• Computational Structural Engineering
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• v.7 no.4
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• pp.145-150
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• 1994

Seismic isolation in ordinary buildings has been successively adapted to provide flexibility for the reduction of base shear forces and its concept is accepting wide agreement in lengthening the natural, period to lessen the spectral acceleration transmitted into the structure. However, one of difficulties in implementing the innovative concept to nuclear structures is due to more severe requirements in both understanding and predicting the characteristics of isolators and the behavior of cushioned structures, Stochastic analysis has been carried out to investigate the response of base isolated nuclear containers to the random earthquake ground motion.

• International Journal of Reliability and Applications
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• v.13 no.1
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• pp.1-17
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• 2012

This Paper deals with the stochastic behavior and failure analysis of a Viscose Staple Fibre Plant which produces fibre for making clothes. The fibre making plant is a complex system with various subsystems as: Vendor (supplies Charcoal and Sulphur, raw materials for the process), Carbon di sulphide Plant, Acid Plant, Pulp Plant and Processing Plant. The considered system can completely fail due to failure of any of the subsystems. The Carbon di Sulphide Plant can fail in two different ways, due to lack of Sulphur or Charcoal. Processing Plant has the configuration 5-out-of-10: d and 6-out-of-10: f. It is also assumed that the system can fail due to workers strike and catastrophic failure. All failures follow exponential time distribution whereas all repairs follow general time distribution. Preventive Maintenance policy has been applied to reduce the failure in the system. Various reliability characteristics such as transition state probabilities, steady state behavior, reliability, availability, M.T.T.F and the cost analysis have been obtained using supplementary variable technique and Gumbel-Hougaard copula methodology.

• Water for future
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• v.23 no.1
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• pp.99-107
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• 1990

The statistical analysis based on the past hydrologic data required to set up the water resources development plan and design the hydraulic structres rationally. Because hydrologic events have random factors implied, the sotchastic analysis is necessary. In this paper, same order of stochastic models of monthly runoff data(multivariate AR(1) and AR(2) models, univariate AR(1) and AR(2) models) are applied to compare the statistical characteristics. The other purpose of this paper is to compare the monthly series, which is generated by univariate and multivariate models. By comparing and estimating of each simulated series, it is known that the multivariate models, including the time and spatial colinearity, are better in prediction than univariate models in the analysis of monthly flow at south Han river basin.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.251-256
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• 2006

In the work package 'Integrated Positioning' of the research project NAVIO (Pedestrian Navigation Systems in Combined Indoor/Outdoor Environements) we are dealing with the navigation and guidance of visitors of our University. Thereby start points are public transport stops in the surroundings of the Vienna University of Technology and the user of the system should be guided to certain office rooms or persons. For the position determination of the user different location sensors are employed, i.e., for outdoor positioning GPS and dead reckoning sensors such as a digital compass and gyro for heading determination and accelerometers for the determination of the travelled distance as well as a barometric pressure sensor for altitude determination and for indoor areas location determination using WiFi fingerprinting. All sensors and positioning methods are combined and integrated using a Kalman filter approach. Then an optimal estimate of the current location of the user is obtained using the filter. To perform an adequate weighting of the sensors in the stochastic filter model, the sensor characteristics and their performance was investigated in several tests. The tests were performed in different environments either with free satellite visibility or in urban canyons as well as inside of buildings. The tests have shown that it is possible to determine the user's location continuously with the required precision and that the selected sensors provide a good performance and high reliability. Selected tests results and our approach will be presented in the paper.

• International Journal of Automotive Technology
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• v.8 no.5
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• pp.623-628
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• 2007

Reliability analysis based on fracture mechanics requires knowledge of the on statistical parameters m and C in the fatigue crack growth law $da/dN=C({\Delta}K)^m$. The purpose of the present study is to investigate if it is possible to explain the change of parameter m by the fluctuation of C only. In this study, we apply the Paris-Erdogan law treating the parameter C as random and the parameter m as constant. Fluctuations in crack growth rate are assumed to be dependent only on C. The material resistance to fatigue crack growth(Z=1/C) is treated as a spatially random process, that varies along the crack path. The theoretical crack growth rates at various stress intensity factors are discussed. Additionally, the results of constant ${\Delta}K$ fatigue crack growth tests are reported for the structural steel, SM45C. The experimental data have been analyzed to determine the probability distribution of fatigue crack growth resistanc.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.11
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• pp.989-995
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• 2015

In the literature, various stochastic anomaly detection methods, such as limit checking and PCA-based approaches, have been applied to weld defect detection. However, it is still a challenge to identify meaningful defect patterns from very limited sensor signals of laser welding, characterized by intermittent, discontinuous, very short, and non-stationary random signals. In order to effectively analyze the physical characteristics of laser weld signals: plasma intensity, weld pool temperature, and back reflection, we first transform the raw data of laser weld signals into the form of event logs. This is done by multidimensional discretization and event-codification, after which the event logs are decoded to extract weld defect patterns by $Na{\ddot{i}}ve$ Bayes classifier. The performance of the proposed method is examined in comparison with the commercial solution of PRECITEC's LWM$^{TM}$ and the most recent PCA-based detection method. The results show higher performance of the proposed method in terms of sensitivity (1.00) and specificity (0.98).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4724-4747
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• 2016

To efficiently reduce on-grid energy consumption, the admission control algorithm in the hybrid energy powered cellular network (HybE-Net) with base stations (BSs) powered by on-grid energy and solar energy is studied. In HybE-Net, the fluctuation of solar energy harvesting and energy consumption may result in the imbalance of solar energy utilization among BSs, i.e., some BSs may be surplus in solar energy, while others may maintain operation with on-grid energy supply. Obviously, it makes solar energy not completely useable, and on-grid energy cannot be reduced at capacity. Thus, how to control user admission to improve solar energy utilization and to reduce on-grid energy consumption is a great challenge. Motivated by this, we first model the energy flow behavior by using stochastic queue model, and dynamic energy characteristics are analyzed mathematically. Then, fuzzy logic based admission control algorithm is proposed, which comprehensively considers admission judgment parameters, e.g., transmission rate, bandwidth, energy state of BSs. Moreover, the index of solar energy utilization balancing is proposed to improve the balance of energy utilization among different BSs in the proposed algorithm. Finally, simulation results demonstrate that the proposed algorithm performs excellently in improving solar energy utilization and reducing on-grid energy consumption of the HybE-Net.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.1
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• pp.42-49
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• 2021

As a measure of susceptibility on the combustion instability, thermo-acoustic instabilities in rocket combustion system was considered for the estimation of the operational stability margin. Growth rate, which governs the asymptotic stability behavior of the system, was determined from the dynamic data measured during combustion tests in order to understand the dynamic characteristics of combustor system. Frequency transform technique was first applied to determine the system parameters such as growth rate and/or damping coefficient for an interested mode from the time series pressure data, and the PDFs of pressure amplitude were extracted from the amplitude envelope of pressure oscillation for the stochastic analysis.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1304-1310
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• 2021

Two-phase flow, especially gas-liquid two-phase flow, has a wide application in industrial field. The diagnosis of two-phase flow parameters, which directly determine the flow and heat transfer characteristics, plays an important role in providing the design reference and ensuring the security of online operation of two-phase flow system. Computer tomography (CT) is a good way to diagnose such parameters with imaging method. This paper has proposed a novel image reconstruction method for thermal neutron CT of two-phase flow with improved simulated annealing (ISA) algorithm, which makes full use of the prior information of two-phase flow and the advantage of stochastic searching algorithm. The reconstruction results demonstrate that its reconstruction accuracy is much higher than that of the reconstruction algorithm based on weighted total difference minimization with soft-threshold filtering (WTDM-STF). The proposed method can also be applied to other types of two-phase flow CT modalities (such as X(𝛄)-ray, capacitance, resistance and ultrasound).

• Composites Research
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• v.22 no.6
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• pp.18-22
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• 2009

In this paper, we examined impact force and impact behavior through low velocity impact tests of composite laminates. And through c-scan as nondestructive inspection, explored the damaged area being difficult to examine with the visual inspection. Through CAI tests, we also measured the compression strength of composite laminates subjected to low velocity impact. To examine the characteristics of impact behavior measured from low velocity impact test, nondestructive inspection, and CAI test, the simulated data are generated from the test data using Monte-Carlo simulation, then represented it by probability distribution. The testing results using visible stochastic distribution were examined and compared.