• Structural Engineering and Mechanics
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• v.25 no.3
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• pp.311-330
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• 2007

Model-based predictions of structural behavior are negatively affected by uncertainties of various type and in various stages of the structural analysis. The present paper focusses on dynamic analysis and addresses the effects of uncertainties concerning material and geometric parameters, mainly in the context of modal analysis of large-scale structures. Given the large number of uncertain parameters arising in this case, highly scalable simulation-based methods are adopted, which can deal with possibly thousands of uncertain parameters. In order to solve the reliability problem, i.e., the estimation of very small exceedance probabilities, an advanced simulation method called Line Sampling is used. In combination with an efficient algorithm for the estimation of the most important uncertain parameters, the method provides good estimates of the failure probability and enables one to quantify the error in the estimate. Another aspect here considered is the uncertainty quantification for closely-spaced eigenfrequencies. The solution here adopted represents each eigenfrequency as a weighted superposition of the full set of eigenfrequencies. In a case study performed with the FE model of a satellite it is shown that the effects of uncertain parameters can be very different in magnitude, depending on the considered response quantity. In particular, the uncertainty in the quantities of interest (eigenfrequencies) turns out to be mainly caused by very few of the uncertain parameters, which results in sharp estimates of the failure probabilities at low computational cost.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.24 no.4
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• pp.492-500
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• 2014

Objectives: The purpose of this study is to estimate the applicability of regional sample collection of environmental samples. The concentration of asbestos fibers were analyzed with two devices. One was an existing commercial air sampling pump that has been proved to be accurate and exact, and the other is a remodeled pump for sample collection which was made from an electric bubble generator originally designed for aquarium fish. Samples were collected with the two devices under the same environmental conditions and collection equipment. A comparative analysis of the concentration of ambient asbestos fiber was then performed. Methods: Based on previous research, six farmhouses with asbestos fiber slate roofs known to have high concentrations of asbestos fiber were selected. Using the existing commercial air sampling pump and the remodeled electric bubble generator, four to seven samples were collected each day one meter downwind from the edge of the slate roof at high volume (about 4 L/min) and low volume (about 1.4 L/min). The analyzer responsible for sample quality control of asbestos fibers counted the number of asbestos fibers with a phase microscope. Results: The rates of flow change of the existed sampler and the remodeled pump at high volume were 0.82% and 0.17%, respectively. The rates of flow change at low volume were 3.83% and 1.09%, but there was not significant difference. The rates of flow change are within the error range (${\pm}5%$) of OSHA analyzing methods. For the high volume sampler, the average asbestos fiber concentration in the air collected by the existed sampler is 6.270 fibers/L and for the remodeled one 5.527 fibers/L, not a significant difference. For the low volume sampler, the average asbestos fiber concentration in the air collected by the existed sampler is 7.755 fibers/L and for the remodeled one 7.706 fibers/L, not a significant difference. The total area of the slate roof of the targeted farmhouse has an effect on the concentration of asbestos fibers in the air from the existing pump and the remodeled one (p<0.01). Conclusions: The sampling function between the existing commercial pump and the remodeled one shows little difference. Therefore, the remodeled pump is considered a pump with a good availability for collecting ambient air asbestos samples.

• Journal of Korean Society for Quality Management
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• v.36 no.4
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• pp.93-101
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• 2008

The rare metals, used for semiconductors, PDP-LCS and other specialized metal areas necessarily, has been playing a key role for the Korean economic development. Rare metals are influenced by exogenous variables, such as production quantity, price and supplied areas. Nowadays the supply base of rare metals is threatened by the sudden increase in price. For the stable supply of rare metals, a rational demand outlook is needed. In this study, focusing on the domestic demand for chromium, the uncertainty and probability materializing from demand and price is analyzed, further, a demand forecast model, which takes into account various exogenous variables, is suggested, differing from the previously static model. Also, through the OOS(out-of-sampling) method, comparing to the preexistence ARIMA model, ARMAX model, multiple regression analysis model and ECM(Error Correction Mode) model, we will verify the superiority of suggested model in this study.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1619-1619
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• 2001

Ourwork aims to assess the content of dry matter, protein, cell wall parameters and water soluble carbohydrates in forages without having to handle samples, transport them to a laboratory, dry, grind and chemically analyze them. for this purpose, the concept of fresh forage analysis under field conditions by means of compact integrated NIRS InGaAs-diode array instruments on small plot harvesters is being evaluated for plant breeding trials. This work was performed with the world first commercial experimental forage plot harvester equipped with a NIRS module for the collection, compression, and scanning of forage samples (including automatic referencing and dark current measure ments). It was used for harvesting and analyzing a number of typical forage grass and forage legume plot trials. After NIRS measurements in the field each sample was again analyzed in the laboratory by means of a conventional grating spectrometer equipped with Si-and PbS-detectors. Conventional laboratory analysis of the samples was restricted to dry matter (DM) content by means of oven drying at 105. Routine chemometric procedures were then employed to assess the comparative accuracy and precision of the DM assessments in the spectral range between 950 and 1650nm by the NIRS diode array as well as by the conventional NIRS scanning instrument. The results of this study confirmed that the type of NIRS diode array instrument employed here functioned well even in rugged field operations. further refinements proved to be necessary for optimizing the automatic filling of the sample compartment to adjust for the wide variation in forage material under conditions of extremely low or high harvest yields. The error achieved in calibrating the apparatus for forages of typical DM content proved to be satisfactory (SECV < 1.0). Possibly as a consequence of higher sampling errors, its performance in atypical forages with elevated DM contents was less satisfactory. The error level obtained on the conventional grating NIR spectrometer was similar to that of the diode array instrument for both types of forage.

• Journal of Internet Computing and Services
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• v.2 no.3
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• pp.27-36
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• 2001

Recently much attention has been paid for interference mitigation technique for the COMA system, since more capacity is available with same bandwidth. In this paper, we introduces a novel adaptive interference suppression techniques for the CDMA system with narrow band interference. The proposed interference rejection scheme employs the adaptive linear prediction techniques in the subband. In each subband, we can more easily find and cancel the narrow band signal as compared to the full band. Thus, the proposed interference rejection can be classified as another time-frequency techniques for the narrow band interference rejection(10). Computer simulation is conducted for the 3-G COMA system with IF band sampling techniques, yielding better interference rejection and bit error rate performance as compared to conventional one. Also, optimum filter is analyzed and from the analysis, it can be shown the subband prediction techniques can suppress narrow band interference more efficiently.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7A
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• pp.794-806
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• 2004

This paper deals with correction of frequency offset and analysis of quantization angle noise in the IEEE 802.1la OFDM system. The rotation phase per symbol due to the carrier frequency offset is estimated from auto-correlation of the short Preambles, which are over-sampled for the reduction of noise in OFDM signals. The pilot signals are introduced to estimate the rotation phase per OFDM symbol due to estimation error of the carrier frequency offset and the sampling frequency onset. During the estimation and correction of the frequency onsets, a CORDIC processor and a look-up table are used for the conversion between a rotation phase and its complex number. Being calculated by a limited number of bits in the CORDIC processor and the look-up table, the rotation phase and its complex number have quantization angle errors. The quantization errors are analyzed as SNR (signal to noise ratio) due to the quantization bit numbers. The minimum bit number is suggested to meet the specification of IEEE 802.1la properly. Finally, the quantization errors are evaluated through simulations on number of quantization bits and SNR of received signals.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.303-314
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• 2011

Surface albedo is an important parameter of the surface energy budget, and its accurate quantification is of major interest to the global climate modeling community. Therefore, in this paper, we consider the direct solution of kernel based bidirectional reflectance distribution function (BRDF) models for retrieval of normalized reflectance of high resolution satellite. The BRD effects can be seen in satellite data having a wide swath such as SPOT/VGT (VEGETATION) have sufficient angular sampling, but high resolution satellites are impossible to obtain sufficient angular sampling over a pixel during short period because of their narrow swath scanning when applying semi-empirical model. This gives a difficulty to run BRDF model inferring the reflectance normalization of high resolution satellites. The principal purpose of the study is to estimate normalized reflectance of high resolution satellite (RapidEye) through BRDF components from SPOT/VGT. We use semi-empirical BRDF model to estimated BRDF components from SPOT/VGT and reflectance normalization of RapidEye. This study used SPOT/VGT satellite data acquired in the S1 (daily) data, and within this study is the multispectral sensor RapidEye. Isotropic value such as the normalized reflectance was closely related to the BRDF parameters and the kernels. Also, we show scatter plot of the SPOT/VGT and RapidEye isotropic value relationship. The linear relationship between the two linear regression analysis is performed by using the parameters of SPOTNGT like as isotropic value, geometric value and volumetric scattering value, and the kernel values of RapidEye like as geometric and volumetric scattering kernel Because BRDF parameters are difficult to directly calculate from high resolution satellites, we use to BRDF parameter of SPOT/VGT. Also, we make a decision of weighting for geometric value, volumetric scattering value and error through regression models. As a result, the weighting through linear regression analysis produced good agreement. For all sites, the SPOT/VGT isotropic and RapidEye isotropic values had the high correlation (RMSE, bias), and generally are very consistent.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.2 no.2
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• pp.60-66
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• 2003

For the estimation of chatter lobe boundary it is very important to calculate the natural mode of cutting process. There are many time series algorithms for getting the natural mode of structural endmilling dynamics considering the cutting process. In this study, we have compared several time series methods such as AR algorithm, ARX, ARMAX, ARMA, Box Jenkins, Output Error, Recursive ARX, Recursive ARMAX considering the sampling frequency. As a results, the ARX, ARMAX and IV 4 are more desirable algorithms for the calculation of modal parameters such as natural frequency and damping ratio In endmilling operation. Also these algorithms may be adopted for the natural mode estimation of endmilling operation for chatter lobe prediction.

• Tribology and Lubricants
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• v.36 no.6
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• pp.297-306
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• 2020

This paper reviews studies on the types and functions of oil sensors used for machine condition monitoring. Machine condition monitoring is essential for maintaining the reliability of machines and can help avoid catastrophic failures while ensuring the safety and longevity of operation. Machine condition monitoring involves several components, such as compliance monitoring, structural monitoring, thermography, non-destructive testing, and noise and vibration monitoring. Real-time monitoring with oil analysis is also utilized in various industries, such as manufacturing, aerospace, and power plants. The three main methods of oil analysis are off-line, in-line, and on-line techniques. The on-line method is the most popular among these three because it reduces human error during oil sampling, prevents incipient machine failure, reduces the total maintenance cost, and does not need complicated setup or skilled analysts. This method has two advantages over the other two monitoring methods. First, fault conditions can be noticed at the early stages via detection of wear particles using wear particle sensors; therefore, it provides early warning in the failure process. Second, it is convenient and effective for diagnosing data regardless of the measurement time. Real-time condition monitoring with oil analysis uses various oil sensors to diagnose the machine and oil statuses; further, integrated oil sensors can be used to measure several properties simultaneously.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.6
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• pp.463-474
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• 1997

Metallic elements in dustfall have been known as notable air pollutants directly or indirectly influencing human health and wealth. The first aim of this study was to obtain precise spatial distribution patterns of 5 elements (Pb, Zn, K, Cr, and Al) in dustfall around Suwon area. To predict isometric lines of metal fluxes deposited on unsupervised random sites, the study has applied both spatial statistics as a receptor model and a GIS (geographic information system). Total of 31 sampling sites were selected in the study area (roughly 3 by 3 km grid basis) and dustfall samples were then collected monthly basis by the British deposit gauges from Dec., 1995 to Nov., 1996. The metallic elements in the dustfall were then analyzed by an atomic absorption spectrometer (AAS). On the other hand, a base map overlapped by 7 layers was constructed by using the AutoCAD R13 and ARC/INFO 3.4D. Four different spatial interpolation and expolation techniques such as IDW (inverse distance weighted averaging), TIN (triangulated irregular network), polynomial regression, and kriging technique were examined to compare spatial distribution patterns. Each pattern obtained by each technique was substantally different as varing pollutant types, land of use types, and topological conditions, etc. Thus, our study focused intensively on uncertainty analysis based on a concept of the jackknife and the sum of error distance. It was found that a kriging technique was the best applicalbe in this study area.