6,538 research outputs found

    The importance of accurate time-integration in the numerical modelling of P-wave propagation

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    The numerical dissipation characteristics of the Newmark and generalised-α time-integration schemes are investigated for P-wave propagation in a fully saturated level-ground sand deposit, where higher frequencies than those for S-waves are of concern. The study focuses on resonance, which has been shown to be of utmost importance for triggering liquefaction due to P-waves alone. The generalised-α scheme performs well, provided that the time-step has been carefully selected. Conversely, the dissipative Newmark method can excessively damp the response, changing radically the computed results. This implies that a computationally prohibiting small time-step would be required for Newmark to provide an accurate solution

    Evidence of photospheric vortex flows at supergranular junctions observed by FG/SOT (Hinode)

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    Twisting motions of different nature are observed in several layers of the solar atmosphere. Chromospheric sunspot whorls and rotation of sunspots or even higher up in the lower corona sigmoids are examples of the large scale twisted topology of many solar features. Nevertheless, their occurrence at large scale in the quiet photosphere has not been investigated. The present study reveals the existence of vortex flows located at the supergranular junctions of the quiet Sun. We use a 1-hour and a 5-hour time series of the granulation in Blue continuum and G-band images from FG/SOT to derive the photospheric flows. A feature tracking technique called Balltracking is performed to track the granules and reveal the underlying flow fields. In both time series we identify long-lasting vortex flow located at supergranular junctions. The first vortex flow lasts at least 1 hour and is ~20-arcsec-wide (~15.5 Mm). The second vortex flow lasts more than 2 hours and is ~27-arcsec-wide (~21 Mm).Comment: 4 pages, 10 figure

    Post-hoc derivation of SOHO Michelson doppler imager flat fields

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    <p><b>Context:</b> The SOHO satellite now offers a unique perspective on the Sun as it is the only space-based instrument that can provide large, high-resolution data sets over an entire 11-year solar cycle. This unique property enables detailed studies of long-term variations in the Sun. One significant problem when looking for such changes is determining what component of any variation is due to deterioration of the instrument and what is due to the Sun itself. One of the key parameters that changes over time is the apparent sensitivity of individual pixels in the CCD array. This can change considerably as a result of optics damage, radiation damage, and aging of the sensor itself. In addition to reducing the sensitivity of the telescope over time, this damage significantly changes the uniformity of the flat field of the instrument, a property that is very hard to recalibrate in space. For procedures such as feature tracking and intensity analysis, this can cause significant errors.</p> <p><b>Aims:</b> We present a method for deriving high-precision flat fields for high-resolution MDI continuum data, using analysis of existing continuum and magnetogram data sets.</p> <p><b>Methods:</b> A flat field is constructed using a large set (1000-4000 frames) of cospatial magnetogram and continuum data. The magnetogram data is used to identify and mask out magnetically active regions on the continuum data, allowing systematic biases to be avoided. This flat field can then be used to correct individual continuum images from a similar time.</p> <p><b>Results:</b> This method allows us to reduce the residual flat field error by around a factor 6-30, depending on the area considered, enough to significantly change the results from correlation-tracking analysis. One significant advantage of this method is that it can be done retrospectively using archived data, without requiring any special satellite operations.</p&gt

    Integrated carbon dioxide reduction system feasibility study, part I Final report

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    Method for physical recovery of carbon dioxide from space cabin atmosphere and chemical recovery of metabolic oxyge

    Recursive Neural Networks Can Learn Logical Semantics

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    Tree-structured recursive neural networks (TreeRNNs) for sentence meaning have been successful for many applications, but it remains an open question whether the fixed-length representations that they learn can support tasks as demanding as logical deduction. We pursue this question by evaluating whether two such models---plain TreeRNNs and tree-structured neural tensor networks (TreeRNTNs)---can correctly learn to identify logical relationships such as entailment and contradiction using these representations. In our first set of experiments, we generate artificial data from a logical grammar and use it to evaluate the models' ability to learn to handle basic relational reasoning, recursive structures, and quantification. We then evaluate the models on the more natural SICK challenge data. Both models perform competitively on the SICK data and generalize well in all three experiments on simulated data, suggesting that they can learn suitable representations for logical inference in natural language

    Numerical Modelling of Multi-directional Earthquake Loading and Its Effect on Sand Liquefaction

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    Earthquakes generate multi-directional ground motions, two components in the horizontal direction and one in the vertical. Nevertheless, the effect of vertical motion on site response analysis has not been the object of extensive research. The 2010/2011 Canterbury sequence of seismic events in New Zealand is a prime example among other earlier field observations strongly corroborating that the vertical acceleration may have a detrimental effect on soil liquefaction. Consequently, this study aims to provide insight into the influence of the input vertical motion on sand liquefaction. For this reason, two ground motions, with very different frequency contents, are used as the input excitations. Non-linear elasto-plastic plane strain fully coupled effective stress-based finite element analyses are conducted to investigate the occurrence of liquefaction in a hypothetical fully saturated Fraser River Sand deposit. The results indicate that the frequency content of the input motion is of utmost importance for the response of sands to liquefaction when the vertical loading is considered

    Improved head-controlled TV system produces high-quality remote image

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    Manipulator operator uses an improved resolution tv camera/monitor positioning system to view the remote handling and processing of reactive, flammable, explosive, or contaminated materials. The pan and tilt motions of the camera and monitor are slaved to follow the corresponding motions of the operators head

    A knowledge based system for valuing variations in civil engineering works: a user centred approach

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    There has been much evidence that valuing variations in construction projects can lead to conflicts and disputes leading to loss of time, efficiency, and productivity. One of the reasons for these conflicts and disputes concerns the subjectivity of the project stakeholders involved in the process. One way to minimise this is to capture and collate the knowledge and perceptions of the different parties involved in order to develop a robust mechanism for valuing variations. Focusing on the development of such a mechanism, the development of a Knowledge Based System (KBS) for valuing variations in civil engineering work is described. Evaluation of the KBS involved demonstration to practitioners in the construction industry to support the contents of the knowledge base and perceived usability and acceptance of the system. Results support the novelty, contents, usability, and acceptance of the system, and also identify further potential developments of the KBS
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