• Title/Summary/Keyword: Dynamic Inversion Model

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Characterization of Deep Shear Wave Velocity Profiles in the Gimhae Plains Using the Microtremor Array Method (상시미동 표면파 분석에 의한 김해평야 퇴적층 심부 전단파 속도 결정)

  • Kim, Jae Hwi;Jeong, Seokho
    • Journal of the Korean Geotechnical Society
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    • v.38 no.8
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    • pp.17-27
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    • 2022
  • To characterize the dynamic properties of Gimhae Plains sediments, we calculated natural frequencies using microtremor horizontal-to-vertical spectral ratios and derived shear wave velocity profiles by inversion of Rayleigh-wave dispersion curves obtained by the high frequency-wavenumber and modified spatial autocorrelation methods. Our results suggest that in this region, strong amplification of ground motion is expected in the vibration frequency (f ≥ 1 Hz). Additionally, obtained velocity profiles show that shear wave velocities are ~200 and 400 m/s for the shallow marine and old fluvial sediments, respectively. Bedrock is possibly encountered at depths of 60-100 m at most sites. We developed a simplified shear wave velocity model of shallow sediments based on the obtained profiles. Our results suggest that a large area in the Gimhae Plains could be categorized as an S6 site based on the Korean seismic design code (KDS 17 10 00).

Markov Chain Monte Carlo Simulation to Estimate Material Properties of a Layered Half-space (층상 반무한 지반의 물성치 추정을 위한 마르코프 연쇄 몬테카를로 모사 기법)

  • Jin Ho Lee;Hieu Van Nguyen;Se Hyeok Lee
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.36 no.3
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    • pp.203-211
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    • 2023
  • A Markov chain Monte Carlo (MCMC) simulation is proposed for probabilistic full waveform inversion (FWI) in a layered half-space. Dynamic responses on the half-space surface are estimated using the thin-layer method when a harmonic vertical force is applied. Subsequently, a posterior probability distribution function and the corresponding objective function are formulated to minimize the difference between estimations and observed data as well as that of model parameters from prior information. Based on the gradient of the objective function, a proposal distribution and an acceptance probability for MCMC samples are proposed. The proposed MCMC simulation is applied to several layered half-space examples. It is demonstrated that the proposed MCMC simulation for probabilistic FWI can estimate probabilistic material properties such as the shear-wave velocities of a layered half-space.

Extended Slip-Weakening Model and Inference of Rupture Velocity (Slip-Weakening 모델의 확장과 단층 파열속도의 추정)

  • Choi, Hang;Yoon, Byung-Ick
    • Journal of the Earthquake Engineering Society of Korea
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    • v.24 no.5
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    • pp.219-232
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    • 2020
  • The slip-weakening model developed by Ohnaka and Yamashita is extended over the breakdown zone by equating the scaling relationships for the breakdown zone and the whole rupture area. For the extension, the study uses the relationship between rupture velocity and radiation efficiency, which was derived in the theory of linear elastic fracture mechanics, and the definition of fmax given in the specific barrier model proposed by Papageorgiou and Aki. The results clearly show that the extended scaling relationship is governed by the ratio of rupture velocity to S wave velocity, and the velocity ratio can be determined by the ratio of characteristic frequencies of a Fourier amplitude spectrum, which are corner frequency, fc, and source-controlled cut-off frequency, fmax, or vice versa. The derived relationship is tested by using the characteristic frequencies extracted from previous studies of more than 130 shallow crustal events (focal depth less than 25 km, MW 3.0~7.5) that occurred in Japan. Under the assumption of a dynamic similarity, the rupture velocity estimated from fmax/fc and the modified integral timescale give quite similar scale-dependence of the rupture area to that given by Kanamori and Anderson. Also, the results for large earthquakes show good agreement to the values from a kinematic inversion in previous studies. The test results also indicate the unavailability of the spectral self-similarity proposed by Aki because of the scale-dependent rupture velocity and the rupture velocity-dependent fmax/fc; however, the results do support the local similarity asserted by Ohnaka. It is also remarkable that the relationship between the rupture velocity and fmax/fc is quite similar to Kolmogorov's hypothesis on a similarity in the theory of isotropic turbulence.

Fault Tolerant Control of Wind Turbine with Sensor and Actuator Faults

  • Kim, Jiyeon;Yang, Inseok;Lee, Dongik
    • Journal of Sensor Science and Technology
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    • v.22 no.1
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    • pp.28-37
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    • 2013
  • This paper presents a fault-tolerant control technique for wind turbine systems with sensor and actuator faults. The control objective is to maximize power production and minimize turbine loads by calculating a desired pitch angle within their limits. Any fault with a sensor and actuator can cause significant error in the pitch position of the corresponding blade. This problem may result in insufficient torque such that the power reference cannot be achieved. In this paper, a fault-tolerant control technique using a robust dynamic inversion observer and control allocation is employed to achieve successful pitch control despite these faults in the sensor and actuator. The observer based detection method is used to detect and isolate sensor faults by checking whether errors are larger than threshold values. In addition, the control allocation technique is adopted to tolerate actuator fault. Control allocation is one of the most commonly used fault-tolerant control techniques, especially for over-actuated systems. Further, the control allocation method can be used to achieve the power reference even in the event of blade actuator fault by redistributing the lost torque due to erroneous pitch position into non-faulty blade actuators. The effectiveness of the proposed method is demonstrated through simulations with a benchmark model of the wind turbine.

Minimizing Energy Consumption in Scheduling of Dependent Tasks using Genetic Algorithm in Computational Grid

  • Kaiwartya, Omprakash;Prakash, Shiv;Abdullah, Abdul Hanan;Hassan, Ahmed Nazar
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.8
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    • pp.2821-2839
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    • 2015
  • Energy consumption by large computing systems has become an important research theme not only because the sources of energy are depleting fast but also due to the environmental concern. Computational grid is a huge distributed computing platform for the applications that require high end computing resources and consume enormous energy to facilitate execution of jobs. The organizations which are offering services for high end computation, are more cautious about energy consumption and taking utmost steps for saving energy. Therefore, this paper proposes a scheduling technique for Minimizing Energy consumption using Adapted Genetic Algorithm (MiE-AGA) for dependent tasks in Computational Grid (CG). In MiE-AGA, fitness function formulation for energy consumption has been mathematically formulated. An adapted genetic algorithm has been developed for minimizing energy consumption with appropriate modifications in each components of original genetic algorithm such as representation of chromosome, crossover, mutation and inversion operations. Pseudo code for MiE-AGA and its components has been developed with appropriate examples. MiE-AGA is simulated using Java based programs integrated with GridSim. Analysis of simulation results in terms of energy consumption, makespan and average utilization of resources clearly reveals that MiE-AGA effectively optimizes energy, makespan and average utilization of resources in CG. Comparative analysis of the optimization performance between MiE-AGA and the state-of-the-arts algorithms: EAMM, HEFT, Min-Min and Max-Min shows the effectiveness of the model.

Control Law Design for a Tilt-Duct Unmanned Aerial Vehicle using Sigma-Pi Neural Networks (Sigma-Pi 신경망을 이용한 틸트덕트 무인기의 제어기 설계연구)

  • Kang, Youngshin;Park, Bumjin;Cho, Am;Yoo, Changsun
    • Journal of Aerospace System Engineering
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    • v.11 no.1
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    • pp.14-21
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    • 2017
  • A Linear parameterized Sigma-Pi neural network (SPNN) is applied to a tilt-duct unmanned aerial vehicle (UAV) which has a very large longitudinal stability ($C_{L{\alpha}}$). It is uncontrollable by a proportional, integral, derivative (PID) controller due to heavy stability. It is shown that the combined inner loop and outer loop of SPNN controllers could overcome the sluggish longitudinal dynamics using a method of dynamic inversion and pseudo-control to compensate for reference model error. The simulation results of the way point guidance are presented to evaluate the performance of SPNN in comparison to a PID controller.

Pose Transformation of a Frontal Face Image by Invertible Meshwarp Algorithm (역전가능 메쉬워프 알고리즘에 의한 정면 얼굴 영상의 포즈 변형)

  • 오승택;전병환
    • Journal of KIISE:Software and Applications
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    • v.30 no.1_2
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    • pp.153-163
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    • 2003
  • In this paper, we propose a new technique of image based rendering(IBR) for the pose transformation of a face by using only a frontal face image and its mesh without a three-dimensional model. To substitute the 3D geometric model, first, we make up a standard mesh set of a certain person for several face sides ; front. left, right, half-left and half-right sides. For the given person, we compose only the frontal mesh of the frontal face image to be transformed. The other mesh is automatically generated based on the standard mesh set. And then, the frontal face image is geometrically transformed to give different view by using Invertible Meshwarp Algorithm, which is improved to tolerate the overlap or inversion of neighbor vertexes in the mesh. The same warping algorithm is used to generate the opening or closing effect of both eyes and a mouth. To evaluate the transformation performance, we capture dynamic images from 10 persons rotating their heads horizontally. And we measure the location error of 14 main features between the corresponding original and transformed facial images. That is, the average difference is calculated between the distances from the center of both eyes to each feature point for the corresponding original and transformed images. As a result, the average error in feature location is about 7.0% of the distance from the center of both eyes to the center of a mouth.