• Journal of Advanced Research in Ocean Engineering
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• v.1 no.3
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• pp.157-167
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• 2015

In order to provide simple and accurate wave theory in design of offshore structure, an analytical approximation is introduced in this paper. The solution is limited to flat bottom having a constant water depth. Water is considered as inviscid, incompressible and irrotational. The solution satisfies the continuity equation, bottom boundary condition and non-linear kinematic free surface boundary condition exactly. Error for dynamic condition is quite small. The solution is suitable in description of breaking waves. The solution is presented with closed form and dispersion relation is also presented with closed form. In the last century, there have been two main approaches to the nonlinear problems. One of these is perturbation method. Stokes wave and Cnoidal wave are based on the method. The other is numerical method. Dean's stream function theory is based on the method. In this paper, power series method was considered. The power series method can be applied to certain nonlinear differential equations (initial value problems). The series coefficients are specified by a nonlinear recurrence inherited from the differential equation. Because the non-linear wave problem is a boundary value problem, the power series method cannot be applied to the problem in general. But finite number of coefficients is necessary to describe the wave profile, truncated power series is enough. Therefore the power series method can be applied to the problem. In this case, the series coefficients are specified by a set of equations instead of recurrence. By using the set of equations, the nonlinear wave problem has been solved in this paper.

• Journal of Korean Society of Steel Construction
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• v.16 no.1 s.68
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• pp.123-134
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• 2004

In this research, a multilevel decomposition technique to enhance the efficiency of the configuration optimization of truss structures was proposed. On the first level, the nonlinear programming problem was formulated considering cross-sectional areas as design variables, weight, or volume as objective function and behavior under multiloading condition as design constraint. Said nonlinear programming problem was transformed into a sequential linear programming problem. which was effective in calculation through the approximation of member forces using behavior space approach. Such approach has proven to be efficient in sensitivity analysis and different form existing shape optimization studies. The modified method of feasible direction (MMFD) was used for the optimization process. On the second level, by treating only shape design variables, the optimum problem was transformed into and unconstrained optimal design problem. A unidirectional search technique was used. As numerical examples, some truss structures were applied to illustrate the applicability. and validity of the formulated algorithm.

• Economic and Environmental Geology
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• v.27 no.3
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• pp.281-287
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• 1994

The present paper deals with numerical modeling of Love channel waves in transversely isotropic elastic medium. First, an explicit finite-difference scheme of second order approximation is formulated with the wave equation of SH particle displacement in transversely isotropic medium. Since it is a heterogeneous formulation, it should enable efficient modeling of complex model structures without additional treatment of the internal boundary matching. With a model of isotropic coal seam embedded in high velocity host rock, seismograms are synthesized and tutn out to be essentially identical with published ones of Korn and $St{\ddot{o}}ckl$. Next, anisotropic coal seams are investigated. It is found that the horizontal velocity of the seam appears to play a major role of determining the group velocity of Love channel waves. The group velocity increases with the increase of the horizontal velocity or vice versa. However, further study will be needed to exploit fully Love channel waves for the determination of lithology, stratification, fracture in sedimentary rocks, for instance, for hydrocarbon exploration and development.

• Structural Engineering and Mechanics
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• v.75 no.4
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• pp.519-527
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• 2020

Dynamic analysis of a vehicle-track coupling system is important to structural design, damage detection and condition assessment of the structural system. Deterministic analysis of the vehicle-track coupling system has been extensively studied in the past, however, the structural parameters of the coupling system have uncertainties in engineering practices. It is essential to treat the parameters of the vehicle-track coupling system with consideration of uncertainties. In this paper, a method for predicting the bounds of the vehicle-track coupling system responses with uncertain parameters is presented. The uncertain system parameters are modeled as fuzzy variables instead of conventional random variables with known probability distributions. Then, the dynamic response functions of the coupling system are transformed into a component function based on the high dimensional representation approximation. The Lagrange interpolation method is used to approximate the component function. Finally, the bounds of the system's dynamic responses can be predicted by using Monte Carlo method for the interpolation polynomials of the Lagrange interpolation function. A numerical example is introduced to illustrate the ability of the proposed method to predict the bounds of the system's dynamic responses, and the results are compared with the direct Monte Carlo method. The results show that the proposed method is effective and efficient to predict the bounds of the system's dynamic responses with fuzzy variables.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.3
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• pp.237-250
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• 2003

Since an orthotropic steel deck bridge has large number of design variables and shows complex structural behavior, it would be very difficult and impractical to directly use a Conventional Single Level (CSL) optimization algorithm for its optimum design. Thus, in this paper, an Improved Multi Level Design Synthesis (IMLDS) optimization algorithm is proposed to improve the computational efficiency. In the proposed IMLDS algorithm, a coordination method is introduced to divide the bridge into main girders and orthotropic steel deck with preserving the characteristics of the structural behavior. For an efficient optimization of the bridge, the IMLDS algorithm incorporates the various crucial approximation techniques such as constraints deletion, Automatic Differentiation (AD), stress reanalysis, and etc. In the case of orthotropic steel deck system, optimum design problems are characterized by mixed continuous discrete variables and discontinuous design space. Thus, a modified Genetic Algorithm (GA) is also applied to optimize discrete member design for orthotropic steel deck. From the numerical example, the efficiency and convergency of the IMLDS algorithm proposed in this paper is investigated. It may be positively stated that the IMLDS algorithm will lead to more effective and practical design compared with previous algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.524-532
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• 2002

This paper reports that the Lambert W function applies to a non-iterative design of minimum mean square-error scalar quantizers for a Laplacian source. Specifically, it considers a non-iterative design algorithm for optimum quantizers for a Laplacian source; it finds that the solution of the recursive nonlinear equation in the non-iterative design is elegantly expressed in term of the principal branch of the Lambert W function in a closed form; and it proves that the non-iterative algorithm applies only to exponential or Laplacian sources. The contribution of the paper is in the reduction of the time needed for the design and the increased accuracy in resulting quantization points and thresholds, because the algorithm is non-iterative and the Lambert W function can be evaluated as accurately as desired. Also, numerical results show how optimal quantization distortion converges monotonically to the Panter-Dite constant and help derive an approximation formula for the key parameters of optimum quantizers.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.6
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• pp.609-615
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• 2011

A two-dimensional Stokes flow past a vertical plate in a channel is analyzed. The vertical plate is located at the center of the channel, and plane Poiseuille flow exists far upstream and downstream of the vertical plate. The Stokes approximation is used, and the flow is investigated analytically using the method of eigenfunction expansion and the point collocation method. From the analysis, the stream function and pressure distribution are obtained, and the pressure and shear stress distributions on the plate and channel wall are calculated. The additional pressure drop induced by the vertical plate and the force exerted on it are calculated as functions of the length of the vertical plate. For a typical length of the vertical plate, the streamline pattern and pressure distribution are shown. In addition, numerical analysis of laminar flow with a small Reynolds number is carried out to analyze the effect of a small Reynolds number on the flow pattern.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1314-1319
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• 2008

Fatigue reliability problems are nowadays actively considered in the design of mechanical components. Recently, Dimension Reduction Method using Kriging approximation (KDRM) was proposed by the authors to efficiently calculate statistical moments of the response function. This method, which is more tractable for its sensitivity-free nature and providing the response PDF in a few number of analyses, is adopted in this study for the reliability analysis. Before applying this method to the practical fatigue problems, accuracies are studied in terms of parameters of the KDRM through a number of numerical examples, from which best set of parameters are suggested. In the fatigue reliability problems, good number of experimental data are necessary to get the statistical distribution of the S-N parameters. The information, however, are not always available due to the limited expense and time. In this case, a family of curves with prediction interval, called P-S-N curve, is constructed from regression analysis. Using the KDRM, once a set of responses are available at the sample points at the mean, all the reliability analyses for each P-S-N curve can be efficiently studied without additional response evaluations. The method is applied to a spring design problem as an illustration of practical applications, in which reliability-based design optimization (RBDO) is conducted by employing stochastic response surface method which includes probabilistic constraints in itself. Resulting information is of great practical value and will be very helpful for making trade-off decision during the fatigue design.

• Structural Engineering and Mechanics
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• v.64 no.4
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• pp.413-426
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• 2017

Probabilistic methods are used in engineering where a computational model contains random variables. The proposed method under development: Direct Optimized Probabilistic Calculation (DOProC) is highly efficient in terms of computation time and solution accuracy and is mostly faster than in case of other standard probabilistic methods. The novelty of the DOProC lies in an optimized numerical integration that easily handles both correlated and statistically independent random variables and does not require any simulation or approximation technique. DOProC is demonstrated by a collection of deliberately selected simple examples (i) to illustrate the efficiency of individual optimization levels and (ii) to verify it against other highly regarded probabilistic methods (e.g., Monte Carlo). Efficiency and other benefits of the proposed method are grounded on a comparative case study carried out using both the DOProC and MC techniques. The algorithm has been implemented in mentioned software applications, and has been used effectively several times in solving probabilistic tasks and in probabilistic reliability assessment of structures. The article summarizes the principles of this method and demonstrates its basic possibilities on simple examples. The paper presents unpublished details of probabilistic computations based on this method, including a reliability assessment, which provides the user with the probability of failure affected by statistically dependent input random variables. The study also mentions the potential of the optimization procedures under development, including an analysis of their effectiveness on the example of the reliability assessment of a slender column.