999 resultados para Earthquake Prediction


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A description is presented of a time-marking calculation of the unsteady flow generated by the interaction of upstream wakes with a moving blade row. The inviscid equations of motion are solved using a finite volume technique. Wake dissipation is modeled using an artificial viscosity. Predictions are presented for the rotor mid-span section of an axial turbine. Reasonable agreement is found between the predicted and measured unsteady blade surface static pressures and velocities. These and other results confirm that simple theories can be used to explain the phenomena of rotor-stator wake interactions.

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A method is presented for predicting the variance of the energy levels in a built-up system to accompany the mean values predicted by SEA. Closed form expressions for the variance are obtained in terms of the standard SEA parameters and an additional set of parameters αk that describe the nature of the power input to each subsystem k, and αks that describe the nature of the coupling between subsystems k and s.

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The seismic performance of waterfront cantilever sheet pile retaining walls is of continuing interest to geotechnical engineers as these structures suffer severe damage and even complete failure during earthquakes. This is often precipitated by liquefaction of the surrounding soil, either in the backfill or in front of the wall. This paper presents results from a series of small-scale plane strain models that were tested on a 1-g shaking table and recorded using a high-speed, high-resolution digital camera. The technique of Particle Image Velocimetry (PIV) was applied in order to allow the failure mechanisms to be visualised. It is shown that using PIV analyses it is possible to obtain failure mechanisms for a cantilever wall in liquefiable soil. These failure mechanisms are compared with those obtained for a cantilever wall in dry soil, previously carried out at a similar scale. It was observed that seismic liquefaction causes significant displacement in much larger zones of soil near the retaining wall compared to an equivalent dry case. The failure mechanism for a cantilever wall with liquefiable backfill, but with a remediated zone designed not to liquefy, is also presented and compared to the unremediated case.

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Accurate predictions of combustor hot streak migration enable the turbine designer to identify high-temperature regions that can limit component life. It is therefore important that these predictions are achieved within the short time scales of a design process. This article compares temperature measurements of a circular hot streak through a turning duct and a research turbine with predictions using a three-dimensional Reynolds-averaged Navier-Stokes solver. It was found that the mixing length turbulence model did not predict the hot streak dissipation accurately. However, implementation of a very simple model of the free stream turbulence (FST) significantly improved the exit temperature predictions on both the duct and research turbine. One advantage of the simple FST model described over more complex alternatives is that no additional equations are solved. This makes the method attractive for design purposes, as it is not associated with any increase in computational time.

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This paper proposes a method for extracting reliable architectural characteristics from complex porous structures using micro-computed tomography (μCT) images. The work focuses on a highly porous material composed of a network of fibres bonded together. The segmentation process, allowing separation of the fibres from the remainder of the image, is the most critical step in constructing an accurate representation of the network architecture. Segmentation methods, based on local and global thresholding, were investigated and evaluated by a quantitative comparison of the architectural parameters they yielded, such as the fibre orientation and segment length (sections between joints) distributions and the number of inter-fibre crossings. To improve segmentation accuracy, a deconvolution algorithm was proposed to restore the original images. The efficacy of the proposed method was verified by comparing μCT network architectural characteristics with those obtained using high resolution CT scans (nanoCT). The results indicate that this approach resolves the architecture of these complex networks and produces results approaching the quality of nanoCT scans. The extracted architectural parameters were used in conjunction with an affine analytical model to predict the axial and transverse stiffnesses of the fibre network. Transverse stiffness predictions were compared with experimentally measured values obtained by vibration testing. © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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A general formula for the prediction of drained weight of canned prawn processed under laboratory condition has been worked out earlier (Chaudhuri et al., 1978). Attempts were made in this communication to modify the general formula to predict the drained weight under commercial conditions of processing particularly blanching, as the moisture content of meat depends on the quantum of heat received during blanching (Govindan, 1975).

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Thus far most studies of operational energy use of buildings fail to take a longitudinal view, or in other words, do not take into account how operational energy use changes during the lifetime of a building. However, such a view is important when predicting the impact of climate change, or for long term energy accounting purposes. This article presents an approach to deliver a longitudinal prediction of operational energy use. The work is based on the review of deterioration in thermal performance, building maintenance effects, and future climate change. The key issues are to estimate the service life expectancy and thermal performance degradation of building components while building maintenance and changing weather conditions are considered at the same time. Two examples are presented to demonstrate the application of the deterministic and stochastic approaches, respectively. The work concludes that longitudinal prediction of operational energy use is feasible, but the prediction will depend largely on the availability of extensive and reliable monitoring data. This premise is not met in most current buildings. © 2011 Elsevier Ltd.