• International Journal of Naval Architecture and Ocean Engineering
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• v.2 no.1
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• pp.24-33
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• 2010

Design of a Pump Jet Propulsor (PJP) was undertaken for an underwater body with axisymmetric configuration using axial/low compressor design techniques supported by Computational Fluid Dynamics (CFD) analysis for performance prediction. Experimental evaluation of the PJP was earned out through experiments in a Wind Tunnel Facility (WTF) using momentum defect principle for propulsive performance prior to proceeding with extensive experimental evaluation in towing tank and cavitation tunnel. Experiments were particularly conducted with respect to Self Propulsion Point (SPP), residual torque and thrust characteristics over a range of vehicle advance ratio in order to ascertain whether sufficient thrust is developed at the design condition with least possible imbalance torque left out due to residual swirl in the slip stream. Pumpjet and body models were developed for the propulsion tests using Aluminum alloy forged material. Tests were conducted from 0 m/s to 30 m/s at four rotational speeds of the PJP. SPP was determined confirming the thrust development capability of PJP. Estimation of residual torque was carried out at SPP corresponding to speeds of 15, 20 and 25 m/s to examine the effectiveness of the stator. Estimation of thrust and residual torque was also carried out at wind speeds 0 and 6 m/s for PJP RPMs corresponding to self propulsion tests to study the propulsion characteristics during the launch of the vehicle m water where advance ratios are close to Zero. These results are essential to assess the thrust performance at very low advance ratios to accelerate the body and to control the body during initial stages. This technique has turned out to be very useful and economical method for quick assessment of overall performance of the propulsor and generation of exhaustive fluid dynamic data to validate CFD techniques employed.

• Journal of the Korean Wood Science and Technology
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• v.45 no.4
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• pp.399-408
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• 2017

Research on the rapid and accurate prediction of physical properties of wood using near-infrared (NIR) spectroscopy has attracted recent attention. In this study, partial least squares analysis was performed between NIR spectra and air-dried specific gravity of five domestic conifer species including larch (Larix kaempferi), Korean pine (Pinus koraiensis), red pine (Pinus densiflora), cedar (Cryptomeria japonica), and cypress (Chamaecyparis obtusa). Fifty different lumbers per species were purchased from the five National Forestry Cooperative Federations of Korea. The air-dried specific gravity of 100 knot- and defect-free specimens of each species was determined by NIR spectroscopy in the range of 680-2500 nm. Spectral data preprocessing including standard normal variate, detrend and forward first derivative (gap size = 8, smoothing = 8) were applied to all the NIR spectra of the specimens. Partial least squares analysis including cross-validation (five groups) was performed with the air-dried specific gravity and NIR spectra. When the performance of the regression model was expressed as $R^2$ (coefficient of determination) and root mean square error of calibration (RMSEC), $R^2$ and RMSEC were 0.63 and 0.027 for larch, 0.68 and 0.033 for Korean pine, 0.62 and 0.033 for red pine, 0.76 and 0.022 for cedar, and 0.79 and 0.027 for cypress, respectively. For the calibration model, which contained all species in this study, the $R^2$ was 0.75 and the RMSEC was 0.37.

• International Journal of Automotive Technology
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• v.5 no.3
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• pp.215-219
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• 2004

A vehicle structure needs to be more precisely analyzed because of complexities and varieties. Structural fatigue which is generated by fluctuations of stresses during the service life of a mechanical system is the primary concern in the structural design for safety. A fatigue life is difficult to obtain in structural components during the service life of mechanical systems since the fluctuating stress contributes to fatigue. This study introduces new procedures to measure the lethargy coefficient and to predict the fatigue life of a mechanical structure by using molecular dynamic simulation. A lethargy coefficient is the total defect-estimating coefficient, which was obtained by using the results of a simple tensile test in this study. With this lethargy coefficient, fatigue life was estimated. The proposed method will be useful in predicting the fatigue life of a structurally-modified vehicle design. The effectiveness of the proposed method using lethargy coefficient measurement to predict the fatigue life of a structure was examined by applying this method to predict the fatigue life of SS41 steel, used extensively as material of vehicle structures. Two types of specimen such as pre-cracked plate and simple plate is discussed. equation of fatigue life using the lethargy coefficient and failure time, both obtained from a simple tensile test, will be useful in engineering. This measurement and prediction technology will be extended for use in analysis of any geometric shapes of modified automotive structures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2037-2042
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• 2017

The manufacturing facility is generally operated by a pre-set program under the existing factory automation system. On the other hand, the manufacturing facility must decide how to operate autonomously in Industry 4.0. Determining the operation mode of the production facility itself means, for example, that it detects the abnormality such as the deterioration of the facility at the shop-floor, prediction of the occurrence of the problem, detection of the defect of the product, In this paper, we propose a manufacturing process modeling using a queue for detection of manufacturing process abnormalities at the shop-floor, and detect abnormalities in the modeling using SVM, one of the machine learning techniques. The queue was used for M / D / 1 and the conveyor belt manufacturing system was modeled based on ${\mu}$, ${\lambda}$, and ${\rho}$. SVM was used to detect anomalous signs through changes in ${\rho}$.

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.5
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• pp.419-426
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• 2000

Generally diode rectifier has been used as Preregulator of arc- welding machine. Its defect is the generation of high current harmonics which result In utility pollution. In this parer, using the three-phase PWM converter, the input performance of arc-welding machine is improved by increasing the input power factor. When the diode rectifier in the arc-welding machine is replaced with three-phase PWM converter, PWM converter should control DC voltage of the output side. If PI controller is used for the output DC voltage regulator, the output DC voltage has high ripple voltage due to the instantaneous load variation in the arc-welding machine. In this paper, the feedforward compensator has been introduced to reduce the DC voltage ripple. It lessens the influence of load current which is the disturbance of the output DC voltage regulator. Theoretical prediction of this analysis has been verified by comparing with experimental data

• Convergence Security Journal
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• v.20 no.2
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• pp.145-153
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• 2020

The aviation safety policy master plan is promoting the development of aviation safety management technology applying the 4th industrial revolution technology with the goal of establishing a flawless aviation safety management system and establishing a future aviation safety infrastructure. The master plan includes the establishment of various aviation safety management systems such as aircraft fault management using AI & Big data and flight training system using VR/AR. Currently, the Air Force is promoting a flight safety management system using new technology under the goal of building smart air force. Therefore, this study intends to apply the 4th Industrial Revolution technology to the aircraft condition check system that finally checks the safety of the aircraft before flight. The Air Force conducts airframe flaw checks and pre-flight aircraft check. In this study, we architect the airframe flaw check system using AI and drones, and the pre-flight aircraft condition check system using the IoT and big data for more precise and detailed check of aircraft condition and flawlessness check.

• Composites Research
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• v.31 no.5
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• pp.251-259
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• 2018

In this paper, statistical volume element modeling method was developed for multi-scale progressive failure analysis of fiber reinforced composite materials. Big-size statistical volume elements (BSVEs) was considered to minimize the size effect in the micro-scale, by including as many fibers as possible. For that purpose, a mesh cutting method is suggested and adapted into the fiber model generator that creates finite element domain rapidly. The fiber defect model was also developed based on the experimental distribution of the fiber strength. The size effects from the local load sharing (LLS) are evaluated by increasing the fiber inclusion in the micro-scale model. Finally, continuum damage mechanics (CDM) model to the fiber direction was extracted from numerical analysis on BSVEs. And it was compared with strength prediction from typical representative volume element (RVE) model.

• Smart Structures and Systems
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• v.19 no.4
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• pp.341-350
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• 2017

Based on the super elastic properties of the shape memory alloy (SMA) and the inverse piezoelectric effect of piezoelectric (PZT) ceramics, a kind of hybrid semi-active control device was designed and made, its mechanical properties test was done under different frequency and different voltage. The local search ability of genetic algorithm is poor, which would fall into the defect of prematurity easily. A kind of adaptive immune memory cloning algorithm(AIMCA) was proposed based on the simulation of clone selection and immune memory process. It can adjust the mutation probability and clone scale adaptively through the way of introducing memory cell and antibody incentive degrees. And performance indicator based on the modal controllable degree was taken as antigen-antibody affinity function, the optimization analysis of damper layout in a space truss structure was done. The structural seismic response was analyzed by applying the neural network prediction model and T-S fuzzy logic. Results show that SMA and PZT friction composite damper has a good energy dissipation capacity and stable performance, the bigger voltage, the better energy dissipation ability. Compared with genetic algorithm, the adaptive immune memory clone algorithm overcomes the problem of prematurity effectively. Besides, it has stronger global searching ability, better population diversity and faster convergence speed, makes the damper has a better arrangement position in structural dampers optimization leading to the better damping effect.

• Journal of Yeungnam Medical Science
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• v.24 no.2
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• pp.179-185
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• 2007

Backgroud : Urinary tract infection (UTI) is common in children. The available gold standard methods for diagnosis, Tc-99m dimercaptosuccinic acid (DMSA) scan and computed tomography (CT) are invasive and expensive. This study was performed to assess the role of power Doppler ultrasound (PDU) for diagnosis of acute pyelonephritis (APN). Materials and Methods : A prospective study was conducted in 25 children with aged 2 weeks to 5 years who were hospitalized with the first episode of febrile UTI suggesting acute pyelonephritis. All children were examined in the first 3-5 days of admission by PDU and Tc-99m DMSA scan. The comparison between PDU and DMSA scan was performed on the basis of patients. Results : The sensitivity and specificity of PDU for the detection of affected kidneys were 38.1% and 50.0%, and the positive predictive value and negative predictive value were 61.9% and 50.0%, respectively. Vesicoureteral refluxes (VUR) were identified in 11 patients (44.4%) and 18 kidneys (36%). The PDU and DMSA scan showed a matching perfusion defect in 23.8% and 50.0% respectively. Conclusion : These data indicate the PDU has a relatively low sensitivity and specificity for differentiating APN from lower UTI but may be a complement tool to DMSA scan for the prediction of VUR in infants and children.

• Korean Journal of Construction Engineering and Management
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• v.16 no.3
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• pp.143-151
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• 2015

The Crack, occurred in the concrete structure, is a major cause of function deterioration such as strength, durability and waterproof. Therefore the need for crack reduction will continue as long as there is concrete structure. But, it is not easy to reduce or prevent crack cause of impact factor of it. There are so many factors of crack such as material, construction and maintenance environment, and structure, and these are acting in combination. So, this study derives a correlation between the cracks and members through reviewing member crack occurred. And member's attribute, related crack, is analyzed by it. It consider that the basic attribute of member is similar when its requirements are similar. Through this study, therefore, foundation of countermeasure of crack will be provided by prediction of crack shape through member's attribute.