Flow visualization in turbulent free convection over horizontal smooth and grooved surfaces

The present paper discusses the flow visualization for turbulent free convection in a tank of water with the bottom surface being a smooth or a grooved surface and the top of the water surface exposed to ambient. The grooved surface is of parallel 90 degrees V-grooves with groove height of 10 mm and groove width of 20 mm. The experiment is carried out with aspect ratio (AR) of 2.9 and Rayleigh number (Ra) in the range, 1.3 x 10(7) - 4 x 10(7). Here AR is the aspect ratio (= width of fluid layer/height of fluid layer). Heat flux at the bottom surface is from electrical heating. From the pH-dye visualization, interesting flow structures are observed and these structures are analyzed with the help of plumes dynamics and temperature variations with time. (C) 2011 Elsevier Ltd. All rights reserved.

High speed digital holographic interferometry for hypersonic flow visualization

Optical imaging techniques have played a major role in understanding the flow dynamics of varieties of fluid flows, particularly in the study of hypersonic flows. Schlieren and shadowgraph techniques have been the flow diagnostic tools for the investigation of compressible flows since more than a century. However these techniques provide only the qualitative information about the flow field. Other optical techniques such as holographic interferometry and laser induced fluorescence (LIF) have been used extensively for extracting quantitative information about the high speed flows. In this paper we present the application of digital holographic interferometry (DHI) technique integrated with short duration hypersonic shock tunnel facility having 1 ms test time, for quantitative flow visualization. Dynamics of the flow fields in hypersonic/supersonic speeds around different test models is visualized with DHI using a high-speed digital camera (0.2 million fps). These visualization results are compared with schlieren visualization and CFD simulation results. Fringe analysis is carried out to estimate the density of the flow field.

Reliable Validation Based on Optical Flow Visualization for CFD Simulations

A reliable validation based on the optical flow visualization for numerical simulations of complex flowfields is addressed in this paper. Several test cases, including two-dimensional, axisymmetric and three-dimensional flowfields, were presented to demonstrate the effectiveness of the validation and gain credibility of numerical solutions of complex flowfields. In the validation, images of these flowfields were constructed from numerical results based on the principle of the optical flow visualization, and compared directly with experimental interferograms. Because both experimental and numerical results are of identical physical representation, the agreement between them can be evaluated effectively by examining flow structures as well as checking discrepancies in density. The study shows that the reliable validation can be achieved by using the direct comparison between numerical and experiment results without any loss of accuracy in either of them.

Flow Visualization with Quantified Spatial and Temporal Errors Using Edge Maps

Robust analysis of vector fields has been established as an important tool for deriving insights from the complex systems these fields model. Traditional analysis and visualization techniques rely primarily on computing streamlines through numerical integration. The inherent numerical errors of such approaches are usually ignored, leading to inconsistencies that cause unreliable visualizations and can ultimately prevent in-depth analysis. We propose a new representation for vector fields on surfaces that replaces numerical integration through triangles with maps from the triangle boundaries to themselves. This representation, called edge maps, permits a concise description of flow behaviors and is equivalent to computing all possible streamlines at a user defined error threshold. Independent of this error streamlines computed using edge maps are guaranteed to be consistent up to floating point precision, enabling the stable extraction of features such as the topological skeleton. Furthermore, our representation explicitly stores spatial and temporal errors which we use to produce more informative visualizations. This work describes the construction of edge maps, the error quantification, and a refinement procedure to adhere to a user defined error bound. Finally, we introduce new visualizations using the additional information provided by edge maps to indicate the uncertainty involved in computing streamlines and topological structures.

A Kinetostatic Formulation for Load-Flow Visualization in Compliant Mechanisms

Load flow visualization, which is an important step in structural and machine assembly design may aid in the analysis and eventual synthesis of compliant mechanisms. In this paper, we present a kineto-static formulation to visualize load flow in compliant mechanisms. This formulation uses the concept of transferred forces to quantify load flow from input to the output of a compliant mechanism. The magnitude and direction of load flow in the constituent members enables functional decomposition of the compliant mechanism into (i) Constraints (C): members that are constrained to deform in a particular direction and (ii) Transmitters (T): members that transmit load to the output. Furthermore, it is shown that a constraint member and an adjacent transmitter member can be grouped together to constitute a fundamental building block known as an CT set whose load flow behavior is maximally decoupled from the rest of the mechanism. We can thereby explain the deformation behavior of a number of compliant mechanisms from literature by visualizing load flow, and identifying building blocks.

Flow visualization and gas density measurement in rarefied gas flow

Mode of access: Internet.

Neutron-mapping polymer flow: Scattering, flow visualization, and molecular theory

Flows of complex fluids need to be understood at both macroscopic and molecular scales, because it is the macroscopic response that controls the fluid behavior, but the molecular scale that ultimately gives rise to rheological and solid-state properties. Here the flow field of an entangled polymer melt through an extended contraction, typical of many polymer processes, is imaged optically and by small-angle neutron scattering. The dual-probe technique samples both the macroscopic stress field in the flow and the microscopic configuration of the polymer molecules at selected points. The results are compared with a recent tube model molecular theory of entangled melt flow that is able to calculate both the stress and the single-chain structure factor from first principles. The combined action of the three fundamental entangled processes of reptation, contour length fluctuation, and convective constraint release is essential to account quantitatively for the rich rheological behavior. The multiscale approach unearths a new feature: Orientation at the length scale of the entire chain decays considerably more slowly than at the smaller entanglement length.

Constriction flows of monodisperse linear entangled polymers: Multiscale modeling and flow visualization

We explore both the rheology and complex flow behavior of monodisperse polymer melts. Adequate quantities of monodisperse polymer were synthesized in order that both the materials rheology and microprocessing behavior could be established. In parallel, we employ a molecular theory for the polymer rheology that is suitable for comparison with experimental rheometric data and numerical simulation for microprocessing flows. The model is capable of matching both shear and extensional data with minimal parameter fitting. Experimental data for the processing behavior of monodisperse polymers are presented for the first time as flow birefringence and pressure difference data obtained using a Multipass Rheometer with an 11:1 constriction entry and exit flow. Matching of experimental processing data was obtained using the constitutive equation with the Lagrangian numerical solver, FLOWSOLVE. The results show the direct coupling between molecular constitutive response and macroscopic processing behavior, and differentiate flow effects that arise separately from orientation and stretch. (c) 2005 The Society of Rheology.

Opacity optimization and inertial particles in flow visualization

Otto-von-Guericke-Universität Magdeburg, Fakultät für Informatik, Dissertation, 2016

ANALYSIS AND VISUALIZATION OF FLOW FIELDS USING INFORMATION-THEORETIC TECHNIQUES AND GRAPH-BASED REPRESENTATIONS

Three-dimensional flow visualization plays an essential role in many areas of science and engineering, such as aero- and hydro-dynamical systems which dominate various physical and natural phenomena. For popular methods such as the streamline visualization to be effective, they should capture the underlying flow features while facilitating user observation and understanding of the flow field in a clear manner. My research mainly focuses on the analysis and visualization of flow fields using various techniques, e.g. information-theoretic techniques and graph-based representations. Since the streamline visualization is a popular technique in flow field visualization, how to select good streamlines to capture flow patterns and how to pick good viewpoints to observe flow fields become critical. We treat streamline selection and viewpoint selection as symmetric problems and solve them simultaneously using the dual information channel [81]. To the best of my knowledge, this is the first attempt in flow visualization to combine these two selection problems in a unified approach. This work selects streamline in a view-independent manner and the selected streamlines will not change for all viewpoints. My another work [56] uses an information-theoretic approach to evaluate the importance of each streamline under various sample viewpoints and presents a solution for view-dependent streamline selection that guarantees coherent streamline update when the view changes gradually. When projecting 3D streamlines to 2D images for viewing, occlusion and clutter become inevitable. To address this challenge, we design FlowGraph [57, 58], a novel compound graph representation that organizes field line clusters and spatiotemporal regions hierarchically for occlusion-free and controllable visual exploration. We enable observation and exploration of the relationships among field line clusters, spatiotemporal regions and their interconnection in the transformed space. Most viewpoint selection methods only consider the external viewpoints outside of the flow field. This will not convey a clear observation when the flow field is clutter on the boundary side. Therefore, we propose a new way to explore flow fields by selecting several internal viewpoints around the flow features inside of the flow field and then generating a B-Spline curve path traversing these viewpoints to provide users with closeup views of the flow field for detailed observation of hidden or occluded internal flow features [54]. This work is also extended to deal with unsteady flow fields. Besides flow field visualization, some other topics relevant to visualization also attract my attention. In iGraph [31], we leverage a distributed system along with a tiled display wall to provide users with high-resolution visual analytics of big image and text collections in real time. Developing pedagogical visualization tools forms my other research focus. Since most cryptography algorithms use sophisticated mathematics, it is difficult for beginners to understand both what the algorithm does and how the algorithm does that. Therefore, we develop a set of visualization tools to provide users with an intuitive way to learn and understand these algorithms.

Image based flow visualisation of experimental flow fields inside a gross pollutant trap

Typical flow fields in a stormwater gross pollutant trap (GPT) with blocked retaining screens were experimentally captured and visualised. Particle image velocimetry (PIV) software was used to capture the flow field data by tracking neutrally buoyant particles with a high speed camera. A technique was developed to apply the Image Based Flow Visualization (IBFV) algorithm to the experimental raw dataset generated by the PIV software. The dataset consisted of scattered 2D point velocity vectors and the IBFV visualisation facilitates flow feature characterisation within the GPT. The flow features played a pivotal role in understanding gross pollutant capture and retention within the GPT. It was found that the IBFV animations revealed otherwise unnoticed flow features and experimental artefacts. For example, a circular tracer marker in the IBFV program visually highlighted streamlines to investigate specific areas and identify the flow features within the GPT.