The half-wave reduction potential is an important electrochemical property used for the characterization of organic compounds. This property, which is a characteristic constant for a reversible oxidation-reduction system, can be useful for predicting electrochemical properties of other organic compounds. In this work, quantitative structure-property relationship (QSPR) models have been introduced for estimating polarographic half-wave reduction potentials of 21 chlorinated organic compounds. Two QSPR models have been developed based on genetic algorithm-partial least squares (GA-PLS) and stepwise regression-partial least squares (SR-PLS) to predict half-wave potentials (E 1/2 ) of some chlorinated organic compounds. Variable selection is very important for QSPR modelling. In the present study, two selection variables methods were compared to choose molecular descriptors for the construction of a model by the PLS method. Both GA-PLS and SR-PLS methods resulted in accurate prediction, with more accurate results obtained by the GA-PLS model. The respective root mean square error of the prediction set obtained by the GA-PLS and SR-PLS models were 0.082 and 0.1302.

In this article, a novel vibration-based damage detection approach is proposed based on selecting effective cepstral coefficients, consisting of three main stages: (1) signal processing and feature extraction, (2) damage detection by combining effective cepstral coefficients through feature selection methods, and (3) performance evaluation. First, two feature extraction techniques are used in damage identification systems, including linear prediction cepstral coefficients and mel frequency cepstral coefficients. Second, to improve the performance of damage detection, the combination of the effective cepstral coefficients is proposed as a damage index. By applying several feature selection methods, the most effective coefficients are found and then combined to create a subset that carries the most significant information about the structural damage. Finally, the support vector machine classifier is performed to evaluate the proposed approach in detecting the structural damage. The proposed technique is verified using a suite of numerical and full-scale studies. Results confirm that the proposed method achieves a significant performance with great accuracy and reduces false alarms.

This paper presents the probabilistic generation of collapse fragility curves for evaluating the performance of 3D, reinforced concrete (RC) moment-resisting building models, considering soil-structure interaction (SSI) by concentration on seismic uncertainties. It considers collapse as the loss of lateral load-resisting capacity of the building structures due to severe ground shaking and consequent large interstory drifts intensified by -Δ effects as well as the strength and stiffness deterioration of their lateral load carrying systems. The estimation of the collapse performance of structures requires the relation between the intensity measure (IM) and the probability of collapse that is determined using the generated collapse fragility curves. Considering a number of 6-, 12-, and 18-story, 3D, RC moment-resisting buildings, two scalar IMs are employed to estimate their collapse fragility curve. On the other hand, the effect of the site soil type on the collapse fragility curves was taken into account by considering the soil-structure interaction. According to the obtained results, adopting the average of spectral acceleration (Saavg) intensity measure is more efficient in capturing the effect of the inherent uncertainties of the strong ground motions on the structural response parameters. In addition, considering the SSI for soil type D with shear-wave velocity of 180 m/s to 360 m/s reduces the median of intensity measure (IM = Sa( 1 )) of fragility curve in 6-, 12-, and 18-story buildings by 4.92%, 22.26%, and 23.03%, respectively.

The seismic behavior of asymmetric structures with a flexible diaphragm was studied by conducting inelastic dynamic time-history analyses. Asymmetric structures with different configurations of mass, stiffness, and strength centers, in combination with a wide range of diaphragm flexibility, were evaluated. The behavior of structures was studied by considering three aspects: (1) effect of structural asymmetry on diaphragms deformation; (2) effect of diaphragm flexibility on demands of the lateral load-resisting elements; (3) optimum configuration of mass, stiffness, and strength centers to limit important engineering demand parameters in asymmetric structures with a flexible diaphragm. The results showed that the shear-dominant deformation of diaphragms is sensitive to both structure asymmetry specifications and the degree of diaphragm flexibility; therefore, it can be used for the qualitative classification of the seismic behavior of structures. Also, the center of strength in structures with flexible diaphragm is more important relative to the stiffness center and has a significant effect on engineering demands at all levels of diaphragm flexibility. Moreover, it was found that a suitable configuration of centers in torsionally stiff structures depends on the degree of diaphragm flexibility, in addition to the intensity of earthquakes (structure yield level) and selected engineering demand parameter.

The use of waste glass in concrete can bring significant economic and environmental benefits due to reduction of landfills and demand for natural aggregates. This paper presents a comprehensive investigation on the feasibility of using high volume of waste glass as fine aggregate in self‐compacting concrete (SCC). A detailed investigation on fresh behavior of mixtures was performed by evaluating filling ability, stability, passing ability, and viscosity of SCC mixtures. Compressive strength and electrical resistivity experiments and scanning electron microscope analysis were also performed to investigate the strength and durability of the concrete mixtures. Furthermore, alkali silica reaction (ASR) potential of different size ranges of the used glass was assessed. The obtained results revealed that excessive bleeding and segregation and deleterious ASR expansion are possible challenges of incorporating fine glass aggregates in SCC. Interestingly, there was no evidence that glass has a considerable impact on the mechanical performance of concrete whereas it increased the electrical resistivity of concrete. Utilizing high volume of waste glass in SCC up to 600 kg/m3 became feasible when a part of portland cement was substituted with zeolite.