• 제목/요약/키워드: nonlinear modeling parameters

검색결과 333건 처리시간 0.021초

Probabilistic seismic assessment of structures considering soil uncertainties

  • Hamidpour, Sara;Soltani, Masoud;Shabdin, Mojtaba
    • Earthquakes and Structures
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    • 제12권2호
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    • pp.165-175
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    • 2017
  • This paper studies soil properties uncertainty and its implementation in the seismic response evaluation of structures. For this, response sensitivity of two 4- and 12-story RC shear walls to the soil properties uncertainty by considering soil structure interaction (SSI) effects is investigated. Beam on Nonlinear Winkler Foundation (BNWF) model is used for shallow foundation modeling and the uncertainty of soil properties is expanded to the foundation stiffness and strength parameters variability. Monte Carlo (MC) simulation technique is employed for probabilistic evaluations. By investigating the probabilistic evaluation results it's observed that as the soil and foundation become stiffer, the soil uncertainty is found to be less important in influencing the response variability. On the other hand, the soil uncertainty becomes more important as the foundation-structure system is expected to experience nonlinear behavior to more sever degree. Since full This paper studies soil properties uncertainty and its implementation in the seismic response evaluation of structures. For this, response sensitivity of two 4- and 12-story RC shear walls to the soil properties uncertainty by considering soil structure interaction (SSI) effects is investigated. Beam on Nonlinear Winkler Foundation (BNWF) model is used for shallow foundation modeling and the uncertainty of soil properties is expanded to the foundation stiffness and strength parameters variability. Monte Carlo (MC) simulation technique is employed for probabilistic evaluations. By investigating the probabilistic evaluation results it's observed that as the soil and foundation become stiffer, the soil uncertainty is found to be less important in influencing the response variability. On the other hand, the soil uncertainty becomes more important as the foundation-structure system is expected to experience nonlinear behavior to more sever degree. Since full probabilistic analysis methods like MC commonly are very time consuming, the feasibility of simple approximate methods' application including First Order Second Moment (FOSM) method and ASCE41 proposed approach for the soil uncertainty considerations is investigated. By comparing the results of the approximate methods with the results obtained from MC, it's observed that the results of both FOSM and ASCE41 methods are in good agreement with the results of MC simulation technique and they show acceptable accuracy in predicting the response variability.

Nonlinear modeling of shear strength of SFRC beams using linear genetic programming

  • Gandomi, A.H.;Alavi, A.H.;Yun, G.J.
    • Structural Engineering and Mechanics
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    • 제38권1호
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    • pp.1-25
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    • 2011
  • A new nonlinear model was developed to evaluate the shear resistance of steel fiber-reinforced concrete beams (SFRCB) using linear genetic programming (LGP). The proposed model relates the shear strength to the geometrical and mechanical properties of SFRCB. The best model was selected after developing and controlling several models with different combinations of the influencing parameters. The models were developed using a comprehensive database containing 213 test results of SFRC beams without stirrups obtained through an extensive literature review. The database includes experimental results for normal and high-strength concrete beams. To verify the applicability of the proposed model, it was employed to estimate the shear strength of a part of test results that were not included in the modeling process. The external validation of the model was further verified using several statistical criteria recommended by researchers. The contributions of the parameters affecting the shear strength were evaluated through a sensitivity analysis. The results indicate that the LGP model gives precise estimates of the shear strength of SFRCB. The prediction performance of the model is significantly better than several solutions found in the literature. The LGP-based design equation is remarkably straightforward and useful for pre-design applications.

Dynamic loading tests and analytical modeling for high-damping rubber bearings

  • Kyeonghoon Park;Taiji Mazda;Yukihide Kajita
    • Earthquakes and Structures
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    • 제25권3호
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    • pp.161-175
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    • 2023
  • High-damping rubber bearings (HDRB) are commonly used as seismic isolation devices to protect civil engineering structures from earthquakes. However, the nonlinear hysteresis characteristics of the HDRB, such as their dependence on material properties and hardening phenomena, make predicting their behavior during earthquakes difficult. This study proposes a hysteretic model that can accurately predicts the behavior of shear deformation considering the nonlinearity when designing the seismic isolation structures using HDR bearings. To model the hysteretic characteristics of the HDR, dynamic loading tests were performed by applying sinusoidal and random waves on scaled-down specimens. The test results show that the nonlinear characteristics of the HDR strongly correlate with the shear strain experienced in the past. Furthermore, when shear deformation occurred above a certain level, the hardening phenomenon, wherein the stiffness increased rapidly, was confirmed. Based on the experimental results, the dynamic characteristics of the HDR, equivalent stiffness, equivalent damping ratio, and strain energy were quantitatively evaluated and analyzed. In this study, an improved bilinear HDR model that can reproduce the dependence on shear deformation and hardening phenomena was developed. Additionally, by proposing an objective parameter-setting procedure based on the experimental results, the model was devised such that similar parameters could be set by anyone. Further, an actual dynamic analysis could be performed by modeling with minimal parameters. The proposed model corresponded with the experimental results and successfully reproduced the mechanical characteristics evaluated from experimental results within an error margin of 10%.

Modeling and Control of VSI type FACTS controllers for Power System Dynamic Stability using the current injection method

  • Park, Jung-Soo;Jang, Gil-Soo;Son, Kwang-M.
    • International Journal of Control, Automation, and Systems
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    • 제6권4호
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    • pp.495-505
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    • 2008
  • This paper describes modeling Voltage Sourced Inverter (VSI) type Flexible AC Transmission System (FACTS) controllers and control methods for power system dynamic stability studies. The considered FACTS controllers are the Static Compensator (STATCOM), the Static Synchronous Series Compensator (SSSC), and the Unified Power Flow Controller (UPFC). In this paper, these FACTS controllers are derived in the current injection model, and it is applied to the linear and nonlinear analysis algorithm for power system dynamics studies. The parameters of the FACTS controllers are set to damp the inter-area oscillations, and the supplementary damping controllers and its control schemes are proposed to increase damping abilities of the FACTS controllers. For these works, the linear analysis for each FACTS controller with or without damping controller is executed, and the dynamic characteristics of each FACTS controller are analyzed. The results are verified by the nonlinear analysis using the time-domain simulation.

웨이브렛 변환과 유전 알고리듬을 이용한 퍼지 모델링 (Fuzzy Modeling Using Wavelet Transform and Genetic Algorithm)

  • 이승준;주영훈;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 D
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    • pp.2327-2329
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    • 2000
  • This paper addresses the use of a nonlinear modeling procedure which construct a wavelet-based fuzzy model using genetic algorithm. A fuzzy inference system has the functional equivalence with a wavelet transform. Therefore, a wavelet-based fuzzy model using GA inherits the advantage of wavelet transform. Hereby, its performance is promoted. By help of the ability of GA to search the optimum globally, parameters of wavelet transform is determined closely to the optimal point. The feasibility of the proposed fuzzy model is proved by modelling a highly nonlinear function and comparing it with previous research.

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Modeling of supersonic nonlinear flutter of plates on a visco-elastic foundation

  • Khudayarov, Bakhtiyar Alimovich
    • Advances in aircraft and spacecraft science
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    • 제6권3호
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    • pp.257-272
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    • 2019
  • Numerical study of the flutter of a plate on a viscoelastic foundation is carried out in the paper. Critical velocity of the flutter of a plate on an elastic and viscoelastic foundation is determined. The mathematical model for the investigation of viscoelastic plates is based on the Marguerre's theory applied to the study of the problems of strength, rigidity and stability of thin-walled structures such as aircraft wings. Aerodynamic pressure is determined in accordance with the A.A. Ilyushin's piston theory. Using the Bubnov - Galerkin method, the basic resolving systems of nonlinear integro-differential equations (IDE) are obtained. At wide ranges of geometric and physical parameters of viscoelastic plates, their influence on the flutter velocity has been studied in detail.

태양광 시스템의 인공신경망 기반 I-V 특성 모델링 향상 (Improved Modeling of I-V Characteristic Based on Artificial Neural Network in Photovoltaic Systems)

  • 박지원;이종환
    • 반도체디스플레이기술학회지
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    • 제21권3호
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    • pp.135-139
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    • 2022
  • The current-voltage modeling plays an important role in characterizing photovoltaic systems. A solar cell has a nonlinear characteristic with various parameters influenced by the external environments such as the irradiance and the temperature. In order to accurately predict current-voltage characteristics at low irradiance, the artificial neural networks are applied to effectively quantify nonlinear behaviors. In this paper, a multi-layer perceptron scheme that can make accurate predictions is employed to learn complex formulas for large amounts of continuous data. The simulated results of artificial neural networks model show the accuracy improvement by using MATLAB/Simulink.

Estimating model parameters of rockfill materials based on genetic algorithm and strain measurements

  • Li, Shouju;Yu, Shen;Shangguan, Zichang;Wang, Zhiyun
    • Geomechanics and Engineering
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    • 제10권1호
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    • pp.37-48
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    • 2016
  • The hyperbolic stress-strain model has been shown to be valid for modeling nonlinear stress-strain behavior for rockfill materials. The Duncan-Chang nonlinear constitutive model was adopted to characterize the behavior of the modeled rockfill materials in this study. Accurately estimating the model parameters of rockfill materials is a key problem for simulating dam deformations during both the dam construction period and the dam operation period. In order to estimate model parameters, triaxial compression experiments of rockfill materials were performed. Based on a genetic algorithm, the constitutive model parameters of the rockfill material were determined from the triaxial compression experimental data. The investigation results show that the predicted strains provide satisfactory precision when compared with the observed strains and the strains forecasted by a gradient-based optimization algorithm. The effectiveness of the proposed inversion procedure of model parameters was verified by experimental investigation in a laboratory.

A Novel Modeling and Performance Analysis of Imperfect Quadrature Modulator in RF Transmitter

  • Park, Yong-Kuk;Kim, Hyeong-Seok;Lee, Ki-Sik
    • Journal of Electrical Engineering and Technology
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    • 제7권4호
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    • pp.570-575
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    • 2012
  • In a wireless communication RF transmitter, the output of a quadrature modulator (QM) is distorted by not only the linear imperfection features such as in/quadrature-phase (I/Q) input gain imbalance, local phase imbalance, and local gain imbalance but also the nonlinear imperfection features such as direct current (DC) offset and mixer nonlinearity related to in-band spurious signal. In this paper, we propose the unified QM model to analyze the combined effects of the linear and nonlinear imperfection features on the performance of the QM. The unified QM model consists of two identical nonlinear systems and modified I/Q inputs based on the two-port nonlinear mixer model. The unified QM model shows that the output signals can be expressed by mixer circuit parameters such as intercept point and gain as well as the imperfection features. The proposed approach is validated by not only simulation but also measurement.

시선 안정화 시스템의 고 정밀 적응제어 (Adaptive High Precision Control of Lime-of Sight Stabilization System)

  • 전병균;전기준
    • 제어로봇시스템학회논문지
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    • 제7권1호
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    • pp.1155-1161
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    • 2001
  • We propose an adaptive nonlinear control algorithm for high precision tracking and stabilization of LOS(Line-of-Sight). The friction parameters of the LOS gimbal are estimated by off-line evolutionary strategy and the friction is compensated by estimated friction compensator. Especially, as the nonlinear control input in a small tracking error zone is enlarged by the nonlinear function, the steady state error is significantly reduced. The proposed algorithm is a direct adaptive control method based on the Lyapunov stability theory, and its convergence is guaranteed under the limited modeling error or torque disturbance. The performance of the pro-posed algorithm is verified by computer simulation on the LOS gimbal model of a moving vehicle.

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