نشریه مهندسی عمران فردوسی
سال بیست و نهم شماره 1 (بهار 1396)

In this paper a semi-active structural damage control strategy using MR dampers and Neural Networks is presented. A multilayer feed-forward neural network has been designed. The input layer is relative displacement of stories and the output layer is the voltage needed for MR damper. The neural network is learned to predict the voltage needed for MR damper that can minimize the Park & Ang damage index of structure. Genetic algorithm has been used to learn the neural network. The Park & Ang damage index of the structure has been used as the fittnees function of the genetic algorithm. To evaluate the structural control system a nonlinear 3 story benchmark building has been selected. The results show the the proposed structural control system can effectively reduce the Park & Ang damage index of the structure.

In this study, the mechanical behavior of the sand and shredded tire mixtures is studied by using direct shear box test. The aim of this research is to understand the effect of size effect of shredded tire particles on the mechanical behavior of the mixtures. Three different sizes of shredded tires are used in this study. First, the compressibility of the mixtures under consolidation pressure is studied and then, the mechanical behavior is investigated during the shear load. Under the compression stage, it is seen that the compressibility of shredded tires are much bigger than the sand alone. Also, it is seen that the compressibility is reduced as the size increases. During the shear loading stage, it is found out that the internal friction angle of the mixtures reduces as the percentage of the shredded tire increases. In addition, the friction angle is obtained larger as the size increases. As obvious, the compressibility of the mixtures increases with the increase in the percentage of shredded tire content. This is more effective until 20% content of shredded tire. The size of the shredded tire is not so effective on the compressibility, since the volumetric variation of medium to coarse shredded tire was almost equal. It is noted that in this paper, the variation of the friction angle and volumetric behavior of mixtures were investigated for different levels of specimen deformations.

Removal of petroleum hydrocarbons from synthetic contaminated water using with photocatalytic process was conducted in the presence of nano TiO2 immobilized on the concrete plates. The solar photoreactor was consisted of storage tank of 60 L with floating pump, cascade system with 5 concrete steps, a 5 L weir on the top of the stairs and metalic chassis. The UV-A radiation of the sunlight was used instead of UV-A lamps as the irradiation source. The optimum parameters were pH of 5, TiO2 mass loading of 60 grm-2, UV equivalent irradiation time of 200 min, initial concentration of 100 mgL-1 and H2O2 concentration of 2000 mgL-1.The results demonstrated that under optimal conditions removal efficiency of chemical oxygen demand (COD), total petroleum hydrocarbons (TPH) and poly aromatic hydrocarbons (PAHs) were 70.48%, 67.63 % and 84.75% respectively. Also the results of GC-FID analysis indicated that most of PAHs were eliminated and only non-toxic aliphatic hydrocarbons were remained.

In this article, Umbrella drainage system is presented as a alternative drainage system for the tunnels under steady state-seepage condition. The arrangement of this system is inspired from pin-hole drainage system and forepoling method of support installation. In this study, the performance of this drainage system is investigated through numerical statical analysis for deep circular tunnels subjected to steady-state seepage by using ABAQUS finite element software. In this regard, three monitoring parameters have been investigated: tunnel domain’s maximum effective principle strain, pore water pressure distribution of the tunnel walls and hydraulic gradient around the drainages. By taking into account these parameters, an optimum arrangement for the draining system is presented through exploring all of the factors affecting the drainage tube performance.

It is widely known and well emphasized that the cemented sand is one of economic and environmental topics in soil stabilization. In some instances, a blend of sand, cement and other materials such as fiber, glass, nano particle and zeolite can commercially available and effectively used in soil stabilization in road construction. In this investigation, zeolite and its effect on compaction studied as one of pozelan additive material to cement. Therefore, cilinopiolite kind of zeolite, Neka cement type II and Babolsar sand are used. Compaction poroctor tests were carried out on 24 combination type of cement and zeolite with include different cement percentages 2, 4, 6 and 8 percent of total dry weight of samples and replacement percent’s of 0, 10, 30, 50, 70 and 90 cement with zeolite. Results show that by replacement cement material by zeolite, the maximum dry density increased 2 to 2.5% in comparison with cemented samples and 14% optimum water content approximately concluded. At the end, a function fits Based on Voltra series presented to relate maximum dry density and zeolite-cement-soil parameters.

River confluences are one of the most complex places in river systems, that it is important to predict the maximum scour depth (Ds) at this place using intelligent systems that consider this complexity. Therefore, in this study, the performance of two artificial intelligence models, namely, SVR (considering different validation techniques including train-test, K-Fold and leave-one-out) and GRNN was evaluated. Results showed that, although all models show approximately good accuracy in predicting the Ds; but, SVR with train-test validation method shows more accuracy (with R2, MAE, MARE, RMSE and NSE of 95.66, 0.0124, 4.26, 0.0168 and 0.993, respectively), and after that SVR K-Fold (at K=9), SVR leave-one-out; and GRNN are the accurate models in this study, respectively.

Due to existence of the facility ducts, such as elevators, heating, and cooling systems in buildings, creating of the openings in the reinforced concrete slabs is inevitable. Usually, small openings have negligible effects on the slab performance whereas the large openings can affect significantly on the slab behavior and can cause the stress concentration adjacent to the openings. In some cases, ignoring this issue can cause serious problems in the integrity, stiffness and even stability of structures. One of the rehabilitation and strengthening methods of such slabs is the use of Fiber Reinforce Polymers sheets (FRPs). In this research, the influence of the lateral and corner openings as well as the impact of using a kind of FRPs known as CFRP (Carbon Fiber Reinforce Polymer sheets) for strengthening of two-way slabs were investigated. The obtained results indicate that this method can be successfully employed in remedy operations for mentioned slabs. CFRP sheets can recover the lost flexural rigidity of the slab considerably and even in some cases can improve it in comparison to that of homogeneous slab (slab with no opening). The results also show that by implementing this method the flexural rigidity of the slab can be increased between 12 to 30 percent in the case of slabs with lateral opening and between 1 to 10 percent in the case of slabs with the corner opening relative to the original weakened slab (slab with opening without strengthening).

The failure probability of structures are rather small and therefore calculation of structural reliability generally has a high computational cost. In order to reduce computational costs, this articles proposes a hybrid approach based on combination of the least squares support vector regression and two advanced Monte Carlo importance sampling and Latin hypercube sampling. Two frames and one truss example are used to evaluate the performance of the proposed algorithm. Results demonstrate that proposed method provides an accurate estimation of failure probability and that the computational costs are lower than those of other methods