• Tribology and Lubricants
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• v.34 no.2
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• pp.49-54
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• 2018

Hydraulic reciprocating seal has been widely used to prevent fluid leakage in hydraulic systems. Also, hydraulic reciprocating seal plays a significant role to provide lubricant film at contacting interface to minimize tribological problems due to sliding with counter material. To predict lifetime of hydraulic reciprocating seal, quantitative understanding of wear characteristics with respect to operating conditions such as normal force and sliding speed is needed. In this work, effect of sliding speed on wear of polyurethane (PU) hydraulic reciprocating seal were experimentally investigated using a pin-on-disk tribo-tester. The wear characteristics of PU specimens were quantitatively determined by comparing the confocal microscope data before and after test. It was found that the wear rate of PU specimens decreased from $4.9{\times}10^{-11}mm^3$ to $1.1{\times}10^{-11}mm^3/Nm$ as sliding speed increased from 120 mm/s to 940 mm/s. Also, it was observed that the friction decreased slightly as the sliding speed increased. Improvement of lubrication state with increasing sliding speed was likely to be responsible for this enhanced friction and wear characteristics. This result also suggests that decrease in sliding distance between PU elastomer and counter materials at lower sliding speed is preferred. Furthermore, the quantitative assessment of wear characteristics of PU specimen may be useful in prediction of lifetime of PU hydraulic reciprocating seal if the allowed degree of wear for failure of the seal is provided.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.309-312
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• 2008

The advent of high resolution products of surface wind and temperature derived by satellite data has permitted us to investigate ocean and atmosphere interaction studies in detail. Especially the Kuroshio extension region of the western North Pacific is considered to be a key area for such studies. We have constructed gridded products of surface wind/wind stress over the world ocean using satellite scatterometer (Qscat/SeaWinds), available as the Japanese Ocean Flux data sets with Use of Remote sensing Observation (J-OFURO). Using new data based on improved algorithm which have been recently delivered, we are reconstructing gridded product with higher spatial resolution. Intercomparison of this product with the previous one reveals that there are some discrepancies between them in short-period and high wind-speed ranges especially in the westerly wind region. The products are validated by not only comparisons with in-situ measurement data by mooring buoys such as TAO/TRITON in the tropical Pacific and the Kuroshio Extension Observation (KEO) buoys, but also intercomparison with numerical weather prediction model (NWPM) products (the NRA-1 and 2). Our products have much smaller mean difference in the study areas than the NWPM ones, meaning higher reliability compared with the NWPM products. Using the high resolution products together with sea surface temperature (SST) data, we examine a new type of relationship between the lower atmosphere and upper ocean in the Kuroshio Extension region. It is suggested that the spatial relation between the wind speed and SST depends upon, more or less, the surrounding oceanic condition.

• Steel and Composite Structures
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• v.22 no.5
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• pp.937-974
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• 2016

While extensive efforts have been made in the past to develop finite element models (FEMs) for concrete-filled steel tubular columns (CFSTCs), these models may not be suitable to be used in some cases, especially in view of the utilisation of high strength steel and high strength concrete. A method is presented herein to predict the complete stress-strain curve of concrete subjected to tri-axial compressive stresses caused by axial load coupled with lateral pressure due to the confinement action in square and rectangular CFSTCs with normal and high strength materials. To evaluate the lateral pressure exerted on the concrete in square and rectangular shaped columns, an accurately developed FEM which incorporates the effects of initial local imperfections and residual stresses using the commercial program ABAQUS is adopted. Subsequently, an extensive parametric study is conducted herein to propose an empirical equation for the maximum average lateral pressure, which depends on the material and geometric properties of the columns. The analysis parameters include the concrete compressive strength ($f^{\prime}_c=20-110N/mm^2$), steel yield strength ($f_y=220-850N/mm^2$), width-to-thickness (B/t) ratios in the range of 15-52, as well as the length-to-width (L/B) ratios in the range of 2-4. The predictions of the behaviour, ultimate axial strengths, and failure modes are compared with the available experimental results to verify the accuracy of the models developed. Furthermore, a design model is proposed for short square and rectangular CFSTCs. Additionally, comparisons with the prediction of axial load capacity by using the proposed design model, Australian Standard and Eurocode 4 code provisions for box composite columns are carried out.

• Journal of Korean Tunnelling and Underground Space Association
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• v.13 no.3
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• pp.243-260
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• 2011

To predict TBM performance in design stage is indispensable for its successful application. The NTNU model, one of the representative TBM performance prediction models uses two distinct parameters such as DRI and CLI obtained from three different tests on bored rock cores. Based on DRI and CLI, it is possible to predict TBM advance rate and cutter life in the NTNU model. In this study, NTNU testing methods and their related testing equipments were introduced to measure DRl and CLI for the NTNU model. Then, in order to derive their relationships, the two key parameters measured for 39 domestic rocks were compared with physico-mechanical properties of rock such as uniaxial compressive strength and quartz content. Lastly, the experimental results were also compared with NTNU database to verify their reliability.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.412-417
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• 2013

Analytical modeling of photovoltaic power systems has been receiving significant attentions in recent years in that it is easy to apply for prediction of its dynamics and fault detection and diagnosis in advanced engineering technologies. This paper presents a novel probabilistic modeling approach for such power systems with a big data sequence. Firstly, we express input/output function of photovoltaic power systems in which solar irradiation and ambient temperature are regarded as input variable and electric power is output variable respectively. Based on this functional relationship, conditional probability for these three random variables(such as irradiation, temperature, and electric power) is mathematically defined and its estimation is accomplished from ratio of numbers of all sample data to numbers of cases related to two input variables, which is efficient in particular for a big data sequence of photovoltaic powers systems. Lastly, we predict the output values from a probabilistic model of photovoltaic power systems by using the expectation theory. Two case studies are carried out for testing reliability of the proposed modeling methodology in this paper.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.11
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• pp.1700-1713
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• 2018

Objective: The aim of this study was to verify the usefulness of artificial neural networks (ANN), multivariate adaptive regression splines (MARS), naïve Bayes classifier (NBC), general discriminant analysis (GDA), and logistic regression (LR) for dystocia detection in Polish Holstein-Friesian Black-and-White heifers and cows and to indicate the most influential predictors of calving difficulty. Methods: A total of 1,342 and 1,699 calving records including six categorical and four continuous predictors were used. Calving category (difficult vs easy or difficult, moderate and easy) was the dependent variable. Results: The maximum sensitivity, specificity and accuracy achieved for heifers on the independent test set were 0.855 (for ANN), 0.969 (for NBC), and 0.813 (for GDA), respectively, whereas the values for cows were 0.600 (for ANN), 1.000 and 0.965 (for NBC, GDA, and LR), respectively. With the three categories of calving difficulty, the maximum overall accuracy for heifers and cows was 0.589 (for MARS) and 0.649 (for ANN), respectively. The most influential predictors for heifers were an average calving difficulty score for the dam's sire, calving age and the mean yield of the farm, where the heifer was kept, whereas for cows, these additionally included: calf sex, the difficulty of the preceding calving, and the mean daily milk yield for the preceding lactation. Conclusion: The potential application of the investigated models in dairy cattle farming requires, however, their further improvement in order to reduce the rate of dystocia misdiagnosis and to increase detection reliability.

• Water for future
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• v.27 no.2
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• pp.147-154
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• 1994

The occurrence condition of debris fiow due to rainfall is given by solving the equations for fiow on a slope. The solution shows that a debris fiow will occur on a slope when the accumulated rainfall within the time of concentration exceeds a certain value determined by the properties of the slope. To estimate this critical value, the system analysis technique would be commendable. In this study, a procedure to fine the critical rainfall from the rainfall data whith and without debris flows is proposed. Reliability of this method is verified by applying to the debris flows in Unzen Volcano which recently began to erupt. Discharge of debris flow in a stream is obtained by solving the equation of continuity using the kinematic wave theory and assuming the cross sectional area to be a function of discharge. The computed hydrographs agree weel with the ones observed at the rivers in Sakurajima and Unzen Volcanos. It is found from the derived equation that the runoff intensity of debris flow is in proportion to the rainfall intensity and accumulated rainfall, jointly. This gives a theoretical basis to the conventional method which has been widely used.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.729-734
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• 2017

A safety relief valve is a device that relieves excessive pressure in piping lines or tanks and maintains pressure at the appropriate pressure level for use. The (pressure in the) safety valve is directly influenced by the change in the back pressure, depending on whether the vents in the spring bonnet are vented to the atmosphere or to the outlet. The back pressure is divided into the built-up back pressure and the superimposed back pressure, and the back pressure characteristics vary according to the usage conditions. The safety valve used in this study is a Conventional Safety Relief Valve. The blowdown of the safety valve is predicted by establishing the equilibrium equation between the opening force and spring force considering the back pressure characteristics. Its reliability is secured by using CFX17.1. In addition, the safety of the safety valve trim was examined through fluid-structure interaction analysis.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.61-69
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• 2017

This study aims to investigate the public big data standard analysis model developed by Ministry of the Interior and examine its accuracy and reliability of prediction. To do this, big data standard analysis index were calculated to apply them to the real world case of CCTV monitoring system prior installation in K city. The result of this case study revealed that the areas to be installed CCTV consisted with the area where residences requested and complained to install CCTV monitoring systems, which indicated that the result of big data standard analysis model provided accurate and reliable outcomes. The result of this study suggested implications on effective exploitation of big data analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.10
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• pp.1291-1296
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• 2013

Risk-based inspection (RBI) is a well-known method that is used to optimize inspection activities based on risk analysis in order to identify the high-risk components of major facilities such as power plants. RBI, when implemented and maintained properly, improves plant reliability and safety while reducing unplanned outages and repair costs. Risk is given by the product of the probability of failure (POF) and the consequence of failure (COF). A semi-quantitative method is generally used for risk assessment. Semi-quantitative risk assessment complements the low accuracy of qualitative risk assessment and the high expense and long calculation time of quantitative risk assessment. The first step of RBI is to identify important failure modes and causes in the equipment. Once these are defined, the POF and COF can be assessed for each failure. During POF and COF assessment, an effective inspection method and range can be easily found. In this paper, the calculation of the POF is improved for accurate risk assessment. A modified semi-quantitative risk assessment was carried out for boiler facilities of thermal power plants, and the next maintenance schedules for the equipment were decided.