Relevant bibliographies by topics / Tensor Field Visualization

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Tensor Field Visualization'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Tensor Field Visualization"

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Guoning Chen, Darrel Palke, Zhongzang Lin, Harry Yeh, Paul Vincent, Robert S. Laramee, and Eugene Zhang. "Asymmetric Tensor Field Visualization for Surfaces." IEEE Transactions on Visualization and Computer Graphics 17, no. 12 (December 2011): 1979–88. http://dx.doi.org/10.1109/tvcg.2011.170.

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Bi, Chongke, Lu Yang, Yulin Duan, and Yun Shi. "A survey on visualization of tensor field." Journal of Visualization 22, no. 3 (March 22, 2019): 641–60. http://dx.doi.org/10.1007/s12650-019-00555-8.

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Zhang, Eugene, James Hays, and Greg Turk. "Interactive Tensor Field Design and Visualization on Surfaces." IEEE Transactions on Visualization and Computer Graphics 13, no. 1 (January 2007): 94–107. http://dx.doi.org/10.1109/tvcg.2007.16.

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Hesselink, L., F. H. Post, and J. J. van Wijk. "Research issues in vector and tensor field visualization." IEEE Computer Graphics and Applications 14, no. 2 (March 1994): 76–79. http://dx.doi.org/10.1109/38.267477.

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Dick, C., J. Georgii, R. Burgkart, and R. Westermann. "Stress Tensor Field Visualization for Implant Planning in Orthopedics." IEEE Transactions on Visualization and Computer Graphics 15, no. 6 (November 2009): 1399–406. http://dx.doi.org/10.1109/tvcg.2009.184.

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Raith, Felix, Christian Blecha, Thomas Nagel, Francesco Parisio, Olaf Kolditz, Fabian Gunther, Markus Stommel, and Gerik Scheuermann. "Tensor Field Visualization using Fiber Surfaces of Invariant Space." IEEE Transactions on Visualization and Computer Graphics 25, no. 1 (January 2019): 1122–31. http://dx.doi.org/10.1109/tvcg.2018.2864846.

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Liang, Xundong, Bin Li, and Shenquan Liu. "Three-dimensional vector field visualization based on tensor decomposition." Journal of Computer Science and Technology 11, no. 5 (September 1996): 452–60. http://dx.doi.org/10.1007/bf02947212.

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McGraw, Tim, Takamitsu Kawai, Inas Yassine, and Lierong Zhu. "Visualizing High-Order Symmetric Tensor Field Structure with Differential Operators." Journal of Applied Mathematics 2011 (2011): 1–27. http://dx.doi.org/10.1155/2011/142923.

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The challenge of tensor field visualization is to provide simple and comprehensible representations of data which vary both directionallyandspatially. We explore the use of differential operators to extract features from tensor fields. These features can be used to generate skeleton representations of the data that accurately characterize the global field structure. Previously, vector field operators such as gradient, divergence, and curl have previously been used to visualize of flow fields. In this paper, we use generalizations of these operators to locate and classify tensor field degenerate points and to partition the field into regions of homogeneous behavior. We describe the implementation of our feature extraction and demonstrate our new techniques on synthetic data sets of order 2, 3 and 4.
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Zhu, Yang-Ming, and Paul A. Farrell. "A vector grouping algorithm for liquid crystal tensor field visualization." Liquid Crystals 29, no. 10 (October 2002): 1259–64. http://dx.doi.org/10.1080/713935624.

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Caldwell, T. Grant, and Hugh M. Bibby. "The instantaneous apparent resistivity tensor: a visualization scheme for LOTEM electric field measurements." Geophysical Journal International 135, no. 3 (December 1998): 817–34. http://dx.doi.org/10.1046/j.1365-246x.1998.00668.x.

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Dissertations / Theses on the topic "Tensor Field Visualization"

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Gerrits, Tim Stefan Verfasser], and Holger [Gutachter] [Theisel. "Visualization of second-order-tensor data and vector field ensembles / Tim Stefan Gerrits ; Gutachter: Holger Theisel." Magdeburg : Universitätsbibliothek Otto-von-Guericke-Universität, 2021. http://d-nb.info/1234654989/34.

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Leonel, Gildo de Almeida. "Método para visualização de campos tensoriais tridimensionais baseado em rastreamento de partículas." Universidade Federal de Juiz de Fora (UFJF), 2011. https://repositorio.ufjf.br/jspui/handle/ufjf/3525.

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Campos tensoriais arbitrários são úteis em diversas áreas do conhecimento como a física, engenharias e áreas da saúde. Um dos principais interesses de profissionais destas áreas é a investigação de objetos colineares e coplanares representados pelos tensores. Esses objetos são formados por subconjuntos estruturados de tensores presentes no campo e que capturam alguma continuidade geométrica. Pela sua natureza multivariada, a visualização de elementos organizados é uma tarefa desafiadora. Geralmente, utilizam-se métodos de detecção direta destas estruturas para que o observador possa analisá-las. A proposta desta dissertação é explorar o fato de que o movimento estimula percepções complexas de forma inata no sistema visual humano. A abordagem desenvolvida utiliza um sistema de rastreamento de partículas e é parametrizado por campos tensoriais de forma que o comportamento das partículas represente as características do campo e tenha um aprimoramento que possibilite o melhor entendimento e a interpretação da informação proveniente dos tensores.
Arbitrary tensor fields are useful in several areas as physics, engineering and medicine. The investigation of collinear and coplanar objects represented by tensors is the main focus of research in these areas. These objects are formed by structured tensorial fields which captures some geometric continuity. The visualization of strutured elements is a challenging task because of their multivariate nature. To be analysed by the user, direct methods are usually used for detecting these structures. The proposal of this dissertation is to explore the fact that movement increases the perception of complex shapes, that are observed in a innate form by the human visual system. The approach developed uses a particle tracing system and is parameterized by tensor fields, so the particles flow represents the characteristics of the field and make an improvement that enables better understanding and interpretation of information derived from tensors.
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Zhu, Lierong. "Topological visualization of tensor fields using a generalized Helmholtz decomposition." Morgantown, W. Va. : [West Virginia University Libraries], 2010. http://hdl.handle.net/10450/10962.

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Thesis (M.S.)--West Virginia University, 2010.
Title from document title page. Document formatted into pages; contains viii, 75 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 72-75).
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Souza, Filho José Luiz Ribeiro de. "Visualização de campos tensoriais utilizando simulação lagrangeana de fluidos." Universidade Federal de Juiz de Fora (UFJF), 2013. https://repositorio.ufjf.br/jspui/handle/ufjf/4786.

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CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Análise e visualização de campos tensoriais simétricos de segunda ordem é um pro blema desafiador, pois eles geralmente representam dados multivariados. Trabalhos nessa área utilizam de diferentes estratégias para tornar perceptíveis propriedades desejadas dos campos. Essas propriedades são, por exemplo, estruturas colineares e coplanares. Em casos como campos tensoriais que representam tecidos orgânicos obtidos por ressonância magnética, ressaltar essas estruturas pode ser útil para a área médica de diagnóstico e neurociência por exemplo. Um tipo específico de visualização consiste na observação da propagação de partículas sobre os campos. Mas, grande parte desses métodos não des creve interações entre partículas e são estáticos. Essa dissertação propõe um método que induz o sistema perceptual humano a perceber de forma mais intuitiva essas estruturas, utilizando dinâmica de fluidos. Foram propostas modificações de uma implementação específica das Equações de Navier-Stokes, chamada Hidrodinâmica de Partículas Suavi zadas (SPH). Diferente de outras abordagens, o modelo proposto explora interação entre partículas para ressaltar a percepção de estruturas subjacentes no campo tensorial. Foi proposta uma força externa para manter partículas em regiões de interesse e também a aplicação de uma distorção na função núcleo, ambas baseadas nas informações dos tenso res. A distorção faz com que as partículas se alinhem de acordo com estruturas colineares e coplanares consecutivas do campo, exibindo continuidades e também conectividades.
Analysis and visualization of symmetric second order tensor fields are challenging since they generally represent multivariate data. Works in this area use different approaches to enhance desired properties of the field. Those properties are, for example, colinear and coplanar structures. In some cases, such as tensor fields obtained by magnetic resonance imaging of organic tissues, highlighting those structures can be useful for studies in neu roscience and diagnostics, for example. A specific technique of visualization consists in observing particles’ trajectories along the field. But, most of those methods are static and does not present interaction between particles. This work proposes a method that induces the human perceptual system to visualize more intuitively those structures, using fluid dynamics. Modifications in a specific implementation of Navier-Stokes equations, called Smoothed Particle Hydrodynamics (SPH) were proposed. Different from other ap proaches, interactions between particles are used to enhance the perception of underlying structures in a tensor field. It was also proposed an external force to keep particles around areas of interest and a distortion in the kernel functions, both based on tensors’ informa tion.The distortion forces particles to align according to consecutive colinear and coplanar structures of a field, showing continuities and connectivities.
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Benger, Werner. "Visualization of general relativistic tensor fields via a fiber bundle data model /." Berlin : Lehmanns Media-LOB.de, 2005. http://deposit.ddb.de/cgi-bin/dokserv?id=2669729&prov=M&dok_var=1&dok_ext=htm.

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Kratz, Andrea [Verfasser]. "Three-Dimensional Second-Order Tensor Fields: Exploratory Visualization and Anisotropic Sampling / Andrea Kratz." Berlin : Freie Universität Berlin, 2013. http://d-nb.info/1036872785/34.

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Auer, Cornelia [Verfasser]. "Visualization of fundamental structures in two dimensional second order tensor fields on planar and curved surfaces / Cornelia Auer." Berlin : Freie Universität Berlin, 2014. http://d-nb.info/1053326599/34.

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Eichelbaum, Sebastian. "Image Space Tensor Field Visualization Using a LIC-like Method." 2009. https://ul.qucosa.de/id/qucosa%3A16526.

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Tensors are of great interest to many applications in engineering and in medical imaging, but a proper analysis and visualization remains challenging. Physics-based visualization of tensor fields has proven to show the main features of symmetric second-order tensor fields, while still displaying the most important information of the data, namely the main directions in medical diffusion tensor data using texture and additional attributes using color-coding, in a continuous representation. Nevertheless, its application and usability remains limited due to its computational expensive and sensitive nature. We introduce a novel approach to compute a fabric-like texture pattern from tensor fields on arbitrary non-selfintersecting surfaces that is motivated by image space line integral convolution (LIC). Our main focus lies on regaining three-dimensionality of the data under user interaction, such as rotation and scaling. We employ a multi-pass rendering approach to estimate proper modification of the LIC noise input texture to support the three-dimensional perception during user interactions.
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Eichelbaum, Sebastian, Mario Hlawitschka, Bernd Hamann, and Gerik Scheuermann. "Image-space Tensor Field Visualization Using a LIC-like Method." 2012. https://ul.qucosa.de/id/qucosa%3A32504.

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Tensors are of great interest to many applications in engineering and in medical imaging, but a proper analysis and visualization remains challenging. Physics-based visualization of tensor fields has proven to show the main features of symmetric second-order tensor fields, while still displaying the most important information of the data, namely the main directions in medical diffusion tensor data using texture and additional attributes using color-coding, in a continuous representation. Nevertheless, its application and usability remains limited due to its computational expensive and sensitive nature. We introduce a novel approach to compute a fabric-like texture pattern from tensor fields motivated by image-space line integral convolution (LIC). Although, our approach can be applied to arbitrary, non-selfintersecting surfaces, we are focusing on special surfaces following neural fibers in the brain.We employ a multipass rendering approach whose main focus lies on regaining three-dimensionality of the data under user interaction as well as being able to have a seamless transition between local and global structures including a proper visualization of degenerated points.
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Eichelbaum, Sebastian, Mario Hlawitschka, Bernd Hamann, and Gerik Scheuermann. "Fabric-like Visualization of Tensor Field Data on Arbitrary Surfaces in Image Space." 2012. https://ul.qucosa.de/id/qucosa%3A32502.

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Tensors are of great interest to many applications in engineering and in medical imaging, but a proper analysis and visualization remains challenging. It already has been shown that, by employing the metaphor of a fabric structure, tensor data can be visualized precisely on surfaces where the two eigendirections in the plane are illustrated as thread-like structures. This leads to a continuous visualization of most salient features of the tensor data set. We introduce a novel approach to compute such a visualization from tensor field data that is motivated by image-space line integral convolution (LIC). Although our approach can be applied to arbitrary, non-selfintersecting surfaces, the main focus lies on special surfaces following important features, such as surfaces aligned to the neural pathways in the human brain. By adding a postprocessing step, we are able to enhance the visual quality of the of the results, which improves perception of the major patterns.
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Books on the topic "Tensor Field Visualization"

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Laidlaw, David, and Joachim Weickert, eds. Visualization and Processing of Tensor Fields. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-88378-4.

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Weickert, Joachim, and Hans Hagen, eds. Visualization and Processing of Tensor Fields. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-31272-2.

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David, Laidlaw, Weickert Joachim, Polthier Konrad, Johnson Christopher R, Hoffman David, Hege Hans-Christian 1954-, Rumpf Martin, and SpringerLink (Online service), eds. Visualization and Processing of Tensor Fields: Advances and Perspectives. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009.

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Laidlaw, David H. New Developments in the Visualization and Processing of Tensor Fields. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Laidlaw, David H., and Anna Vilanova, eds. New Developments in the Visualization and Processing of Tensor Fields. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27343-8.

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Inc, ebrary, ed. Visualization of fields and applications in engineering. Chichester [England]: Wiley, 2011.

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United States. National Aeronautics and Space Administration., ed. Visualization of 3-D tensor fields. Stanford, Calif: Stanford University, 1996.

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United States. National Aeronautics and Space Administration., ed. Visualization of 3-D tensor fields. Stanford, Calif: Stanford University, 1996.

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Hagen, Hans, and Joachim Weickert. Visualization and Processing of Tensor Fields. Springer, 2014.

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United States. National Aeronautics and Space Administration., ed. Visualization of 3-D tensor fields. Stanford, Calif: Stanford University, 1996.

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Book chapters on the topic "Tensor Field Visualization"

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McGraw, Tim. "Tensor Field Visualization." In Encyclopedia of Computer Graphics and Games, 1–9. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-08234-9_96-1.

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Lin, Zhongzang, Harry Yeh, Robert S. Laramee, and Eugene Zhang. "2D Asymmetric Tensor Field Topology." In Mathematics and Visualization, 191–204. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23175-9_13.

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Weickert, Joachim, and Martin Welk. "Tensor Field Interpolation with PDEs." In Mathematics and Visualization, 315–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-31272-2_19.

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Pajevic, Sinisa, Akram Aldroubi, and Peter J. Basser. "Continuous Tensor Field Approximation of Diffusion Tensor MRI data." In Mathematics and Visualization, 299–314. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-31272-2_18.

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Zhang, Eugene. "Tensor Field Design: Algorithms and Applications." In Mathematics and Visualization, 111–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27343-8_6.

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Wang, Bei, and Ingrid Hotz. "Robustness for 2D Symmetric Tensor Field Topology." In Mathematics and Visualization, 3–27. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61358-1_1.

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Hotz, Ingrid, Louis Feng, Hans Hagen, Bernd Hamann, and Kenneth Joy. "Tensor Field Visualization Using a Metric Interpretation." In Mathematics and Visualization, 269–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-31272-2_16.

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Zhang, Yue, Xiaofei Gao, and Eugene Zhang. "Applying 2D Tensor Field Topology to Solid Mechanics Simulations." In Mathematics and Visualization, 29–41. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61358-1_2.

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Eichelbaum, Sebastian, Mario Hlawitschka, Bernd Hamann, and Gerik Scheuermann. "Image-Space Tensor Field Visualization Using a LIC-like Method." In Mathematics and Visualization, 191–208. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-21608-4_11.

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Renhe, Marcelo Caniato, José Luiz de Souza Filho, Marcelo Bernardes Vieira, and Antonio Oliveira. "Tensor Field Visualization Using Eulerian Fluid Simulation." In Lecture Notes in Computer Science, 332–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39640-3_25.

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Conference papers on the topic "Tensor Field Visualization"

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Auer, Cornelia, Jens Kasten, Andrea Kratz, Eugene Zhang, and Ingrid Hotz. "Automatic, tensor-guided illustrative vector field visualization." In 2013 IEEE Pacific Visualization Symposium (PacificVis). IEEE, 2013. http://dx.doi.org/10.1109/pacificvis.2013.6596154.

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Zobel, Valentin, Markus Stommel, and Gerik Scheuermann. "Feature-based tensor field visualization for fiber reinforced polymers." In 2015 IEEE Scientific Visualization Conference (SciVis). IEEE, 2015. http://dx.doi.org/10.1109/scivis.2015.7429491.

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Mcgraw, Tim, and Mariappan Nadar. "FAST TEXTURE-BASED TENSOR FIELD VISUALIZATION FOR DT-MRI." In 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro. IEEE, 2007. http://dx.doi.org/10.1109/isbi.2007.356963.

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Penney, Devon, Jian Chen, and David H. Laidlaw. "Effects of illumination, texture, and motion on task performance in 3D tensor-field streamtube visualizations." In 2012 IEEE Pacific Visualization Symposium (PacificVis). IEEE, 2012. http://dx.doi.org/10.1109/pacificvis.2012.6183579.

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Nakayama, Katsuyuki, Kenji Umeda, Toshio Ichikawa, Teruyuki Nagano, and Hideyuki Sakata. "Visualization System of Swirl Motion." In 12th International Conference on Nuclear Engineering. ASMEDC, 2004. http://dx.doi.org/10.1115/icone12-49189.

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An instrumentation of system composed of experimental device and numerical analysis is presented to visualize flow and identify swirling motion. Experiment is performed with transparent material and PIV (Particle Image Velocimetry) instrumentation, by which velocity vector field is obtained. This vector field is then analyzed numerically by “swirling flow analysis”, which estimate its velocity gradient tensor and the corresponding eigenvalue (swirling function). As an instantaneous flow field in steady/unsteady states is captured by PIV, the flow field is analyzed, and existence of vortices or swirling motions and their locations are identified in spite of their size. In addition, intensity of swirling is evaluated. The analysis enables swirling motion to emerge, even though it is hidden in uniform flow and velocity filed does not indicate any swirling. This visualization system can be applied to investigate condition to control flow or design flow.
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Kobayashi, Yuto, Keita Takahashi, and Toshiaki Fujii. "From focal stacks to tensor display: A method for light field visualization without multi-view images." In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2017. http://dx.doi.org/10.1109/icassp.2017.7952508.

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Waterman, S., T. Holme, S. McIlwain, and A. Pollard. "Investigation of Various Structure Identification Methods and the Effects of Tabs on the Near Field of Round Jets." In ASME 2002 Joint U.S.-European Fluids Engineering Division Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/fedsm2002-31409.

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The effects of various combinations of vortex-generating tabs on the turbulence structures in the near-field of a round jet are investigated using LES simulation and flow visualization techniques. The visualization methods include stream-wise and non-streamwise vorticity, and a variety of methods that use the invariant of the velocity gradient tensor (the discriminant, Q value and the second eigenvalue condition). Integration of the LES data sets suggest that the structural changes as a result of introducing tabs is significant; however, the methods used to deduce these changes are not always consistent with one another. In some cases, one scheme will produce large amounts of background “noise” while others are less prone to this effect. It is concluded that qualitatively, the four tab case produces the greatest amount of small scale structure.
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Straccia, Mattia, Rodolfo Hofmann, and Volker Gümmer. "New Methods for Secondary Flow Phenomena Visualization and Analysis." In ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gt2019-91378.

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Abstract This work focuses on presenting new techniques for the visualization of Secondary Flow Phenomena (SFP) in transonic turbomachinery. Here, Rotor 37 has been used to develop and apply these techniques in order to study vortices, shocks and secondary flows. They are also used to provide a comparison between turbulence models in Ansys CFX environment, here the Spalart-Allmaras (SA) and Shear Stress Tensor (SST) turbulence models. The scope of this paper is to give an improved understanding of SFP and how their onset and evolution are influenced from the turbulence model. The analysis is based on results of three-dimensional steady-state RANS simulations, for operating points between design point and near-stall condition, achieved by varying the outlet static pressure radial equilibrium distribution at the rotor exit. The new visualization techniques highlight important flow field features less investigated in previous research works, in particular secondary weak strength vortices. They will give a better visualization of and insight to the interaction of the passage shock and the tip leakage vortex, the interaction between vortices and boundary layers and the interaction of the shock wave and endwall boundary layers.
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Ukeiley, L., D. Wick, and M. Glauser. "Coherent Structure Identification in a Lobed Mixer." In ASME 1991 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1991. http://dx.doi.org/10.1115/91-gt-307.

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The influence of large scale structures on the flow in a lobed mixer (a device utilized to enhance streamwise vorticity for increased mixing) is examined by a pseudo flow visualization method (v. Delville et al. 1988), and the Proper Orthogonal Decomposition (POD) (v. Lumley 1967). The pseudo flow visualization method utilizes specially designed hot wire rakes with high spatial resolution to provide the capability of plotting instantaneous velocity profiles. In this work, a rake of 15 hot wires is used to provide these profiles for a velocity ratio of 2:1, at several positions downstream of the lobed mixer. From these profiles a detailed description of the flow field is achieved. In particular, from this information, an idea of the spatial extent and shedding frequency of the large scale structures is determined. The shedding frequencies found are consistent with those found from spectral measurements. A one-dimensional version of the POD is then applied, which utilizes the measured streamwise velocity two-point correlation tensor. The pseudo flow visualization technique is then used to view the contribution from each proper orthogonal mode to the instantaneous signal and comparisons made to the full signal.
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10

Panigrahi, P. K. "PIV Investigation of Flow Behind Surface Mounted Detached Square Cylinder." In ASME 2006 2nd Joint U.S.-European Fluids Engineering Summer Meeting Collocated With the 14th International Conference on Nuclear Engineering. ASMEDC, 2006. http://dx.doi.org/10.1115/fedsm2006-98077.

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The flow field behind surface mounted detached square ribs over an approaching flat plate turbulent boundary layer has been studied. The Reynolds number based on the rib height has been set equal to 11075. The ratio of gap size from the flat plate surface to the square rib size has been varied between 0.2 and 1.0. The ratio of the approaching boundary layer thickness to the rib height is equal to 0.2. The PIV (2-component and stereo) technique in both stream wise and cross-stream measurement planes have been implemented. The PIV data has been acquired at two different resolutions. The high resolution measurements have been used to show the flow field at immediate downstream of the detached ribs. The oil flow visualization study has been carried out to relate the surface flow patterns to that of the flow structures. The mean and rms velocity field, average stream wise and span wise vorticity field, turbulent energy production and stream traces have been reported. The invariant of the velocity gradient tensor has been calculated to distinguish between the rotational and shear contribution of the vorticity field. The recirculation bubbles with foci like structure behind the detached ribs are displaced upward and its size drops with an increase in the gap size. The flow below the detached rib is film like flow for lower gap size leading to significant near wall modification of the flow structures. For higher gap size, the viscous effect predominates in the near wall region. The stream traces in the cross stream plane show additional node-saddle patterns in the near wall region indicating greater near wall flow structures and hence better mixing. The turbulence intensity, vorticity and velocity gradient tensor invariant results confirm the efficacy of the detached rib with smaller gap to cylinder size as an effective passive flow control tool for near wall mixing enhancement.
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Reports on the topic "Tensor Field Visualization"

1

Bajaj, Chandrajit L. Visualization and Querying of Scalar, Vector, and Tensor Field Data. Fort Belvoir, VA: Defense Technical Information Center, December 1997. http://dx.doi.org/10.21236/ada379438.

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