A hybrid Particle Swarm Optimization - Simplex algorithm (PSOS) for structural damage identification

This study proposes a new PSOS-model based damage identification procedure using frequency domain data. The formulation of the objective function for the minimization problem is based on the Frequency Response Functions (FRFs) of the system. A novel strategy for the control of the Particle Swarm Optimization (PSO) parameters based on the Nelder-Mead algorithm (Simplex method) is presented; consequently, the convergence of the PSOS becomes independent of the heuristic constants and its stability and confidence are enhanced. The formulated hybrid method performs better in different benchmark functions than the Simulated Annealing (SA) and the basic PSO (PSO(b)). Two damage identification problems, taking into consideration the effects of noisy and incomplete data, were studied: first, a 10-bar truss and second, a cracked free-free beam, both modeled with finite elements. In these cases, the damage location and extent were successfully determined. Finally, a non-linear oscillator (Duffing oscillator) was identified by PSOS providing good results. (C) 2009 Elsevier Ltd. All rights reserved

Reducing Urban Transport Energy Dependence: A New Urban Development Framework and GIS-Based Tool

High urban transport energy consumption is directly influenced by transport energy dependence. Dramatic reductions in urban transport energy dependence or consumption are not yet being widely observed despite the variety of urban planning tools currently available. A new urban development framework is presented to tackle this issue that makes use of a recently developed and successfully trialed GIS-based tool, the Transport Energy Specification (TES). The TES was simulated on a neighborhood in Sao Carlos, Brazil. In the simulation, energy dependence was reduced by a factor of 8 through activity location or infrastructure modifications to the built environment.

Development of new rapid prototyping process

Purpose - The purpose of this paper is to identify the key elements of a new rapid prototyping process, which involves layer-by-layer deposition of liquid-state material and at the same time using an ultraviolet line source to cure the deposited material. This paper reports studies about the behaviour of filaments, deposition accuracy, filaments interaction and functional feasibility of system. Additionally, the author describes the process which has been proposed, the equipment that has been used for these studies and the material which was developed in this application. Design/methodology/approach - The research has been separated into three study areas in accordance with their goals. In the first, both the behaviour of filament and deposition accuracy was studied. The design of the experiment is described with focus on four response factors (bead width, filament quality, deposition accuracy and deposition continuity) along with function of three control factors (deposition height, deposition velocity and extrusion velocity). The author also studied the interaction between filaments as a function of bead centre distance. In addition, two test samples were prepared to serve as a proof of the methodology and to verify the functional feasibility of the process which has been studied. Findings - The results show that the proposed process is functionally feasible, and that it is possible to identify the main effects of control factors over response factors. That analysis is used to predict the condition of process as a function of the parameters which control the process. Also identified were distances of centre beads which result in a specific behaviour. The types of interaction between filaments were analysed and sorted into: union, separation and indeterminate. At the end, the functional feasibility of process was proved whereby two test parts could be built. Originality/value - This paper proposes a new rapid prototyping process and also presents test studies related to this proposition. The author has focused on the filament behaviour, deposition accuracy, interaction between filaments and studied the functional feasibility of process to provide new information about this process, which at the same time is useful to the development of other rapid prototyping processes.

Molecular characterization of a miraculin-like gene differentially expressed during coffee development and coffee leaf miner infestation

The characterization of a coffee gene encoding a protein similar to miraculin-like proteins, which are members of the plant Kunitz serine trypsin inhibitor (STI) family of proteinase inhibitors (PIs), is described. PIs are important proteins in plant defence against insects and in the regulation of proteolysis during plant development. This gene has high identity with the Richadella dulcifica taste-modifying protein miraculin and with the tomato protein LeMir; and was named as CoMir (Coffea miraculin). Structural protein modelling indicated that CoMir had structural similarities with the Kunitz STI proteins, but suggested specific folding structures. CoMir was up-regulated after coffee leaf miner (Leucoptera coffella) oviposition in resistant plants of a progeny derived from crosses between C. racemosa (resistant) and C. arabica (susceptible). Interestingly, this gene was down-regulated during coffee leaf miner herbivory in susceptible plants. CoMir expression was up-regulated after abscisic acid application and wounding stress and was prominent during the early stages of flower and fruit development. In situ hybridization revealed that CoMir transcripts accumulated in the anther tissues that display programmed cell death (tapetum, endothecium and stomium) and in the metaxylem vessels of the petals, stigma and leaves. In addition, the recombinant protein CoMir shows inhibitory activity against trypsin. According to the present results CoMir may act in proteolytic regulation during coffee development and in the defence against L. coffeella. The similarity of CoMir with other Kunitz STI proteins and the role of CoMir in plant development and plant stress are discussed.

Exploring the potential of functionally graded materials concept for the development of fiber cement

In this study we establish the concept of functionally graded fiber cement. We discuss the use of statistical mixture designs to choose formulations and present ideas for the production of functionally graded fiber cement components for Hatschek machines. The feasibility of producing functionally graded fiber cement by grading PVA fiber content has been experimentally evaluated. Thermogravimetric analysis (TG) was employed to assess fiber distribution profiles and four-point bending tests were applied to evaluate the mechanical performance of both conventional and graded composites. The results show that grading PVA fiber content is an effective way to produce functionally graded fiber cement, which allows for a reduction of the total fiber volume without a significant reduction on modulus of rupture of composite. TG tests were found adequate to assess the fiber content at different points in functionally graded fiber cements. (C) 2009 Elsevier Ltd. All rights reserved.

Modeling of Distributed Control Systems in Intelligent Building based on Colored Petri Nets

Distributed control systems consist of sensors, actuators and controllers, interconnected by communication networks and are characterized by a high number of concurrent process. This work presents a proposal for a procedure to model and analyze communication networks for distributed control systems in intelligent building. The approach considered for this purpose is based on the characterization of the control system as a discrete event system and application of coloured Petri net as a formal method for specification, analysis and verification of control solutions. With this approach, we develop the models that compose the communication networks for the control systems of intelligent building, which are considered the relationships between the various buildings systems. This procedure provides a structured development of models, facilitating the process of specifying the control algorithm. An application example is presented in order to illustrate the main features of this approach.

Adaptive Approach for a Maximum Entropy Algorithm in Ecological Niche Modeling

This paper presents an Adaptive Maximum Entropy (AME) approach for modeling biological species. The Maximum Entropy algorithm (MaxEnt) is one of the most used methods in modeling biological species geographical distribution. The approach presented here is an alternative to the classical algorithm. Instead of using the same set features in the training, the AME approach tries to insert or to remove a single feature at each iteration. The aim is to reach the convergence faster without affect the performance of the generated models. The preliminary experiments were well performed. They showed an increasing on performance both in accuracy and in execution time. Comparisons with other algorithms are beyond the scope of this paper. Some important researches are proposed as future works.

Evaluation of Adaptive Genetic Algorithm to Environmental Modeling of Peponapis and Cucurbita

This paper presents a free software tool that supports the next-generation Mobile Communications, through the automatic generation of models of components and electronic devices based on neural networks. This tool enables the creation, training, validation and simulation of the model directly from measurements made on devices of interest, using an interface totally oriented to non-experts in neural models. The resulting model can be exported automatically to a traditional circuit simulator to test different scenarios.

Harmonic Distortion State Estimation Using an Evolutionary Strategy

This paper presents a new methodology to estimate harmonic distortions in a power system, based on measurements of a limited number of given sites. The algorithm utilizes evolutionary strategies (ES), a development branch of evolutionary algorithms. The main advantage in using such a technique relies upon its modeling facilities as well as its potential to solve fairly complex problems. The problem-solving algorithm herein proposed makes use of data from various power-quality (PQ) meters, which can either be synchronized by high technology global positioning system devices or by using information from a fundamental frequency load flow. This second approach makes the overall PQ monitoring system much less costly. The algorithm is applied to an IEEE test network, for which sensitivity analysis is performed to determine how the parameters of the ES can be selected so that the algorithm performs in an effective way. Case studies show fairly promising results and the robustness of the proposed method.

A 2-D Delaunay refinement algorithm using an initial prerefinement from the boundary mesh

An improvement to the quality bidimensional Delaunay mesh generation algorithm, which combines the mesh refinement algorithms strategy of Ruppert and Shewchuk is proposed in this research. The developed technique uses diametral lenses criterion, introduced by L. P. Chew, with the purpose of eliminating the extremely obtuse triangles in the boundary mesh. This method splits the boundary segment and obtains an initial prerefinement, and thus reducing the number of necessary iterations to generate a high quality sequential triangulation. Moreover, it decreases the intensity of the communication and synchronization between subdomains in parallel mesh refinement.

Transmission lines distance protection using artificial neural networks

This work presents the development and implementation of an artificial neural network based algorithm for transmission lines distance protection. This algorithm was developed to be used in any transmission line regardless of its configuration or voltage level. The described ANN-based algorithm does not need any topology adaptation or ANN parameters adjustment when applied to different electrical systems. This feature makes this solution unique since all ANN-based solutions presented until now were developed for particular transmission lines, which means that those solutions cannot be implemented in commercial relays. (c) 2011 Elsevier Ltd. All rights reserved.

An exact conserving algorithm for nonlinear dynamics with rotational DOFs and general hyperelasticity. Part 2: shells

Following the approach developed for rods in Part 1 of this paper (Pimenta et al. in Comput. Mech. 42:715-732, 2008), this work presents a fully conserving algorithm for the integration of the equations of motion in nonlinear shell dynamics. We begin with a re-parameterization of the rotation field in terms of the so-called Rodrigues rotation vector, allowing for an extremely simple update of the rotational variables within the scheme. The weak form is constructed via non-orthogonal projection, the time-collocation of which ensures exact conservation of momentum and total energy in the absence of external forces. Appealing is the fact that general hyperelastic materials (and not only materials with quadratic potentials) are permitted in a totally consistent way. Spatial discretization is performed using the finite element method and the robust performance of the scheme is demonstrated by means of numerical examples.

An exact conserving algorithm for nonlinear dynamics with rotational DOFs and general hyperelasticity. Part 1: Rods

A fully conserving algorithm is developed in this paper for the integration of the equations of motion in nonlinear rod dynamics. The starting point is a re-parameterization of the rotation field in terms of the so-called Rodrigues rotation vector, which results in an extremely simple update of the rotational variables. The weak form is constructed with a non-orthogonal projection corresponding to the application of the virtual power theorem. Together with an appropriate time-collocation, it ensures exact conservation of momentum and total energy in the absence of external forces. Appealing is the fact that nonlinear hyperelastic materials (and not only materials with quadratic potentials) are permitted without any prejudice on the conservation properties. Spatial discretization is performed via the finite element method and the performance of the scheme is assessed by means of several numerical simulations.

Planning and operation of large-scale water distribution systems with preemptive priorities

This paper describes the development of an optimization model for the management and operation of a large-scale, multireservoir water supply distribution system with preemptive priorities. The model considers multiobjectives and hedging rules. During periods of drought, when water supply is insufficient to meet the planned demand, appropriate rationing factors are applied to reduce water supply. In this paper, a water distribution system is formulated as a network and solved by the GAMS modeling system for mathematical programming and optimization. A user-friendly interface is developed to facilitate the manipulation of data and to generate graphs and tables for decision makers. The optimization model and its interface form a decision support system (DSS), which can be used to configure a water distribution system to facilitate capacity expansion and reliability studies. Several examples are presented to demonstrate the utility and versatility of the developed DSS under different supply and demand scenarios, including applications to one of the largest water supply systems in the world, the Sao Paulo Metropolitan Area Water Supply Distribution System in Brazil.

Fast experimental identification of suspension models for control design

This paper presents both the theoretical and the experimental approaches of the development of a mathematical model to be used in multi-variable control system designs of an active suspension for a sport utility vehicle (SUV), in this case a light pickup truck. A complete seven-degree-of-freedom model is successfully quickly identified, with very satisfactory results in simulations and in real experiments conducted with the pickup truth. The novelty of the proposed methodology is the use of commercial software in the early stages of the identification to speed up the process and to minimize the need for a large number of costly experiments. The paper also presents major contributions to the identification of uncertainties in vehicle suspension models and in the development of identification methods using the sequential quadratic programming, where an innovation regarding the calculation of the objective function is proposed and implemented. Results from simulations of and practical experiments with the real SUV are presented, analysed, and compared, showing the potential of the method.