• Tribology and Lubricants
• /
• v.36 no.5
• /
• pp.279-289
• /
• 2020

In this paper, a method is proposed for establishing an approximate prediction model of rotor-dynamics through modal testing. In particular, the proposed method is applicable to systems that cannot be established according to conventional methods owing to the absence of information regarding the dimensions and material of the rotor-bearing system. The proposed method is demonstrated by employing a motor dynamometer driven by a 1 MW class induction motor without dimension and material information. The proposed method comprises a total of seven steps, wherein an initial model is established by incorporating approximate dimensions and material information, and the model is improved on the basis of the natural frequency characteristics of the system. During model improvement, the modification factor is introduced for adjusting the elastic modulus and shear modulus of the system. Analysis of critical speed and imbalance response indicates that the separation margin is 67% and the maximum vibration amplitude is less than the amplitude limit of 0.032 mm under the API 611 standard, which means that the motor dynamometer can stably operate at a rated speed of 1800 rpm. Hence, the obtained results validate the feasibility of the proposed method. Furthermore, for broad usage, it is necessary to accordingly apply and validate the proposed method for various rotor-bearing systems.

• Food Science of Animal Resources
• /
• v.39 no.4
• /
• pp.565-575
• /
• 2019

This study evaluated Campylobacter jejuni risk in ground meat products. The C. jejuni prevalence in ground meat products was investigated. To develop the predictive model, survival data of C. jejuni were collected at $4^{\circ}C-30^{\circ}C$ during storage, and the data were fitted using the Weibull model. In addition, the storage temperature and time of ground meat products were investigated during distribution. The consumption amount and frequency of ground meat products were investigated by interviewing 1,500 adults. The prevalence, temperature, time, and consumption data were analyzed by @RISK to generate probabilistic distributions. In 224 samples of ground meat products, there were no C. jejuni-contaminated samples. A scenario with a series of probabilistic distributions, a predictive model and a dose-response model was prepared to calculate the probability of illness, and it showed that the probability of foodborne illness caused by C. jejuni per person per day from ground meat products was $5.68{\times}10^{-10}$, which can be considered low risk.

• Journal of Navigation and Port Research
• /
• v.32 no.3
• /
• pp.215-221
• /
• 2008

Dynamic characteristics of a structure, i.e., natural frequency and mode shape, have been widely using as an input data in the area of structural integrity or health monitoring which combined with the damage evaluation and structural system identification techniques. It is very difficult, however, to get those information by the conventional modal analysis method from large structures, such as the offshore structure or the long-span bridge, since the source of vibration is not available. In this paper, a method to obtain the frequencies and the mode shapes of a large span truss structure using only acceleration responses is studied. The calculation procedures to obtain acceleration responses and frequency response functions are provided utilizing a numerical model of the truss, and the process to extract natural frequencies and mode shapes from the modal analysis is cleary explained. The extracted mode shapes by proposed method are compared with those from eigenvalue analysis for the estimation of accuracy. The validity of the mode shapes is also demonstrated using an existing damage detection technique for the truss structure by simulated damage cases.

• Journal of Korean Society of Steel Construction
• /
• v.20 no.6
• /
• pp.761-771
• /
• 2008

When the crossing frequency of a train meets the natural frequency of a railway bridge, the bridge is bound to become resonant. There are few available time response samples involving a train that passes a bridge at high speed. Very effective modal-parameter extraction techniques for such special high-speed railway bridge conditions are introduced in this paper. Utilizing the cross-correlations of the free-vibration responses after the train passes, mode shapes and the temporal modal parameters (e.g., natural frequency and damping ratio) are extracted using the TDD and SI techniques, respectively. This approach has been applied to a two-span steel composite bridge in the Kyung-Bu high-speed railway system. The estimation results were compared with those obtained using the existing methods. The results fully coincide with those that were extracted using the existing aforementioned technique.

• Structural Engineering and Mechanics
• /
• v.74 no.1
• /
• pp.129-143
• /
• 2020

This study proposes a new shape memory alloy-tuned mass damper (SMA-TMD) and investigates the effectiveness of this damper in reducing and controlling the vibrations of a transmission tower-line system under various seismic excitations. Based on a practical transmission line system and considering the geometric nonlinearity of this system, the finite element (FE) software ANSYS is used to create an FE model of the transmission tower-line system and simulate the proposed SMA-TMD. Additionally, the parameters of the SMA springs are optimized. The effectiveness of a conventional TMD and the proposed SMA-TMD in reducing and controlling the vibrations of the transmission tower-line system under seismic excitations is investigated. Moreover, the effects of the ground motion intensity and frequency ratio on the reduction ratio (η) of the SMA-TMD are studied. The vibration reduction effect of the SMA-TMD under various seismic excitations is superior to that of the conventional TMD. Changes in the ground motion intensity and frequency ratio have a significant impact on the η of the SMA-TMD. As the ground motion intensity and frequency ratio increase, the η values of the SMA-TMD first increase and then decrease. Studying the vibration reduction effects of the SMA-TMD can provide a reference for the practical engineering application of this damper.

• Culinary science and hospitality research
• /
• v.16 no.3
• /
• pp.147-160
• /
• 2010

This study aims to analyze the effect of emotional response from dining out experience on satisfaction after dining out based on the customers who have visited a luxurious Korean restaurant. For this study, it designed a research model through literary research and derived hypotheses. For the empirical analysis, 250 copies of the questionnaire using the self-administered method were distributed and 230(94%) copies were collected. Among them, 220(88%) copies were used for the analysis. SPSS WIN Version 12.0 statistical package program was used for the analysis of data processing, the frequency analysis, reliability analysis and factor analysis were operated, and the hypothesis testing was verified by the regression analysis. The results of the analyses are as follows. For the hypothesis that "the dining-out consumption pattern will have a significant effect on the emotional response," it was verified that the style which pursues health and the style which is loyal to relationships had significant effects on pleasure while the style which pursues rest didn't. Also, the style which pursues health and the style which is loyal to relationships had significant effects on arousal while the style which pursues rest didn't. For the hypothesis that "emotional response will have a significant effect on satisfaction," it was verified that pleasure and simulation had significant effects on satisfaction. As a result of the study, the current dining-out consumption pattern is changed from the purpose of having meals for the biological needs in the past to considering emotional response such as preferred taste or mood.

• Toxicological Research
• /
• v.20 no.2
• /
• pp.89-100
• /
• 2004

The comet assay (also called the single-cell gel electrophoresis assay) has been widely used for detecting DNA damage and repair in individual cells. Since the conventional methods of evaluating comet assay data using frequency statistics are unsatisfactory we developed a new quantitative measure of DNA damage/repair that is based on all information residing in the dose/time-response curves of a comet experiment. Blood samples were taken from 25 breast cancer patients before undergoing radiotherapy. The comet assay was performed under alkaline conditions using isolated lymphocytes. Tail DNA, tail length, tail moment and tail inertia of the comet were measured for each patient at four doses of $\gamma$-rays (0, 2, 4 and 8 Gy) and at four time points after irradiation (0, 10, 20 and 30 min) using 100 cells each. The resulting three-dimensional dose-time response surface was modeled by multiple regression, and the second derivative, termed 2D, on dose and time was determined. A software module was programmed in SAS/AF to compute 2D values. We applied the new method successfully to data obtained from cancer patients to be assessed for their radiation sensitivity. We computed the 2D values for the four damage measures, i.e., tail moment, tail length, tail DNA and tail inertia, and examined the pairwise correlation coefficients of 2D both on the log scale and the unlogged scale. 2D values based on tail moment and tail DNA showed a high correlation and, therefore, these two damage measures can be used interchangeably as far as DNA repair is concerned. 2D values based on tail inertia have a correlation profile different from the other 2D values which may reflect different facets of DNA damage/repair. Using the dose-time response surface, other statistical models, e.g., the proportional hazards model, become applicable for data analysis. The 2D approach can be applied to all DNA repair measures, Le., tail moment, tail length, tail DNA and tail inertia, and appears to be superior to conventional evaluation methods as it integrates all data of the dose/time-response curves of a comet assay.

• Journal of the Korea Convergence Society
• /
• v.9 no.8
• /
• pp.95-100
• /
• 2018

The Korea Convergence Society. The aim of this study was to evaluate the association between alcohol consumption and periodontal diseases in Korea adults. The date from the 2014 Korean National Health and Nutrition Survey were used, and 4,328 subjects over 30 years were included in the analysis. Periodontal disease was assessed using the Community Periodontal Index. The adjusted odds ratio of drinking experience, drinking frequency, the drinking amount and the drinking duration were calculated from the logistic regression model with the never-drinkers as a reference group and the logistic model controlled for age, gender, education, and diabetes. This study found that the risk of periodontal disease according to the drinking status of adults over 30 years of age was 1.39 times (95% CI=1.01-1.90) higher than that of non-drinking group when the number of drinks consumed at one time was more than seven glasses. The frequency of binge alcohol consumption, amount of alcohol consumption and duration of alcohol consumption were significantly associated with the risk of periodontal disease in a dose-response pattern among over 30 years. Alcohol consumption was discovered to be a potential risk indicator for periodontitis. Dental practitioners need to be aware that patients who drink may be at higher risk of periodontitis and could benefit from advice to quit drinking and maintain regular dental visits.

• Journal of the Korean earth science society
• /
• v.32 no.1
• /
• pp.1-11
• /
• 2011

The impact echo and impulse response methods were applied to the safety inspection of concrete structure, which has the rear cavity. The concrete structure model used in this study was divided into four sections, pure concrete, concrete+cavity, reinforced concrete with iron bar, and reinforced concrete+cavity, respectively. Previous study performed by authors have showed a possibility of success to use these method for detection of the rear cavity of concrete structure. Therefore, we tried to get more enhanced result with IE and IR methods through this study. Especially, IE and IR methods are relatively accurate to map the point of measurement, which makes it possible to interpret the depth of the concrete bed and effect by rear cavity with confidence. Followings were revealed from the results; the IE method shows some small peak zones probably indicating the rear cavity in the frequency lower than the resonance frequency and the changes of mobility and dynamic stiffness in the IR method indicate the weak zones. The proposed methods can be used to delineate the weak zones of the concrete structure.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2002.05a
• /
• pp.43-50
• /
• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.