• Geomechanics and Engineering
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• v.36 no.6
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• pp.601-618
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• 2024

The joint probability distribution of uncertain geomechanical parameters of geotechnical strata is a crucial aspect in constructing the reliability functional function for roof structures. However, due to the limited number of on-site exploration and test data samples, it is challenging to conduct a scientifically reliable analysis of roof geotechnical strata. This study proposes a Copula method based on small sample exploration and test data to construct the intensity characteristics of roof geotechnical strata. Firstly, the theory of multidimensional copula is systematically introduced, especially the construction of four-dimensional Gaussian copula. Secondly, data from measurements of 176 groups of geomechanical parameters of roof geotechnical strata in 31 coal mines in China are collected. The goodness of fit and simulation error of the four-dimensional Gaussian Copula constructed using the Pearson method, Kendall method, and Spearman methods are analyzed. Finally, the fitting effects of positive and negative correlation coefficients under different copula functions are discussed respectively. The results demonstrate that the established multidimensional Gaussian Copula joint distribution model can scientifically represent the uncertainty of geomechanical parameters in roof geotechnical strata. It provides an important theoretical basis for the study of reliability functional functions for roof structures. Different construction methods for multidimensional Gaussian Copula yield varying simulation effects. The Kendall method exhibits the best fit in constructing correlations of geotechnical parameters. For the bivariate Copula fitting ability of uncertain parameters in roof geotechnical strata, when the correlation is strong, Gaussian Copula demonstrates the best fit, and other Copula functions also show remarkable fitting ability in the region of fixed correlation parameters. The research results can offer valuable reference for the stability analysis of roof geotechnical engineering.

• Bulletin of the Korean Chemical Society
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• v.24 no.8
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• pp.1097-1101
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• 2003

The cubic and quartic anharmonic force field of malonaldehyde is calculated using density functional theory at the B3LYP/6-31G(d,p) level, and used to simulate coherent infrared vibrational spectra. 12 normal modes are included in the simulation, and the Arnoldi method is employed for the diagonalization of the Hamiltonian. The calculated three pulse infrared signals in the k1 + k2 - k3 direction show signatures of the intramolecular hydrogen bond couplings between the C=O stretch, H-O-C bend and O-H stretch vibrations.

• Journal of the korean Society of Automotive Engineers
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• v.13 no.1
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• pp.66-74
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• 1991

A multidimensional numerical simulation of turbulent combustion in a constant volume bomb is implemented to clarify the effects of swirl on combustion. This simulation includes the ICED-ALE numerical technique, the skew-upwind differencing scheme, the modified .Kappa.-.epsilon. turbulence model, and the combustion model of the Arrhenius type and the turbulence-mixing-control type. The calculations of the turbulent combustion with swirl are carried out. It shows that the results agree with the measurements allowably. Therefore, the effects of swirl on turbulent combustion are examined through the parametric study of swirl.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.265-276
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• 2015

In this paper, we propose hierarchical cluster analysis and multidimensional scaling for joint distribution valued data. Information technology is increasing the necessity of statistical methods for large and complex data. Symbolic Data Analysis (SDA) is an attractive framework for the data. In SDA, target objects are typically represented by aggregated data. Most methods on SDA deal with objects represented as intervals and histograms. However, those methods cannot consider information among variables including correlation. In addition, objects represented as a joint distribution can contain information among variables. Therefore, we focus on methods for joint distribution valued data. We expanded the two well-known exploratory methods using the dissimilarities adopted Hall Type relative projection index among joint distribution valued data. We show a simulation study and an actual example of proposed methods.

• Journal of Mechanical Science and Technology
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• v.16 no.3
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• pp.344-353
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• 2002

A reliable computational heat transfer model has been investigated to define the heat transfer characteristics of a spray column direct contact heat exchanger, which is often utilized in the process involving counterflows for heat and mass transfer operations. Most of the previous studies investigated are one-dimensional unsteady solutions based on rather fragmentary experimental data. Development of a multidimensional numerical model and a computational algorithm are essential to analyze the inherent multidimensional characteristics of a direct contact heat exchanger. The present study has been carried out numerically and establishes a solid simulation algorithm for the operation of a direct contact heat exchanger. Operational and system parameters such as the speed and direction of working fluid droplets at the injection point, and the effects of aspect ratio and void fraction of continuous fluid are examined thoroughly as well to assess their influence on the performance of a spray column.

• Journal of Multimedia Information System
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• v.2 no.3
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• pp.263-274
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• 2015

The subject of this work is the complex discrete systems simulation special features with the aid of dynamic graph models. The proposed simulation technique allows to determine the ways for tasks solutions in terms of discrete systems analysis and synthesis of various complication: one-dimensional and multidimensional, steady and unstable, with the pulse elements abnormal operating mode and others. Often complex control systems analysis and synthesis task solutions, via classical approach comes out to be insolvent, because of the computational problems. The application of graph models allows to perform clear and strict characterization and computer procedures automation. The optimal controls synthesis algorithm presented in this paper, transferring the discrete system from target initial state to target final state within the minimum time, allows to consider the zero initial conditions systems, with the initial potential energy, with the control actions limitations and complex pulse elements operating mode.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.597-603
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• 2000

A versatile dimensionality assessment index DETECT has been developed for binary item response data by Kim (1994). The present paper extends the use of DETECT to the polytomously scored item data. A simulation study shows DETECT performs well in differentiating multidimensional data from unidimensional one by yielding a greater value of DETECT in the case of multidimensionality. An additional investigation is necessary for the dimensionally meaningful clustering methods, such as HAC for binary data, particularly sensitive to the polytomous data.

• 한국전산유체공학회:학술대회논문집
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• 1999.05a
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• pp.1-10
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• 1999

This paper briefly introduces the work done up to 1998 during the past twenty years for numerical modeling of ocean process focussing on the neighbouring seas of Korean Peninsula. Modeling of global ocean dynamics has also been performed as a pathway to understand the regional ocean dynamics. The ocean simulation produces a vast amount of multidimensional multivariate dataset therefore adoption of scientific and technical visualization techniques were essential to properly understand the physics involved.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.11
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• pp.151-162
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• 1994

A new neural network structure called Self-organized Distributed Networks (SODN) is proposed for developing the neural network-based multidimensional system models. The learning with the proposed networks is fast and precise. Such properties are caused from the local learning mechanism. The structure of the networks is combination of dual networks such as self-organized networks and multilayered local networks. Each local networks learns only data in a sub-region. Large number of memory requirements and low generalization capability for the untrained region, which are drawbacks of conventional local network learning, are overcomed in the proposed networks. The simulation results of the proposed networks show better performance than the standard multilayer neural networks and the Radial Basis function(RBF) networks.

• Electronics and Telecommunications Trends
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• v.33 no.5
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• pp.111-120
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• 2018

Agent-based modeling and simulation (ABMS) is a computational method for analyzing research targets through observations of agent-to-agent interactions, and can be applied to multidimensional policy experiments in various fields of social sciences to support policy and decision making. Recently, according to increasing complexity of society and the rapid growth of collected data, the need for high-speed processing is considered to be more important in this field. For this reason, in the ABMS research field, a scalable and large-scale computing infrastructure is becoming an essential element, and cloud computing has been considered a promising infrastructure of ABMS. This paper surveys the technology trends of ABMS tools, cloud computing-based modeling, and simulation studies, and forecasts the use of cloud-computing infrastructure for future modeling and simulation tools. Although fundamental studies are underway to apply and operate cloud computing in the areas of modeling and simulation, new and additional studies are required to devise an optimal cloud computing infrastructure to satisfy the needs of large-scale ABMS.