• Journal of Korean Society for Atmospheric Environment
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• v.27 no.1
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• pp.30-40
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• 2011

Numerical simulations were carried out to investigate the impact of SST spatial distribution on the result of air quality modeling. Eulerian photochemical dispersion model CAMx (Comprehensive Air quality Model with eXtensions, version 4.50) was applied in this study and meteorological fields were prepared by RAMS (Regional Atmospheric Modeling System). Three different meteorological fields, due to different SST spatial distributions were used for air quality modeling to assess the sensitivity of CAMx modeling to the different meteorological input data. The horizontal distributions of surface ozone concentrations were analyzed and compared. In each case, the simulated ozone concentrations were different due to the discrepancies of horizontal SST distributions. The discrepancies of land-sea breeze velocity caused the difference of daytime and nighttime ozone concentrations. The result of statistic analysis also showed differences for each case. Case NG, which used meteorological fields with high resolution SST data was most successfully estimated correlation coefficient, root mean squared error and index of agreement value for ground level ozone concentration. The prediction accuracy was also improved clearly for case NG. In conclusion, the results suggest that SST spatial distribution plays an important role in the results of air quality modeling on high ozone episode at coastal region.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.645-652
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• 2016

The statistical modeling of input random variables is necessary in reliability analysis, reliability-based design optimization, and statistical validation and calibration of analysis models of mechanical systems. In statistical modeling methods, there are the Akaike Information Criterion (AIC), AIC correction (AICc), Bayesian Information Criterion, Maximum Likelihood Estimation (MLE), and Bayesian method. Those methods basically select the best fitted distribution among candidate models by calculating their likelihood function values from a given data set. The number of data or parameters in some methods are considered to identify the distribution types. On the other hand, the engineers in a real field have difficulties in selecting the statistical modeling method to obtain a statistical model of the experimental data because of a lack of knowledge of those methods. In this study, commonly used statistical modeling methods were compared using statistical simulation tests. Their advantages and disadvantages were then analyzed. In the simulation tests, various types of distribution were assumed as populations and the samples were generated randomly from them with different sample sizes. Real engineering data were used to verify each statistical modeling method.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.13.1-13
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• 2003

The Markovian arrival process with marked transitions (MMAP) is useful in modeling input processes of stochastic system with several types. Especially, the MMAP can be used to model the phenomena where the correlation of different types is considered. In this talk we discuss modeling issues for the queue with three types of customers; ordinary customers, negative customers and disasters which are correlated by using MMAP. We also present the recent results and further studies.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.525-528
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• 2000

This paper presents a circuit analysis and cotnrol example of favored configuration 6/4 SRM. SRM modeling and analysis are necessary for experiment. Thus this paper proposes a SRM modeling with PI controller (of driving converter) input voltage chopping and inductance profile when rotor position transformed. Through this simulation the designer can predict operating states of systems over a broad range of operating conditions.

• Progress in Superconductivity and Cryogenics
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• v.4 no.1
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• pp.66-72
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• 2002

This paper describes numerical modeling for thermal characteristic of vapor-cooled current leads under pulse operation. The transient thermal analysis considers the temperature difference between a helium gas (low and a copper lead and temperature dependent properties of helium gas, copper and stainless steel. This numerical modeling was compensated and validated by an experiment with commercially available 100 A vapor-cooled current leads. A proper overloading factor was suggested for the current leads under pulse operation through this modeling, which can significantly reduce heat input to a cryostat.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.373-373
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• 2000

In this paper, we propose a fuzzy modeling algorithm which divides the input space more efficiently than convention methods by taking into consideration correlations between components of sample data. The proposed fuzzy modeling algorithm consists of two steps: coarse tuning, which determines consequent parameters approximately using FCRM clustering method, and fine tuning, which adjusts the premise and consequent parameters more precisely by gradient descent algorithm. To evaluate the performance of the proposed fuzzy mode, we use the numerical data of nonlinear function.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.12
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• pp.579-587
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• 2014

This paper deals with precise analytical state equation modeling of a variable speed refrigeration system (VSRS) for optimum control in state space. The VSRS is described as multi-input and multi-output (MIMO) system, which has two controlled variables and two control inputs. First, the Navier-Stokes equation and mass flow rate were applied to each component of the basic refrigeration cycle to build a dynamic model. The dynamic model, represented by a differential equation, was transformed into the state equation formula. Next, a full-order state observer was built to estimate all of the state variables to compose an optimum control system. Then, an optimum controller was designed to minimize an evaluation function that has input energy and control error. Finally, simulations and experiments were conducted to verify the validity of the proposed modeling and designed optimum controller to regulate target temperature and superheat in a 1RT oil cooler system. The results show that the proposed method, state equation modeling and optimum control, is efficient to ensure optimal control performance of the VSRS.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.239-246
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• 2003

Statisticians, or data miners, are often requested to assess the importances of input variables in the given supervised learning model. For the purpose, one may rely on separate ad hoc measures depending on modeling types, such as linear regressions, the neural networks or trees. Consequently, the conceptual consistency in input variable importance measures is lacking, so that the measures cannot be directly used in comparing different types of models, which is often done in data mining processes, In this short communication, we propose a unified approach to the importance measurement of input variables. Our method uses sensitivity analysis which begins by perturbing the values of input variables and monitors the output change. Research scope is limited to the models for continuous output, although it is not difficult to extend the method to supervised learning models for categorical outcomes.

• Journal of Construction Engineering and Project Management
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• v.3 no.1
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• pp.14-21
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• 2013

To analyze building energy consumption, the building description for building energy performance analysis (BEPA) is required. The required data input for subject building is a basic step in the BEPA process. Since building information modeling (BIM) is applied in the construction industry, the required data for BEPA can be gathered from a single international standard file format like IFCXML. However, in most BEPA processes, since the required data cannot be fully used from the IFCXML file, a building description for BEPA must be created again. This paper proposes IFCXML-based automatic data input approach for BEA. After the required data for BEPA has been defined, automatic data input for BEPA is developed by a prototype system. To evaluate the proposed system, a common BIM file from the BuildingSMART website is applied as a sample model. This system can increase the efficiency and reliability of the BEPA process, since the data input is automatically and efficiently improved by directly using the IFCXML file..

• International conference on construction engineering and project management
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• 2013.01a
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• pp.173-180
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• 2013

To analyze building energy consumption, the building description for building energy performance analysis (BEPA) is required. The required data input for subject building is a basic step in the BEPA process. Since building information modeling (BIM) is applied in the construction industry, the required data for BEPA can be gathered from a single international standard file format like IFCXML. However, in most BEPA processes, since the required data cannot be fully used from the IFCXML file, a building description for BEPA must be created again. This paper proposes IFCXML-based automatic data input approach for BEA. After the required data for BEPA has been defined, automatic data input for BEPA is developed by a prototype system. To evaluate the proposed system, a common BIM file from the BuildingSMART website is applied as a sample model. This system can increase the efficiency and reliability of the BEPA process, since the data input is automatically and efficiently improved by directly using the IFCXML file.