• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.190-206
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• 1996

In case measurements are made on units of production in time order, it is reasonable to expect that the measurement errors will sometimes be first order autocorrelated, and a technique to test such autocorrelation is required to give good control of the productive process. Tool-wear process provide an example for which regression model can sometimes be useful in modeling and controlling the process. For the control of such process, we present a simple method for testing first order autocorrelation in regression errors. The method is based on Bayesian test method via Bayes factor and derived by observing that in general, a Bayes factor can be written as the product of a quantity called the Savage-Dickey density ratio and a correction factor ; both terms are easily estimated from Gibbs sampling technique. Performance of the method is examined by means of Monte Carlo simulation. It is noted that the test not only achieves satisfactory power but eliminates the inconvenience occurred in using the well-known Durbin-Watson test.

• Steel and Composite Structures
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• v.16 no.5
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• pp.507-519
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• 2014

In this paper, a higher order shear deformation beam theory is developed for static and free vibration analysis of functionally graded beams. The theory account for higher-order variation of transverse shear strain through the depth of the beam and satisfies the zero traction boundary conditions on the surfaces of the beam without using shear correction factors. The material properties of the functionally graded beam are assumed to vary according to power law distribution of the volume fraction of the constituents. Based on the present higher-order shear deformation beam theory, the equations of motion are derived from Hamilton's principle. Navier type solution method was used to obtain frequencies. Different higher order shear deformation theories and classical beam theories were used in the analysis. A static and free vibration frequency is given for different material properties. The accuracy of the present solutions is verified by comparing the obtained results with the existing solutions.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.03a
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• pp.50-54
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• 1997

An expert drawbead model is developed to model a cranky drawbead in the finite element analysis of stamping processes. The expert model calculates the drawbead restraining forces (DBRF's) and bead-exit thinning, which are boundary conditions. DBRF's are calculated by considering bending force, unbending force, and friction force in order. Bead-exit thinning are due to the bending and tension during the deformation. The DBFR's and thinning computed form the mathematical model for the basic beads are compared with measurements and correction factors compensating for the differences are found using the multiple linear regression method. The composition beads are assumed to be a combination of basic beads so that the DBRF's and bead-exit thinning are computed to the sum of those of basic beads.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.92-93
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• 2019

Estimates based on BIM makes it possible to perform from quantity take-off to construction cost estimates by using model, which is made in the phase of design and construction. As the BIM models are made up of the units of element, there an advantage of the automative quantity take-off, if the correction or change of element occurs. Work items, not included in the elements of the BIM model, are excepted from bill of quantity. Level of detail(LoD) of the BIM model can be improved for detailed estimates, but an excessive modeling for estimates is inefficient. This study presents the measure for selection and quantity take-off of work items, those are not expressed in the BIM model. The proposed method avoids the creation of excessive BIM Models and enables quantity take-off in conjunction with the element.

• Journal of Aerospace System Engineering
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• v.13 no.1
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• pp.38-46
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• 2019

There is a growing interest in engine diagnostic technology for gas turbine engines. An engine simulation program, precisely simulating the engine performance, is required in order to apply it to the engine diagnosis technology for engine health monitoring. In particular, the simulation program can predict not only design point performance but also off-design point and partial load performance in accurate. So the engine simulation program for the 2-spool separate flow type turbofan engine was developed and the JT9D-7R4G engine of PW(Pratt & Whitney) was analyzed. The steady-sate performance analysis is conducted at both design and off-design points in flight path and the differences between analysis results of takeoff and cruise conditions are compared. The effect of Reynold's correction method was analyzed as a scaling method of the engine component performance. The simulation results was compared with NPSS.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.396-409
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• 2023

In the field of autonomous vehicles, where high accuracy and reliability are critical, various satellite navigation augmentation systems have been developed to improve system performance. These systems generate correction and integrity information based on measurements and navigation data collected from ground reference stations, enhancing user positioning accuracy. Thus, the performance of the system heavily relies on the deployment and spacing of reference stations. To construct an effective satellite navigation augmentation system, careful consideration must be given to the installation points of reference stations. This paper presents a user positioning performance modeling formula and proposes a method for selecting the installation points of new reference stations. The proposed method involves selecting a candidate group area that can optimize the user's positioning performance. By utilizing this method, the system's performance can be improved, ensuring high accuracy and reliability for autonomous vehicle applications.

• Journal of Astronomy and Space Sciences
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• v.25 no.2
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• pp.227-238
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• 2008

GNSS (Global Navigation Satellite System) Ground Station monitors navigation satellite signal, analyzes navigation result, and uploads correction information to satellite. GNSS Ground Station is considered as a main object for constructing GNSS infra-structure and applied in various fields. ETRI (Electronics and Telecommunications Research Institute) is developing Monitoring and Control subsystem, which is subsystem of GNSS Ground Station. Monitoring and Control subsystem acquires GPS and Galileo satellite signal and provides signal monitoring data to GNSS control center. In this paper, the configurations of GNSS Ground Station and Monitoring and Control subsystem are introduced and the preliminary design of Monitoring and Control subsystem is performed. Monitoring and Control subsystem consists of data acquisition module, data formatting and archiving module, data error correction module, navigation solution determination module, independent quality monitoring module, and system operation and maintenance module. The design process uses UML (Unified Modeling Language) method which is a standard for developing software and consists of use-case modeling, domain design, software structure design, and user interface structure design. The preliminary design of Monitoring and Control subsystem enhances operation capability of GNSS Ground Station and is used as basic material for detail design of Monitoring and Control subsystem.

• Journal of Urban Science
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• v.7 no.2
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• pp.53-60
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• 2018

Digital Twin is a technology that creates a photocopy of real-world objects on a computer and analyzes the past and present operational status by fusing the structure, context, and operation of various physical systems with property information, and predicts the future society's countermeasures. In particular, 3D rendering technology (UAS, LiDAR, GNSS, etc.) is a core technology in digital twin. so, the research and application are actively performed in the industry in recent years. However, UAS (Unmanned Aerial System) and LiDAR (Light Detection And Ranging) have to be solved by compensating blind spot which is not reconstructed according to the object shape. In addition, the terrestrial LiDAR can acquire the point cloud of the object more precisely and quickly at a short distance, but a blind spot is generated at the upper part of the object, thereby imposing restrictions on the forward digital twin modeling. The UAS is capable of modeling a specific range of objects with high accuracy by using high resolution images at low altitudes, and has the advantage of generating a high density point group based on SfM (Structure-from-Motion) image analysis technology. However, It is relatively far from the target LiDAR than the terrestrial LiDAR, and it takes time to analyze the image. In particular, it is necessary to reduce the accuracy of the side part and compensate the blind spot. By re-optimizing it after fusion with UAS and Terrestrial LiDAR, the residual error of each modeling method was compensated and the mutual correction result was obtained. The accuracy of fusion-based 3D model is less than 1cm and it is expected to be useful for digital twin construction.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1135-1147
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• 2021

In order to geometrically correct high-resolution satellite imagery, the sensor modeling process that restores the geometric relationship between the satellite sensor and the ground surface at the image acquisition time is required. In general, high-resolution satellites provide RPC (Rational Polynomial Coefficient) information, but the vendor-provided RPC includes geometric distortion caused by the position and orientation of the satellite sensor. GCP (Ground Control Point) is generally used to correct the RPC errors. The representative method of acquiring GCP is field survey to obtain accurate ground coordinates. However, it is difficult to find the GCP in the satellite image due to the quality of the image, land cover change, relief displacement, etc. By using image maps acquired from various sensors as reference data, it is possible to automate the collection of GCP through the image matching algorithm. In this study, the RPC of KOMPSAT-3A satellite image was corrected through the extracted matching point using the UAV (Unmanned Aerial Vehichle) imagery. We propose a pre-porocessing method for the extraction of matching points between the UAV imagery and KOMPSAT-3A satellite image. To this end, the characteristics of matching points extracted by independently applying the SURF (Speeded-Up Robust Features) and the phase correlation, which are representative feature-based matching method and area-based matching method, respectively, were compared. The RPC adjustment parameters were calculated using the matching points extracted through each algorithm. In order to verify the performance and usability of the proposed method, it was compared with the GCP-based RPC correction result. The GCP-based method showed an improvement of correction accuracy by 2.14 pixels for the sample and 5.43 pixelsfor the line compared to the vendor-provided RPC. In the proposed method using SURF and phase correlation methods, the accuracy of sample was improved by 0.83 pixels and 1.49 pixels, and that of line wasimproved by 4.81 pixels and 5.19 pixels, respectively, compared to the vendor-provided RPC. Through the experimental results, the proposed method using the UAV imagery presented the possibility as an alternative to the GCP-based method for the RPC correction.

• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.877-889
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• 2009

This study is to assess the future potential impact of climate change on stream water quality for a 6,581.1 km$^2$ dam watershed using SWAT (Soil and Water Assessment Tool) model. The ECHAM5-OM climate data of IPCC (The Intergovernmental Panel on Climate Change) A2, A1B, and B1 emission scenarios were adopted and the future data (2007-2099) were corrected using 30 years (1977-2006, baseline period) weather data and downscaled by Change Factor (CF) method. After model calibration and validation using 6 years (1998-2003) observed daily streamflow and monthly water quality (SS, T-N, and T-P) data, the future (2020s, 2050s and 2080s) hydrological behavior and stream water quality were projected.