• Water for future
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• v.29 no.6
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• pp.167-178
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• 1996

The simulation techniques of hydrologic data series have been developed for the purposes of the design of water resources system, the optimization of reservoir operation, and the design of flood control of reservoir, etx. While the stochastic models are usually used in most analysis of water resources fields for the generation of data sequences, the indexed sequential modeling (ISM) method based on generation of a series of overlapping short-term flow sequences directly from the historical record has been used for the data generation in western USA since the early of 1980's. It was reported that the reliable results by ISM were obtained in practical applications. In this study, we generate annual inflow series at a location of Hong Cheon Dam site by using ISM method and first order autoregressive model (AR(1)), and estimate the drought characteristics for the comparison aim between ISM and AR(1).

• International Journal of Vascular Biomedical Engineering
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• v.2 no.1
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• pp.17-24
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• 2004

Tumor angiogenesis was simulated using a two-dimensional computational model. The equation that governed angiogenesis comprised a tumor angiogenesis factor (TAF) conservation equation in time and space, which was solved numerically using the Galerkin finite element method. The time derivative in the equation was approximated by a forward Euler scheme. A stochastic process model was used to simulate vessel formation and vessel elongation towards a paracrine site, i.e., tumor-secreted basic fibroblast growth factor (bFGF). In this study, we assumed a two-dimensional model that represented a thin (1.0 mm) slice of the tumor. The growth of the tumor over time was modeled according to the dynamic value of bFGF secreted within the tumor. The data used for the model were based on a previously reported model of a brain tumor in which four distinct stages (namely multicellular spherical, first detectable lesion, diagnosis, and death of the virtual patient) were modeled. In our study, computation was not continued beyond the 'diagnosis' time point to avoid the computational complexity of analyzing numerous vascular branches. The numerical solutions revealed that no bFGF remained within the region in which vessels developed, owing to the uptake of bFGF by endothelial cells. Consequently, a sharp, declining gradient of bFGF existed near the surface of the tumor. The vascular architecture developed numerous branches close to the tumor surface (the brush-border effect). Asymmetrical tumor growth was associated with a greater degree of branching at the tumor surface.

• Journal of the Korean Society for Advanced Composite Structures
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• v.1 no.2
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• pp.29-35
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• 2010

In addition to the Young's modulus, the Poisson's ratio is also at the center of attention in the field stochastic finite element analysis since the parameters play an important role in determining structural behavior. Accordingly, the sole effect of this parameter on the response variability is of importance from the perspective of estimation of uncertain response. To this end, a formulation to determine the response variability in laminate composite plates due to the spatial randomness of Poisson's ratio is suggested. The independent contributions of random Poisson's ratiocan be captured in terms of sub-matrices which include the effect of the random parameter in the same order, which can be attained by using the Taylor's series expansion about the mean of the parameter. In order to validate the adequacy of the proposed formulation, several example analyses are performed, and then the results are compared with Monte Carlo simulation (MCS). A good agreement between the suggested scheme and MCS is observed showing the adequacy of the scheme.

• Journal of Korean Society of Steel Construction
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• v.20 no.1
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• pp.21-31
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• 2008

response surface method (RSM) is widely used to evaluate th e extremely smal probability of ocurence or toanalyze the reliability of very complicated structures. Althoug h Monte-Carlo Simulation (MCS) technique can evaluate any system, the procesing time of MCS dependson the reciprocal num ber of the probability of failure. The stochastic finite element method could solve thislimitation. However, it is limit ed to the specific program, in which the mean and coeficient o f random variables are programed by a perturbation or by a weigh ted integral method. Therefore, it is not aplicable when erequisite programing. In a few number of stage analyses, RSM can construct a regresion model from the response of the c omplicated structural system, thus, saving time and efort significantly. However, the acuracy of RSM depends on the dist ance of the axial points and on the linearity of the limit stat e functions. To improve the convergence in exact solution regardl es of the linearity limit of state functions, an improved adaptive response surface method is developed. The analyzed res ults have ben verified using linear and quadratic forms of response surface functions in two examples. As a result, the be st combination of the improved RSM techniques is determined and programed in a numerical code. The developed linear adapti ve weighted response surface method (LAW-RSM) shows the closest converged reliability indices, compared with quadratic form or non-adaptive or non-weighted RSMs.

• Wind and Structures
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• v.10 no.4
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• pp.367-382
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• 2007

A nonlinear numerical method was developed to assess the stability of suspension bridge catwalks under a wind load. A section model wind tunnel test was used to obtain a catwalk's aerostatic coefficients, from which the displacement-dependent wind loads were subsequently derived. The stability of a suspension bridge catwalk was analyzed on the basis of the geometric nonlinear behavior of the structure. In addition, a full model test was conducted on the catwalk, which spanned 960 m. A comparison of the displacement values between the test and the numerical simulation shows that a numerical method based on a section model test can be used to effectively and accurately evaluate the stability of a catwalk. A case study features the stability of the catwalk of the Runyang Yangtze suspension bridge, the main span of which is 1490 m. Wind can generally attack the structure from any direction. Whenever the wind comes at a yaw angle, there are six wind load components that act on the catwalk. If the yaw angle is equal to zero, the wind is normal to the catwalk (called normal wind) and the six load components are reduced to three components. Three aerostatic coefficients of the catwalk can be obtained through a section model test with traditional test equipment. However, six aerostatic coefficients of the catwalk must be acquired with the aid of special section model test equipment. A nonlinear numerical method was used study the stability of a catwalk under a yaw wind, while taking into account the six components of the displacement-dependent wind load and the geometric nonlinearity of the catwalk. The results show that when wind attacks with a slight yaw angle, the critical velocity that induces static instability of the catwalk may be lower than the critical velocity of normal wind. However, as the yaw angle of the wind becomes larger, the critical velocity increases. In the atmospheric boundary layer, the wind is turbulent and the velocity history is a random time history. The effects of turbulent wind on the stability of a catwalk are also assessed. The wind velocity fields are regarded as stationary Gaussian stochastic processes, which can be simulated by a spectral representation method. A nonlinear finite-element model set forepart and the Newmark integration method was used to calculate the wind-induced buffeting responses. The results confirm that the turbulent character of wind has little influence on the stability of the catwalk.