• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.426-426
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• 2000

When real robot manipulators arc mathematically modeled, uncertainties are not avoidable. The uncertainties are often nonlinear and time varying, The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance and etc. We proposed a class of robust hybrid position/force control of manipulators and provided the stability analysis in the previous work. In the work, we propose a class of adaptive robust hybrid position/force control of manipulators with bound estimation and the stability based on Lyapunov function is presented. Especially, this controller does not need the information of uncertainty bound. The simulation results are provided to show the effectiveness of the algorithm.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1999.04a
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• pp.61-68
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• 1999

In the nonlinear dynamic structural analysis the given ground excitation as an input should be well defined. Because of the lack of recorded accelerograms in Korea it is required to generate an artificial earthquake by a stochastic model of ground excitation with various dynamic properties rather than recorded accelerograms. It is well known that earthquake motions are generally non-stationary with time-varying intensity and frequency content. Many researchers have proposed non-stationary random process models. Yeh and Wen (1990) proposed a non-stationary modulation function and a power spectral density function to describe such non-stationary characteristics. Satio and Wen(1994) proposed a non-stationary stochastic process model to generate earthquake ground motions which are compatible with design reponse spectrum at sites in Japan. this paper shows the process to modify power spectrum compatible with target design response spectrum for generating of nonstationary artificial earthquake ground motions. Target reponse spectrum is chosen by ATC14 to calibrate the response spectrum according to a give recurrence period.

• Journal of Power Electronics
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• v.19 no.1
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• pp.190-200
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• 2019

The flyback converter, which can be regarded as a nonlinear time-varying system, has complex dynamics and nonlinear behaviors. These phenomena can affect the stability of the converter. To simplify the modeling process and retain the information of the output capacitor branch, a special sampled-data model of a peak current-mode (PCM) controlled flyback converter is established in this paper. Based on this, its dynamic behaviors are analyzed, which provides guidance for designing the circuit parameters of the converter. With the critical stability boundary equation derived by a Jacobian matrix, the stable operation range with a varied output capacitor, proportional coefficient of error the amplifier, input voltage, reference voltage and slope of the compensation ramp of a PCM controlled flyback converter are investigated in detail. Research results show that the duty ratio should be less than 0.5 for a PCM controlled flyback converter without ramp compensation to operate in a stable state. The stability regions in the parameter space between the output capacitor and the proportional coefficient of the error amplifier are enlarged by increasing the input voltage or by decreasing the reference voltage. Furthermore, the ramp compensation also can extend to the stable region. Finally, time-domain simulations and experimental results are presented to verify the theoretical analysis results.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.2
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• pp.85-91
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• 2016

The most important factor in the structural design of ships and offshore structures operating in arctic region is ice load, which results from ice-structure interaction during the ice collision process. The mechanical properties of ice related to strength and failure, however, show very complicated aspect varying with temperature, volume fraction of brine, grain size, strain rate and etc. So it is nearly impossible to establish a perfect material model of ice satisfying all the mechanical characteristics completely. Therefore, in general, ice collision analysis was carried out by relatively simple material models considering only specific aspects of mechanical characteristics of ice and it would be the most significant cause of inevitable errors in the analysis. Especially, it is well-known that the most distinctive mechanical property of ice is high dependency on strain rate. Ice shows brittle attribute in higher strain rate while it becomes ductile in lower strain rate range. In this study, the simulation method of ice collision to ship hull using the nonlinear dynamic FE analysis was dealt with. To consider the strain rate effects of ice during ice-structural interaction, strain rate dependent constitutive model in which yield stress and hardening behaviors vary with strain rate was adopted. To reduce the huge amount of computing time, the modeling range of ice and ship structure were restricted to the confined region of interest. Under the various scenario of ice-ship hull collision, the structural behavior of hull panels and failure modes of ice were examined by nonlinear FE analysis technique.

• Computers and Concrete
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• v.20 no.1
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• pp.31-38
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• 2017

In the present study an Artificial Neural Network (ANN) was used to predict the compressive strength of self-compacting concrete. The data developed experimentally for self-compacting concrete and the data sets of a total of 99 concrete samples were used in this work. ANN's are considered as nonlinear statistical data modeling tools where complex relationships between inputs and outputs are modeled or patterns are found. In the present ANN model, eight input parameters are used to predict the compressive strength of self-compacting of concrete. These include varying amounts of cement, coarse aggregate, fine aggregate, fly ash, fiber, water, super plasticizer (SP), viscosity modifying admixture (VMA) while the single output parameter is the compressive strength of concrete. The importance of different input parameters for predicting the strengths at various ages using neural network was discussed in the study. There is a perfect correlation between the experimental and prediction of the compressive strength of SCC based on ANN with very low root mean square errors. Also, the efficiency of ANN model is better compared to the multivariable regression analysis (MRA). Hence it can be concluded that the ANN model has more potential compared to MRA model in developing an optimum mix proportion for predicting the compressive strength of concrete without much loss of material and time.

• Composites Research
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• v.12 no.5
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• pp.98-109
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• 1999

An investigation has been performed to develop a nonlinear finire element method for the analysis of the long-term behavior of an artificial hip joint. The three dimensional multi-layered brick element is used to analyze the design performances of hip prodtheses with various materials and the thick laminated composite hip prostheses with various layup sequences. The used element can accommodate the varying material properties of the element and allow the ply-drop-off along the eleement edge. The nonlinear finite element analysis program has been verified by the comparison with the exact solution of the bean problem subjected to uniaxial loading. By using the program, the density changes and strength ratios of artificial hip joint are calculated according to the hip prosthesis materials and the layers of composite hip prosthesis. The numerical results are easily applied to evaluate design performances of a hip prosthesis, and decrease the difficulty and time of hip prosthesis design.

• Structural Engineering and Mechanics
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• v.88 no.4
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• pp.389-403
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• 2023

In order to explore the influence of tooth root cracks on the dynamic characteristics of multi-stage planetary gear transmission systems, a concentrated parameter method was used to construct a nonlinear dynamic model of the system with 30-DOF in bending and torsion, taking into account factors such as crack depth, length, angle, error, time-varying meshing stiffness (TVMS), and damping. In the model, the energy method was used to establish a TVMS model with cracks, and the influence of cracks on the TVMS of the system was studied. By using the Runge- Kutta method to calculate the differential equations of system dynamics, a series of system vibration diagrams containing cracks were obtained, and the influence of different crack parameters on the vibration of the system was analyzed. And vibration testing experiments were conducted on the system with planetary gear cracks. The results show that when the gear contains cracks, the TVMS of the system will decrease, and as the cracks intensify, the TVMS will decrease. When cracks appear on the II-stage planetary gear, the system will experience impact effects with intervals of rotation cycles of the II-stage planetary gear. There will be obvious sidebands near the meshing frequency doubling, and the vibration trajectory of the gear will also become disordered. These situations will become more and more obvious as the degree of cracks intensifies. Through experiments, the theoretical results are in good agreement with experimental results, verifying the correctness of the theoretical model. This provides a theoretical basis for fault diagnosis and reliability research of the system.

• Advances in nano research
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• v.10 no.2
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• pp.151-163
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• 2021

The main target of this study is to investigate nonlinear transient responses of moving polymer nano-size plates fortified by means of Graphene Platelets (GPLs) and resting on a Winkler-Pasternak foundation under a transverse pressure force and a temperature variation. Two graphene spreading forms dispersed through the plate thickness are studied, and the Halpin-Tsai micro-mechanics model is used to obtain the effective Young's modulus. Furthermore, the rule of mixture is employed to calculate the effective mass density and Poisson's ratio. In accordance with the first order shear deformation and von Karman theory for nonlinear systems, the kinematic equations are derived, and then nonlocal strain gradient scheme is used to reflect the effects of nonlocal and strain gradient parameters on small-size objects. Afterwards, a combined approach, kinetic dynamic relaxation method accompanied by Newmark technique, is hired for solving the time-varying equation sets, and Fortran program is developed to generate the numerical results. The accuracy of the current model is verified by comparative studies with available results in the literature. Finally, a parametric study is carried out to explore the effects of GPL's weight fractions and dispersion patterns, edge conditions, softening and hardening factors, the temperature change, the velocity of moving nanoplate and elastic foundation stiffness on the dynamic response of the structure. The result illustrates that the effects of nonlocality and strain gradient parameters are more remarkable in the higher magnitudes of the nanoplate speed.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.2
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• pp.106-121
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• 2020

In order to make harbor outskirt facilities robust using the reliability-based design, probabilistic models of wave heights at varying stage of shoaling process optimized for Korean sea waves are prerequisite. In this rationale, we numerically simulate the nonlinear shoaling process of random waves over the beach with a sandbar at its foreshore. In doing so, comprehensive numerical models made of spatially filtered Navier-Stokes Eq., LES [Large Eddy Simulation], dynamic Smagorinsky turbulence closure were used. Considering the characteristics of swells observed at the east coast of Korean Peninsula, random waves were simulated using JONSWAP wave spectrum of various peak enhancement coefficients and random phase method. The coefficients of probabilistic models proposed in this study are estimated from the results of frequency analysis of wave crests and its associated trough detected by Wave by Wave Analysis of the time series of numerically simulated free surface displacements based on the threshold crossing method. Numerical results show that Modified Glukhovskiy wave height distribution, the most referred probabilistic models at finite water depth in the literature, over-predicts the occurring probability of relatively large and small wave heights, and under predicts the occurrence rate of waves of moderate heights. On the other hand, probabilistic models developed in this study show vary encouraging agreements. In addition, the discrepancy of the Modified Glukhovskiy distribution from the measured one are most visible over the surf zone, and as a result, the Modified Glukhovskiy distribution should be applied with caution for the reliability-based design of harbor outskirt facilities deployed near the surf-zone.

• Computers and Concrete
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• v.15 no.2
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• pp.167-181
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• 2015

"Mortar or concrete pneumatically projected at high velocity onto a surface" is called Shotcrete. Models that predict shotcrete design parameters (e.g. compressive strength, slump etc) from any mixing proportions of admixtures could save considerable experimentation time consumed during trial and error based procedures. Artificial Neural Network (ANN) has been widely used for similar purposes; however, such models have been rarely applied on shotcrete design. In this study 19 samples of shotcrete test panels with varying quantities of water, steel fibers and silica fume were used to determine their slump, cost and compressive strength at different ages. A number of 3-layer Back propagation Neural Network (BPNN) models of different network architectures were used to train the network using 15 samples, while 4 samples were randomly chosen to validate the model. The predicted compressive strength from linear regression lacked accuracy with $R^2$ value of 0.36. Whereas, outputs from 3-5-3 ANN architecture gave higher correlations of $R^2$ = 0.99, 0.95 and 0.98 for compressive strength, cost and slump parameters of the training data and corresponding $R^2$ values of 0.99, 0.99 and 0.90 for the validation dataset. Sensitivity analysis of output variables using ANN can unfold the nonlinear cause and effect relationship for otherwise obscure ANN model.