• Computational Structural Engineering
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• v.10 no.3
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• pp.125-131
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• 1997

Most dynamic systems have are known to various random properties in excitation and system parameters. In this paper, a procedure for response analysis is proposed for the linear dynamic system with random properties in both excitation and system parameters. The system parameters and responses with random properties are modeled by perturbation technique, and then response analysis is formulated by probabilistic and vibration theories. And probabilistic FEM is also used for the calculation of mean response which is difficult by the proposed response model. As an applicative example, the transient response is considered for systems of single degree of freedom with random mass and spring constant subjected to stationary white-noise excitation and the results are compared to those of numerical simulation.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1993.10a
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• pp.248-255
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• 1993

Recently, due to the increasing attention to the structural safety under uncertain environments, many researches on the structural reliability analysis have been peformed. Some useful methods are available to evaluate performance reliability of structures with explicit limit states. However, for large structures, in which structural behaviors can be analyzed with finite element models and the limit states are only expressed implicitly, Monte-Carlo simulation method has been mainly used. However, Monte-Carlo simulation method spends too much computational time on repetitive structural analysis. Many alternative methods are suggested to reduce the computational work required in Monte-Carlo simulation. Response surface method is widely used to improve the efficiency of structural reliability analysis. Response surface method is based on the concept of approximating simple polynomial function of basic random variables for the limit state which is not easily expressed in explicit forms of design random variables. The response surface method has simple algorithm. However, the accuracy of results highly depends on how properly the stochastic characteristics of the original limit state has been represented by approximated function, In this study, an improved response surface method is proposed in which the sampling points for creating response surface are modified to represent the failure surface more adequately and the combined use of a linear response surface function and Rackwitz-Fiessler method has been employed. The method is found to be more effective and efficient than previous response surface methods. In addition more consistent convergence is achieved, Accuracy of the proposed method has been investigated through example.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1322-1327
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• 2003

It is important to determine supporting locations for structural stability of a structure under non-uniform load in space interfered by other parts. In this case, There are many local optima with discontinuous design space. Therefore, The traditional optimization methods based on derivative are not suitable. Whereas, Genetic algorithm(GA) based on stochastic search technique is a very robust and general method. This paper has been presented to determine supporting locations of the vertical supports for reducing stress of the KSTAR(Korea super Superconducting Tokamak Advanced Research) IVCC(In-vessel control coil) under non-uniform electromagnetic load and space interfered by other parts using genetic algorithm. For this study, we develop a program combining finite element analysis with a genetic algorithm to perform structural analysis of IVCC. In addition, this paper presents a technique to perform optimization with FEM when design variables are trapped in an incongruent design space.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5271-5289
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• 2016

On large-scale data analysis platforms deployed on cloud infrastructures over the Internet, the instability of the data transfer time and the dynamics of the processing rate require a more sophisticated data distribution scheme which maximizes parallel efficiency by achieving the balanced load among participated computing elements and by eliminating the idle time of each computing element. In particular, under the constraints that have the real-time and limited data buffer (in-memory storage) are given, it needs more controllable mechanism to prevent both the overflow and the underflow of the finite buffer. In this paper, we propose an auto regulated data provisioning model based on receiver-driven data pull model. On this model, we provide a synchronized data replenishment mechanism that implicitly avoids the data buffer overflow as well as explicitly regulates the data buffer underflow by adequately adjusting the buffer resilience. To estimate the optimal size of buffer resilience, we exploits an adaptive buffer resilience control scheme that minimizes both data buffer space and idle time of the processing elements based on directly measured sample path analysis. The simulation results show that the proposed scheme provides allowable approximation compared to the numerical results. Also, it is suitably efficient to apply for such a dynamic environment that cannot postulate the stochastic characteristic for the data transfer time, the data processing rate, or even an environment where the fluctuation of the both is presented.

• Structural Engineering and Mechanics
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• v.37 no.6
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• pp.593-615
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• 2011

This study determines the water length effects on the modal behavior of a prototype arch dam using Operational and Analytical Modal Analyses. Achievement of this purpose involves construction of a prototype arch dam-reservoir-foundation model under laboratory conditions. In the model, reservoir length was taken to be as much as three times the dam height. To determine the experimental dynamic characteristics of the arch dam using Operational Modal Analysis, ambient vibration tests were implemented for empty reservoir and three different reservoir water lengths. In the ambient vibration tests, the dam was vibrated by natural excitations provided from small impact effects and the response signals were measured using sensitive accelerometers. Operational Modal Analysis software process signals collected from the ambient vibration tests, and Enhanced Frequency Domain Decomposition and Stochastic Subspace Identification techniques estimated modal parameters of the dams. To validate the experimental results, 3D finite element model of the prototype arch dam was modeled by ANSYS software for empty reservoir and three different reservoir water lengths, and dynamic characteristics of each model were determined analytically. At the end of the study, experimentally and analytically identified dynamic characteristics compared to each other. Also, changes on the natural frequencies along to water length are plotted as graphs. Results suggest that reservoir water complicates the modal behavior of the arch dam significantly.

• Composites Research
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• v.17 no.2
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• pp.34-39
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• 2004

In this paper, a modified and representative unit cell model was employed to study the tensile behaviour of closed-cell metallic foams with varying spatial density distribution as well as material imperfections. The density variation was assumed to follow a statistical probability distribution of the Gaussian type. A multiple cell finite element model, utilising the modified unit cell, was developed. The model exhibits deformation patterns similar to those observed in tensile testing. The nominal stress-strain curve obtained from quasistatic tensile of the foam was compared with experimental findings and was found to be in good agreement in the scheme of maximum strength only if the appropriate density distribution and volume fraction of internal imperfections are taken into account. Moreover, maximum tensile strength of the aluminium foam was found to be more sensitive to the volume fraction of imperfection than standard deviation of the density.

• Journal of the Society of Naval Architects of Korea
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• v.35 no.3
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• pp.46-53
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• 1998

The aim of the present study is to develop a direct structural analysis system for more reliable and effective structural safety estimation of floating tripe ocean structures. In this system, the following three modules are included; i.e., a rigid body motion analysis module based on the three dimensional panel method, a structural analysis module, and a stochastic analysis module based on short and long term spectral analysis techniques. The structural analysis module consists of the general purpose finite element analysis program NASTRAN and the automatic load data generation program LOADGEN. As an illustrative example, the developed system is applied to structural design of a PILOT Barge Mounted Plant(BMP). Results of the structural analysis are compared with those obtained using a two dimensional strip method.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.344-352
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• 2019

Marine production strings are continuously affected by unstable internal fluid during operation. In this paper, the structural governing equation for marine production string self-induced vibration is constructed. A finite element analysis model is established based on Euler-Bernoulli theory and solved by the Newmark method. Furthermore, based on reliability theory, a self-design procedure is developed to determine the operability envelope for marine production string self-induced vibration. Case studies show: the response frequency of the production strings is consistent with the excitation frequency under harmonic fluctuation and mainly determined by the first-order natural frequency under stochastic fluctuation. The operability envelope for marine production string self-induced vibration is a near symmetrical trapezium. With the increasing of natural gas output, the permissible fluctuation coefficient dramatically decreases. A reasonable centralizer spacing, increasing top tension, and controlling natural gas output are of great significance to the risk control in marine production string operation.

• Structural Engineering and Mechanics
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• v.84 no.3
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• pp.323-335
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• 2022

The main idea of the framework is to seamlessly combine a reasonably accurate and fast surrogate model with the importance sampling strategy. Developing a surrogate model for predicting structures' dynamic responses is challenging because it involves high-dimensional inputs and outputs. For this purpose, a novel surrogate model based on cutting-edge deep learning architectures specialized for capturing temporal relationships within time-series data, namely Long-Short term memory layer and Transformer layer, is designed. After being properly trained, the surrogate model could be utilized in place of the finite element method to evaluate structures' responses without requiring any specialized software. On the other hand, the importance sampling is adopted to reduce the number of calculations required when computing the failure probability by drawing more relevant samples near critical areas. Thanks to the portability of the trained surrogate model, one can integrate the latter with the Importance sampling in a straightforward fashion, forming an efficient framework called TTIS, which represents double advantages: less number of calculations is needed, and the computational time of each calculation is significantly reduced. The proposed approach's applicability and efficiency are demonstrated through three examples with increasing complexity, involving a 1D beam, a 2D frame, and a 3D building structure. The results show that compared to the conventional Monte Carlo simulation, the proposed method can provide highly similar reliability results with a reduction of up to four orders of magnitudes in time complexity.

• Journal of Korea Water Resources Association
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• v.31 no.5
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• pp.553-564
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• 1998

For the proper design and management of underground storage cavern, groundwater flow around cavern should be analyzed. Since this flow is influenced by spatial nonuniformity of hudraulic conductivity, the two-dimensional finite element flow model incorporating stochastic concepts was developed to analyze influences due to this nonuniformity. Monte Carlo technique was applied to obtain an approximate solution for two-dimensional, steady flow in a stochastically defined nonuniform medisu. For this purpose, the values of hydraulic conductivity were generated for each element with known mean and standard deviations. The uncertainty in model prediction depends on both the nonuniformity in hydraulic conductivity and the natures of the flow system such as water curtain and boundary condition. Therefore the uncertainties in predicted hydraulic head and gradient are the greatest where the mean hydraulic gradients are relatively large and far from the boundaries. Especially, we relate these uncertainties with well known gas tightness condition.