902 resultados para dimension stone


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Stone masonry spires are vulnerable to seismic loading. Computational methods are often used to predict the dynamic linear elastic response of masonry towers and spires, but this approach is only applicable until the first masonry joint begins to open, limiting the ability to predict collapse. In this paper, analytical modeling is used to investigate the uplift, rocking and collapse of stone spires. General equations for static equilibrium of the spire under lateral acceleration are first presented, and provide a reasonable lower bound for predicting collapse. The dynamic response is then considered through elastic modal analysis and rigid body rocking. Together, these methods are used to provide uplift curves and single impulse overturning collapse curves for a complete range of possible spire geometries. Results are used to evaluate the historic collapse of two specific stone spires. © 2012 Elsevier Ltd.

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Analytical methods provide a global context from which to understand the dynamics of stone spires, but computational and experimental methods are useful to predict more specific behavior of multiple block structures. In this paper, the spire of St. Mary Magdalene church in Waltham-on-the-Wolds, UK, which was damaged in the 2008 Lincolnshire Earthquake, is used as a case study. Both a physical model and a discrete element computational model of the spire were created and used to investigate collapse under constant horizontal acceleration, impulse base motion, and earthquake ground motion. Results indicate that the global behavior compares well with analytical modeling, but local block displacements evident in DEM and experimental results also reduce the stability of the structure. In this context, the observed damage to St. Mary Magdalene church is evaluated and discussed. © 2012 Elsevier Ltd.

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An anomaly detection approach is considered for the mine hunting in sonar imagery problem. The authors exploit previous work that used dual-tree wavelets and fractal dimension to adaptively suppress sand ripples and a matched filter as an initial detector. Here, lacunarity inspired features are extracted from the remaining false positives, again using dual-tree wavelets. A one-class support vector machine is then used to learn a decision boundary, based only on these false positives. The approach exploits the large quantities of 'normal' natural background data available but avoids the difficult requirement of collecting examples of targets in order to train a classifier. © 2012 The Institution of Engineering and Technology.

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Innovation policies play an important role throughout the development process of emerging industries in China. Existing policy and industry studies view the emergence process as a black-box, and fail to understand the impacts of policy to the process along which it varies. This paper aims to develop a multi-dimensional roadmapping tool to better analyse the dynamics between policy and industrial growth for new industries in China. Through reviewing the emergence process of Chinese wind turbine industry, this paper elaborates how policy and other factors influence the emergence of this industry along this path. Further, this paper generalises some Chinese specifics for the policy-industry dynamics. As a practical output, this study proposes a roadmapping framework that generalises some patterns of policy-industry interactions for the emergence process of new industries in China. This paper will be of interest to policy makers, strategists, investors and industrial experts. Copyright © 2013 Inderscience Enterprises Ltd.

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The defect creation at low energy events was studied using density functional theory molecular dynamics simulations in silicon carbide nanotubes, and the displacement threshold energies determined exhibit a dependence on sizes, which decrease with decreasing diameter of the nanotubes. The Stone-Wales (SW) defect, which is a common defect configurations induced through irradiation in nanotubes, has also been investigated, and the formation energies of the SW defects increase with increasing diameter of the nanotubes. The mean threshold energies were found to be 23 and 18 eV for Si and C in armchair (5,5) nanotubes. (C) 2009 American Institute of Physics. [doi: 10.1063/1.3238307]

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In the light of descriptive geometry and notions in set theory, this paper re-defines the basic elements in space such as curve and surface and so on, presents some fundamental notions with respect to the point cover based on the High-dimension space (HDS) point covering theory, finally takes points from mapping part of speech signals to HDS, so as to analyze distribution information of these speech points in HDS, and various geometric covering objects for speech points and their relationship. Besides, this paper also proposes a new algorithm for speaker independent continuous digit speech recognition based on the HDS point dynamic searching theory without end-points detection and segmentation. First from the different digit syllables in real continuous digit speech, we establish the covering area in feature space for continuous speech. During recognition, we make use of the point covering dynamic searching theory in HDS to do recognition, and then get the satisfying recognized results. At last, compared to HMM (Hidden Markov models)-based method, from the development trend of the comparing results, as sample amount increasing, the difference of recognition rate between two methods will decrease slowly, while sample amount approaching to be very large, two recognition rates all close to 100% little by little. As seen from the results, the recognition rate of HDS point covering method is higher than that of in HMM (Hidden Markov models) based method, because, the point covering describes the morphological distribution for speech in HDS, whereas HMM-based method is only a probability distribution, whose accuracy is certainly inferior to point covering.

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This paper discusses the algorithm on the distance from a point and an infinite sub-space in high dimensional space With the development of Information Geometry([1]), the analysis tools of points distribution in high dimension space, as a measure of calculability, draw more attention of experts of pattern recognition. By the assistance of these tools, Geometrical properties of sets of samples in high-dimensional structures are studied, under guidance of the established properties and theorems in high-dimensional geometry.

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We show the four-dimensional Newton's constant obtained naturally from five-dimensional brane world with a tinily sloping extra dimension, which is independent of the bulk Weyl tensor. The corresponding universe is stiff fluid dominated when the slope of extra dimension is very small. Otherwise, the universe may be undergoing a self-acceleration at present epoch and have a decelerated phase in very recent past.

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Herein we report the spectroscopic, electrochemical, TEM and DLS characterizations Of C-60 supramolecular inclusion complexes with alpha-, beta- and gamma-cyclodextrins prepared using anionic C-60. The results indicate that the cyclodextrin itself has little effect on the encapsulated C-60 or on the properties of the inclusion complex. Instead, the cyclodextrin has a significant influence on the aggregation behavior of individual complex in aqueous solution, which in turn affects the property of the supramolecular complex of cyclodextrin and C-60 greatly, As the cavity dimension of cyclodextrin becomes smaller as it changes from gamma-CD to beta-CD, and finally to alpha-CD, it is observed that more aggregation occurs for the corresponding inclusion complex in aqueous solution.

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A new flow field was designed to search flow fields fitting polymer electrolyte membrane fuel cells (PEMFCs) better due its extensible. There are many independent inlets and outlets in the new flow field. The new flow field we named NINO can extend to be more general when pressures at the inlet and outlet vary and some usual flow fields will be obtained. A new mathematical model whose view angle is obverse is used to describe the flow field.