• Journal of the Society of Naval Architects of Korea
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• v.57 no.5
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• pp.287-296
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• 2020

The present study aims to improve the accuracy of the maneuvering simulations based on captive model test results. To derive the hydrodynamic coefficients in a self-propelled condition, a mathematical maneuvering model using a whole vehicle model was established. Captive model tests were carried out using the Vertical Planar Motion Mechanism (VPMM) equipment. A motor controller was used to control the constant propeller revolution rate during pure motion tests. The resistance tests, self-propulsion tests, static drift tests, and VPMM tests were performed in the towing tank of Seoul National University. When the vertical drift angle changes, the gravity load on the sensors were changed. The hydrodynamic forces were deduced by subtracting the gravity load from the measured forces. The hydrodynamic coefficients were calculated using the least-square method. The simulation of the turning circle test was compared with the free-running model test result, and the error of the turning radius was 8.3 % compared to the free-running model test.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.5
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• pp.531-538
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• 2016

Driving behaviors such as speeding and illegal u-turn which violate traffic rules are main causes of car accidents, and they can lead to serious accidents. Bus drivers are less aware of dangers of illegal u-turn, and infrastructures such as traffic enforcement equipment and watchmen are deficient. This research aims to develop technology for estimating driving behaviors based on map-matching in order to prevent illegal u-turns. For this research, 23,782 of u-turn permit data and 146,000 of speed limit data are collected nationwide, and an estimation algorithm is built with these data. Then, an application based on android is developed, and finally, tests are conducted to assess the accuracy in data computations and GPS data map-matching, and to extrapolate driving behavior. As a result of the tests, the accuracy results in the map-matching is 86% and the assessment of driving behavior is 83%, while the display of the data output yielded 100% accuracy. Additional research should focus on improvement in accuracy through the development of a robust monitoring system, and study of service scenarios for technology application.

• Structural Engineering and Mechanics
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• v.47 no.5
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• pp.679-700
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• 2013

Two new predictive design methods are presented in this study. The first is a hybrid method, called neuro-fuzzy, based on neural networks with fuzzy learning. A total of 280 experimental datasets obtained from the literature concerning concentric punching shear tests of reinforced concrete slab-column connections without shear reinforcement were used to test the model (194 for experimentation and 86 for validation) and were endorsed by statistical validation criteria. The punching shear strength predicted by the neuro-fuzzy model was compared with those predicted by current models of punching shear, widely used in the design practice, such as ACI 318-08, SIA262 and CBA93. The neuro-fuzzy model showed high predictive accuracy of resistance to punching according to all of the relevant codes. A second, more user-friendly design method is presented based on a predictive linear regression model that supports all the geometric and material parameters involved in predicting punching shear. Despite its simplicity, this formulation showed accuracy equivalent to that of the neuro-fuzzy model.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.984-989
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• 2003

The integrated global position system (GPS) and inertial navigation system (INS) has been considered as a cost-effective way of providing an accurate and reliable navigation system for civil and military system. Even the integration of a navigation sensor as a supporting device requires the development of non-traditional approaches and algorithms. The objective of this paper is to assess the feasibility of integrated with GPS and INS information, to provide the navigation capability for long term accuracy of the integrated system. Advanced algorithms are used to integrate the GPS and INS sensor data. That is fuzzy inference system based Weighted Extended Kalman Filter(FWEKF) algorithm INS signal corrections to provided an accurate navigation system of the integrated GPS and INS. Repeatedly, these include INS error, calculated platform corrections using GPS outputs, velocity corrections, position correction and error model estimation for prediction. Therefore, the paper introduces the newly developed technology which is aimed at achieving high accuracy results with integrated system. Finally, in this paper are given the results of simulation tests of the integrated system and the results show very good performance

• Smart Structures and Systems
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• v.14 no.6
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• pp.1105-1129
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• 2014

The unscented Kalman filter (UKF) has been developed for nonlinear model parametric identification, and it assumes that the model parameters are symmetrically distributed about their mean values without any constrains. However, the parameters in many applications are confined within certain ranges to make sense physically. In this paper, a constrained unscented Kalman filter (CUKF) algorithm is proposed to improve accuracy of numerical substructure modeling in hybrid testing. During hybrid testing, the numerical models of numerical substructures which are assumed identical to the physical substructures are updated online with the CUKF approach based on the measurement data from physical substructures. The CUKF method adopts sigma points (i.e., sample points) projecting strategy, with which the positions and weights of sigma points violating constraints are modified. The effectiveness of the proposed hybrid testing method is verified by pure numerical simulation and real-time as well as slower hybrid tests with nonlinear specimens. The results show that the new method has better accuracy compared to conventional hybrid testing with fixed numerical model and hybrid testing based on model updating with UKF.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.5
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• pp.713-718
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• 2016

Predicting precise specifications of differential mixed-signal circuits is a difficult problem, because analytically derived correlation between process variations and conventional specifications exhibits the limited prediction accuracy due to the phase unbalance, for most self-tests. This paper proposes an efficient prediction technique to provide accurate specifications of differential mixed-signal circuits in a system-on-chip (SoC) based on a nonlinear statistical nonlinear regression technique. A spectrally pure sinusoidal signal is applied to a differential DUT, and its output is fed into another differential DUT through a weighting circuitry in the loopback configuration. The weighting circuitry, which is employed from the previous work [3], efficiently produces different weights on the harmonics of the loopback responses, i.e., the signatures. The correlation models, which map the signatures to the conventional specifications, are built based on the statistical nonlinear regression technique, in order to predict accurate nonlinearities of individual DUTs. In production testing, once the efficient signatures are measured, and plugged into the obtained correlation models, the harmonic coefficients of DUTs are readily identified. This work provides a practical test solution to overcome the serious test issue of differential mixed-signal circuits; the low accuracy of analytically derived model is much lower by the errors from the unbalance. Hardware measurement results showed less than 1.0 dB of the prediction error, validating that this approach can be used as production test.

• Journal of TMJ Balancing Medicine
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• v.2 no.1
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• pp.8-12
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• 2012

Objectives: It has been reported to continue that temporomandibular joint balancing medicine (functional cerebrospinal therapy; FCST) is effective in treating incurable diseases in clinic recently. FCST is based on the results of restricted cervical rotation test, it means that the results of restricted cervical rotation test has a very high reliability on test results. Methods: This study has the aim to understand restricted cervical rotation test method and to use well with high technical skill. So manual muscle test method which was based on the upper limb lifting resistance test method are compared with restricted cervical rotation test method and had been discussed. Results: Results are that restricted cervical rotation test by using the passive motion of arrested persons (patients) have high the reliability and accuracy. Conclusions: It is concluded that restricted cervical rotation test is the new type of manual muscle tests and the results of test are very high the reliability and accuracy so that the acquirement of test method is helpful in clinic practically.

• Earthquakes and Structures
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• v.12 no.6
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• pp.699-712
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• 2017

This study evaluates the effectiveness of a newly developed retrofitting scheme for masonry-infilled non-ductile RC frames experimentally and by numerical simulation. The technique focuses on modifying the load path and yield mechanism of the infilled frame to enhance the ductility. A vertical gap between the column and the infill panel was strategically introduced so that no shear force is directly transferred to the column. Steel brackets and small vertical steel members were then provided to transfer the interactive forces between the RC frame and the masonry panel. Wire meshes and high-strength mortar were provided in areas with high stress concentration and in the panel to further reduce damage. Cyclic load tests on a large-scale specimen of a single-bay, single-story, masonry-infilled RC frame were carried out. Based on those tests, the retrofitting scheme provided significant improvement, especially in terms of ductility enhancement. All retrofitted specimens clearly exhibited much better performances than those stipulated in building standards for masonry-infilled structures. A macro-scale computer model based on a diagonal-strut concept was also developed for predicting the global behavior of the retrofitted masonry-infilled frames. This proposed model was effectively used to evaluate the global responses of the test specimens with acceptable accuracy, especially in terms of strength, stiffness and damage condition.

• Steel and Composite Structures
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• v.28 no.5
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• pp.517-525
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• 2018

The specimens made by Z2CND18.12N austenitic stainless steel were conducted on a 100 kN closed loop servo hydraulic tension-compression testing machine with a digital controller. Uniaxial tension and uniaxial ratcheting effect tests were carried out at $25^{\circ}C$. Moreover, Uniaxial tension tests were conducted at $150^{\circ}C$, $250^{\circ}C$ and $350^{\circ}C$. Based on these experimental data, the prediction models of stress-strain curve and the relationship of ratcheting strain and number of cycles were established by the algorithm principle of BP neural network. The results indicated that the predicted results of neural network model were in well agreement with experimental data. It was found that the BP neural network model had high validity and accuracy.

• Steel and Composite Structures
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• v.34 no.5
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• pp.715-732
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• 2020

High-strength steel composite Y-eccentrically braced frame (Y-HSS-EBF) is a novel structural system. In this study, the spatial substructure hybrid simulation test (SHST) method is used to further study the seismic performance of Y-HSS-EBF. Firstly, based on the cyclic loading tests of two single-story single-span Y-HSS-EBF planar specimens, a finite element model in OpenSees was verified to provide a reference for the numerical substructure analysis model for the later SHST. Then, the SHST was carried out on the OpenFresco test platform. A three-story spatial Y-HSS-EBF model was taken as the prototype, the top story was taken as the experimental substructure, and the remaining two stories were taken as the numerical substructure to be simulated in OpenSees. According to the test results, the validity of the SHST was verified, and the main seismic performance indexes of the SHST model were analyzed. The results show that, the SHST based on the OpenFresco platform has good stability and accuracy, and the results of the SHST agree well with the global numerical model of the structure. Under strong seismic action, the plastic deformation of Y-HSS-EBF mainly occurs in the shear link, and the beam, beam-columns and braces can basically remain in the elastic state, which is conducive to post-earthquake repair.