• Structural Engineering and Mechanics
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• v.22 no.3
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• pp.371-399
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• 2006

The theoretical background and capabilities of the developed program, SAR-CWF, for stochastic analysis of 3D reinforced-concrete shear wall-frame structures subject to seismic excitations is presented. Incremental stiffness and strength properties of system members are modeled by extended Roufaiel-Meyer hysteretic relation for bending while shear deformations for walls by Origin-Oriented hysteretic model. For the critical height of shear-walls, division to sub-elements is performed. Different yield capacities with respect to positive and negative bending, finite extensions of plastic hinges and P-${\delta}$ effects are considered while strength deterioration is controlled by accumulated hysteretic energy. Simulated strong motions are obtained from a Gaussian white-noise filtered through Kanai-Tajimi filter. Dynamic equations of motion for the system are formed according to constitutive and compatibility relations and then inserted into equivalent It$\hat{o}$-Stratonovich stochastic differential equations. A system reduction scheme based on the series expansion of eigen-modes of the undamaged structure is implemented. Time histories of seismic response statistics are obtained by utilizing the computer programs developed for different types of structures.

• Journal of Power Electronics
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• v.12 no.1
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• pp.145-156
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• 2012

These days, the application of electronic power transformers (EPTs) is expanding in place of ordinary power transformers. These transformers can transmit power via three or four wire converters. Their dynamic performance is extremely important, due to their complex structure. In this paper, a new method is proposed for improving the dynamic performance of distribution electronic power transformers (DEPT) by using sliding mode control (SMC). Hence, to express the dynamic characteristics of a system, different factors such as the voltage unbalance, voltage sag, voltage harmonics and voltage flicker in the system primary side are considered. The four controlling aims of the improvement in dynamic performance include: 1) maintaining the input currents so that they are in sinusoidal form and in phase with the input voltages so they have a unity power factor, 2) keeping the dc-link voltage within the reference amount, 3) keeping the output voltages at a fixed amount and 4) keeping the output voltages in sinusoidal and symmetrical forms. Simulation results indicate the potential and capability of the proposed method in improving DEPT behavior.

• Steel and Composite Structures
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• v.24 no.2
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• pp.249-264
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• 2017

In this paper free linear vibration of lattice composite conical shells will be investigated. Lattice composite conical shell consists of composite helical ribs and thin outer skin. A smeared method is employed to obtain the variable coefficients of stiffness of conical shell. The ribs are modeled as a beam and in addition to the axial loads, endure shear loads and bending moments. Therefore, theoretical formulations are based on first-order shear deformation theory of shell. For verification of the obtained results, comparison is made with those available in open literature. Also, using FEM software the 3D finite element model of composite lattice conical shell is built and analyzed. Comparing results of analytical and numerical analyses show a good agreement between them. Some special cases as variation of geometric parameters of lattice part, effect of the boundary conditions and influence of the circumferential wave numbers on the natural frequencies of the conical shell are studied. It is concluded, when mass and the geometrical ratio of the composite lattice conical shell do not change, increment the semi vertex angle of cone leads to increase the natural frequencies. Moreover for shell thicknesses greater than a specific value, the presence of the lattice structure has not significant effect on the natural frequencies. The obtained results have novelty and can be used for further and future researches.

• Structural Monitoring and Maintenance
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• v.5 no.3
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• pp.325-343
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• 2018

This study aims to propose a performance-based design method of a novel passive base isolation system, BIO isolation system, which is inspired by an energy dissipation mechanism called 'sacrificial bonds and hidden length'. Fragility functions utilized in this study are derived, indicating the probability that a component, element, or system will be damaged as a function of a single predictive demand parameter. Based on PEER framework methodology for Performance-Based Earthquake Engineering (PBEE), a systematic design procedure using performance and fragility objectives is presented. Base displacement, superstructure absolute acceleration and story drift ratio are selected as engineering demand parameters. The new design method is then performed on a general two degree-of-freedom (2DOF) structure model and the optimal design under different seismic intensities is obtained through numerical analysis. Seismic performances of the biologically inspired (BIO) isolation system are compared with that of the linear isolation system. To further demonstrate the feasibility and effectiveness of this method, the BIO isolation system of a 4-storey reinforced concrete building is designed and investigated. The newly designed BIO isolators effectively decrease the superstructure responses and base displacement under selected earthquake excitations, showing good seismic performance.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.8
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• pp.664-674
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• 2001

In this paper, as a new category of fuzzy-neural networks architecture, we propose Fuzzy Polynomial Neural Networks (FPNN) and discuss a comprehensive design methodology related to its architecture. FPNN dwells on the ideas of fuzzy rule-based computing and neural networks. The FPNN architecture consists of layers with activation nodes based on fuzzy inference rules. Here each activation node is presented as Fuzzy Polynomial Neuron(FPN). The conclusion part of the rules, especially the regression polynomial, uses several types of high-order polynomials such as linear, quadratic and modified quadratic. As the premise part of the rules, both triangular and Gaussian-like membership functions are studied. It is worth stressing that the number of the layers and the nods in each layer of the FPNN are not predetermined, unlike in the case of the popular multilayer perceptron structure, but these are generated in a dynamic manner. With the aid of two representative time series process data, a detailed design procedure is discussed, and the stability is introduced as a measure of stability of the model for the comparative analysis of various architectures.

• Knowledge Management Research
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• v.15 no.4
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• pp.207-221
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• 2014

Due to the awareness for the importance of social capital, many researches have investigated that social capital contributes to the successful implementation of product innovation. Although most researchers tried to model the effect of social capital on product innovation as a linear relation, we consider it too simplistic and fuzzy because knowledge utilization which ultimately leads to product innovation should exist in the relationship between social capital and product innovation. Using 107 survey data, this study found there is a partial mediating effect of knowledge utilization on the link between structure aspect of social capital and product innovation (i.e., new product development and improvement in existing products). Next, this study reported knowledge utilization does act as a perfect mediating variable on the link between awareness aspect of social capital and improvement of existing products, but act as a partial mediating variable on the link between awareness aspect of social capital and new product development. Finally, this study found that knowledge utilization does not act as a mediating variable on the link between relation aspect of social capita and product innovation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.5
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• pp.705-711
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• 2013

In this paper, we introduce an design of multi-output fuzzy neural networks based on Interval Type-2 fuzzy set. The proposed Interval Type-2 fuzzy set-based fuzzy neural networks with multi-output (IT2FS-based FNNm) comprise the network structure generated by dividing the input space individually. The premise part of the fuzzy rules of the network reflects the individuality of the division space for the entire input space and the consequent part of the fuzzy rules expresses three types of polynomial functions with interval sets such as constant, linear, and modified quadratic inference for pattern recognition. The learning of fuzzy neural networks is realized by adjusting connections of the neurons in the consequent part of the fuzzy rules, and it follows a back-propagation algorithm. In addition, in order to optimize the network, the parameters of the network such as apexes of membership functions, uncertainty factor, learning rate and momentum coefficient were automatically optimized by using real-coded genetic algorithm. The proposed model is evaluated with the use of numerical experimentation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2068-2086
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• 2011

Based on the quincunx sub-sampling grid, the New Interleaved Hierarchical INTerpolation (NIHINT) method is recognized as a superior pyramid data structure for the lossless and progressive coding of natural images. In this paper, we propose a new image interpolation algorithm, Edge Adaptive Hierarchical INTerpolation (EAHINT), for a further reduction in the entropy of interpolation errors. We compute the local variance of the causal context to model the strength of a local edge around a target pixel and then apply three statistical decision rules to classify the local edge into a strong edge, a weak edge, or a medium edge. According to these local edge types, we apply an interpolation method to the target pixel using a one-directional interpolator for a strong edge, a multi-directional adaptive weighting interpolator for a medium edge, or a non-directional static weighting linear interpolator for a weak edge. Experimental results show that the proposed algorithm achieves a better compression bit rate than the NIHINT method for lossless image coding. It is shown that the compression bit rate is much better for images that are rich in directional edges and textures. Our algorithm also shows better rate-distortion performance and visual quality for progressive image transmission.

• Structural Engineering and Mechanics
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• v.63 no.1
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• pp.47-53
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• 2017

The fundamental goal of this study is to minimize the uncertainty of the median fragility curve and to assess the structural vulnerability under earthquake excitation. Bayesian Inference with Markov Chain Monte Carlo (MCMC) simulation has been presented for efficient collapse response assessment of the independent intake water tower. The intake tower is significantly used as a diversion type of the hydropower station for maintaining power plant, reservoir and spillway tunnel. Therefore, the seismic fragility assessment of the intake tower is a pivotal component for estimating total system risk of the reservoir. In this investigation, an asymmetrical independent slender reinforced concrete structure is considered. The Bayesian Inference method provides the flexibility to integrate the prior information of collapse response data with the numerical analysis results. The preliminary information of risk data can be obtained from various sources like experiments, existing studies, and simplified linear dynamic analysis or nonlinear static analysis. The conventional lognormal model is used for plotting the fragility curve using the data from time history simulation and nonlinear static pushover analysis respectively. The Bayesian Inference approach is applied for integrating the data from both analyses with the help of MCMC simulation. The method achieves meaningful improvement of uncertainty associated with the fragility curve, and provides significant statistical and computational efficiency.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.77-87
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• 2012

Recently, Load and Resistance Factor Design (LRFD) based on reliability analysis has become a global trend for economical and rational design. In order to implement the LRFD, quantification of uncertainty for load and resistance should be done. The reliability of result relies on input variable, and therefore, it is important to obtain exact uncertainty properties of load and resistance. Since soil stress is the main reason causing the settlement or deformation of ground and load on the underground structure, it is essential to clarify the uncertainty of soil stress distribution for accurately predict the uncertainty of load in LRFD. In this study, laboratory model test on silty sand bed under probabilistic load is performed to observe propagation of upper load uncertainty. The results show that the coefficient of variation (COV) of soil stress are varied depending on location due to non-linear relationship between upper load increment and soil pressure increment. In addition, when the load uncertainty is transmitted through ground, COV is decreased by damping effect.