Measurement of the depth of maximum of extensive air showers above 10(18) eV

We describe the measurement of the depth of maximum, X(max), of the longitudinal development of air showers induced by cosmic rays. Almost 4000 events above 10(18) eV observed by the fluorescence detector of the Pierre Auger Observatory in coincidence with at least one surface detector station are selected for the analysis. The average shower maximum was found to evolve with energy at a rate of (106 +/- 35-21) g/cm(2)/decade below 10(18.24) +/- (0.05) eV, and d24 +/- 3 g/cm(2)/ecade above this energy. The measured shower-to-shower fluctuations decrease from about 55 to 26 g/cm(2). The interpretation of these results in terms of the cosmic ray mass composition is briefly discussed.

Limit on the diffuse flux of ultrahigh energy tau neutrinos with the surface detector of the Pierre Auger Observatory

Data collected at the Pierre Auger Observatory are used to establish an upper limit on the diffuse flux of tau neutrinos in the cosmic radiation. Earth-skimming nu(tau) may interact in the Earth's crust and produce a tau lepton by means of charged-current interactions. The tau lepton may emerge from the Earth and decay in the atmosphere to produce a nearly horizontal shower with a typical signature, a persistent electromagnetic component even at very large atmospheric depths. The search procedure to select events induced by tau decays against the background of normal showers induced by cosmic rays is described. The method used to compute the exposure for a detector continuously growing with time is detailed. Systematic uncertainties in the exposure from the detector, the analysis, and the involved physics are discussed. No tau neutrino candidates have been found. For neutrinos in the energy range 2x10(17) eV < E(nu)< 2x10(19) eV, assuming a diffuse spectrum of the form E(nu)(-2), data collected between 1 January 2004 and 30 April 2008 yield a 90% confidence-level upper limit of E(nu)(2)dN(nu tau)/dE(nu)< 9x10(-8) GeV cm(-2) s(-1) sr(-1).

Skewness, splitting number and vertex deletion of some toroidal meshes

The skewness sk(G) of a graph G = (V, E) is the smallest integer sk(G) >= 0 such that a planar graph can be obtained from G by the removal of sk(C) edges. The splitting number sp(G) of C is the smallest integer sp(G) >= 0 such that a planar graph can be obtained from G by sp(G) vertex splitting operations. The vertex deletion vd(G) of G is the smallest integer vd(G) >= 0 such that a planar graph can be obtained from G by the removal of vd(G) vertices. Regular toroidal meshes are popular topologies for the connection networks of SIMD parallel machines. The best known of these meshes is the rectangular toroidal mesh C(m) x C(n) for which is known the skewness, the splitting number and the vertex deletion. In this work we consider two related families: a triangulation Tc(m) x c(n) of C(m) x C(n) in the torus, and an hexagonal mesh Hc(m) x c(n), the dual of Tc(m) x c(n) in the torus. It is established that sp(Tc(m) x c(n)) = vd(Tc(m) x c(n) = sk(Hc(m) x c(n)) = sp(Hc(m) x c(n)) = vd(Hc(m) x c(n)) = min{m, n} and that sk(Tc(m) x c(n)) = 2 min {m, n}.

A simulation-based evolutionary multiobjective approach to manufacturing cell formation

The purpose of this paper is to propose a multiobjective optimization approach for solving the manufacturing cell formation problem, explicitly considering the performance of this said manufacturing system. Cells are formed so as to simultaneously minimize three conflicting objectives, namely, the level of the work-in-process, the intercell moves and the total machinery investment. A genetic algorithm performs a search in the design space, in order to approximate to the Pareto optimal set. The values of the objectives for each candidate solution in a population are assigned by running a discrete-event simulation, in which the model is automatically generated according to the number of machines and their distribution among cells implied by a particular solution. The potential of this approach is evaluated via its application to an illustrative example, and a case from the relevant literature. The obtained results are analyzed and reviewed. Therefore, it is concluded that this approach is capable of generating a set of alternative manufacturing cell configurations considering the optimization of multiple performance measures, greatly improving the decision making process involved in planning and designing cellular systems. (C) 2010 Elsevier Ltd. All rights reserved.

Thermal error evaluation and modelling of a CNC cylindrical grinding machine

With the relentless quest for improved performance driving ever tighter tolerances for manufacturing, machine tools are sometimes unable to meet the desired requirements. One option to improve the tolerances of machine tools is to compensate for their errors. Among all possible sources of machine tool error, thermally induced errors are, in general for newer machines, the most important. The present work demonstrates the evaluation and modelling of the behaviour of the thermal errors of a CNC cylindrical grinding machine during its warm-up period.

Stability analysis of core-annular flow and neutral stability wave number

A general transition criterion is proposed in order to locate the core-annular flow pattern in horizontal and vertical oil-water flows. It is based on a rigorous one-dimensional two-fluid model of liquid-liquid two-phase flow and considers the existence of critical interfacial wave numbers related to a non-negligible interfacial tension term to which the linear stability theory still applies. The viscous laminar-laminar flow problem is fully resolved and turbulence effects on the stability are analyzed through experimentally obtained shape factors. The proposed general transition criterion includes in its formulation the inviscid Kelvin-Helmholtz`s discriminator. If a theoretical maximum wavelength is considered as a necessary condition for stability, a stability criterion in terms of the Eotvos number is achieved. Effects of interfacial tension, viscosity ratio, density difference, and shape factors on the stability of core-annular flow are analyzed in detail. The more complete modeling allowed for the analysis of the neutral-stability wave number and the results strongly suggest that the interfacial tension term plays an indispensable role in the correct prediction of the stable region of core-annular flow pattern. The incorporation of a theoretical minimum wavelength into the transition model produced significantly better results. The criterion predictions were compared with recent data from the literature and the agreement is encouraging. (C) 2007 American Institute of Chemical Engineers.

A Constructive Genetic Algorithm for permutation flowshop scheduling

The general flowshop scheduling problem is a production problem where a set of n jobs have to be processed with identical flow pattern on in machines. In permutation flowshops the sequence of jobs is the same on all machines. A significant research effort has been devoted for sequencing jobs in a flowshop minimizing the makespan. This paper describes the application of a Constructive Genetic Algorithm (CGA) to makespan minimization on flowshop scheduling. The CGA was proposed recently as an alternative to traditional GA approaches, particularly, for evaluating schemata directly. The population initially formed only by schemata, evolves controlled by recombination to a population of well-adapted structures (schemata instantiation). The CGA implemented is based on the NEH classic heuristic and a local search heuristic used to define the fitness functions. The parameters of the CGA are calibrated using a Design of Experiments (DOE) approach. The computational results are compared against some other successful algorithms from the literature on Taillard`s well-known standard benchmark. The computational experience shows that this innovative CGA approach provides competitive results for flowshop scheduling; problems. (C) 2007 Elsevier Ltd. All rights reserved.

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

An accurate estimate of machining time is very important for predicting delivery time, manufacturing costs, and also to help production process planning. Most commercial CAM software systems estimate the machining time in milling operations simply by dividing the entire tool path length by the programmed feed rate. This time estimate differs drastically from the real process time because the feed rate is not always constant due to machine and computer numerical controlled (CNC) limitations. This study presents a practical mechanistic method for milling time estimation when machining free-form geometries. The method considers a variable called machine response time (MRT) which characterizes the real CNC machine`s capacity to move in high feed rates in free-form geometries. MRT is a global performance feature which can be obtained for any type of CNC machine configuration by carrying out a simple test. For validating the methodology, a workpiece was used to generate NC programs for five different types of CNC machines. A practical industrial case study was also carried out to validate the method. The results indicated that MRT, and consequently, the real machining time, depends on the CNC machine`s potential: furthermore, the greater MRT, the larger the difference between predicted milling time and real milling time. The proposed method achieved an error range from 0.3% to 12% of the real machining time, whereas the CAM estimation achieved from 211% to 1244% error. The MRT-based process is also suggested as an instrument for helping in machine tool benchmarking.

Lifecycle assessment of fuel ethanol from sugarcane in Brazil

This paper presents the lifecycle assessment (LCA) of fuel ethanol, as 100% of the vehicle fuel, from sugarcane in Brazil. The functional unit is 10,000 km run in an urban area by a car with a 1,600-cm(3) engine running on fuel hydrated ethanol, and the resulting reference flow is 1,000 kg of ethanol. The product system includes agricultural and industrial activities, distribution, cogeneration of electricity and steam, ethanol use during car driving, and industrial by-products recycling to irrigate sugarcane fields. The use of sugarcane by the ethanol agribusiness is one of the foremost financial resources for the economy of the Brazilian rural area, which occupies extensive areas and provides far-reaching potentials for renewable fuel production. But, there are environmental impacts during the fuel ethanol lifecycle, which this paper intents to analyze, including addressing the main activities responsible for such impacts and indicating some suggestions to minimize the impacts. This study is classified as an applied quantitative research, and the technical procedure to achieve the exploratory goal is based on bibliographic revision, documental research, primary data collection, and study cases at sugarcane farms and fuel ethanol industries in the northeast of SA o pound Paulo State, Brazil. The methodological structure for this LCA study is in agreement with the International Standardization Organization, and the method used is the Environmental Design of Industrial Products. The lifecycle impact assessment (LCIA) covers the following emission-related impact categories: global warming, ozone formation, acidification, nutrient enrichment, ecotoxicity, and human toxicity. The results of the fuel ethanol LCI demonstrate that even though alcohol is considered a renewable fuel because it comes from biomass (sugarcane), it uses a high quantity and diversity of nonrenewable resources over its lifecycle. The input of renewable resources is also high mainly because of the water consumption in the industrial phases, due to the sugarcane washing process. During the lifecycle of alcohol, there is a surplus of electric energy due to the cogeneration activity. Another focus point is the quantity of emissions to the atmosphere and the diversity of the substances emitted. Harvesting is the unit process that contributes most to global warming. For photochemical ozone formation, harvesting is also the activity with the strongest contributions due to the burning in harvesting and the emissions from using diesel fuel. The acidification impact potential is mostly due to the NOx emitted by the combustion of ethanol during use, on account of the sulfuric acid use in the industrial process and because of the NOx emitted by the burning in harvesting. The main consequence of the intensive use of fertilizers to the field is the high nutrient enrichment impact potential associated with this activity. The main contributions to the ecotoxicity impact potential come from chemical applications during crop growth. The activity that presents the highest impact potential for human toxicity (HT) via air and via soil is harvesting. Via water, HT potential is high in harvesting due to lubricant use on the machines. The normalization results indicate that nutrient enrichment, acidification, and human toxicity via air and via water are the most significant impact potentials for the lifecycle of fuel ethanol. The fuel ethanol lifecycle contributes negatively to all the impact potentials analyzed: global warming, ozone formation, acidification, nutrient enrichment, ecotoxicity, and human toxicity. Concerning energy consumption, it consumes less energy than its own production largely because of the electricity cogeneration system, but this process is highly dependent on water. The main causes for the biggest impact potential indicated by the normalization is the nutrient application, the burning in harvesting and the use of diesel fuel. The recommendations for the ethanol lifecycle are: harvesting the sugarcane without burning; more environmentally benign agricultural practices; renewable fuel rather than diesel; not washing sugarcane and implementing water recycling systems during the industrial processing; and improving the system of gases emissions control during the use of ethanol in cars, mainly for NOx. Other studies on the fuel ethanol from sugarcane may analyze in more details the social aspects, the biodiversity, and the land use impact.

Design and Characterization of Novel Wear Resistant Multilayer CVD Coatings with Improved Adhesion Between Al(2)O(3) and Ti(C,N)

Multilayer CVD coatings for high speed cutting applications were designed to achieve high wear and heat resistance during machining of steel alloys. In this work the microstructure and cutting performance of these novel multilayer CVD coatings are investigated and compared with standard CVD multilayer coatings. 3D-FIB tomography is used to characterize the microstructure of the layers, especially the transition between the Ti(C,N) and the Al(2)O(3) layer. The 3D reconstruction of the surface of the Ti(C,N) layer shows the formation of protruded Ti(C,N) grains with a very particular architecture, which penetrate into the Al(2)O(3) top-layer, providing a mechanical anchoring between both layers. Cemented carbides coated with the novel CVD multilayer present reduced crater and flank wear as well as improved adherence between the Al(2)O(3) top-layer and the Ti(C,N) layer leading to a dramatic improvement of cutting performance.

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.

Acoustic Simulation of a Special Switched Reluctance Drive by Means of Field-Circuit Coupling and Multiphysics Simulation

The approach presented in this paper consists of an energy-based field-circuit coupling in combination with multi-physics simulation of the acoustic radiation of electrical machines. The proposed method is applied to a special switched reluctance motor with asymmetric pole geometry to improve the start-up torque. The pole shape has been optimized, subject to low torque ripple, in a previous study. The proposed approach here is used to analyze the impact of the optimization on the overall acoustic behavior. The field-circuit coupling is based on a temporary lumped-parameter model of the magnetic part incorporated into a circuit simulation based on the modified nodal analysis. The harmonic force excitation is calculated by means of stress tensor computation, and it is transformed to a mechanical mesh by mapping techniques. The structural dynamic problem is solved in the frequency domain using a finite-element modal analysis and superposition. The radiation characteristic is obtained from boundary element acoustic simulation. Simulation results of both rotor types are compared, and measurements of the drive are presented.

Multiobjective Particle Swarm Approach for the Design of a Brushless DC Wheel Motor

The roots of swarm intelligence are deeply embedded in the biological study of self-organized behaviors in social insects. Particle swarm optimization (PSO) is one of the modern metaheuristics of swarm intelligence, which can be effectively used to solve nonlinear and non-continuous optimization problems. The basic principle of PSO algorithm is formed on the assumption that potential solutions (particles) will be flown through hyperspace with acceleration towards more optimum solutions. Each particle adjusts its flying according to the flying experiences of both itself and its companions using equations of position and velocity. During the process, the coordinates in hyperspace associated with its previous best fitness solution and the overall best value attained so far by other particles within the group are kept track and recorded in the memory. In recent years, PSO approaches have been successfully implemented to different problem domains with multiple objectives. In this paper, a multiobjective PSO approach, based on concepts of Pareto optimality, dominance, archiving external with elite particles and truncated Cauchy distribution, is proposed and applied in the design with the constraints presence of a brushless DC (Direct Current) wheel motor. Promising results in terms of convergence and spacing performance metrics indicate that the proposed multiobjective PSO scheme is capable of producing good solutions.

A Study of Influence of Configurations of the Windings on the Performance of Single Phase Induction Motor with Capacitor Start

The single phase induction motors needs two stator windings to produce rotating magnetic field : one main winding and the other auxiliary winding. The aim of the auxiliary winding is to create the rotating electromagnetic field when the machine is started-up and is afterwards turned off, generally through the centrifugal switch coupled together with the shaft of the machine rotor. The main purpose of this document is to evaluate the influence that the two windings have on the external characteristics of the single phase induction motor. For this purpose, two different kinds of windings were carried out and simulated, with the proposal to obtain some benefits. The main winding and the auxiliary winding were prepared and mounted on a prototype. The simulation was done via software based FEM, to make the extraction and results analysis possible. This results are shown at the end this document.

Mitigation of the torque ripple of a switched reluctance motor through a multiobjective optimization

The purpose of this work is to perform a multiobjective optimization in a 4:2 switched reluctance motor aiming both to maximize the mitigation of the torque ripple and to minimize the degradations of the starting and mean torques. To accomplish this task the Pareto Archived Evolution Strategy was implemented jointly with the Kriging Method, which acts as a surrogate function. The technique was applied on the optimization of some rotor geometrical parameters with the aid of finite element simulations to evaluate the approximation points for the Kriging model. The numerical results were compared to those from tests.