18 resultados para bars

em Cambridge University Engineering Department Publications Database


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Designers who want to manufacture a hardenable steel component need to select both the steel and its heat treatment. This project aims to develop a selection methodology for steels and process routes as an aid to designers. Three studies were conducted: - production of software to calculate the "equivalent diameter" and "equivalent Jominy distance" for simple shapes of a steel component; - prediction of semi-empirical Jominy curves (as-cooled) using CCT diagrams and process modelling methods, which were validated by experiment on plain carbon steels; - investigation of tempering of Jominy bars to explore the potential for semi-empirical models for the hardness after tempering.

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A report on characterisation of technology roadmaps, its purpose and formats are presented. A fast-start process is developed to support the initiation of technology roadmapping in firms to address the industrial needs. The purpose of each roadmap is related to a number of planning aims: product, capability, integration, strategic, long-range, programme and process planning. The second set of categories are related to the format of the roadmap, based on observed structure: multiple or single layers, bars, tables, graphs, pictorial forms, flow diagrams and text. It is concluded that technology roadmaps processes a great potential for supporting the development and implementation of business product and technology strategy.

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This paper describes a program of work, largely experimental, which was undertaken with the objective of developing an improved blade profile for the low-pressure turbine in aero-engine applications. Preliminary experiments were conducted using a novel technique. An existing cascade of datum blades was modified to enable the pressure distribution on the suction surface of one of the blades to be altered. Various means, such as shaped inserts, an adjustable flap at the trailing edge, and changing stagger were employed to change the geometry of the passage. These experiments provided boundary layer and lift data for a wide range of suction surface pressure distributions. The data was then used as a guide for the development of new blade profiles. The new blade profiles were then investigated in a low-speed cascade that included a set of moving bars upstream of the cascade of blades to simulate the effect of the incoming wakes from the previous blade row in a multistage turbine environment.

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The use of anti-roll bars to provide additional roll stiffness and therefore to reduce the trade-off between ride and rollover performance has previously been studied. However, little work has been carried out to investigate the benefits of a switchable roll stiffness. Such a semi-active anti-roll system has the ability to have a low roll stiffness during straight-ahead driving for improved ride performance and high roll stiffness during cornering for improved roll performance. Modelling of such a system is conducted and the model is validated against a semi-active anti-roll system fitted to an experimental vehicle. Experimental and theoretical investigations are used to investigate the performance of such a system with several different strategies employed to switch to the high-stiffness state. The use of an air suspension on the vehicle to roll into corners is also investigated, as is the possibility of exploiting the road layout by allowing the vehicle to be in a low-roll-stiffness configuration during a corner, and then to switch to the high-roll-stiffness configuration midcorner, hence 'locking in' a roll angle. The best rollover performance improvement that was achieved was 12.5 per cent. © IMechE 2008.

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Demodulation is an ill-posed problem whenever both carrier and envelope signals are broadband and unknown. Here, we approach this problem using the methods of probabilistic inference. The new approach, called Probabilistic Amplitude Demodulation (PAD), is computationally challenging but improves on existing methods in a number of ways. By contrast to previous approaches to demodulation, it satisfies five key desiderata: PAD has soft constraints because it is probabilistic; PAD is able to automatically adjust to the signal because it learns parameters; PAD is user-steerable because the solution can be shaped by user-specific prior information; PAD is robust to broad-band noise because this is modeled explicitly; and PAD's solution is self-consistent, empirically satisfying a Carrier Identity property. Furthermore, the probabilistic view naturally encompasses noise and uncertainty, allowing PAD to cope with missing data and return error bars on carrier and envelope estimates. Finally, we show that when PAD is applied to a bandpass-filtered signal, the stop-band energy of the inferred carrier is minimal, making PAD well-suited to sub-band demodulation. © 2006 IEEE.

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Post-earthquake structural safety evaluations are currently performed manually by a team of certified inspectors and/or structural engineers. This process is time-consuming and costly, keeping owners and occupants from returning to their businesses and homes. Automating these evaluations would enable faster, and potentially more consistent, relief and response processes. In order to do this, the detection of exposed reinforcing steel is of utmost significance. This paper presents a novel method of detecting exposed reinforcement in concrete columns for the purpose of advancing practices of structural and safety evaluation of buildings after earthquakes. Under this method, the binary image of the reinforcing area is first isolated using a state-of-the-art adaptive thresholding technique. Next, the ribbed regions of the reinforcement are detected by way of binary template matching. Finally, vertical and horizontal profiling are applied to the processed image in order to filter out any superfluous pixels and take into consideration the size of reinforcement bars in relation to that of the structural element within which they reside. The final result is the combined binary image disclosing only the regions containing rebar overlaid on top of the original image. The method is tested on a set of images from the January 2010 earthquake in Haiti. Preliminary test results convey that most exposed reinforcement could be properly detected in images of moderately-to-severely damaged concrete columns.

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An innovative technique based on optical fibre sensing that allows continuous strain measurement has recently been introduced in structural health monitoring. Known as Brillouin Optical Time-Domain Reflectometry (BOTDR), this distributed optical fibre sensing technique allows measurement of strain along the full length (up to 10km) of a suitably installed optical fibre. Examples of recent implementations of BOTDR fibre optic sensing in piles are described in this paper. Two examples of distributed optical fibre sensing in piles are demonstrated using different installation techniques. In a load bearing pile, optical cables were attached along the reinforcing bars by equally spaced spot gluing to measure the axial response of pile to ground excavation induced heave and construction loading. Measurement of flexural behaviour of piles is demonstrated in the instrumentation of a secant piled wall where optical fibres were embedded in the concrete by simple endpoint clamping. Both methods have been verified via laboratory works. © 2009 IOS Press.

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The design of a deployable structure which deploys from a compact bundle of six parallel bars to a rectangular ring is considered. The structure is a plane symmetric Bricard linkage. The internal mechanism is described in terms of its Denavit-Hartenberg parameters; the nature of its single degree of freedom is examined in detail by determining the exact structure of the system of equations governing its movement; a range of design parameters for building feasible mechanisms is determined numerically; and polynomial continuation is used to design rings with certain specified desirable properties. © 2013 Elsevier Ltd.

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We study unsupervised learning in a probabilistic generative model for occlusion. The model uses two types of latent variables: one indicates which objects are present in the image, and the other how they are ordered in depth. This depth order then determines how the positions and appearances of the objects present, specified in the model parameters, combine to form the image. We show that the object parameters can be learnt from an unlabelled set of images in which objects occlude one another. Exact maximum-likelihood learning is intractable. However, we show that tractable approximations to Expectation Maximization (EM) can be found if the training images each contain only a small number of objects on average. In numerical experiments it is shown that these approximations recover the correct set of object parameters. Experiments on a novel version of the bars test using colored bars, and experiments on more realistic data, show that the algorithm performs well in extracting the generating causes. Experiments based on the standard bars benchmark test for object learning show that the algorithm performs well in comparison to other recent component extraction approaches. The model and the learning algorithm thus connect research on occlusion with the research field of multiple-causes component extraction methods.

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This paper presents the production and testing of an ortho-planar one-way micro-valve. The main advantages of such valves are that they are very compact and can be made from a single flat piece of material. A previous paper presents and discusses a micro-valve assembly based on a spider spring. The present paper focuses on the valve assembly process and the valve performance.. Several prototypes with a bore of 0.2 mm have been built using two manufacturing techniques (μEDM and stereo-lithography) and tested for pressures up to 7 bars. © 2008 International Federation for Information Processing.

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To determine the load at which FRPs debond from concrete beams using global-energy-balance-based fracture mechanics concepts, the single most important parameter is the fracture energy of the concrete-FRP interface, which is easy to define but difficult to determine. Debonding propagates in the narrow zone of concrete, between the FRP and the (tension) steel reinforcement bars in the beam, and the presence of nearby steel bars prevents the fracture process zone, which in concrete is normally extensive, from developing fully. The paper presents a detailed discussion of the mechanism of the FRP debonding, and shows that the initiation of debonding can be regarded as a Mode I (tensile) fracture in concrete, despite being loaded primarily in shear. It is shown that the incorporation of this fracture energy in the debonding model developed by the authors, details of which are presented elsewhere, gives predictions that match the test results reported in the literature. © 2013 Elsevier Ltd.

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We demonstrate how the Gaussian process regression approach can be used to efficiently reconstruct free energy surfaces from umbrella sampling simulations. By making a prior assumption of smoothness and taking account of the sampling noise in a consistent fashion, we achieve a significant improvement in accuracy over the state of the art in two or more dimensions or, equivalently, a significant cost reduction to obtain the free energy surface within a prescribed tolerance in both regimes of spatially sparse data and short sampling trajectories. Stemming from its Bayesian interpretation the method provides meaningful error bars without significant additional computation. A software implementation is made available on www.libatoms.org.