This article presents a time varying wavelet‐based pole assignment (WPA) method to control seismic vibrations in multi‐degree of freedom (MDOF) structural systems. The discrete wavelet transform is used to determine the energy content over the frequency band of the response in real time. The frequency content was implemented in the Big Bang–Big Crunch algorithm to update the optimum values of the closed‐loop poles of the structural system adaptively. To calculate optimum gain matrix, a robust pole placement algorithm was used. The gain matrix is calculated online based on response characteristic in real time and must not be calculated a priori (offline) choice. The WPA is tested on a 10‐story structural system subject to several historical ground motions. It is observed that the WPA has advantages in some design problems. Numerical examples illustrate that the proposed approach reduces the displacement response of the structure in real time more than conventional linear quadratic regulator (LQR) controller.

An adjustable cuckoo-search wavelet-based fuzzy logic controller (ACSWBFLC) is introduced to mitigate structural responses during seismic motion by using magnetorheological (MR) dampers. The ACSWBFLC incorporates four algorithms: discrete wavelet transform (DWT), fuzzy logic controller (FLC), modified Bouc-Wen model and geometrical nonlinearity algorithm. DWT is applied to acquire the local energy distribution of seismic excitation over the frequency bands. These online data are transmitted to FLC to operate MR damper intelligently based on online excitation frequency. Furthermore, modified Bouc-Wen phenomenological algorithm was utilized to generate the nonlinear behavior of the MR dampers. A wavelet low-pass filter is employed to prevent the stabilization of coefficients and minimize the computational burden. Moreover, geometrical nonlinearities were considered to design a more robust controller. Furthermore, a novel evolutionary algorithm of cuckoo search was used to optimize the placement and the number of MR dampers and sensors in the sense of minimum resultant vibration magnitude. Numerical efforts were considered to validate the efficiency of the proposed FLC. From a designer's point of view, the proposed ACSWBFLC controller can determine the optimal solutions during a reasonable number of iterations. Finally, numerical examples are utilized to demonstrate the efficiency of ACSWBFLC under several far-and near-fault seismic excitations. The results indicate that ACSWBFLC attenuates the excessive responses of the structural building in real time more efficiently than traditional FLC controllers by using appropriate control force.

Cement is a common and widespread building material over the world. Similarly, carbon dioxide emissions have been significantly increased due to cement production. Alternative low-carbon binders rather than cement have been progressively sought in recent years. Fly ash was found as an available option, since it is being largely disposed annually as a waste material. In this research several studies have been reviewed and recent applications of fly ash on concrete specification, including strength and fracture toughness of green concrete have been perused. Furthermore, transport properties of high volume fly ash after exposure to high temperature and influence of curing temperature on strength development of fly ash-recycled concrete aggregate blends have been investigated. The investigated test results showed that the properties of composites incorporating fly ash depend on the age of the concrete. Test results also revealed that transport properties of concrete increased notably after exposure to 400cº and the results achieved on fly ash-recycled concrete aggregate led to the conclusion that 15% FA is the optimum blend for road stabilization applications.

The aim of this study is to propose two numerical models by a well-known soft computing method, Genetic Programming (GP), for the estimation of soils compaction parameters. Genetic Programming is a pattern recognition approach that has the ability of modeling the non-linear behavior of complex engineering problems. The input variables were the soil classification properties, and the outputs were the Optimum Moisture Content (OMC) and Maximum Dry Density (MDD). To provide model, a database including properties of different soils classified as CH, CI, CL, GC, GM, MH, MI, ML and SC was used. In addition, a new Multiple Linear Regression (MLR) based formula using the database, compared with the GP based model. Study results revealed that the proposed formula by GP can predict the compaction parameters of soils in a highly precise manner, and its outputs were in satisfactory conformity with real test results. Performances of the proposed models evaluated using the regression statistical analyses. The proposed formulae can be useful for the preliminary design of engineering projects and are more useful for cases with time and financial limitations.

GhAnooni-BAGhA M, ShAyAnfAr MA, rezA-zAdeh o, zABihi-SAMAni M. The effect of materials on the reliability of reinforced concrete beams in normal and intense corrosions. eksploatacja i niezawodnosc -Maintenance and reliability 2017; 19 (3): 393-402, http://dx.doi.

Control devices can be used to dissipate the energy and attenuate undesirable vibration on engineering structures. Recently, to mitigate the response of structures during the earthquakes and high intensity winds, semi active control has been widely used. MR dampers are semi active control devices that are managed by sending external voltage supply. A new adaptive fuzzy logic controller (FLC) is introduced to manage MR damper intelligently. Furthermore, a novel evolutionary algorithm of particle swarm optimization (PSO) was used to optimize the placement and the number of MR dampers and sensors in the sense of minimum resultant vibration magnitude. Numerical efforts were considered to validate the efficiency of proposed FLC. In designer's point of view, the proposed PSO-FLC controller can find the optimal solutions during a reasonable number of iterations. Finally, results demonstrate that proposed PSO-FLC controller could find the appropriate control force and attenuates the excessive responses in several buildings.

Progressive collapse in a building has caused local and subsequent damage throughout the system to spread and large-scale causes the collapse of the entire building. Progressive collapse is usually due to fire, gas explosion, terrorist attack, vehicle collisions, misplaced design and construction. Therefore, it is necessary to study the iMPact of this phenomenon and rebuild the building against it. Based on this, in this research, we will examine and evaluate practical solutions for reinforcing reinforced concrete frames against progressive collapse. The proposed solutions in this study were the use of reinforcing bars at the top and bottom of the beam, the effect of the layout of the cross section reinforcement for the participation in the chain performance, the use of Carbon Fiber Reinforced Polymer (CFRP) sheet at the bottom and three sides of the beam and the effect of the additional layer of CFRP sheet in the section performance of the beam against progressive collapse. In this study, a 2-story frame is modeled using OpenSees software and retrofitted with the above techniques, and the effectiveness of each of these techniques is evaluated in the final performance. The results show that the best approach to reinforcing the beam is by rebar and CFRP, which has resulted in improved chain performance and the greatest reduction of vertical displacement in the beam.

Active control is one of the modern approaches in seismic design of steel structures. Recently, induced by economic considerations, especially high expenses of control systems, optimality has become an important issue. In this paper an active system is used to control a steel structure's displacements by a simplified pole assignment method. To optimize the number, the locations, and the total driving force of the required actuators, an improved particle swarm algorithm is presented focusing on the parameters of the velocity equation. A Geographical neighborhood topology and an adaptive inertia weight are used to improve the standard PSO algorithm. In addition to the local and global best solutions, the positions of the best particles in the geographical neighborhood are mathematically represented in an additional term. The performance of the proposed algorithm is compared with the traditional Genetic Algorithm (GA) and the standard particle swarm considering the optimal control of a 12-story steel structure as a numerical example. High capabilities of the proposed method in terms of the control target, convergence rate, and accuracy are simultaneously clarified by the results.