Ferdowsi Civil Engineering
Year:2017 | Volume:28 | Issue:2 (16)|Papers Count:9

Water contaminated with petroleum hydrocarbons has harmful effects on health, economy and environment. In this study, photolysis process for treating petroleum hydrocarbons was investigated. Hence different initial CODs with different UV-C radiation power were examined. Based on the energy consumption per unit of COD removed, COD of 350 mg/L and radiation power of 80 W were chosen as the optimum conditions. To improve model prediction, in addition to the aforementioned CODs, COD=1000 mg/L in 60 W was also tested. The findings indicated that photolysis can be considered as a suitable pretreatment process for the biological systems.

The energy available in the terminal of dam structures causes erosion of the river bed. Different parameters such as discharge, difference between upstream and downstream, radius of jet, mean diameter of bed materials, velocity of the jet and the tail water are recognized on the score hole and its geometry. The cognizance of these parameters aids the designers to provide a suitable layout for the scoring pool...

This paper presents a method for identification of linear system physical parameters (structural mass, damping and stiffness matrices) using the inverse solution of equation of motion in the frequency domain, by focus on the reducing the ill conditioning effect. The method utilizes the measured responses from the forced vibration test of structure in order to identify the system properties and detect the probable damages. Inputs and outputs data is gathered in an augmented matrix [A|b], that large number of this data is caused to ill condition problem. Moreover, as an inevitable problem, there is a noise in the measurement and makes discrepancy in result of identification. Ill conditioning causes instability in the result of identification, the instability and noisy result reduce validity of the results and accordingly will be valueless statistic methods in the system identification (SI). This paper is presented an algorithm to improve the ill conditioning problem that is a special upper triagularization matrix method. The proposed algorithm can identify parallel and pseudo parallel vectors in coefficient matrix of linear equations. By removing these linearly dependent vectors and thus reducing singularity of the matrix, stabilization is resulted which is a key objective in numerical linear algebra. In order to optimal estimation of identification results, least-squares and penalty function methods is used. The validity and efficiency of the reduce singularity of matrix method is tested on a eight non shear story frame structure by using direct model updating method. Aforementioned structures have a non-proportional damped matrix and subjected to sweep harmonic forces. The results show that the proposed algorithm improves the stability of the estimation and the answer is quite useful.

In this paper, an analytical model is introduced to show the cyclic behavior of the structures, considering degradation phenomena including pinching, stiffness degradation, strength deterioration and sliding effects. This model is based on well-known Mostaghel’s model though some essential modifications as well as sliding effect are also taken into account. This model is developed based on a simple single degree of freedom and multi-degree of freedom multi-linear mechanical systems and developing of partial differential equations. The proposed model includes basic characteristics of the hysteresis cycles that can be easily measured through the experimental tests. It is notable that usually the experiments conducted on the structural members are displacement-control based. Hence, in order to properly implement the analytical model with the experimental results, the proposed model has been developed according to displacement-control. The cyclic loading regime applied to this model is based on standard ASTM E2126-07 method B. In order to demonstrate the degrading phenomena of the hysteresis behavior of the structures, several examples of a structural system are presented to show that the proposed analytical model can provide realistic descriptions of the structural hysteretic performances.

Very large floating structures (VLFSs) have attracted the attention of many researchers and engineers working in the offshore and marine industry. They have proposed VLFSs for various applications such as floating airports, bridges, breakwaters, piers and docks, fuel storage facilities, emergency bases, entertainment facilities, recreation parks, mobile offshore military bases, and even for habitation. There are various approaches to decrease differential deflection in VLFS...

Performance measure approach (PMA) is a method for evaluating the probabilistic constraints in reliability-based design optimization of structures. The advanced mean-value (AMV) method is suitable for PMA, simply and efficiently. The iterative AMV scheme could be yielded to unstable solutions such as periodic-oscillation and chaos for highly nonlinear performance functions. In the present paper, an improved stability transformation method (ISTM) is proposed for appropriate convergence of nonlinear performance functions. This iterative approach has been established based on a suitable stepsize between one and zero that is simply calculated on the basis of the new results of AMV scheme and the previous results of the improved stability transformation iterative formula. The descent condition was applied in the iterative sequences of the ISTM to achieve stable convergence. The results of several nonlinear performance functions in reliability-based design optimization demonstrate that the ISTM is laded to control instability solutions of PMA and also, it is more robust than AMV and more efficient that stability transformation method in structural problems with nonlinear performance functions.

In this research, prediction methods of artificial neural network and local prediction method (LPM) based on the chaos theory are employed to predict daily, weekly and monthly runoff. For achieving this purpose, runoff series data observed at Pole-Kohneh located in the Qareh-Soo River were utilized. The nonlinear predictions of LPM are found to be in close agreement with the observed runoff, with high correlation coefficient for daily and weekly time scales. Predicted results of monthly time scale are not satisfying which indicating the signs of existing chaos behavior in daily and weekly scales. The predicted results of ANN are inferior to LPM for daily and weekly scales but superior to LPM for monthly scale.

The support vector machine (SVM) is a relatively new machine learning method which is increasingly being applied to engineering problems and have yielded encouraging results. Because of complex behavior of elastoplastic of web panels of plate girders under patch loading, almost none of the proposed methods provides consistent and accurate predictions of patch load capacity. Consequently, alternative solutions are required to overcome these limitations. In this paper SVM models are developed for predicting the ultimate resistance of plate girders subjected to patch loading. The training and testing patterns of the proposed SVM models are based on well established experimental results taken from literature. Finally a comparison is made between predictions obtained from the SVM models and a traditional method for determining patch loading resistance. The comparison confirms that the SVM models developed in this paper, outperform the traditional method.

This paper deals with the interfacial effects of silica fume (sf) and styrene-butadiene polymer (SBR) on compressive strength of concrete. Analyzing the compressive strength results of 32 concrete mixes performed over two water-binder ratios (0.35, 0.45), four percentages replacement of silica fume (0%, 5%, 7.5%, 10%) and four percentages of SBR (0%, 5%, 10%, 15%) were investigated. A mathematical model base on Abrams’ law has been proposed for evaluation strength of silica fume-SBR concretes. This simplified model might serve as useful guides for commixture concrete admixtures containing of silica fume and SBR. The accuracy of the proposed model is investigated.