• Earthquakes and Structures
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• v.16 no.5
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• pp.523-532
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• 2019

Different types of gas reservoir such as Liquid Natural Gas (LNG) are among the strategic infrastructures, and have great importance for any government or their private owners. To keep the tank and its contents safe during earthquakes especially if the contents are of hazardous or flammable materials; using seismic protection systems such as base isolator can be considered as an effective solution. However, the major deficiency of this system can be the large deformation in the isolation level which may lead to the failure of bearing system. In this paper, as a solution, the efficacy of an optimally designed combined vibration control system, the combined laminated rubber isolator and rotational friction damper, is investigated to evaluate the enhancement of an existing metal tank response under both far- and near-field earthquakes. Responses like impulsive and convective accelerations, base shear, and sloshing height are studied herein. The probabilistic framework is used to consider the uncertainties in the structural modeling, as well as record-to-record variability. Due to the high calculation cost of probabilistic methods, a simplified structural model is used. By using the Mont-Carlo simulation approach, it is revealed that this combined isolation system is a highly reliable system which provides considerable enhancement in the performance of reservoir, not only leads to the reduction of probability of catastrophic failure of the tank but also decrease the reservoir damage during the earthquake. Moreover, the relative displacement of the isolation level is controlled very well by this combined system.

• Geomechanics and Engineering
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• v.23 no.1
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• pp.15-30
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• 2020

The probabilistic bearing capacity of a strip footing placed on the edge of a purely cohesive reinforced soil slope is computed by combining lower bound finite element limit analysis technique with random field method and Monte Carlo simulation technique. To simulate actual field condition, anisotropic random field model of undrained soil shear strength is generated by using the Cholesky-Decomposition method. With the inclusion of a single layer of reinforcement, dimensionless bearing capacity factor, N always increases in both deterministic and probabilistic analysis. As the coefficient of variation of the undrained soil shear strength increases, the mean N value in both unreinforced and reinforced slopes reduces for particular values of correlation length in horizontal and vertical directions. For smaller correlation lengths, the mean N value of unreinforced and reinforced slopes is always lower than the deterministic solutions. However, with the increment in the correlation lengths, this difference reduces and at a higher correlation length, both the deterministic and probabilistic mean values become almost equal. Providing reinforcement under footing subjected to eccentric load is found to be an efficient solution. However, both the deterministic and probabilistic bearing capacity for unreinforced and reinforced slopes reduces with the consideration of loading eccentricity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3689-3700
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• 2016

It is not practically feasible to apply hardware-based fault-tolerant schemes, such as hardware replication, in mobile devices. Therefore, software-based fault-tolerance techniques, such as checkpoint and rollback schemes, are required. In checkpoint and rollback schemes, the optimal checkpoint interval should be applied to obtain the best performance. Most previous studies focused on minimizing the expected execution time or response time for completing a given task. Currently, most mobile applications run in real-time environments. Therefore, it is extremely essential for mobile devices to employ optimal checkpoint intervals as determined by the real-time constraints of tasks. In this study, we tackle the problem of determining the optimal inter-checkpoint interval of checkpoint and rollback schemes to maximize the deadline meet ratio in real-time systems and to build a probabilistic cost model. From this cost model, we can numerically find the optimal checkpoint interval using mathematical tools. The performance of the proposed solution is evaluated using analytical estimates.

• Journal of Korean Society on Water Environment
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• v.25 no.1
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• pp.112-119
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• 2009

Based on the study of soil water dynamics, this study is to suggest an advanced stochastic soil water model for future study for drought application. One distinguishable remark of this study is the derivation of soil water dynamic controling equation for 3-stage loss functions in order to understand the temporal behaviour of soil water with reaction to the precipitation. In terms of modeling, a model with rather simpler structure can be applied to regenerate the key characteristics of soil water behavior, and especially the probabilistic solution of the derived soil water dynamic equation can be helpful to provide better and clearer understanding of soil water behavior. Moreover, this study will be the future cornerstone of applying to more realistic phenomenon such as drought management.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.6
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• pp.1448-1454
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• 1994

Data which gathered and used in the field of fatigue and fracture mechanics have a lot of uncertainties. In this case, those uncertainties will make scatter band in evaluation of fatigue life and fracture toughness. Thus, the probabilistic analysis of these data will be needed. For determining the fatigue life in mixed mode, using crack direction law and fatigue crack growth law, the problem is studied as a constrained life minimization. Stress intensity factor(SIF) is computed by approximate solution table(Ewalds/Wanhill 1984) and 0th order PFEM. The variance of fatigue life and SIF are computed by differentiation of tabulated approximate solution and 1st order PFEM. And these are used for criterion of design values, principal parameter determination and modelling. The problem of center cracked plate is solved for checking the PFEM model which is influenced by various parameters like as initial crack length, final crack length, two fatigue parameters in Paris Equation and applied stress.

• The Journal of Korea Robotics Society
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• v.1 no.1
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• pp.46-57
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• 2006

It is well known that mathematical solutions for multi-agent planning problems are very difficult to obtain due to the complexity of mutual interactions among multi-agent. Most of the past research results thus are based on the probabilistic completeness. However, the practicality and effectiveness of the solution from the probabilistic completeness is significantly reduced by heavy computational burden. In this paper, we propose a practically applicable solution technique for multi-agent planning problems, which assures a reasonable computation time and a real world application for more than 3 multi-agents for the case of general shaped paths in agent movement. First, to reduce the computation time, a collision map is utilized for detecting potential collisions and obtaining collision-free solutions for multi-agents. Second, to minimize the maximum of multi-agent task execution time, a method is developed for selecting an optimal priority order. Simulations are finally provided for more than 20 agents to emphasize the effectiveness of the proposed interactive approach to multi-agent planning problems.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.1
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• pp.119-131
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• 1988

Vehicle Scheduling Problem (VSP) is a generic name given to a whole class of problems involving the visiting of "stations" by "vehicles," where a time is associated with each activity. The studies performed to date have the common feature of a single objective while satisfying a set of restrictions and known customer supplies or demands. However, VSPs may involve relevant multiple objectives and probabilistic supplies or demands at stations, creating multicriteria stochastic VSPs. This paper proposes a heuristic algorithm based on goal programming approach to schedule the most satisfactory vehicle routes of a bicriteria VSP with probabilistic supplies at stations. The two relevant objectives are the minimization of the expected travel distance of vehicles and the minimization of the due time violation for collection service at stations by vehicles. The algorithm developed consists of three major stages. In the first stage, an artificial capacity of vehicle is determined, on the basis of decision maker's subjective estimates. The second one clusters a set of stations into subsets by applying an efficient cluster method developed. In the third one, the stations in each subset are scheduled by applying an iterative goal programming heuristic procedure to each cluster.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.1148-1154
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• 2006

Composite discharge capacity tests and smear effect tests are carried out to estimate the parameters for the reliability-based design of vertical drain method. Also the probabilistic and deterministic solutions of radial consolidation theory are presented. It compared to the result of reliability-based design and that of deterministic design using the tested and estimated parameters. The results indicated that the drain spacing is larger the deterministic method than the probabilistic method because the former is not considered the uncertainties in the properties of soil. The divergence of methods is dependent on the probability of achieving target degree of consolidation by a given time and the coefficient of variation(COV) of the coefficient of horizontal consolidation$(c_h)$.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1075-1086
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• 2018

In this paper a cross-validation algorithm for training probabilistic neural networks (PNNs) is presented in order to be applied to automatic face identification. Actually, standard PNNs perform pretty well for small and medium sized databases but they suffer from serious problems when it comes to using them with large databases like those encountered in biometrics applications. To address this issue, we proposed in this work a new training algorithm for PNNs to reduce the hidden layer's size and avoid over-fitting at the same time. The proposed training algorithm generates networks with a smaller hidden layer which contains only representative examples in the training data set. Moreover, adding new classes or samples after training does not require retraining, which is one of the main characteristics of this solution. Results presented in this work show a great improvement both in the processing speed and generalization of the proposed classifier. This improvement is mainly caused by reducing significantly the size of the hidden layer.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.4
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• pp.249-255
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• 2016

Recently, transaction data is accumulated everywhere very rapidly. Association analysis methods are usually applied to analyze transaction data, but the methods have several problems. For example, these methods can only consider one-way relations among items and cannot reflect domain knowledge into analysis process. In order to overcome defect of association analysis methods, we suggest a transaction data analysis method based on probabilistic graphical model (PGM) in this study. The method we suggest has several advantages as compared with association analysis methods. For example, this method has a high flexibility, and can give a solution to various probability problems regarding the transaction data with relationships among items.