• Journal of Astronomy and Space Sciences
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• v.12 no.2
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• pp.265-274
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• 1995

The purpose of perigee kick motor firing is to place a satellite into transfer orbit and that of apogee kick motor firing is to place the satellite into geosynchonous orbit in order to increase the semi-major axis of the transfer orbit and reduce the inclination of the transfer orbit. Because apogee motor firing is always accompanied with injection errors, the satellite is not placed into geosynchonous orbit but into a near-geosynchonous orbit, also knows as a drift orbit. Thus, the orbital maneuver to correct drift orbit into gteosynchonous orbit is required, this maneuver is called the station acquisition. For reduction of expenditure and performance of mission, we estimate $\Delta$V budget and required fuel allowance for station acquisition. As the uncertainty of drift orbit by injection error of perigee and apogee kick motor firing prevents us from obtaining exact $\Delta$V budget, statistical Monte Carlo simulation technique is used in order to get optimal $\Delta$V budget and required fuel allowance with a probability of 99%. With respect to Korea satellite launched by Delta-2 launch vehicle in 1995, Monte Carlo analysis is used in order to get various orbital parameters, $\Delta$V budget and required fuel allowance for station acquisition with a probability of 99%.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.80.2-80.2
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• 2012

We firstly present the unified Far-UV continuum map of the Taurus-Auriga-Perseus (TPA) complex, one of the largest local associations of dark cloud located in (l, b)=([152,180], [-28, 0]), by merging both FIMS and GALEX. The FUV continuum map shows that dust extinction correlate well with the FUV around the complex. It says strong absorption in the dense Taurus cloud and Auriga cloud. Although the column density of Perseus and California cloud is similar to Taurus' and Auriga's, Perseus and California cloud do not show strong absorption in FUV because they are more distant than Taurus and Auriga cloud. We also present the dust scattering simulation based on Monte Carlo Radiative Transfer technique. Through the result of Monte-Carlo dust scattering simulation and comparing the result with FIMS-GALEX unified map we gain deeper understanding related to the spatial dust distribution of TPA region. As a preliminary result of the simulation we present the most probable front face, thickness, albedo, and asymmetry factor in this region, respectively. Through this work we can show a certain inclination of the spatial dust distribution. During this study we have developed the FUV dust scattering simulation code using Monte-Carlo method. We expect that it will be generally used to simulate dust scattering in the Galaxy.

• Geomechanics and Engineering
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• v.3 no.3
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• pp.169-188
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• 2011

Response of buried flexible pipe-soil system is studied, through numerical analysis, with respect to deflection and buckling in a spatially varying soil media. In numerical modeling procedure, soil parameters are modeled as two-dimensional non-Gaussian homogeneous random field using Cholesky decomposition technique. Numerical analysis is performed using random field theory combined with finite difference numerical code FLAC 5.0 (2D). Monte Carlo simulations are performed to obtain the statistics, i.e., mean and variance of deflection and circumferential (buckling) stresses of buried flexible pipe-soil system in a spatially varying soil media. Results are compared and discussed in the light of available analytical solutions as well as conventional numerical procedures in which soil parameters are considered as uniformly constant. The statistical information obtained from Monte Carlo simulations is further utilized for the reliability analysis of buried flexible pipe-soil system with respect to deflection and buckling. The results of the reliability analysis clearly demonstrate the influence of extent of variation and spatial correlation structure of soil parameters on the performance assessment of buried flexible pipe-soil systems, which is not well captured in conventional procedures.

• Steel and Composite Structures
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• v.8 no.2
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• pp.129-144
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• 2008

This paper demonstrates an application of the perturbation based stochastic finite element method (SFEM) for predicting the performance of structural systems made of composite sections with random material properties. The composite member consists of materials in contact each of which can surround a finite number of inclusions. The perturbation based stochastic finite element analysis can provide probabilistic behavior of a structure, only the first two moments of random variables need to be known, and should therefore be suitable as an alternative to Monte Carlo simulation (MCS) for realizing structural analysis. A summary of stiffness matrix formulation of composite systems and perturbation based stochastic finite element dynamic analysis formulation of structural systems made of composite sections is given. Two numerical examples are presented to illustrate the method. During stochastic analysis, displacements and sectional forces of composite systems are obtained from perturbation and Monte Carlo methods by changing elastic modulus as random variable. The results imply that perturbation based SFEM method gives close results to MCS method and it can be used instead of MCS method, especially, if computational cost is taken into consideration.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1993.10a
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• pp.248-255
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• 1993

Recently, due to the increasing attention to the structural safety under uncertain environments, many researches on the structural reliability analysis have been peformed. Some useful methods are available to evaluate performance reliability of structures with explicit limit states. However, for large structures, in which structural behaviors can be analyzed with finite element models and the limit states are only expressed implicitly, Monte-Carlo simulation method has been mainly used. However, Monte-Carlo simulation method spends too much computational time on repetitive structural analysis. Many alternative methods are suggested to reduce the computational work required in Monte-Carlo simulation. Response surface method is widely used to improve the efficiency of structural reliability analysis. Response surface method is based on the concept of approximating simple polynomial function of basic random variables for the limit state which is not easily expressed in explicit forms of design random variables. The response surface method has simple algorithm. However, the accuracy of results highly depends on how properly the stochastic characteristics of the original limit state has been represented by approximated function, In this study, an improved response surface method is proposed in which the sampling points for creating response surface are modified to represent the failure surface more adequately and the combined use of a linear response surface function and Rackwitz-Fiessler method has been employed. The method is found to be more effective and efficient than previous response surface methods. In addition more consistent convergence is achieved, Accuracy of the proposed method has been investigated through example.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.8 s.239
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• pp.1102-1108
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• 2005

The integrity of nuclear piping systems has to be maintained sufficiently all the times during operation. In order to maintain the integrity, reliable assessment procedures including fracture mechanics analysis, etc, are required. Up to now, the integrity assessment has been performed using conventional deterministic approach even though there are lots of uncertainties to hinder a rational evaluation. In this respect, probabilistic approach is considered as an appropriate method for piping system evaluation. The objectives of this paper are to develop a probabilistic assessment program using reliability index and simulation technique and to estimate the damage probability of wall-thinned pipes in secondary systems. The probabilistic assessment program consists of three evaluation modules which are first order reliability method, second order reliability method and Monte Carlo simulation method. The developed program has been applied to evaluate damage probabilities of wall-thinned pipes subjected to internal pressure, global bending moment and combined loading. The sensitivity analysis results as well as prototypal evaluation results showed a promising applicability of the probabilistic integrity assessment program.

• 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 Soil and Groundwater Environment
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• v.20 no.3
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• pp.51-64
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• 2015

In the present study, we develop two history matching techniques based on Markov chain Monte Carlo method where radial basis function and Gaussian distribution generated by unconditional geostatistical simulation are employed as the random walk transition kernels. The Bayesian inverse methods for aquifer characterization as the developed models can be effectively applied to the condition even when the targeted information such as hydraulic conductivity is absent and there are transient hydraulic head records due to imposed stress at observation wells. The model which uses unconditional simulation as random walk transition kernel has advantage in that spatial statistics can be directly associated with the predictions. The model using radial basis function network shares the same advantages as the model with unconditional simulation, yet the radial basis function network based the model does not require external geostatistical techniques. Also, by employing radial basis function as transition kernel, multi-scale nested structures can be rigorously addressed. In the validations of the developed models, the overall predictabilities of both models are sound by showing high correlation coefficient between the reference and the predicted. In terms of the model performance, the model with radial basis function network has higher error reduction rate and computational efficiency than with unconditional geostatistical simulation.

• Nuclear Engineering and Technology
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• v.47 no.5
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• pp.546-558
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• 2015

Chord length sampling method in Monte Carlo simulations is a method used to model spherical particles with random sampling technique in a stochastic media. It has received attention due to the high calculation efficiency as well as user convenience; however, a technical issue regarding boundary effect has been noted. In this study, after analyzing the distribution characteristics of spherical particles using an explicit method, an alternative chord length sampling method is proposed. In addition, for modeling in finite media, a correction method of the boundary effect is proposed. Using the proposed method, sample probability distributions and relative errors were estimated and compared with those calculated by the explicit method. The results show that the reconstruction ability and modeling accuracy of the particle probability distribution with the proposed method were considerably high. Also, from the local packing fraction results, the proposed method can successfully solve the boundary effect problem. It is expected that the proposed method can contribute to the increasing of the modeling accuracy in stochastic media.

• Nuclear Engineering and Technology
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• v.35 no.3
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• pp.234-242
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• 2003

The full energy peak efficiency of a hyper pure germanium (HPGe) detector was calibrated in a wide energy range from 0.06 to 11 MeV. Both the experimental technique and the Monte Carlo method were used for the efficiency calibration. The measurement was performed using the standard radioisotopes in the low energy region of $60{\sim}1408$ keV, which was further extended up to 11 MeV by using the $^{14}N(n,r)\;and\;^{35}Cl(n,r)$ reactions. The GEANT Monte Carlo code was used for efficiency calculation. The calculated efficiency had the same dependency on the r-ray energy with the measurement, and the discrepancy between the calculation and the measurement was minimized by fine-tuning of the detector geometry. From the calculated result, the efficiency curve of the HPGe detector was reliably determined particularly in the high energy region above several MeV, where the number of measured efficiency points is relatively small despite the wide energy region. The calculated efficiency agreed with the measurement within about $7\%$. In addition to the efficiency calculation, the origin of the local minimum near 600 keV on the efficiency curve was analyzed as a general characteristics of a HPGe detector.