• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.95-126
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• 2009

The present contribution addresses the parallelization of advanced simulation methods for structural reliability analysis, which have recently been developed for large-scale structures with a high number of uncertain parameters. In particular, the Line Sampling method and the Subset Simulation method are considered. The proposed parallel algorithms exploit the parallelism associated with the possibility to simultaneously perform independent FE analyses. For the Line Sampling method a parallelization scheme is proposed both for the actual sampling process, and for the statistical gradient estimation method used to identify the so-called important direction of the Line Sampling scheme. Two parallelization strategies are investigated for the Subset Simulation method: the first one consists in the embarrassingly parallel advancement of distinct Markov chains; in this case the speedup is bounded by the number of chains advanced simultaneously. The second parallel Subset Simulation algorithm utilizes the concept of speculative computing. Speedup measurements in context with the FE model of a multistory building (24,000 DOFs) show the reduction of the wall-clock time to a very viable amount (<10 minutes for Line Sampling and ${\approx}$ 1 hour for Subset Simulation). The measurements, conducted on clusters of multi-core nodes, also indicate a strong sensitivity of the parallel performance to the load level of the nodes, in terms of the number of simultaneously used cores. This performance degradation is related to memory bottlenecks during the modal analysis required during each FE analysis.

• Earthquakes and Structures
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• v.11 no.4
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• pp.701-721
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• 2016

Base isolation is a well-established passive strategy for seismic response control of buildings. In this paper, an efficient framework is proposed for reliability-based design optimization (RBDO) of isolated buildings subjected to uncertain earthquakes. The framework uses reduced function evaluations method, as an efficient tool for structural reliability analysis, and an efficient optimization algorithm for optimal structural design. The probability of failure is calculated considering excessive base displacement, superstructure inter-storey drifts, member stress ratios and absolute accelerations of floors of the isolated building as failure events. The behavior of rubber bearing isolators is modeled using nonlinear hysteretic model and the variability of future earthquakes is modeled by applying a probabilistic approach. The effects of pulse component of stochastic near-fault ground motions, fixity-factor of semi-rigid beam-to-column connections, values of isolator parameters, earthquake magnitude and epicentral distance on the performance and safety of semi-rigidly connected base-isolated steel framed buildings are studied. Suitable RBDO examples are solved to illustrate the results of investigations.

• Journal of Computing Science and Engineering
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• v.10 no.3
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• pp.75-84
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• 2016

Medical cyber-physical systems (MCPS) integrate sensors, actuators, and software to improve patient safety and quality of healthcare. These systems introduce major challenges to safety analysis because the patient's physiology is complex, nonlinear, unobservable, and uncertain. To cope with the challenge that unidentified physiological parameters may exhibit short-term variances in certain clinical scenarios, we propose a novel run-time predictive safety monitoring technique that leverages a maximal model coupled with online training of a computational virtual subject (CVS) set. The proposed monitor predicts safety-critical events at run-time using only clinically available measurements. We apply the technique to a surgical glucose control case study. Evaluation on retrospective real clinical data shows that the algorithm achieves 96% sensitivity with a low average false alarm rate of 0.5 false alarm per surgery.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.467-482
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• 2004

One of the uncertain damage parameters to jeopardize the safety of existing PSC bridges is the loss of the prestress force. A substantial prestress-loss can lead to severe problems in the serviceability and safety of the PSC bridges. In this paper, a nondestructive method to detect prestress-loss in beam-type PSC bridges using a few natural frequencies is presented. An analytical model is formulated to estimate changes in natural frequencies of the PSC bridges under various prestress forces. Also, an inverse-solution algorithm is proposed to detect the prestress-loss by measuring the changes in natural frequencies. The feasibility of the proposed approach is evaluated using PSC beams for which a few natural frequencies were experimentally measured for a set of prestress-loss cases. Numerical models of two-span continuous PSC beams are also examined to verify that the proposed algorithm works on more complicated cases.

• Nuclear Engineering and Technology
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• v.19 no.4
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• pp.249-265
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• 1987

For the probabilistic risk assessment of the high level radioactive waste repository, some methods have been proposed up to now. Since the system has highly uncertain input parameters, the evaluated risk for some input parameter values has high uncertainty. In this paper, methods of uncertainty and sensitivity analysis are devised to analyse systematically these factors and applied to a probabilistic risk assessment model of the high level waste repository, The statistical package SPUSA developed through this study can be used for any other fields, e.g., statistical thermal margin analysis, source term uncertainty analysis, etc.

• Structural Engineering and Mechanics
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• v.20 no.5
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• pp.527-542
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• 2005

The main objective of this study is to examine the accuracy of the complete quadratic combination (CQC) rule with the modal responses defined by the ordinates of the uniform hazard spectra (UHS) to evaluate the peak responses of the multi-degree-of-freedom (MDOF) systems subjected to nonstationary seismic excitations. For the probabilistic analysis of the peak responses, it is considered that the seismic excitations can be modeled using evolutionary power spectra density functions with uncertain model parameters. More specifically, a seismological model and the Kanai-Tajimi model with the boxcar or the exponential modulating functions were used to define the evolutionary power spectral density functions in this study. A set of UHS was obtained based on the probabilistic analysis of transient responses of single-degree-of-freedom systems subjected to the seismic excitations. The results of probabilistic analysis of the peak responses of MDOF systems were obtained, and compared with the peak responses calculated by using the CQC rule with the modal responses given by the UHS. The comparison seemed to indicate that the use of the CQC rule with the commonly employed correlation coefficient and the peak modal responses from the UHS could lead to significant under- or over-estimation when contributions from each of the modes are similarly significant.

• Journal of the Earthquake Engineering Society of Korea
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• v.2 no.3
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• pp.83-86
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• 1998

The results from the Individual Plant Examination of External Event of Yonggwyang nuclear power plants, unit 3 & 4, in Korea have shown that the high degree of diversities of the experts' opinions on seismicity and attenuation models is su, pp.sed to be generic cause of uncertainty of APEs(annual exceedance probability) in the PAHA(probabilistic seismic hazard analysis). This study investigated the sensitivity of the focal depth, which is one of the most uncertain seismicity parameters in Korea, Significant differences in resultant values of annual exceedance probabilities and much more symmetrical shape of the resultant PDFs(probability density functions), in case of consideration of focal depth, are found. These two results suggest that, even for the same seismic input data set including the seismicity models and ground motion attenuation models, to consider focal depth additionally for probabilistic seismic hazard analysis evaluation makes significant influence on the distributions of uncertainties and probabilities of exceedance per year for the whole ranges of seismic hazard levels. These facts suggest that it is necessary to derive focal depth parameter more effectively from the historical and instrumental documents on earthquake phenomena in Koran Peninsula for the future study of PSHA.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.43-52
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• 1997

Ultrasonic sensors are widely employed in detecting range to a target by the virtue of their low cost and simplicity. However, the sensor's measurements are corrupted by systematic errors due mainly to the dependency of sound speed upon surrounding conditions and random errors of uncertain origin. In this paper, we present the results of research carried out to reduce these errors for increasing the reliability of an untrasonic sensor system to be used in orbotic or other automated system's range finding. The sensor system designed herein is in a peuliar structure having a reference target and two receivers. Echoes from a small reference target placed at a known distance are used for compensating the variations of sound speed according to the changes of sensing conditions. Unlike existing ones, the technique proposed can compensate the effects of temperature or any other physical parameters without an additional sensor dedicated to the compensation. The measurements by two redundantly employed receivers are fused to reduce random errors in a statistical sense. The correlation of the signals from the receivers sharing a hardware in part is considered in the fusion process. The methodology desicribed in this paepr is conceptually simple, easy to be implemented, and effetive to increase the accuracy of the sensor measurements as experimental results confirm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.211-216
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• 2004

In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.432-441
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• 2000

This paper deals with the fuzzy modeling for the complex and uncertain nonlinear systems, in which conventional and mathematical models may fail to give satisfactory results. Genetic algorithm has been used to identifY parameters and structure of fuzzy model because it has the ability to search optimal solution somewhat globally. The genetic algorithm, however, has a problem, which optimization process can be premature convergence in the case of lack of genetic divergence of population. Virus- evolutionary genetic algorithm(VEGA) could be a strategy against this local convergence. Therefore, we use VEGA for fuzzy modeling. In this method, local information is exchanged in population so that population can sustain genetic divergence. finally, to prove the theoretical hypothesis, we provide numerical examples to evaluate the feasibility and generality of fuzzy modeling using VEGA.