924 resultados para Nano-composite structure
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The problem of uncertainty propagation in composite laminate structures is studied. An approach based on the optimal design of composite structures to achieve a target reliability level is proposed. Using the Uniform Design Method (UDM), a set of design points is generated over a design domain centred at mean values of random variables, aimed at studying the space variability. The most critical Tsai number, the structural reliability index and the sensitivities are obtained for each UDM design point, using the maximum load obtained from optimal design search. Using the UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on supervised evolutionary learning. Finally, using the developed ANN a Monte Carlo simulation procedure is implemented and the variability of the structural response based on global sensitivity analysis (GSA) is studied. The GSA is based on the first order Sobol indices and relative sensitivities. An appropriate GSA algorithm aiming to obtain Sobol indices is proposed. The most important sources of uncertainty are identified.
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This synopsis summarizes the key chemical and bacteriological characteristics of β-lactams, penicillins, cephalosporins, carbanpenems, monobactams and others. Particular notice is given to first-generation to fifth-generation cephalosporins. This reviewalso summarizes the main resistancemechanism to antibiotics, focusing particular attention to those conferring resistance to broad-spectrum cephalosporins by means of production of emerging cephalosporinases (extended-spectrum β-lactamases and AmpC β-lactamases), target alteration (penicillin-binding proteins from methicillin-resistant Staphylococcus aureus) and membrane transporters that pump β-lactams out of the bacterial cell.
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The principal topic of this work is the application of data mining techniques, in particular of machine learning, to the discovery of knowledge in a protein database. In the first chapter a general background is presented. Namely, in section 1.1 we overview the methodology of a Data Mining project and its main algorithms. In section 1.2 an introduction to the proteins and its supporting file formats is outlined. This chapter is concluded with section 1.3 which defines that main problem we pretend to address with this work: determine if an amino acid is exposed or buried in a protein, in a discrete way (i.e.: not continuous), for five exposition levels: 2%, 10%, 20%, 25% and 30%. In the second chapter, following closely the CRISP-DM methodology, whole the process of construction the database that supported this work is presented. Namely, it is described the process of loading data from the Protein Data Bank, DSSP and SCOP. Then an initial data exploration is performed and a simple prediction model (baseline) of the relative solvent accessibility of an amino acid is introduced. It is also introduced the Data Mining Table Creator, a program developed to produce the data mining tables required for this problem. In the third chapter the results obtained are analyzed with statistical significance tests. Initially the several used classifiers (Neural Networks, C5.0, CART and Chaid) are compared and it is concluded that C5.0 is the most suitable for the problem at stake. It is also compared the influence of parameters like the amino acid information level, the amino acid window size and the SCOP class type in the accuracy of the predictive models. The fourth chapter starts with a brief revision of the literature about amino acid relative solvent accessibility. Then, we overview the main results achieved and finally discuss about possible future work. The fifth and last chapter consists of appendices. Appendix A has the schema of the database that supported this thesis. Appendix B has a set of tables with additional information. Appendix C describes the software provided in the DVD accompanying this thesis that allows the reconstruction of the present work.
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Wireless Sensor Networks (WSN) are being used for a number of applications involving infrastructure monitoring, building energy monitoring and industrial sensing. The difficulty of programming individual sensor nodes and the associated overhead have encouraged researchers to design macro-programming systems which can help program the network as a whole or as a combination of subnets. Most of the current macro-programming schemes do not support multiple users seamlessly deploying diverse applications on the same shared sensor network. As WSNs are becoming more common, it is important to provide such support, since it enables higher-level optimizations such as code reuse, energy savings, and traffic reduction. In this paper, we propose a macro-programming framework called Nano-CF, which, in addition to supporting in-network programming, allows multiple applications written by different programmers to be executed simultaneously on a sensor networking infrastructure. This framework enables the use of a common sensing infrastructure for a number of applications without the users having to worrying about the applications already deployed on the network. The framework also supports timing constraints and resource reservations using the Nano-RK operating system. Nano- CF is efficient at improving WSN performance by (a) combining multiple user programs, (b) aggregating packets for data delivery, and (c) satisfying timing and energy specifications using Rate- Harmonized Scheduling. Using representative applications, we demonstrate that Nano-CF achieves 90% reduction in Source Lines-of-Code (SLoC) and 50% energy savings from aggregated data delivery.
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This paper studies fractional variable structure controllers. Two cases are considered namely, the sliding reference model and the control action, that are generalized from integer into fractional orders. The test bed consists in a mechanical manipulator and the effect of the fractional approach upon the system performance is evaluated. The results show that fractional dynamics, both in the switching surface and the control law are important design algorithms in variable structure controllers.
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This article describes a finite element-based formulation for the statistical analysis of the response of stochastic structural composite systems whose material properties are described by random fields. A first-order technique is used to obtain the second-order statistics for the structural response considering means and variances of the displacement and stress fields of plate or shell composite structures. Propagation of uncertainties depends on sensitivities taken as measurement of variation effects. The adjoint variable method is used to obtain the sensitivity matrix. This method is appropriated for composite structures due to the large number of random input parameters. Dominant effects on the stochastic characteristics are studied analyzing the influence of different random parameters. In particular, a study of the anisotropy influence on uncertainties propagation of angle-ply composites is carried out based on the proposed approach.
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An approach for the analysis of uncertainty propagation in reliability-based design optimization of composite laminate structures is presented. Using the Uniform Design Method (UDM), a set of design points is generated over a domain centered on the mean reference values of the random variables. A methodology based on inverse optimal design of composite structures to achieve a specified reliability level is proposed, and the corresponding maximum load is outlined as a function of ply angle. Using the generated UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on an evolutionary learning process. Then, a Monte Carlo simulation using ANN development is performed to simulate the behavior of the critical Tsai number, structural reliability index, and their relative sensitivities as a function of the ply angle of laminates. The results are generated for uniformly distributed random variables on a domain centered on mean values. The statistical analysis of the results enables the study of the variability of the reliability index and its sensitivity relative to the ply angle. Numerical examples showing the utility of the approach for robust design of angle-ply laminates are presented.
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In this cross-sectional study we analyzed, whether team climate for innovation mediates the relationship between team task structure and innovative behavior, job satisfaction, affective organizational commitment, and work stress. 310 employees in 20 work teams of an automotive company participated in this study. 10 teams had been changed from a restrictive to a more self-regulating team model by providing task variety, autonomy, team-specific goals, and feedback in order to increase team effectiveness. Data support the supposed causal chain, although only with respect to team innovative behavior all required effects were statistically significant. Longitudinal designs and larger samples are needed to prove the assumed causal relationships, but results indicate that implementing self-regulating teams might be an effective strategy for improving innovative behavior and thus team and company effectiveness.
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This paper explores the management structure of the team-based organization. First it provides a theoretical model of structures and processes of work teams. The structure determines the team’s responsibilities in terms of authority and expertise about specific regulation tasks. The responsiveness of teams to these responsibilities are the processes of teamwork, in terms of three dimensions, indicating to what extent teams indeed use the space provided to them. The research question that this paper addresses is to what extent the position of responsibilities in the team-based organization affect team responsiveness. This is done by two hypotheses. First, the effect of the so-called proximity of regulation tasks is tested. It is expected that the responsibility for tasks positioned higher in the organization (i.e. further from the team) generally has a negative effect on team responsiveness, whereas tasks positioned lower in the organization (i.e. closer to the team) will have a positive effect on the way in which teams respond. Second, the relationship between the number of tasks for which the team is responsible with team responsiveness is tested. Theory suggests that teams being responsible for a larger number of tasks perform better, i.e. show higher responsiveness. These hypotheses are tested by a study of 109 production teams in the automotive industry. The results show that, as the theory predicts, increasing numbers of responsibilities have positive effects on team responsiveness. However, the delegation of expertise to teams seems to be the most important predictor of responsiveness. Also, not all regulation tasks show to have effects on team responsiveness. Most tasks do not show to have any significant effect at all. A number of tasks affects team responsiveness positively, when their responsibility is positioned lower in the organization, but also a number of tasks affects team responsiveness positively when located higher in the organization, i.e. further from the teams in the production. The results indicate that more attention can be paid to the distribution of responsibilities, in particular expertise, to teams. Indeed delegating more expertise improve team responsiveness, however some tasks might be located better at higher organizational levels, indicating that there are limitations to what responsibilities teams can handle.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Física Laboratorial, Ensino e História da Física
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OBJECTIVE Develop an index to evaluate the maternal and neonatal hospital care of the Brazilian Unified Health System.METHODS This descriptive cross-sectional study of national scope was based on the structure-process-outcome framework proposed by Donabedian and on comprehensive health care. Data from the Hospital Information System and the National Registry of Health Establishments were used. The maternal and neonatal network of Brazilian Unified Health System consisted of 3,400 hospitals that performed at least 12 deliveries in 2009 or whose number of deliveries represented 10.0% or more of the total admissions in 2009. Relevance and reliability were defined as criteria for the selection of variables. Simple and composite indicators and the index of completeness were constructed and evaluated, and the distribution of maternal and neonatal hospital care was assessed in different regions of the country.RESULTS A total of 40 variables were selected, from which 27 single indicators, five composite indicators, and the index of completeness of care were built. Composite indicators were constructed by grouping simple indicators and included the following variables: hospital size, level of complexity, delivery care practice, recommended hospital practice, and epidemiological practice. The index of completeness of care grouped the five variables and classified them in ascending order, thereby yielding five levels of completeness of maternal and neonatal hospital care: very low, low, intermediate, high, and very high. The hospital network was predominantly of small size and low complexity, with inadequate child delivery care and poor development of recommended and epidemiological practices. The index showed that more than 80.0% hospitals had a low index of completeness of care and that most qualified heath care services were concentrated in the more developed regions of the country.CONCLUSIONS The index of completeness proved to be of great value for monitoring the maternal and neonatal hospital care of Brazilian Unified Health System and indicated that the quality of health care was unsatisfactory. However, its application does not replace specific evaluations.
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The characteristics of carbon fiber-reinforced plastics allow a very broad range of uses. Drilling is often necessary to assemble different components, but this can lead to various forms of damage, such as delamination which is the most severe. However, a reduced thrust force can decrease the risk of delamination. In this work, two variables of the drilling process were compared: tool material and geometry, as well as the effect of feed rate and cutting speed. The parameters that were analyzed include: thrust force, delamination extension and mechanical strength through open-hole tensile test, bearing test, and flexural test on drilled plates. The present work shows that a proper combination of all the factors involved in drilling operations, like tool material, tool geometry and cutting parameters, such as feed rate or cutting speed, can lead to the reduction of delamination damage and, consequently, to the enhancement of the mechanical properties of laminated parts in complex structures, evaluated by open-hole, bearing, or flexural tests.
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Adhesive-bonding for the unions in multi-component structures is gaining momentum over welding, riveting and fastening. It is vital for the design of bonded structures the availability of accurate damage models, to minimize design costs and time to market. Cohesive Zone Models (CZM’s) have been used for fracture prediction in structures. The eXtended Finite Element Method (XFEM) is a recent improvement of the Finite Element Method (FEM) that relies on traction-separation laws similar to those of CZM’s but it allows the growth of discontinuities within bulk solids along an arbitrary path, by enriching degrees of freedom. This work proposes and validates a damage law to model crack propagation in a thin layer of a structural epoxy adhesive using the XFEM. The fracture toughness in pure mode I (GIc) and tensile cohesive strength (sn0) were defined by Double-Cantilever Beam (DCB) and bulk tensile tests, respectively, which permitted to build the damage law. The XFEM simulations of the DCB tests accurately matched the experimental load-displacement (P-d) curves, which validated the analysis procedure.
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This paper presents the Pseudo phase plane (PPP) method for detecting the existence of a nanofilm on the nitroazobenzene-modified glassy carbon electrode (NAB-GC) system. This modified electrode systems and nitroazobenze-nanofilm were prepared by the electrochemical reduction of diazonium salt of NAB at the glassy carbon electrodes (GCE) in nonaqueous media. The IR spectra of the bare glassy carbon electrodes (GCE), the NAB-GC electrode system and the organic NAB film were recorded. The IR data of the bare GC, NAB-GC and NAB film were categorized into five series consisting of FILM1, GC-NAB1, GC1; FILM2, GC-NAB2, GC2; FILM3, GC-NAB3, GC3 and FILM4, GC-NAB4, GC4 respectively. The PPP approach was applied to each group of the data of unmodified and modified electrode systems with nanofilm. The results provided by PPP method show the existence of the NAB film on the modified GC electrode.
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This paper describes the design and manufacture of a low-cost full scale pultrusion prototype equipment and discusses the production and obtained mechanical properties of polypropylene/glass (GF/PP) reinforced composite ba rs fabricated by using the prototype equipment. Three different GF/PP pre-impregnated ra w-materials, a commercial GF/PP comingled system from Vetrotex, a GF/PP powder coat ed towpreg [1-3] and, a GF/PP pre- consolidated tape (PCT) produced in our laboratorie s, were used in the production of composite bars that were subsequently submitted to mechanical testing in order to determine the relevant mechanical properties and quantify the consolidation quality. Samples of the different composite profiles were also observed und er SEM microscopy.