• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.21-26
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• 2001

In this study, we propose a two degree of freedom robust output tracking control method for a class of nonlinear system. We consider hyperbolically nonminimum phase single-input single-output uncertain nonlinear systems. We also consider the case that the nominal input-state equation is differentially flat. Nominal stable state trajectory is obtained in the flat output space via the flat output. Nominal feedforward control input is also computed from the nominal state trajectory. Due to the nature of the method, the generated flat output trajectory and control input are noncausal. Robust feedback control is designed to stabilize the systems around the nominal trajectory. A numerical example is given is given to demonstrate that robust tracking is achieved.

• Journal of Environmental Science International
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• v.14 no.6
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• pp.577-582
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• 2005

Enormous apartment complexes in urban areas, temporary inversion state and heat island effect occur due to the strong sunshine and weak wind speeds which hinders the dispersion of air pollutants that are emitted from neighboring areas of apartment complexes. In this study, analysis were conducted by using the Fluent code based on the CFD(Computation Fluid Dynamics), including building layout, material, building height from the ground surface, the heat, analysis of flow field in the apartment complex. It was estimated that the temporal radiation inversion phenomenon during the daytime, which was caused by the weak wind speed and higher temperatures in the upper level, contributed to the stagnation of the air pollutants in the lower layer of the apartment complex.

• Journal of information and communication convergence engineering
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• v.17 no.4
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• pp.227-233
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• 2019

In long-haul optical communication system consisting of standard single-mode fiber spans and fiber amplifiers, such as the erbium-doped fiber amplifier, performance is deteriorated by signal distortion due to chromatic dispersion and nonlinearity of the fiber. A combination of dispersion management and optical phase conjugation is an effective technique to compensate for the distortion. In an optical link configured by this combination, a dispersion map mainly affects the compensation of the distorted optical signals. This paper proposes new dispersion maps configured by the decaying or expanding distribution of residual dispersion per span (RDPS) in a dispersion-managed link combined with a midway optical phase conjugator. The effect of the proposed dispersion maps on the compensation for distorted 24 channel × 40 Gbps wavelength-division multiplexed signals was assessed through numerical simulation. It was confirmed that all the proposed dispersion maps are most appropriate for the compensation and, furthermore, for the flexibility of link configuration than conventional links.

• Geophysics and Geophysical Exploration
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• v.9 no.1
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• pp.93-101
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• 2006

In this study, we propose a joint inversion method, using genetic algorithms, to determine the shear-wave velocity structure of deep sedimentary layers from receiver functions and surface-wave phase velocity. Numerical experiments with synthetic data indicate that the proposed method can avoid the trade-off between shear-wave velocity and thickness that arises when inverting the receiver function only, and the uncertainty in deep structure from surface-wave phase velocity inversion alone. We apply the method to receiver functions obtained from earthquake records with epicentral distances of about 100 km, and Rayleigh-wave phase velocities obtained from a microtremor array survey in the Kanto Plain, Japan. The estimated subsurface structure is in good agreement with the previous results of seismic refraction surveys and deep borehole data.

• The Journal of the Acoustical Society of Korea
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• v.39 no.3
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• pp.151-162
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• 2020

This paper presents an acoustic inversion method for estimating the bubble size distribution. The estimation error of the attenuation coefficient represented by a Fredholm integral equation of the first kind is defined as an objective function, and an optimal solution is found by applying the Levenberg-Marquardt (LM) method. In order to validate the effectiveness of the inversion method, numerical simulations using two types of bubble distribution are performed. In addition, a series of experiments are carried out in a water tank (1.0 m × 0.54 m × 0.6 m), using bubbles generated by three different generators. Images of the distributed bubbles are obtained by a high-speed camera, and the insertion losses of the bubble layer are measured using a source and a hydrophone. The image is post-processed to glance a distribution characteristics of each bubble generator. Finally, the size distribution of bubbles is estimated by applying the inversion method to the measured insertion loss. From the inversion results, it was observed that the number of bubbles increases exponentially as the bubble size decreases, and then increases again after the local peak at 70 ㎛ - 120 ㎛.

• Geophysics and Geophysical Exploration
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• v.16 no.4
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• pp.217-224
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• 2013

We developed a time-lapse inversion using new cross-model constraints based on change ratio and resolution of model parameters. The cross-model constraint based on change ratio imposes the same penalty on the model parameters with equal change ratio. This constraint can emphasize the model parameters with significant change regardless of their increase or decrease. The resolution cross-model constraint imposes a small penalty on the model parameters with poor resolution, but a large penalty on the model parameters with good resolution. Thus, the model parameter with poor resolution can be effectively identified in the inversion result if they are significantly changed with time. Through the numerical tests for 3D resistivity monitoring data sets, the performance of these two cross-model constraints was confirmed. Finally, for the safety estimation of a sea dyke, we applied the developed time-lapse inversion to the 3D resistivity monitoring data that were acquired at a sea dike located in western coastal area of Korea. The result of time-lapse inversion suggested that there were no significant changes at the sea dike during the monitoring period.

• Geophysics and Geophysical Exploration
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• v.16 no.4
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• pp.211-216
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• 2013

In general, smoothing filters regularize functions by reducing differences between adjacent values. The smoothing filters, therefore, can regularize inverse solutions and produce more accurate subsurface structure when we apply it to full waveform inversion. If we apply a smoothing filter with a constant coefficient to subsurface image or velocity model, it will make layer interfaces and fault structures vague because it does not consider any information of geologic structures and variations of velocity. In this study, we develop a selective smoothing regularization technique, which adapts smoothing coefficients according to inversion iteration, to solve the weakness of smoothing regularization with a constant coefficient. First, we determine appropriate frequencies and analyze the corresponding wavenumber coverage. Then, we define effective maximum wavenumber as 99 percentile of wavenumber spectrum in order to choose smoothing coefficients which can effectively limit the wavenumber coverage. By adapting the chosen smoothing coefficients according to the iteration, we can implement multi-scale full waveform inversion while inverting multi-frequency components simultaneously. Through the successful inversion example on a salt model with high-contrast velocity structures, we can note that our method effectively regularizes the inverse solution. We also verify that our scheme is applicable to field data through the numerical example to the synthetic data containing random noise.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.84-93
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• 2023

The supervised learning-based deep-learning seismic inversion techniques have demonstrated successful performance in synthetic data examples targeting small-scale areas. The supervised learning-based deep-learning seismic inversion uses time-domain wavefields as input and subsurface velocity models as output. Because the time-domain wavefields contain various types of wave information, the data size is considerably large. Therefore, research applying supervised learning-based deep-learning seismic inversion trained with a significant amount of field-scale data has not yet been conducted. In this study, we predict subsurface velocity models using Laplace-domain wavefields as input instead of time-domain wavefields to apply a supervised learning-based deep-learning seismic inversion technique to field-scale data. Using Laplace-domain wavefields instead of time-domain wavefields significantly reduces the size of the input data, thereby accelerating the neural network training, although the resolution of the results is reduced. Additionally, a large grid interval can be used to efficiently predict the velocity model of the field data size, and the results obtained can be used as the initial model for subsequent inversions. The neural network is trained using only synthetic data by generating a massive synthetic velocity model and Laplace-domain wavefields of the same size as the field-scale data. In addition, we adopt a towed-streamer acquisition geometry to simulate a marine seismic survey. Testing the trained network on numerical examples using the test data and a benchmark model yielded appropriate background velocity models.

• Economic and Environmental Geology
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• v.33 no.1
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• pp.41-50
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• 2000

Geo-radar survey which has the advantage of high-resolution and relatively fast survey has been widely used for engineering and environmental problems. Three-dimensional effects have to be considered in the interpretation of geo-radar for high-resolution. However, there exists a trouble on the analysis of the three dimensional effects. To solve this problem an efficient three dimension numerical modeling algorithm is needed. Numerical radar modeling in three dimensional case requires large memory and long calculating time. In this paper, a finite difference method time domain solution to Maxwell's equations for simulating electromagnetic wave propagation in three dimensional media was developed to make economic algorithm which requires smaller memory and shorter calculating time. And in using boundary condition Liao absorption boundary. The numerical result of cross-hole radar survey for tunnel is compared with real data. The two results are well matched. To prove application to three dimensional analysis, the results with variation of tunnel's incident angle to survey cross-section and the result when the tunnel is parallel to the cross-section were examined. This algorithm is useful in various geo-radar survey and can give basic data to develop dat processing and inversion program.

• Tunnel and Underground Space
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• v.7 no.4
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• pp.334-340
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• 1997

Alpha center theory which was first proposed by Stefanescu has been proved to be effective for the detection of the location of the conductive orebody. A numerical forward modeling was conducted to verify the effectiveness of this method. Field works were carried out along the three profiles in two different areas for the purpose of finding fractured zone which might be accompanied with the presence of the groundwater. And the results were modeled by alpha center method, which was later testified by wellproven 2-dimensional finite difference inversion scheme. Field data could be successfully modeled with this alpha center algorithm, especially for the smooth-varying resistivity models. For the abrupt change of the resistivity values, the alpha center coefficients have a tendency to be negative to simulate the steep resistivity gradients. This method is quite simple and easy for the future applications. The numerical calculation can be performed very quickly with the personal computers.