• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.609-615
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• 2001

In this paper, the eigenvalue sensitivity of vehicle powertrain was investigated by analytic method. The powertrain system was considered as a rigid body with multiple engine mounts, and the engine mounts were supposed as three linear springs in three orthogonal directions. The design parameters for the sensitivity analysis were engine mount properties (positions, stiffness, and orientations) and powertrain properties (mass, second moment of inertia, and center of gravity). Firstly, an effective form of eigenvalue problem for the powertrain system was introduced. Then, the analytic sensitivity of eigenvalue was derived using the equation. Lastly, the derived sensitivity equation was applied to a real powertrain system to provide its correctness and applicability.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.4
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• pp.305-312
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• 2000

This paper presents a new control scheme using a sliding mode controller with a multilayer neural network for the robot manipulator operating under the sea which has large uncertainties such as the buoyancy and the added mass/moment of inertia. The multilayer neural network using the error back propagation loaming algorithm acts as a compensator of the conventional sliding mode controller to improve the control performance when the initial assumptions of uncertainty bounds are not valid. Computer simulation results show that the proposed control scheme gives an effective path way to cope with the unexpected large uncertainties in the underwater robot manipulator.

• Journal of the Earthquake Engineering Society of Korea
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• v.3 no.2
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• pp.1-8
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• 1999

The present paper describes an approximation for estimation of earthquake-induced hydrodynamic loads in rigid storage tank which accelerated in horizontal direction. The storage tank is vertically cylindrical, and the sectional shape may be circular, rectangular or irregular. The solution for harmonic excitation is studied based on velocity potential theory, and then the time domain solution for earthquake is obtained by using design response spectrum. As a result, earthquake load is influenced primarily by the inertia force of high frequency effective mass of the storage tank, responding to the characteristics of design response spectrum, tank sectional shape, and the ratio of tank base length to depth. Earthquake-induced hydrodynamic loads in rigid storage tank can be effectively obtained by using the high frequency approximation method in case of quite large, or small ratio of the tank base length to water depth.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.5
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• pp.309-316
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• 2022

This study proposes a finite element analysis method that can analyze the vibration of a beam by considering the inertia effect of moving masses in a vertical direction. The proposed method is effective when a precise interaction analysis is not required. The inertial effects of the moving masses are included in the equation of motion, and the interaction forces between the masses and the beam are considered only as external loads. Time domain analyses were performed using Abaqus, a general-purpose finite element analysis software, and an implementation method using multi-point constraints wais presented to link the displacements of the beam element nodes and moving rigid masses. The proposed method was verified by comparing its solution with that obtained using an existing analytical method, and the analysis results for continuous beam vibrations under dynamic gait loadings were used to examine the mass effect of pedestrians.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.2
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• pp.238-244
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• 2002

A 5-valve(intake 3-valve) engine has been developed to increase engine performance. These engines have a high power caused by the decrease of inertia mass of an intake valve and the increase of intake effective area. In this study, in-cylinder flow patterns were visualized with laser sheet method and velocity profiles at near intake valves were inspected by using a two-color PIV. In addition, steady flow tests were performed to quantify tumble ratio of flow-fields generated by a tumble control valve(TCV). Experimental results of steady flow test show that the cure of tumble ratio in intake 3-valve engine farmed as a S shape with valve lift changes. This tendency is different from the one in intake 2-valve engine. Using laser sheet method and two color PIV method, we can find that the intake flow through upper valve increases and the velocity gradient also slightly increases as valve lift increases. From this study, the in-cylinder flow characteristics around intake valves were made clearly.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.10
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• pp.1157-1162
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• 2014

Two acceleration methods, an effective force method (or inertia method) and a large mass method, have been applied for performing time history seismic analysis. The acceleration methods for uncracked structures have been verified via previous studies. However, no study has identified the validity of these acceleration methods for cracked piping. In this study, the validity of the acceleration methods for through-wall cracked piping is assessed via time history implicit dynamic elastic seismic analysis from the viewpoint of linear elastic fracture mechanics. As a result, it is identified that both acceleration methods show the same results for cracked piping if a large mass magnitude and maximum time increment are adequately selected.

• Structural Engineering and Mechanics
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• v.85 no.4
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• pp.469-484
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• 2023

A deep recursive bidirectional Cuda Deep Neural Network Long Short Term Memory (Bi-CuDNNLSTM) layer is recruited in this paper to predict the entire force time histories, and the corresponding hysteresis and backbone curves of reinforced concrete (RC) bridge piers using experimental fast and slow cyclic tests. The proposed stacked Bi-CuDNNLSTM layers involve multiple uncertain input variables, including horizontal actuator displacements, vertical actuators axial loads, the effective height of the bridge pier, the moment of inertia, and mass. The functional application programming interface in the Keras Python library is utilized to develop a deep learning model considering all the above various input attributes. To have a robust and reliable prediction, the dataset for both the fast and slow cyclic tests is split into three mutually exclusive subsets of training, validation, and testing (unseen). The whole datasets include 17 RC bridge piers tested experimentally ten for fast and seven for slow cyclic tests. The results bring to light that the mean absolute error, as a loss function, is monotonically decreased to zero for both the training and validation datasets after 5000 epochs, and a high level of correlation is observed between the predicted and the experimentally measured values of the force time histories for all the datasets, more than 90%. It can be concluded that the maximum mean of the normalized error, obtained through Box-Whisker plot and Gaussian distribution of normalized error, associated with unseen data is about 10% and 3% for the fast and slow cyclic tests, respectively. In recapitulation, it brings to an end that the stacked Bi-CuDNNLSTM layer implemented in this study has a myriad of benefits in reducing the time and experimental costs for conducting new fast and slow cyclic tests in the future and results in a fast and accurate insight into hysteretic behavior of bridge piers.