Considering dynamic parameters of damaged structure in MPA and YPS nonlinear static procedures for asymmetric buildings

The yield point spectra and modal pushover procedures have already been used in seismic design of new buildings and vulnerability evaluation of existing structures. This paper initially identifies the similarities and differences of the two procedures. Then, the modal characteristics of damaged structure are used to modify their methodologies. The applications of the procedures in estimating displacement, interstory drift index and plastic hinge rotation responses of asymmetric buildings are investigated for three 5‐story reinforced concrete moment‐resisting frame‐building models. The results show considerable improvement in estimating the responses of those asymmetric buildings. Copyright © 2013 John Wiley & Sons, Ltd.     

PREDICTION OF PRESSURE DROP IN PNEUMATIC TRANSPORT SYSTEMS AT VARIOUS PIPE ORIENTATIONS USING AN EMPIRICAL CORRELATION FOR THE PARTICLE VELOCITY

A new empirical correlation for the particle velocity which incorporates the angle of inclination is proposed here. This correlation coupled with the expression for the solids friction factor obtained from the force balance on the particle was used to predict the pressure drops in the 0.0266 m and 0.0504 m systems held at various angles of inclination. Particles used in these systems included glass particles of 67, 450, and 900 µm weight mean diameter. The existence of minimum points in the predicted pressure drop curves as a function of gas velocity was corroborated by these two expressions.     

Electromechanical modeling and analytical investigation of nonlinearities in energy harvesting piezoelectric beams

Piezoelectric materials are extensively applied for vibrational energy harvesting especially in micro-scale devices where other energy conversion mechanisms such as electromagnetic and electrostatic methods encounter fabrication limitations. A cantilevered piezoelectric bimorph beam with an attached proof (tip) mass for the sake of resonance frequency reduction is the most common structure in vibrational harvesters. According to the amplitude and frequency of applied excitations and physical parameters of the harvester, the system may be pushed into a nonlinear regime which arises from material or geometric nonlinearities. In this study nonlinear dynamics of a piezoelectric bimorph harvester implementing constitutive relations of nonlinear piezoelectricity together with nonlinear curvature and shortening effect relations, is investigated. To achieve this goal first of all a comprehensive fully-coupled electromechanical nonlinear model is presented through a variational approach. The governing nonlinear partial differential equations of the proposed model are order reduced and solved by means of the perturbation method of multiple scales. Results are presented for a PZT/Silicon/PZT laminated beam as a case study. Findings indicate that material nonlinearities of the PZT layer has the dominant effect leading to softening behavior of the frequency response. At the primary resonance, different frequency responses of the extracted power can be distinguished according to the excitation amplitude, which is due to harmonic generation as a result of piezoelectric nonlinearity. The extracted power is analytically computed and validated with a good agreement by a numerical solution.     

Design and analysis of a low-noise saw-less receiver front-end resistant to strong out-of-band blocker

Regulatory changes to spectrum management frameworks in the U.S. and worldwide are promoting the use of dynamic spectrum access (DSA) and spectrum sharing mechanisms. Wireless service environments that use these mechanisms will rely heavily on radio interference control and management techniques to coordinate the boundaries of spectrum use for devices owned/managed by different entities. To communicate the characteristics and limits of spectrum use of an RF transmitter, receiver, system or collection of systems, a common data structure to represent this information must be in place. Spectrum consumption models (SCMs) attempt to capture this information and support a set of computations that allow for the determination of the compatibility of the use of spectrum between devices and/or systems that communicate the characteristics of their use of spectrum with these models. SCMs are currently being standardized within the IEEE DySPAN-SC 1900.5.2 workgroup. This paper presents our results and ongoing efforts in developing an open source tool for the construction and analysis of SCMs as a means to promote their use and showcase their potential for enhancing spectrum sharing and DSA interactions.     

Experimental and theoretical investigation of sound transmission loss for polycarbonate,poly(methyl methacrylate), and glass

In this study, the effects of the soundproofing properties of polycarbonate (PC), poly(methyl methacrylate) (PMMA), and glass were investigated. We fabricated the specimens into 3 mm thick sheets by direct hot compression molding as a monolithic sample and also by gluing three thin sheets together into a multilayer. Sound transmission loss (STL) was measured by an impedance tube over the frequency range 63–1600 Hz. The results indicate that because of the close density, the STLs for PC and PMMA were almost the same above 1200 Hz. Also, PMMA had a greater STL than PC in the range 63–300 Hz. In a comparison of the monolithic and multilayered samples, we demonstrated that the epoxy‐based adhesive interlayers had more efficient bonding than the silicone‐based ones. The multilayered polymer/silicone specimens showed a sharp drop in the STL values compared to the monolithic samples. However, the multilayered polymer/epoxy specimens revealed similar behavior to the monolithic polymers. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 42988.     

A learning‐based approach for virtual machine placement in cloud data centers

In recent years, the increasing use of cloud services has led to the growth and importance of developing cloud data centers. One of the challenging issues in the cloud environments is high energy consumption in data centers, which has been ignored in the corporate competition for developing cloud data centers. The most important problems of using large cloud data centers are high energy costs and greenhouse gas emission. So, researchers are now struggling to find an effective approach to decreasing energy consumption in cloud data centers. One of the preferred techniques for reducing energy consumption is the virtual machines (VMs) placement. In this paper, we present a VM allocation algorithm to reduce energy consumption and Service Level Agreement Violation (SLAV). The proposed algorithm is based on best‐fit decreasing algorithm, which uses learning automata theory, correlation coefficient, and ensemble prediction algorithm to make better decisions in VM allocation. The experimental results indicated improvement regarding energy consumption and SLAV, compared with well‐familiar baseline VM allocation algorithms.     

An ant colony optimization based routing algorithm for extending network lifetime in wireless sensor networks

Reducing the energy consumption of network nodes is one of the most important problems for routing in wireless sensor networks because of the battery limitation in each sensor. This paper presents a new ant colony optimization based routing algorithm that uses special parameters in its competency function for reducing energy consumption of network nodes. In this new proposed algorithm called life time aware routing algorithm for wireless sensor networks (LTAWSN), a new pheromone update operator was designed to integrate energy consumption and hops into routing choice. Finally, with the results of the multiple simulations we were able to show that LTAWSN, in comparison with the previous ant colony based routing algorithm, energy aware ant colony routing algorithms for the routing of wireless sensor networks, ant colony optimization-based location-aware routing algorithm for wireless sensor networks and traditional ant colony algorithm, increase the efficiency of the system, obtains more balanced transmission among the nodes and reduce the energy consumption of the routing and extends the network lifetime.     

A New Automated Design Method Based on Machine Learning for CMOS Analog Circuits

A new simulation based automated CMOS analog circuit design method which applies a multi-objective non-Darwinian-type evolutionary algorithm based on Learnable Evolution Model (LEM) is proposed in this article. The multi-objective property of this automated design of CMOS analog circuits is governed by a modified Strength Pareto Evolutionary Algorithm (SPEA) incorporated in the LEM algorithm presented here. LEM includes a machine learning method such as the decision trees that makes a distinction between high- and low-fitness areas in the design space. The learning process can detect the right directions of the evolution and lead to high steps in the evolution of the individuals. The learning phase shortens the evolution process and makes remarkable reduction in the number of individual evaluations. The expert designer’s knowledge on circuit is applied in the design process in order to reduce the design space as well as the design time. The circuit evaluation is made by HSPICE simulator. In order to improve the design accuracy, bsim3v3 CMOS transistor model is adopted in this proposed design method. This proposed design method is tested on three different operational amplifier circuits. The performance of this proposed design method is verified by comparing it with the evolutionary strategy algorithm and other similar methods.