90 resultados para hard controls


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This paper is an extension to an idea coined during the 13th EUSPEN Conference (P6.23) named "surface defect machining" (SDM). The objective of this work was to demonstrate how a conventional CNC turret lathe can be used to obtain ultra high precision machined surface finish on hard steels without recourse to a sophisticated ultra precision machine tool. An AISI 4340 hard steel (69 HRC) workpiece was machined using a CBN cutting tool with and without SDM. Post-machining measurements by a Form Talysurf and a Scanning Electron Microscope (FEI Quanta 3D) revealed that SDM culminates to several key advantages (i) provides better quality of the machined surface integrity and offers (ii) lowering feed rate to 5μm/rev to obtain a machined surface roughness of 30 nm (optical quality).

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The proliferation of mobile devices in society accessing data via the ‘cloud’ is imposing a dramatic increase in the amount of information to be stored on hard disk drives (HDD) used in servers. Forecasts are that areal densities will need to increase by as much as 35% compound per annum and by 2020 cloud storage capacity will be around 7 zettabytes corresponding to areal densities of 2 Tb/in2. This requires increased performance from the magnetic pole of the electromagnetic writer in the read/write head in the HDD. Current state-of-art writing is undertaken by morphologically complex magnetic pole of sub 100 nm dimensions, in an environment of engineered magnetic shields and it needs to deliver strong directional magnetic field to areas on the recording media around 50 nm x 13 nm. This points to the need for a method to perform direct quantitative measurements of the magnetic field generated by the write pole at the nanometer scale. Here we report on the complete in situ quantitative mapping of the magnetic field generated by a functioning write pole in operation using electron holography. Opportunistically, it points the way towards a new nanoscale magnetic field source to further develop in situ Transmission Electron Microscopy.

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A huge variety of proteins are able to form fibrillar structures(1), especially at high protein concentrations. Hence, it is surprising that spider silk proteins can be stored in a soluble form at high concentrations and transformed into extremely stable fibres on demand(2,3). Silk proteins are reminiscent of amphiphilic block copolymers containing stretches of polyalanine and glycine-rich polar elements forming a repetitive core flanked by highly conserved non-repetitive amino-terminal(4,5) and carboxy-terminal(6) domains. The N-terminal domain comprises a secretion signal, but further functions remain unassigned. The C-terminal domain was implicated in the control of solubility and fibre formation(7) initiated by changes in ionic composition(8,9) and mechanical stimuli known to align the repetitive sequence elements and promote beta-sheet formation(10-14). However, despite recent structural data(15), little is known about this remarkable behaviour in molecular detail. Here we present the solution structure of the C-terminal domain of a spider dragline silk protein and provide evidence that the structural state of this domain is essential for controlled switching between the storage and assembly forms of silk proteins. In addition, the C-terminal domain also has a role in the alignment of secondary structural features formed by the repetitive elements in the backbone of spider silk proteins, which is known to be important for the mechanical properties of the fibre.

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In this study, 39 sets of hard turning (HT) experimental trials were performed on a Mori-Seiki SL-25Y (4-axis) computer numerical controlled (CNC) lathe to study the effect of cutting parameters in influencing the machined surface roughness. In all the trials, AISI 4340 steel workpiece (hardened up to 69 HRC) was machined with a commercially available CBN insert (Warren Tooling Limited, UK) under dry conditions. The surface topography of the machined samples was examined by using a white light interferometer and a reconfirmation of measurement was done using a Form Talysurf. The machining outcome was used as an input to develop various regression models to predict the average machined surface roughness on this material. Three regression models - Multiple regression, Random Forest, and Quantile regression were applied to the experimental outcomes. To the best of the authors’ knowledge, this paper is the first to apply Random Forest or Quantile regression techniques to the machining domain. The performance of these models was compared to each other to ascertain how feed, depth of cut, and spindle speed affect surface roughness and finally to obtain a mathematical equation correlating these variables. It was concluded that the random forest regression model is a superior choice over multiple regression models for prediction of surface roughness during machining of AISI 4340 steel (69 HRC).

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Continuous research endeavors on hard turning (HT), both on machine tools and cutting tools, have made the previously reported daunting limits easily attainable in the modern scenario. This presents an opportunity for a systematic investigation on finding the current attainable limits of hard turning using a CNC turret lathe. Accordingly, this study aims to contribute to the existing literature by providing the latest experimental results of hard turning of AISI 4340 steel (69 HRC) using a CBN cutting tool. An orthogonal array was developed using a set of judiciously chosen cutting parameters. Subsequently, the longitudinal turning trials were carried out in accordance with a well-designed full factorial-based Taguchi matrix. The speculation indeed proved correct as a mirror finished optical quality machined surface (an average surface roughness value of 45 nm) was achieved by the conventional cutting method. Furthermore, Signal-to-noise (S/N) ratio analysis, Analysis of variance (ANOVA), and Multiple regression analysis were carried out on the experimental datasets to assert the dominance of each machining variable in dictating the machined surface roughness and to optimize the machining parameters. One of the key findings was that when feed rate during hard turning approaches very low (about 0.02mm/rev), it could alone be most significant (99.16%) parameter in influencing the machined surface roughness (Ra). This has, however also been shown that low feed rate results in high tool wear, so the selection of machining parameters for carrying out hard turning must be governed by a trade-off between the cost and quality considerations.

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Fast-electron generation and dynamics, including electron refluxing, is at the core of understanding high-intensity laser-plasma interactions. This field is itself of strong relevance to fast ignition fusion and the development of new short-pulse, intense, x-ray, gamma-ray, and particle sources. In this paper, we describe experiments that explicitly link fast-electron refluxing and anisotropy in hard-x-ray emission. We find the anisotropy in x-ray emission to be strongly correlated to the suppression of refluxing. In contrast to some previous work, the peak of emission is directly along the rear normal to the target rather than along either the incident laser direction or the specular reflection direction.

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We present a model for academia with heterogeneous author types and endogenous effort to evaluate recent changes in the publication process in Economics. We analyze the implications of these developments on research output. Lowering the precision of refereeing signals lowers effort choices of golden middle authors, but invites more submissions from less able authors. Increasing the number of journals stimulates less able authors to submit their papers. The editor can improve the journal's quality pool of submitted manuscripts by improving the precision of refereeing, but not by lowering acceptance standards. The submission strategy of an author is informative of his ability.

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Under the European Union Renewable Energy Directive each Member State is mandated to ensure that 10% of transport energy (excluding aviation and marine transport) comes from renewable sources by 2020. The Irish Government intends to achieve this target with a number of policies including ensuring that 10% of all vehicles in the transport fleet are powered by electricity by 2020. This paper investigates the impact of the 10% electric vehicle target in Ireland in 2020 using a dynamic programming based long term generation expansion planning model. The model developed optimizes power dispatch using hourly electricity demand curves up to 2020, while incorporating generator characteristics and certain operational requirements such as energy not served and loss of load probability while satisfying constraints on environmental emissions, fuel availability and generator operational and maintenance costs. Two distinct scenarios are analysed based on a peak and off-peak charging regimes in order to simulate the effects of the electric vehicles charging in 2020. The importance and influence of the charging regimes on the amount of energy used and tailgate emissions displaced is then determined.