20 resultados para Feature scale simulation


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This paper presents a novel coarse-to-fine global localization approach inspired by object recognition and text retrieval techniques. Harris-Laplace interest points characterized by scale-invariant transformation feature descriptors are used as natural landmarks. They are indexed into two databases: a location vector space model (LVSM) and a location database. The localization process consists of two stages: coarse localization and fine localization. Coarse localization from the LVSM is fast, but not accurate enough, whereas localization from the location database using a voting algorithm is relatively slow, but more accurate. The integration of coarse and fine stages makes fast and reliable localization possible. If necessary, the localization result can be verified by epipolar geometry between the representative view in the database and the view to be localized. In addition, the localization system recovers the position of the camera by essential matrix decomposition. The localization system has been tested in indoor and outdoor environments. The results show that our approach is efficient and reliable. © 2006 IEEE.

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In this paper we shall discuss the use of the TSIM simulation software for modelling large-scale industrial processes. The discussion draws on our recent experience of modelling a large plant in the food-processing industry. We shall focus on those features of software organization and software engineering which proved to be particularly necessary for the execution of this project, and illustrate the extent to which the use of TISM facilitated the implementation of these features. We shall also make some general remarks about the 'life-cycle' of models resulting from projects of this kind.

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In this paper we explore the possibility of using the equations of a well known compact model for CMOS transistors as a parameterized compact model for a variety of FET based nano-technology devices. This can turn out to be a practical preliminary solution for system level architectural researchers, who could simulate behaviourally large scale systems, while more physically based models become available for each new device. We have used a four parameter version of the EKV model equations and verified that fitting errors are similar to those when using them for standard CMOS FET transistors. The model has been used for fitting measured data from three types of FET nano-technology devices obeying different physics, for different fabrication steps, and under different programming conditions. © 2009 IEEE NANO Organizers.

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There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame. This is because manually inspecting bridges is a time-consuming and costly task, and some state Departments of Transportation (DOT) cannot afford the essential costs and manpower. In this paper, a novel method that can detect large-scale bridge concrete columns is proposed for the purpose of eventually creating an automated bridge condition assessment system. The method employs image stitching techniques (feature detection and matching, image affine transformation and blending) to combine images containing different segments of one column into a single image. Following that, bridge columns are detected by locating their boundaries and classifying the material within each boundary in the stitched image. Preliminary test results of 114 concrete bridge columns stitched from 373 close-up, partial images of the columns indicate that the method can correctly detect 89.7% of these elements, and thus, the viability of the application of this research.

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Manually inspecting bridges is a time-consuming and costly task. There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame as some state DOTs cannot afford the essential costs and manpower. This paper presents a novel method that can detect bridge concrete columns from visual data for the purpose of eventually creating an automated bridge condition assessment system. The method employs SIFT feature detection and matching to find overlapping areas among images. Affine transformation matrices are then calculated to combine images containing different segments of one column into a single image. Following that, the bridge columns are detected by identifying the boundaries in the stitched image and classifying the material within each boundary. Preliminary test results using real bridge images indicate that most columns in stitched images can be correctly detected and thus, the viability of the application of this research.

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The performance of algebraic flame surface density (FSD) models has been assessed for flames with nonunity Lewis number (Le) in the thin reaction zones regime, using a direct numerical simulation (DNS) database of freely propagating turbulent premixed flames with Le ranging from 0.34 to 1.2. The focus is on algebraic FSD models based on a power-law approach, and the effects of Lewis number on the fractal dimension D and inner cut-off scale η i have been studied in detail. It has been found that D is strongly affected by Lewis number and increases significantly with decreasing Le. By contrast, η i remains close to the laminar flame thermal thickness for all values of Le considered here. A parameterisation of D is proposed such that the effects of Lewis number are explicitly accounted for. The new parameterisation is used to propose a new algebraic model for FSD. The performance of the new model is assessed with respect to results for the generalised FSD obtained from explicitly LES-filtered DNS data. It has been found that the performance of the most existing models deteriorates with decreasing Lewis number, while the newly proposed model is found to perform as well or better than the most existing algebraic models for FSD. © 2012 Mohit Katragadda et al.

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The diversity of non-domestic buildings at urban scale poses a number of difficulties to develop building stock models. This research proposes an engineering-based bottom-up stock model in a probabilistic manner to address these issues. School buildings are used for illustrating the application of this probabilistic method. Two sampling-based global sensitivity methods are used to identify key factors affecting building energy performance. The sensitivity analysis methods can also create statistical regression models for inverse analysis, which are used to estimate input information for building stock energy models. The effects of different energy saving measures are analysed by changing these building stock input distributions.

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A direct numerical simulation (DNS) database of freely propagating statistically planar turbulent premixed flames with a range of different turbulent Reynolds numbers has been used to assess the performance of algebraic flame surface density (FSD) models based on a fractal representation of the flame wrinkling factor. The turbulent Reynolds number Ret has been varied by modifying the Karlovitz number Ka and the Damköhler number Da independently of each other in such a way that the flames remain within the thin reaction zones regime. It has been found that the turbulent Reynolds number and the Karlovitz number both have a significant influence on the fractal dimension, which is found to increase with increasing Ret and Ka before reaching an asymptotic value for large values of Ret and Ka. A parameterisation of the fractal dimension is presented in which the effects of the Reynolds and the Karlovitz numbers are explicitly taken into account. By contrast, the inner cut-off scale normalised by the Zel'dovich flame thickness ηi/δz does not exhibit any significant dependence on Ret for the cases considered here. The performance of several algebraic FSD models has been assessed based on various criteria. Most of the algebraic models show a deterioration in performance with increasing the LES filter width. © 2012 Mohit Katragadda et al.

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Hybrid large-eddy type simulations for cold jet flows from a serrated nozzle are performed at an acoustic Mach number Ma ac = 0.9 and Re = 1.03×10 6. Since the solver being used tends towards having dissipative qualities, the subgrid scale (SGS) model is omitted, giving a numerical type LES (NLES) or implicit LES (ILES) reminiscent procedure. To overcome near wall streak resolution problems a near wall RANS (Reynolds averaged Navier-Stokes) model is smoothly blended to the LES making a hybrid RANS-ILES. The geometric complexity of the serrated nozzle is fully considered without simplification or emulation. An improved but still modest hexahedral multi-block grid with circa 20 million grid points (with respect to 12.5 million in Xia et al.; Int J Heat Fluid Flow 30:1067-1079, 2009) is used. Despite the modest grid size, encouraging and improved results are obtained. Directly resolved mean and second-order fluctuating quantities along the jet centerline and in the jet shear layer compare favorably with measurements. The radiated far-field sound predicted using the Ffowcs Williams and Hawkings (FW-H) surface integral method shows good agreement with the measurements in directivity and sound spectra. © 2011 Springer Science+Business Media B.V.

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Computations are made for chevron and coflowing jet nozzles. The latter has a bypass ratio of 6:1. Also, unlike the chevron nozzle, the core flow is heated, making the inlet conditions reminiscent of those for a real engine. A large-eddy resolving approach is used with circa 12 × 10 6 cell meshes. Because the codes being used tend toward being dissipative the subgrid scale model is abandoned, giving what can be termed numerical large-eddy simulation. To overcome near-wall modeling problems a hybrid numerical large-eddy simulation-Reynolds-averaged Navier-Stokes related method is used. For y + ≤ 60 a Reynolds-averaged Navier-Stokes model is used. Blending between the two regions makes use of the differential Hamilton-Jabobi equation, an extension of the eikonal equation. For both nozzles, results show encouraging agreement with measurements of other workers. The eikonal equation is also used for ray tracing to explore the effect of the mean flow on acoustic ray trajectories, thus yielding a coherent solution strategy. © 2011 by Cambridge University.

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Computations are made of a short cowl coflowing jet nozzle with a bypass ratio 8 : 1. The core flow is heated, making the inlet conditions reminiscent of those for a real engine. A large eddy resolving approach is used with a 12 × 106 cell mesh. Since the code being used tends towards being dissipative the sub-grid scale (SGS) model is abandoned giving what can be termed Numerical Large Eddy Simulation (NLES). To overcome near wall modelling problems a hybrid NLES-RANS (Reynolds Averaged Navier-Stokes) related method is used. For y+ ≤ 60 a κ-l model is used. Blending between the two regions makes use of the differential Hamilton-Jabobi (HJ) equation, an extension of the eikonal equation. Results show encouraging agreement with existing measurements of other workers. The eikonal equation is also used for acoustic ray tracing to explore the effect of the mean flow on acoustic ray trajectories, thus yielding a coherent solution strategy. Copyright © 2011 by ASME.

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Measurements and predictions are made of a short-cowl coflowing jet with a bypass ratio of 8:1. The Reynolds number is 300,000, and the inlet Mach numbers are representative of aeroengine conditions. The low Reynolds number of the measurements makes the case well suited to the assessment of large-eddy-simulation-related strategies. The nozzle concentricity is carefully controlled to deal with the emerging metastability issues of jets with coflow. Measurements of mean quantities and turbulence statistics are made using both laser Doppler anemometry and particle image velocimetry. The simulations are completed on 6× 106, 12× 106, and 50 × 106 cell meshes. To overcome near-wall modeling problems, a hybrid large-eddy-simulation-Reynolds-averaged-Navier-Stokesrelated method is used. The near-wall Reynolds-averaged-Navier-Stokes layer is helpful in preventing nonphysical separation from the nozzle wall.Copyright © 2010 by the American Institute of Aeronautics and Astronautics, Inc.