Electrical and mechanical properties of BZT − xBCT lead-free piezoceramics

In this study, lead-free (1 − x)Ba(Zr_0.2Ti_0.8)O₃ − x(Ba_0.7Ca_0.3)TiO₃ compositions are synthesized via conventional solid oxide route, and the ceramics are fabricated with normal sintering in air. The effects of composition fluctuations on dielectric, piezoelectric, and mechanical properties are investigated. The phase structure and the microstructure are analyzed with X-ray diffraction and scanning electron microscopy. The best dielectric and piezoelectric properties of ε_r = 11 207 and d₃₃ = 330 pC/N were obtained for BZT−0.35BCT and BZT−0.5BCT ceramics, respectively. The mechanical behavior—in terms of Vickers hardness and compressive and flexural strengths—was investigated, and the best mechanical behavior was found in the vicinity of the phase transition boundary with x values between 0.5 and 0.6.     

Topology optimization of trusses using genetic algorithm,force method and graph theory

In this article size/topology optimization of trusses is performed using a genetic algorithm (GA), the force method and some concepts of graph theory. One of the main difficulties with optimization with a GA is that the parameters involved are not completely known and the number of operations needed is often quite high. Application of some concepts of the force method, together with theory of graphs, make the generation of a suitable initial population well‐matched with critical paths for the transformation of internal forces feasible. In the process of optimization generated topologically unstable trusses are identified without any matrix manipulation and highly penalized. Identifying a suitable range for the cross‐section of each member for the ground structure in the list of profiles, the length of the substrings representing the cross‐sectional design variables are reduced. Using a contraction algorithm, the length of the strings is further reduced and a GA is performed in a smaller domain of design space. The above process is accompanied by efficient methods for selection, and by using a suitable penalty function in order to reduce the number of numerical operations and to increase the speed of the optimization toward a global optimum. The efficiency of the present method is illustrated using some examples, and compared to those of previous studies. Copyright © 2003 John Wiley & Sons, Ltd.     

NEXUS — Resilient Intelligent Middleware

Service-oriented computing is the latest software paradigm brought about by the computing revolution. The different viewpoint and granularity of software components used in technologies based on the service-oriented architecture paradigm, compared to traditional object-oriented methodologies makes them better suited to many of the efforts that are being made in the pervasive and ubiquitous computing world. In the NEXUS project we are seeking ways of fusing the SOA and pervasive computing paradigms in order to build intelligent, robust and resilient networks connecting dynamic islands of service resources.     

Wavefront reduction using graphs,neural networks and genetic algorithm

This paper presents an algorithm for nodal numbering in order to obtain a small wavefront. Element clique graphs are employed as the mathematical models of finite element meshes. A priority function containing five vectors is used, which can be viewed as a generalization of Sloan's function. These vectors represent different connectivity properties of the graph models. Unlike Sloan's algorithm, which uses two fixed coefficients, here, five coefficients are employed, based on an evaluation by artificial neural networks. The networks weights are obtained using a simple genetic algorithm. Examples are included to illustrate the performance of the present hybrid method. Copyright © 2004 John Wiley & Sons, Ltd.     

Eigensolution of specially structured matrices with hyper‐symmetry

Recently, four canonical forms have been developed and applied to the dynamics and stability analysis of symmetric frames. In this paper, hyper‐symmetric matrices and specially structured matrices are defined and efficient methods are proposed for the eigensolution of such matrices. Applications are extended to hyper‐graphs and specially structured graphs. Simple methods are developed for calculating the eigenvalues of the Laplacian matrices of such graphs. The developments presented in this paper can also be considered as generalization of Form II and Form III symmetry, previously defined by the authors. Copyright © 2006 John Wiley & Sons, Ltd.     

A set theoretical shuffled shepherd optimization algorithm for optimal design of cantilever retaining wall structures

Engineering with Computers - In this paper, a recently developed meta-heuristic algorithm, shuffled shepherd optimization algorithm (SSOA), is employed for optimal design of reinforced concrete...     

A combinatorial study of the rigidity of planar structures

Summary A combinatorial method is presented for examining the rigidity of planar structures. In this approach, an expansion process is used for the formation of a statically determinate substructure, known as a -tree of a structure. The algorithm of Lováz and Yemini, and the method of Sugihara are employed for the recognition of the elementary subgraphs, during this process.With 4 Figures     

A new intelligent algorithm for dynamic facility layout problem in state of fuzzy constraints

In the present paper, the dynamic facilities layout problem is studied in presence of ambiguity of information flow. Product demand (and consequently material flow) is defined as fuzzy numbers with different membership functions. The problem is modeled in fuzzy programming. Three models of expected value, chance-constrained programming and dependent-chance programming and two hybrid intelligent algorithms are then presented. At the end, efficiency of algorithms for solving fuzzy models of dynamic facilities layout is shown through some numerical examples.     

A comparative study of two approaches for supporting optimal network location queries

Given a set S of sites and a set O of weighted objects, an optimal location query finds the location(s) where introducing a new site maximizes the total weight of the objects that are closer to the new site than to any other site. With such a query, for instance, a franchise corporation (e.g., McDonald’s) can find a location to open a new store such that the number of potential store customers (i.e., people living close to the store) is maximized. Optimal location queries are computationally complex to compute and require efficient solutions that scale with large datasets. Previously, two specific approaches have been proposed for efficient computation of optimal location queries. However, they both assume p-norm distance (namely, L₁ and L₂/Euclidean); hence, they are not applicable where sites and objects are located on spatial networks. In this article, we focus on optimal network location (ONL) queries, i.e., optimal location queries in which objects and sites reside on a spatial network. We introduce two complementary approaches, namely EONL (short for Expansion-based ONL) and BONL (short for Bound-based ONL), which enable efficient computation of ONL queries with datasets of uniform and skewed distributions, respectively. Moreover, with an extensive experimental study we verify and compare the efficiency of our proposed approaches with real world datasets, and we demonstrate the importance of considering network distance (rather than p-norm distance) with ONL queries.