• Advances in environmental research
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• 제1권4호
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• pp.257-276
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• 2012

QSAR models for chlorinated alkenes were developed between $E_{HOMO}$ and their chlorine and carbon content. The aim is to provide valid QSAR model which is statistically validated for $E_{LUMO}$ prediction. Different molecular descriptors, $N_{Cl}$, $N_C$ and $E_{HOMO}$ have been used to take into account relevant information provided by molecular features and physicochemical properties. The best model were selected using Partial Least Square (PLS) and Multiple Linear Regression (MLR) led to models with satisfactory predictive ability for a data set of 15 chlorinated alkene compounds.

• Coupled systems mechanics
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• 제1권4호
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• pp.345-360
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• 2012

In this article we have presented a unique representation for interval arithmetic. The traditional interval arithmetic is transformed into crisp by symbolic parameterization. Then the proposed interval arithmetic is extended for fuzzy numbers and this fuzzy arithmetic is used as a tool for uncertain finite element method. In general, the fuzzy finite element converts the governing differential equations into fuzzy algebraic equations. Fuzzy algebraic equations either give a fuzzy eigenvalue problem or a fuzzy system of linear equations. The proposed methods have been used to solve a test problem namely heat conduction problem along with fuzzy finite element method to see the efficacy and powerfulness of the methodology. As such a coupled set of fuzzy linear equations are obtained. These coupled fuzzy linear equations have been solved by two techniques such as by fuzzy iteration method and fuzzy eigenvalue method. Obtained results are compared and it has seen that the proposed methods are reliable and may be applicable to other heat conduction problems too.

• Smart Structures and Systems
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• 제11권1호
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• pp.103-122
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• 2013

It is essential to update the model with reflecting observation or inspection data for reliability estimation of existing structures. Authors proposed updated reliability analysis by using Particle Filter. We discuss how to apply the proposed method through numerical examples on reinforced concrete structures after verification of the method with hypothetical linear Gaussian problem. Reinforced concrete structures in a marine environment deteriorate with time due to chloride-induced corrosion of reinforcing bars. In the case of existing structures, it is essential to monitor the current condition such as chloride-induced corrosion and to reflect it to rational maintenance with consideration of the uncertainty. In this context, updated reliability estimation of a structure provides useful information for the rational decision. Accuracy estimation is also one of the important issues when Monte Carlo approach such as Particle Filter is adopted. Especially Particle Filter approach has a problem known as degeneracy. Effective sample size is introduced to predict the covariance of variance of limit state exceeding probabilities calculated by Particle Filter. Its validity is shown by the numerical experiments.

• Structural Engineering and Mechanics
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• 제46권3호
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• pp.337-352
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• 2013

Seismic performance of critical facilities has been focused on the structural components over the past decade. However, most earthquake damages were observed to the nonstructural components during and after the earthquakes. The primary objective of this research was to develop the seismic fragility of the piping system incorporating the nonlinear Tee-joint finite element model in the full scale piping configuration installed in critical facilities. The procedure for evaluating fragility curves corresponding to the first damage state was considered the effects of the top floor acceleration sensitivities for 5, 10, 15, and 20 story linear RC and steel building systems subjected to 22 selected ground motions as a function of ground motion uncertainties. The result of this study revealed that the conditional probability of failure of the piping system on the top floor in critical facilities did not increase with increased level of story height and in fact, story level in buildings can tune the fragilities between the building and the piping system.

• Smart Structures and Systems
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• 제11권1호
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• pp.123-134
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• 2013

Identifying structural modal parameters, especially those modes within high frequency range, from ambient data is still a challenging problem due to various kinds of uncertainty involved in vibration measurements. A procedure applying an ensemble empirical mode decomposition (EEMD) method is proposed for accurate and robust structural modal identification. In the proposed method, the EEMD process is first implemented to decompose the original ambient data to a set of intrinsic mode functions (IMFs), which are zero-mean time series with energy in narrow frequency bands. Subsequently, a Sub-PolyMAX method is performed in narrow frequency bands by using IMFs as primary data for structural modal identification. The merit of the proposed method is that it performs structural identification in narrow frequency bands (take IMFs as primary data), unlike the traditional method in the whole frequency space (take original measurements as primary data), thus it produces more accurate identification results. A numerical example and a multiple-span continuous steel bridge have been investigated to verify the effectiveness of the proposed method.

• Structural Engineering and Mechanics
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• 제25권3호
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• pp.331-345
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• 2007

Uncertainties enter a complex analysis from a variety of sources: variability, lack of data, human errors, model simplification and lack of understanding of the underlying physics. However, for many important engineering applications insufficient data are available to justify the choice of a particular probability density function (PDF). Sometimes the only data available are in the form of interval estimates which represent, often conflicting, expert opinion. In this paper we demonstrate that Bayesian estimation techniques can successfully be used in applications where only vague interval measurements are available. The proposed approach is intended to fit within a probabilistic framework, which is established and widely accepted. To circumvent the problem of selecting a specific PDF when only little or vague data are available, a hierarchical model of a continuous family of PDF's is used. The classical Bayesian estimation methods are expanded to make use of imprecise interval data. Each of the expert opinions (interval data) are interpreted as random interval samples of a parent PDF. Consequently, a partial conflict between experts is automatically accounted for through the likelihood function.

• Structural Engineering and Mechanics
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• 제34권4호
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• pp.417-447
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• 2010

The uncertainty often observed in experimental strengths of masonry constituents makes critical the selection of the appropriate inputs in finite element analysis of complex masonry buildings, as well as requires modelling the building ultimate load as a random variable. On the other hand, the utilization of expensive Monte Carlo simulations to estimate collapse load probability distributions may become computationally impractical when a single analysis of a complex building requires hours of computer calculations. To reduce the computational cost of Monte Carlo simulations, direct computer calculations can be replaced with inexpensive Response Surface (RS) models. This work investigates the use of RS models in Monte Carlo analysis of complex masonry buildings with random input parameters. The accuracy of the estimated RS models, as well as the good estimations of the collapse load cumulative distributions obtained via polynomial RS models, show how the proposed approach could be a useful tool in problems of technical interest.

• Smart Structures and Systems
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• 제13권1호
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• pp.155-171
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• 2014

Various monitoring techniques are now available for structural health monitoring and Acoustic Emission (AE) is one of them. One of the major advantages of the AE technique is its capability to locate active cracks in structural members. AE crack locating approaches are affected by the signal attenuation and dispersion of elastic waves due to inhomogeneity and geometry of reinforced concrete (RC) members. In this paper, a novel technique is described based on signal processing and sensor arrangement to process multisensory AE data generated by the onset and propagation of cracks and is validated with experimental results from an in-situ load test. Considering the sources of uncertainty in the AE crack location process, a methodology is proposed to capture and locate events generated by cracks. In particular, the relationship between AE events and load is analyzed, and the feasibility of using the AE technique to evaluate the cracking behavior of two RC slab strips during loading to failure is studied.

• Smart Structures and Systems
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• 제14권3호
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• pp.367-376
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• 2014

Ambient vibration techniques are nowadays a very popular tool to assess dynamic properties of buildings. Due to its non destructive character, this method is particularly valuable, especially for health monitoring of historical monuments. The present ambient vibration experiment consists on the evaluation of vibration modes of a Medieval tower. Situated in Soncino (close to Cremona, in the Northern Italian region named Lombardia), the tower of 41.5 meters height has been monitored by seismometers located at different points inside the structure. Spectral ratios of the recorded ambient vibrations clearly identify a fundamental mode at about 1 Hz, with a slight difference in the two horizontal components. A second mode is also evidenced at approx 4-5 Hz, with a moderate degree of uncertainty. The records of a ML 4.4 earthquake, occurred during the monitoring period, confirm the information obtained by microtremor analysis. Daily variations of both 1st and 2nd mode were detected: these variations, of an amount up to 2%, seem to be well related with the temperature.

• Structural Engineering and Mechanics
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• 제8권5호
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• pp.477-490
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• 1999

The uncertainties associated with structural parameters and dynamic loading are identified and discussed. Structural parametric uncertainties are treated as random variables and dynamic wind load is simulated as a random process. Dynamic wind-induced responses of structures with parametric uncertainties are investigated by using stochastic finite element method. The formulas for structural dynamic reliability analysis considering the randomness of structural resistance and loading are proposed. Two numerical examples of high-rise structures are presented to illustrate the proposed methodology. The calculated results demonstrate that the variation in structural parameters indeed influences the dynamic response and the first passage probability evaluation of structures.