The simulation results are obtained by the polynomial chaos approach for dynamic analysis under uncertainty. The proposed method is an efficient probabilistic tool for uncertainty propagation. It was found to be an interesting alternative to the parametric studies. The polynomial chaos results are compared with Monte Carlo simulations.

• Research in Mathematical Education
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• v.18 no.4
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• pp.289-305
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• 2014

The current mathematical education calls for a learning environment from the constructionism perspective that actively creates mathematical objects. This research first analyzes JavaMAL's expression 'move' that enables students to express the agent's behavior constructively before they learn vector as a formal concept. Since expression 'move' is based on a coordinate, it naturally corresponds with the expression of vectors used in school mathematics and lets students take an embodied approach to the concept of vector. Furthermore, as a design tool, expression 'move' can be used in various activities that include vector structure. This research studies the educational significance entailed in JavaMAL's expression 'move'.

• Journal of Energy Engineering
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• v.11 no.1
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• pp.47-58
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• 2002

This paper presents a new method for the evaluation of avoided generation costs. Unlike conventional load decrement method, it exactly considers forced outage rate and economic loading order of IPPs (Independent Power Producers). Therefore we can provide exact generation avoided costs of IPPs by the developed method. Because probabilistic simulation is conducted in this method, effects on the costs of IPPs are exactly considered. Also we suggest an allocation method of avoided generation costs by participation factor. In the case studies we have shown avoided generation costs considering loading order and forced out-age rate by using this method.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.499-504
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• 1996

Current Probabilistic Safety Assessment (PSA) techniques are not usually utilized for day-to-day applications in nuclear power plants. The major reason for this anomaly is the complexity of plant models developed for PSA studies and the multitude of resulting fault trees. This impediment can be overcome by the use of simplified plant models. However, oversimplified models usually result in loss of valuable information and therefore. simplification approaches have to be used judiciously in order to achieve accurate and meaningful results. For this reason. development of an appropriate simplification approach must be performed using extreme caution followed with results verification in sequence as well as system levels. If there are no significant differences between the simplified and the original models, the simplified model can be efficiently used in the application of the PSA. This paper presents a methodology for how to develop a suitable simplification technique and the results of its verification for sample systems and sequences. The results show that the utilization of simplified plant models will significantly reduce the number of fault trees with no significant loss of accuracy.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.910-917
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• 2016

Sensors have limited resources in sensor networks, so efficient use of energy is important. Representative clustering methods, LEACH, LEACHC, TEEN generally use direct transmission methods from cluster headers to the sink node to pass collected data. However, the communication distance of the sensor nodes at low cost and at low power is not long, it requires a data transfer through the multi-hop to transmit data to the sink node. In the existing cluster-based sensor network studies, cluster process and route selection process are performed separately in order to configure the routing path to the sink node. In this paper, in order to use the energy of the sensor nodes that have limited resources efficiently, a cluster-based multi-hop routing protocol which merges the clustering process and routing process is proposed. And the proposed method complements the problem of uneven cluster creation that may occur in probabilistic cluster methods and increases the energy efficiency of whole sensor nodes.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.127_128
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• 2009

A new technique using a search method which is based on fuzzy multi-criteria function is proposed for GMS(generator maintenance scheduling) in order to consider multi-objective function. Not only minimization of probabilistic production cost but also maximization of system reliability level are considered for fuzzy multi-criteria function. To obtain an optimal solution for generator maintenance scheduling under fuzzy environment, fuzzy multi-criteria relaxation method(fuzzy search method) is used. The practicality and effectiveness of the proposed approach are demonstrated by simulation studies for a real size power system model in Korea in 2010.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1826-1835
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• 2007

In this paper, we present a new approach for automatic detection and tracking for multiple targets. We combine a highest probability data association(HPDA) algorithm for target detection with a particle filter for multiple target tracking. The proposed approach evaluates the probabilities of one-to-one assignments of measurement-to-track and the measurement with the highest probability is selected to be target- originated, and the measurement is used for probabilistic weight update of particle filtering. The performance of the proposed algorithm for target tracking in clutter is compared with the existing clustering algorithm and the sequential monte carlo method for probability hypothesis density(SMC PHD) algorithm for multi-target detection and tracking. Computer simulation studies demonstrate that the HPDA algorithm is robust in performing automatic detection and tracking for multiple targets even though the environment is hostile in terms of high clutter density and low target detection probability.