• Structural Engineering and Mechanics
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• v.54 no.1
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• pp.149-168
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• 2015

In the bolted connections, bolt placements are generally described and are generally made in the direction of design effects and in the perpendicular direction to design effects. In these both directions, the reliability of the distance of bolts to the edges of connection plate and the distance of bolts to each other is investigated for high strength steel connections built up with high strength bolts in this study. For this purpose, simple SL (bearing type shear connection) and SLP (bearing type shear connection for body-fit bolts) type steel connections with St 52 grade steel plates with 8 different thicknesses and with 8.8D grade high strength bolts (HV) were constituted and analyzed under H (Dead Loads+Live Loads+Snow Loads+Roof Loads) and HZ (H Loads+Wind Loads+Earthquake Loads) loadings. Geometric properties, material properties and design actions were taken as random variables. Monte Carlo Simulation method was used to compute failure risk and the first order second moment method was used to determine the reliability indexes of those different distances describing the placement of bolts. Results obtained from computations have been presented in graphics and in a Table. Then, they were compared with some values proposed by some structural codes. Finally, new equations were constituted for minimum and maximum values of distances describing bolt placement by regression analyses performed on those results.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.331-343
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• 2019

Dynamic thermal rating of the overhead transmission lines is affected by many uncertain factors. The ambient temperature, wind speed and wind direction are the main sources of uncertainty. Measurement uncertainty is an important parameter to evaluate the reliability of measurement results. This paper presents the uncertainty analysis based on Monte Carlo. On the basis of establishing the mathematical model and setting the probability density function of the input parameter value, the probability density function of the output value is determined by probability distribution random sampling. Through the calculation and analysis of the transient thermal balance equation and the steady- state thermal balance equation, the steady-state current carrying capacity, the transient current carrying capacity, the standard uncertainty and the probability distribution of the minimum and maximum values of the conductor under 95% confidence interval are obtained. The simulation results indicate that Monte Carlo method can decrease the computational complexity, speed up the calculation, and increase the validity and reliability of the uncertainty evaluation.

• Journal of Radiation Industry
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• v.7 no.2_3
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• pp.115-119
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• 2013

The density profile measurement technology by gamma transmission has been widely used to diagnose processes in the field of refinery and petrochemical industry. This technology can reveal a clue and position of abnormal phenomenon of industrial processes during their operation. In this paper, the feasibility of the gamma transmission technology for detecting changes in the amount of fluid in a distillation column was evaluated by using Monte Carlo simulations. The simulations assumed that $^{60}Co$ (1.17, 1.33 MeV) sources and NaI (Tl) detectors (${\Phi}5{\times}5cm$) are located in opposite sides of a column and it concurrently moves in vertical direction. To determine the dependency of a spatial resolution on aperture size of a collimator, the simulation model for a tray in a column were simulated with the aperture sizes of 1 and 2 cm. The thickness of the high density area including a tray and fluid was 7.6 cm in the simulation. The spatial resolution of the tray was 8.2 and 8.5 cm, respectively. As a result, it was revealed that the conventional density profile measurement technique is not able to show the deviation of liquid level on a tray in a column.

• Journal of Biomedical Engineering Research
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• v.15 no.1
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• pp.71-76
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• 1994

In the source localization using single dipole model, the influence of the number of electrodes, the position and direction of a single dipole on the relation between S/W ratio and dipole parameter estimation errors is important. Monte Carlo simulation was used to investigate this influence. The forward problem was calculated using three spherical shell model, and dipole parameters were optimized by means of simplex method. As the number of electrodes became large, as the dipole went from midbrain to cortex, and as the direction of dipole changed from radial to tangential, the average and standard deviation of estimation errors became small.

• Smart Structures and Systems
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• v.21 no.5
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.

• Computational Structural Engineering
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• v.3 no.2
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• pp.109-115
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• 1990

The probabilistic characteristics of wind loads have been analyzed using statistical data on wind speeds, pressure coefficient, exposure coefficient, and gust factor. The wind speed data collected at 25 nationwide weather stations have been modified to be consistent in measuring height, exposure condition as well as averaging time. Having performed Monte Carlo simulation for various heights and site conditions, the statistical models of wind loads were determined, in which Type-I extreme value distribution has been applied. The models also incorporate a reduction factor of 0.85 to account for the reduced probability that the maximum wind speed will occur in a direction most unfavorable to the response of structure.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.9
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• pp.903-912
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• 2009

This study is focused on simulation-based dimensional tolerance optimization process (DTOP) to minimize vehicle pulls by reduction of dimensional variation in front suspension system. In previous studies, the effect of tires and wheel alignment sensitivity have mainly been investigated to eliminate vehicle pulls in nominal design condition without allocating optimal tolerance level for selected components, among various factors regarding vehicle pulls such as vehicle design parameters, vehicle weight balance, tires, and environmental factors. Unfortunately, there are wide variations in the real vehicle, and these have impacted actual vehicle pulls, especially wheel alignment effects from suspension geometry variation has not been considered in the previous studies. In the tolerance design of suspension, tolerance variables with the uncertainty such as parts dimensional variation, assembly process, datum position and direction, and assembly tool tolerance has a great influence on the variation of the suspension dimensional performances. This study introduces total vehicle pull prediction model in considering major key factors for vehicle pull sensitivity. The Monte Carlo-based tolerance analysis model using Taguchi robust method is developed to optimize dimensional tolerance parameters, satisfying on the target variation level.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1510-1521
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• 1996

This paper presents acquisition algorithm and an improved detection technique for the DS/CDMA (direction sequence code division multiple access) RAKE receiver in multipath fading channel. The DS/CDMA systems use the RAKE receiver, an accurate code acquisition is required for the RAKE branches. The algorithmis able to findthe pseudonoise (PN) code delay estimates for the RAKE branches in a multipath fading channel. In this paper a numerical method and computer simulation simulation have been developed for the acquisition system. The detection probability and mean acquisition time are investigated asa performance measure of the system using the Monte Carlo method. And also in order to analyze the effect of the acquisition on the RAKE receiver this paper bring out the effect of integration time, doppler frequency, processing gain and the number of users on the acquired code phase.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.161-168
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• 2004

A single-index model is useful in fields which employ multidimensional regression models. Many methods have been developed in parametric and nonparametric approaches. In this paper, posterior inference is considered and a wavelet series is thought of as a function approximated to a true function in the single-index model. The posterior inference needs a prior distribution for each parameter estimated. A prior distribution of each coefficient of the wavelet series is proposed as a hierarchical distribution. A direction $\beta$ is assumed with a unit vector and affects estimate of the true function. Because of the constraint of the direction, a transformation, a spherical polar coordinate $\theta$, of the direction is required. Since the posterior distribution of the direction is unknown, we apply a Metropolis-Hastings algorithm to generate random samples of the direction. Through a Monte Carlo simulation we investigate estimates of the true function and the direction.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.31-39
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• 2001

For estimating parameters of possibly nonlinear and/or non-stationary seasonal autoregressive(AR) processes, we introduce a new instrumental variable method which use the direction vector of the regressors in the same period as an instrument. On the basis of the new estimator, we propose new seasonal random walk tests whose limiting null distributions are standard normal regardless of the period of seasonality and types of mean adjustments. Monte-Carlo simulation shows that he powers of he proposed tests are better than those of the tests based on ordinary least squares estimator(OLSE).