• Structural Engineering and Mechanics
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• v.41 no.4
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• pp.527-538
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• 2012

In seismic analyses of structures, additional eccentricity is introduced to take account for oscillations of random and unknown origins. In many codes of practice, the torsion about the vertical axis is considered through empirical accidental eccentricity formulation. Due to the random nature of structural systems, it is very difficult to evaluate the accidental eccentricity in a deterministic way and to specify its effect on the overall seismic response of structures. The aim of this study is to develop a procedure for the evaluation of the accidental eccentricity induced by uncertainties in stiffness and mass of structural members, using the neural network techniques coupled with Monte Carlo simulations. This method gives very interesting results for single story structures. For real structures, this method can be used as a tool to determine the accidental eccentricity in the seismic vulnerability studies of buildings.

• Journal of the Korean Institute of Landscape Architecture
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• v.23 no.1
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• pp.23-38
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• 1995

ELEECTRE is a less demanding and potentially Bffective multiattribute evaluation method for pre-editing proeedure. The method, however, was developed based on probabilistic mathematicsand its reliability has never'been emprieally tested. This article examined the reliability of ELECTRo under various conditions of linear and non-linear utility func- tions using a Monte-Carlo shnulation, and found the method eausea a considerably high rate of error. To enhance the reliability of ELECTRE, two ways of modi(ication - adjust- ment of threshold values of concordance and discordance matrices, and adjustment of the required nunlber of probably-dominant alternatives to eliminate a probably-dominated alternative - were suggested, and their effctiveness was also tesed by a Monte-Carlo simulation. The simulation result chows that these modifications cponsiderably improve the reliability of ELECTRE, and yet maintain a reasonably high level of efficiency. Through these modifications, ELECTRE can be used as an efficient and feliable pre-editing method. Ways to implement ELECTRE in the construction of plainning decision support systens were discussed. The impli(els combination of this method and other multiattribute evaluation methods will help to create more effective decision suport systems.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.7
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• pp.647-656
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• 2014

To supplement the ISO-GUM method for the evaluation of measurement uncertainty, a simulation program using the Monte Carlo method (MCM) was developed, and the MCM and GUM methods were compared. The results are as follows: (1) Even under a non-normal probability distribution of the measurand, MCM provides an accurate coverage interval; (2) Even if a probability distribution that emerged from combining a few non-normal distributions looks as normal, there are cases in which the actual distribution is not normal and the non-normality can be determined by the probability distribution of the combined variance; and (3) If type-A standard uncertainties are involved in the evaluation of measurement uncertainty, GUM generally offers an under-valued coverage interval. However, this problem can be solved by the Bayesian evaluation of type-A standard uncertainty. In this case, the effective degree of freedom for the combined variance is not required in the evaluation of expanded uncertainty, and the appropriate coverage factor for 95% level of confidence was determined to be 1.96.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.154-160
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• 2001

For major structural components periodic inspections and integrity assessments are needed for the safety. However, many flaws are undetectable because sampling inspection is carried out during in-service inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties and undetectable cracks. This paper describes a Probabilistic Fracture Mechanics(PFM) analysis based on the Monte Carlo(MC) algorithms. Taking a number of sampling data of probabilistic variables such as fracture toughness value, crack depth and aspect ratio of an initial surface crack, a MC simulation of failure judgement of samples is performed. for the verification of this analysis, a comparison study of the PFM analysis using a commercial code, mathematical method is carried out and a good agreement was observed between those results.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.8
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• pp.24-32
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• 2006

Using a deterministic design optimization, the effect of uncertainty can result in violation of constraints and deterioration of performances. For this reason, design optimization is required to guarantee reliability for constraints and ensure robustness for an objective function under uncertainty. Therefore, this study drew Monte Carlo Simulation(MCS) for the evaluation of reliability and robustness, and selected an artificial neural network as an approximate model that is suitable for MCS. Applying to the aero-structural optimization problem of aircraft wing, we can explore robuster optima satisfying the sigma level of reliability than the baseline.

• Nuclear Engineering and Technology
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• v.51 no.8
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• pp.1998-2004
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• 2019

The Multi-Physics (MP) instrument is one of 20 neutron spectrometers planned in the China Spallation Neutron Source (CSNS). This paper presents a shielding calculation for the MP instrument using Monte Carlo codes MCNPX and FLUKA. First, the neutrons that escape from the CSNS decoupled water moderator and are delivered to the beam line of the MP instrument are calculated to use as the source term of the shielding calculation. Then, to validate the calculation method based on multiple variance reduction techniques, a cross check between MCNPX and FLUKA codes is performed by comparing the calculation results of the dose rate distribution on a simplified beam line model. Finally, a complete geometry model of the MP instrument is set up, and the primary parameters for the shielding design are obtained according to the calculated dose rate map considering different worst-case scenarios.

• The Journal of Information Systems
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• v.17 no.3
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• pp.25-37
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• 2008

In a fault tree analysis, an uncertainty importance measure is often used to assess how much uncertainty of the top event probability (Q) is attributable to the uncertainty of a basic event probability ($q_i$), and thus, to identify those basic events whose uncertainties need to be reduced to effectively reduce the uncertainty of Q. For evaluating the measures suggested by many authors which assess a percentage change in the variance V of Q with respect to unit percentage change in the variance $v_i$ of $q_i$, V and ${\partial}V/{\partial}v_i$ need to be estimated analytically or by Monte Carlo simulation. However, it is very complicated to analytically compute V and ${\partial}V/{\partial}v_i$ for large-sized fault trees, and difficult to estimate them in a robust manner by Monte Carlo simulation. In this paper, we propose a method for evaluating the measure using discretization technique and Monte Carlo simulation. The proposed method provides a stable uncertainty importance of each basic event.

• Journal of Korea Game Society
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• v.18 no.5
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• pp.77-82
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• 2018

Go is the most complex board game in which the computer can not search all possible moves using an exhaustive search to find the best one. Prior to AlphaGo, all powerful computer Go programs have used the Monte-Carlo Tree Search (MCTS) to overcome the difficulty in positional evaluation and the very large branching factor in a game tree. In this paper, we tried to find the best sequence of moves using an MCTS on a very small Go board. We found that a $2{\times}2$ Go game would be ended in a tie and the size of Komi should be 0 point; Meanwhile, in a $3{\times}3$ Go Black can always win the game and the size of Komi should be 9 points.

• Journal of Welding and Joining
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• v.23 no.6
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• pp.61-66
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• 2005

A probabilistic approach for evaluating failure risk is suggested in this paper. Probabilistic fracture analyses were performed for a pressurized pipe of a Cr-Mo steel reflecting variation of material properties at high temperature. A crack was assumed to be located along the weld fusion line. Probability density functions of major variables were determined by statistical analyses of material creep and creep crack growth data measured by the previous experimental studies by authors. Distributions of these variables were implemented in Monte Carlo simulation of this study. As a fracture parameter for characterizing growth of a fusion line crack between two materials with different creep properties, $C_t$ normalized with $C^*$ was employed. And the elapsed time was also normalized with tT, Resultingly, failure probability as a function of operating time was evaluated fur various cases. Conventional deterministic life assessment result was turned out to be conservative compared with that of probabilistic result. Sensitivity analysis for each input variable was conducted to understand the most influencing variable to the analysis results. Internal pressure, creep crack growth coefficient and creep coefficient were more sensitive to failure probability than other variables.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.406-412
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• 2010

In this paper, we formally define the problem of maximizing the coverage of sensor deployment, which is the optimization problem appeared in real-world sensor deployment, and analyze the properties of its solution space. To solve the problem, we proposed novel genetic algorithms, and we could show their superiority through experiments. When applying genetic algorithms to maximum coverage sensor deployment, the most important issue is how we evaluate the given sensor deployment efficiently. We could resolve the difficulty by using Monte Carlo method. By regulating the number of generated samples in the Monte Carlo evaluation of genetic algorithms, we could also reduce the computing time significantly without loss of solution quality.