• The Journal of the Acoustical Society of Korea
• /
• 제15권3E호
• /
• pp.66-73
• /
• 1996

In this paper, we propose the filtered-x least mean fourth (LMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the filtered-x LMF adaptive filter to active noise control(ANC) requires estimating of the transfer characteristic of the acoustic path between the output and error signal of the adaptive controller. The results of the convergence analysis of the filtered-x LMF algorithm indicates that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that convergence behavior can differ depending on the relative sizes of the Gaussian measurement noise and convergence constant.

• 한국지반공학회:학술대회논문집
• /
• 한국지반공학회 2010년도 추계 학술발표회 2차
• /
• pp.122-130
• /
• 2010

In recent days, the foundations of huge structures in general and mega foundations of grand bridges in particular are required in geotechnical engineering. However, previous design method based on virtual fixed point theory cannot adequately predict Pile-Bent structure‘s physical behavior. Therefore, this paper describes a new analysis and design of Pile-Bent structure for grand bridges. A detailed analysis was performed for column-pile interactions using FB-Pier program and Midas program. As a result, the behavior of a column-pile is estimated and highlighted. Moreover, based on this study, it is found that the minimum reinforcement ratio(=0.4%) is applicable for plastic behavior of columns.

• Structural Engineering and Mechanics
• /
• 제41권4호
• /
• pp.539-558
• /
• 2012

The diagnosis of bridge serviceability is carried out by a combination of in-situ visual inspection, static and dynamic loading tests and analyses. Structural health monitoring (SHM) using information technology and sensors is increasingly being used for providing a better estimate of structural performance characteristics rather than above traditional methods. Because the mechanical behavior of bridges with various kinds of damage can not be made clear, it is very difficult to estimate both the damage mode and degree of damage of existing bridges. In this paper, the sensitivity of both static and dynamic behaviors of bridges are studied as a measure of damage assessment through experiments on model bridges induced with some specified artificial damages. And, a method of damage assessment of bridges based on those behaviors is discussed in detail. Finally, based on the results, a possible application for structural health monitoring systems for existing bridges is also discussed.

• Geomechanics and Engineering
• /
• 제21권2호
• /
• pp.103-109
• /
• 2020

The inflow rate is of interest in the design of underground structures such as tunnels and buried pipes below the groundwater table. Soil permeability governing the inflow rate significantly affects the hydro-geological behavior of soils but is difficult to estimate due to its wide range of distribution, nonlinearity and anisotropy. Volume changes induced by stress can cause nonlinear stress-strain behavior, resulting in corresponding permeability changes. In this paper, the nonlinearity and anisotropy of permeability are investigated by conducting Rowe cell tests, and a nonlinear permeability model considering anisotropy was proposed. Model modification and parameter evaluation for field application were also addressed. Significance of nonlinear permeability was illustrated by carrying out numerical analysis of a tunnel. It is highlighted that the effect of nonlinear permeability is significant in soils of which volume change is considerable, and particularly appears in the short-term flow behavior.

• 전자공학회논문지B
• /
• 제32B권11호
• /
• pp.1506-1516
• /
• 1995

In this paper, we propose the filtered-x least mean fourth (FXLMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the FXLMF adaptive filter to active noise control requires to estimate the transfer characteristics of the acoustic path between the output and the error signal of the adaptive controller. The results of the convergence analysis of the FXLMF algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that the convergence behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant.

• 한국음향학회:학술대회논문집
• /
• 한국음향학회 1998년도 학술발표대회 논문집 제5권
• /
• pp.80-83
• /
• 1998

In this paper, we propose a new filtered-x least mean fouth (LMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior or a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the filtered-x LMF adaptive filter to active noise cancellation (ANC) requires estimating of the transfer characteristic of the acoustic path between the ouput and error signal of the adaptive canceller. The results of the convergence analysis of the filtered-x LMF algorithm indicates that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct component . Phase estimation error and estimated again. In particular , the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that convergence behavior can differ depending on the relative sizes of the Gaussian measurement noise and convergence constant.

• Structural Engineering and Mechanics
• /
• 제4권3호
• /
• pp.227-242
• /
• 1996

An important class of problems in the field of geotechnical engineering may be analyzed with the aid of a simple integro-differential equation. Behavior of "rigid" piles(say concrete piles), "deformable" piles(say gravel piles), pile groups, pile-raft foundations, heavily reinforced earth, flow within circular silos and down drag on cylindrical structures (for example the crusher unit of a mineral processing complex) are the type of situations that can be handled by this type of equation. The equation under consideration has the form; $$\frac{{\partial}w(r,\;z)}{{\partial}z}+f(z){\int}^z_0g({\xi})(\frac{{\partial}^2w(r,\;{\xi})}{{\partial}r^2}+\frac{1}{r}\frac{{\partial}w(r,\;{\xi})}{{\partial}r})d{\xi}+h(r,\;z)=0$$ where w(r, z) is the vertical displacement of a soil particle expressed as a function of the polar cylindrical space coordinates (r, z) and the symbols f, g and h represent soil properties and the loading conditions. The merit of the analysis is its simplicity (both in concept and in application) and the ease with which it can be expressed in a computer code. In the present paper the analysis is applied to investigate the behavior of a single rigid pile to bedrock. The emphasis, however, is placed on developing the equation, the numerical techique used in its evaluation and validation of the technique, hereafter called the ID technique, against a formal program, CRISP, which uses the FEM.

• 한국강구조학회 논문집
• /
• 제12권4호통권47호
• /
• pp.339-350
• /
• 2000

본 연구의 목적은 개량 T-stub를 이용한 1층 1스팬 골조의 구조적 거동을 파악하고 중층규모의 건축물에 대하여 개량 T-stub의 적용가능성을 확인하기 위한 것이다. 연구방법으로 개량 T-stub 및 기존 T-stub를 이용한 반강접 골조의 반복가력실험을 하였으며 개량 T-stub의 플랜지 두께와 볼트중심거리를 변수로 하여 유한요소해석을 수행하여 그 결과를 실험결과와 비교하였다. 본 연구의 실험 및 해석결과로부터 개량 T-stub의 거동을 정성적으로 파악하고 반강접합부로서의 적용가능성을 확인하였다.

• 한국구조물진단유지관리공학회 논문집
• /
• 제2권4호
• /
• pp.137-147
• /
• 1998

The neural net application was tried to develop the technique for monitoring the health status of a steel truss bridge which was scaled down to 1/15 of the real bridge for the laboratory experiments. The damage scenarios were chosen as 7 cases. The dynamic behavior, which was changed due to the breakage of the members, of the bridge was investigated by finite element analysis. The bridge consists of single spam, and eight (8) main structural subsystems. The loading vehicle, which weighs as 100 kgf, was operated by the servo-motor controller. The accelerometers were bonded on the surface of 7 cross-beams to measure the dynamic behavior induced by the abnormal structural condition. Artificial neural network technique was used to determine the severity of the damage. At first, the neural net was learnt by the results of finite element analysis, and also, the maximum detection error was 3.65 percents. Another neural net was also learnt, and verified by the experimental results, and in this case, the maximum detection error was 1.05 percents. In future study, neural net is necessary to be learnt and verified by various data from the real bridge.

• 한국암반공학회:학술대회논문집
• /
• 한국암반공학회 2008년도 국제학술회의
• /
• pp.43-51
• /
• 2008

Currently an increasing number of urban tunnels with small overburden are excavated according to the principle of the New Austrian Tunneling Method (NATM). For rational management of tunnels from planning to construction and maintenance stages, prediction, control and monitoring of displacements of and around the tunnel have to be performed with high accuracy. Computational method tools, such as finite element method, have been and are indispensable tool for tunnel engineers for many years. It is, however, a commonly acknowledged fact that determination of input parameters, especially material properties exhibiting nonlinear stress-strain relationship, is not an easy task even for an experienced engineer. Use and application of the acquired tunnel information is important for prediction accuracy and improvement of tunnel behavior on construction. Artificial Neural Network (ANN) model is a form of artificial intelligence that attempts to mimic behavior of human brain and nervous system. The main objective of this paper is to perform the deformation analysis in NATM tunnel by means of numerical simulation and artificial neural network (ANN) with field database. Developed ANN model can achieve a high level of prediction accuracy.