Image based flow visualization for curved surfaces

We present a technique for direct visualization of unsteady flow on surfaces from computational fluid dynamics. The method generates dense representations of time-dependent vector fields with high spatio-temporal correlation using both Lagrangian-Eulerian advection and image based flow visualization as its foundation. While the 3D vector fields are associated with arbitrary triangular surface meshes, the generation and advection of texture properties is confined to image space. Frame rates of up to 20 frames per second are realized by exploiting graphics card hardware. We apply this algorithm to unsteady flow on boundary surfaces of, large, complex meshes from computational fluid dynamics composed of more than 250,000 polygons, dynamic meshes with time-dependent geometry and topology, as well as medical data.

We propose unsteady flow advection-convolution (UFAC) as a novel visualization approach for unsteady flows. It performs time evolution governed by pathlines, but builds spatial correlation according to instantaneous streamlines whose spatial extent is controlled by the flow unsteadiness. UFAC is derived from a generic framework that provides spacetime-coherent dense representations of time dependent-vector fields by a two-step process: 1) construction of continuous trajectories in spacetime for temporal coherence; and 2) convolution along another set of paths through the above spacetime for spatially correlated patterns. Within the framework, known visualization techniques-such as Lagrangian-Eulerian advection, image-based flow visualization, unsteady flow LIC, and dynamic LIC-can be reproduced, often with better image quality, higher performance, or increased flexibility of the visualization style. Finally, we present a texture-based discretization of the framework and its interactive implementation on graphics hardware, which allows the user to gradually balance visualization speed against quality.

A flow visualization-based investigation of the transition of planar submerged water jet shear layers at moderate Reynolds number is presented. The development of the free shear layers under low level artificial excitation was captured on video tape by dye injection flow visualization. Despite “clean” initial conditions and the imposition of periodic excitation, examination of vortex trajectories revealed that the flow structure was not strictly periodic but exhibited “jitter” in the vortex roll-up location and subsequent vortex interaction events. This study focuses on this non-periodic character of the flow. Since even very simple nonlinear systems can exhibit chaotic behavior, the flow visualization images were examined for evidence of whether the observed non-periodic behavior could be associated with chaos. The flow visualization frames were utilized to derive return maps enabling examination of the flow visualization images in pseudo phase space. Results indicate that many aspects of the non-periodic vortical motion show evidence of chaos similar to that exhibited by lower dimension nonlinear dynamical systems.

Automatic path planning for high performance measurement by laser plane sensors

3D-Particle Tracking Velocimetry (PTV) is one of the most flexible techniques for flow measurement, which allows the determination of three-dimensional velocity fields. Research activities in this field performed by the Institute of Geodesy and Photogrammetry at ETH Zurich for more than a decade have reached a status of an operational and reliable measurement method used in hydrodynamics and space applications. The method is based on the visualization of a flow with small, neutrally buoyant particles and recording of particle image sequences with 3-4 CCD cameras. In cooperation with the Institute of Hydromechanics and Water Resources Management at ETH Zurich further progress has been achieved in the improvement of the existing hardand software solutions. Regarding the algorithmic aspect of the method a new spatiotemporal matching method was developed, implemented and tested on different data sets. In former implementations the determination of the 3D particle positions was separated from the tracking of each particle, while the new method uses a combination of image and object space based information to establish spatio-temporal correspondences between particle positions of consecutive time steps. A system based on 4 CCD cameras is capable of tracking up to 1000 particles at video frequency (25Hz) with a relative accuracy of the velocity vectors of approximately 1:4000 of the field of view. The latest developments of the algorithmic aspects of 3D PTV are described and some examples of the successful application of the method are given in this paper. INTRODUCTION The 3D PTV is a technique for the determination of 3D velocity fields in flows. The existing 3D PTV solution developed at the Institute of Geodesy and Photogrammetry applying a object space based tracking algorithm should be improved in a way that the redundant information in image and object space is exploited more efficiently. The use of image and object space based information in combination with a prediction of the particle motion was thought to lead to enhanced results in the velocity field determination. The most important result to be expected from this work is a substantial increase of the tracking rate in 3D PTV. This is of importance mainly in the context of a Lagrangian analysis of particle trajectories, which can be considered the actual domain of the technique. Long trajectories are an absolute requisite for a Lagrangian flow analysis, as integral time and length scales can only be determined if long correlation lengths have been recorded. In addition, the number of simultaneous trajectories should be large enough to form a sufficient basis for a statistical analysis. Due to interruptions of particle trajectories caused by unsolved ambiguities the number of long trajectories decreases exponentially with the trajectory length. Very long trajectories over hundred and more time instances can so far only be determined if the probability of ambiguities is reduced by a low seeding density, thus concurrently reducing the spatial resolution of the system and the basis for a statistical analysis. A reduction of the trajectory interruptions due to unsolved ambiguities can multiply the yield of long trajectories and thus the usefulness of the results of 3D PTV, which further enlarges the application potential of the technique. Within the framework of a research project of the Swiss National Science Foundation a new spatio-temporal matching algorithm was developed and implemented. The technique has reached a status of an operational and reliable measurement tool used in hydrodynamics and space applications (Becker et al, 1995, Maas et al, 1997, Willneff and Maas, 2000). NOMENCLATURE XO,YO, ZO: 3D coordinates of projective center O Xi,Yi, Zi: 3D coordinates of object point Pi xi, yi: Image coordinates of Pi c: Principle distance of the camera xh, yh: Coordinates of the principle point ω, φ, κ: Rotation angles of the direction of the optical axis Drot: Rotation matrix as function of the rotation angles ω, φ, κ aij: Elements of 3x3 rotation matrix ti: Time step of image sequence

Spatial operators used in unstructured finite volume flow solvers are analysed for accuracy using Taylor series expansion and Fourier analysis. While approaching second-order accuracy on very regular grids, operators in common use are shown to have errors resulting in accuracy of only first-, zeroth- or even negative-order on three-dimensional tetrahedral meshes. A technique using least-squares optimization is developed to design improved operators on arbitrary meshes. This is applied to the fourth-order edge sum smoothing operator. The improved numerical dissipation leads to a much more accurate prediction of the Strouhal number for two-dimensional flow around a cylinder and a reduction of a factor of three in the loss coefficient for inviscid flow over a three-dimensional hump. Copyright © 2001 John Wiley & Sons, Ltd.

This paper presents an overview of the research project “High-Performance Hybrid Simulation/Measurement-Based Tools for Proactive Operator Decision-Support”, performed under the auspices of the U.S. Department of Energy grant DE-OE0000628. The objective of this project is to develop software tools to provide enhanced real-time situational awareness to support the decision making and system control actions of transmission operators. The integrated tool will combine high-performance dynamic simulation with synchrophasor measurement data to assess in real time system dynamic performance and operation security risk. The project includes: (i) The development of high-performance dynamic simulation software; (ii) the development of new computationally effective measurement-based tools to estimate operating margins of a power system in real time using measurement data from synchrophasors and SCADA; (iii) the development a hybrid framework integrating measurement-based and simulation-based approaches, and (iv) the use of cutting-edge visualization technology to display various system quantities and to visually process the results of the hybrid measurement-base/simulation-based security-assessment tool. Parallelization and high performance computing are utilized to enable ultrafast transient stability analysis that can be used in a real-time environment to quickly perform “what-if” simulations involving system dynamics phenomena. EPRI's Extended Transient Midterm Simulation Program (ETMSP) is modified and enhanced for this work. The contingency analysis is scaled for large-scale contingency analysis using MPI-based parallelization. Simulations of thousands of contingencies on a high performance computing machine are performed, and results show that parallelization over contingencies with MPI provides good scalability and computational gains. Different ways to reduce the I/O bottleneck have been also exprored. Thread-parallelization of the sparse linear solve is explored also through use of the SuperLU_MT library. Based on performance profiling results for the implicit method, the majority of CPU time is spent on the integration steps. Hence, in order to further improve the ETMSP performance, a variable time step control scheme for the original trapezoidal integration method has been developed and implemented. The Adams-Bashforth-Moulton predictor-corrector method was introduced and designed for ETMSP. Test results show superior performance with this method.

Indirect illumination plays an important role in global illumination. However, computing indirect illumination is a time-consuming process and needs to be approximated to achieve interactive performance. Indirect illumination varies rather slowly across the surface. This leads to the idea of computing indirect illumination sparsely in the scene and interpolating the result. This paper presents a hierarchical structure, which enables efficient sampling. The hierarchy is constructed in the image space by exploiting coherences among the screen-space pixels. From the hierarchy, samples are chosen, each of which represents a group of coherent pixels. This paper presents two methods of utilizing the samples for indirect lighting computation. The methods produce plausible lighting results and show high performances. The proposed algorithms run entirely in the image space and are easy to implement in contemporary graphic hardware.

In this paper it is argued that the Brownian image model is the least committed, scale invariant, statistical image model which describes the second order statistics of natural images. Various properties of three different types of Gaussian image models (white noise, Brownian and fractional Brownian images) will be discussed in relation to linear scale-space theory, and it will be shown empirically that the second order statistics of natural images mapped into jet space may, within some scale interval, be modeled by the Brownian image model. This is consistent with the 1/f2 power spectrum law that apparently governs natural images. Furthermore, the distribution of Brownian images mapped into jet space is Gaussian and an analytical expression can be derived for the covariance matrix of Brownian images in jet space. This matrix is also a good approximation of the covariance matrix of natural images in jet space. The consequence of these results is that the Brownian image model can be used as a least committed model of the covariance structure of the distribution of natural images.

Needle-based interventions are pervasive treatments in Minimally Invasive Surgery (MIS), which can be used in a number of diagnostic and therapeutic procedures, including biopsy, radioactive seed implantation, delivery of therapeutic agents, and thermal therapy. Intra-operative medical imaging promises high precision and improved workflow for interventional procedures, by offering intuitive anatomic structure of the tissue in situ. Magnetic Resonance Image (MRI) can provide high quality, real time, high soft tissue contrast imaging without ionizing radiation, and therefore is an ideal guidance tool for image-guided therapy (IGT). To date, a variety of robotic devices for image-guided interventional procedures have been developed such as these described in [1–4]. However, most of these devices are driven manually or by the actuators that are not compatible with MRI, and thus not suitable for MRI-guided therapy.In this study, we designed and evaluated a compact, reconfigurable MRI-compatible needle driver, using modular design approach, to support various needle-based interventions (e.g. straight needle insertion, asymmetric tip-based needle steering, and concentric-tube needle deployment). Integrated with an imaging coordinate registration fiducial frame concentric with the needle, the needle driver could be visualized and localized in the image space directly, and therefore enable the real-time MRI-guided percutaneous interventions with high precision and reliability.A modular design approach is utilized in the design of the needle driver to enable universal and multipurpose needle intervention. This driver is designed to couple with an existing base platform described in [5], or a variety of other existing and yet to be developed platforms such as [6]. The needle driver consists of multiple actuation units, which are essentially identical and have independent, decoupled motion, as show in Fig. 1. Each individual actuation unit drives a single needle, cannula, or tube, and offers 2 degrees of freedom (DOF) motion - 1 DOF linear translation and 1 DOF axial rotation, as show in Fig. 2. The actuation units ride on a common lead screw and linear guide which is firmly fixed on the base, and the nut is rotated by a timing belt drive mechanism, enabling linear translation (DOF #1). The needle clamping mechanism is attached to a pulley which is driven by similar timing belt drive mechanism, implementing axial rotation of the tube (DOF #2). The needle is gripped by a universal collet supporting varying sizes of standard needles from 25 Gauge (0.51 mm) to 16 Gauge (1.65 mm). An insert may be used to ensure sterility of all needle-contacting components. An eccentric belt tensioner is utilized to adjust the center distance between the motor and the tube clamping mechanism, by twisting the motor housing to varying angles with respect to the tube clamping mechanism, and thus guarantee the effective and smooth power transmission [5]. Nonconductive materials were utilized to build the majority of the components of the needle driver, non-ferrous aluminum is chosen for linear guide and lead screw, which require high stiffness, to maintain MRI compatibility. Piezoelectric motors (PiezoMotor actuators, Uppsala, Sweden) are selected as the actuators, for its high accuracy, dynamic performance and robustness as well as MRI compatibility utilizing the custom-developed MRI-compatible piezoelectric drive system described in [7]. Optical encoders with shielded, filtered differential signaling (US Digital, Vancouver, Washington) are utilized as the position feedback sensors.The most import feature of the design is modularity, which makes it possible to readily add more concentric needles, tubes, or cannulas, and thus enables more complex controlled motion profiles for procedures such as biopsy, brachytherapy, interstitial ablation, and concentric-tube needle deployment. The needle driver can also potentially be lengthened or shortened based on the requirement of specific applications, by modifying the length of lead screw and linear guide.To register the robot to the patient coordinate system in the MR image space, a compact cylindrical helix imaging coordinate registration fiducial frame is designed and integrated in this needle driver such that its axis is concentric with the needle base. The mathematical model of this new fiducial frame design is developed and evaluated in [8]. With compact size (37 mm OD, 30 mm long), the tubular shaped fiducial frame is particularly suitable for attaching to the distal end of the needle, to offer direct visualization and localization from in situ MR imaging. In this design, the fiducial frame is attached concentrically with the axis of the first actuation unit such that it translates and rotates with the needle synchronously.To validate the feasibility and evaluate the accuracy of this design, individual joint space accuracy tests and phantom experiments were performed. In the process of test, individual joints were set to 10 target positions driven by the robot controller, and a digital dial gauge was used to measure the actual position. An 18G Nitinol tube was placed in the needle driver and inserted into a gelatin phantom to validate the motion performance and driving power of the needle driver.The prototype needle driver is shown in Fig. 3 with two actuation units (total of 4-DOF). The dimensions of individual actuation units are 73×116×96 mm, and the overall dimensions of the needle driver set are 300×116×96 mm. In this configuration with two actuation units, the needle driver set is able to offer a 130 mm linear translation and 360 degrees axial rotation for each needle or tube attached. The RMS accuracy for the individual joints was determined to be 0.18 mm (SD = 0.17 mm), which is clinically sufficient for most needle-based interventional therapy. During the phantom experiments, the needle proved to be capable of deploying the tube to arbitrary target points within its workspace freely, with no stall. MRI compatibility has been previously demonstrated for equivalent system architecture in [5,7].A modular design approach is employed in this compact needle driver to control delivery of various tubular shaped surgical tools, including straight needle insertion, asymmetric tip needle steering or compensation, and concentric-tube deployment. Integrated with a concentric compact fiducial frame, the robot can be visualized and localized in the MRI image space directly and in a real-time fashion, and thus potentially improve the workflow and enhance the accuracy of the surgery. The accuracy evaluation test demonstrates a 0.18 mm RMS error for individual joints, indicating a clinically satisfactory result.In the future work, the accuracy of the full multi-DOF needle driver set will be evaluated in tissue using real-time MR image-guidance. The needle driver may be useful for various needle-based interventional surgeries, including prostate biopsy, brachytherapy as well as stereotactic neurosurgery.

In this paper, we firstly propose an art style classification system based on the RNN model to study the development of the art industry, and continuously fine-tune this white noise image according to the long and short-term memory network and gated recurrent unit network until it makes this white noise image similar to the artwork image style, and the ink painting image feature extraction is mainly studied from the recurrent neural network based ink style feature extraction and the overall nested edge based The two aspects of brushstroke feature extraction based on overall nested edge detection are studied. Then, based on the art industry and big data, the ink painting style classification system is constructed, and the effectiveness of the system is verified by model art classification effect analysis. The results show that the RNN performs well on the face dataset, where the accuracy of multiple classifications up to 10 categories is above 85%. This indicates that the RNN model in this paper can maintain good performance in the ink painting art classification task.

Multiple smoke wires are used to investigate the secondary flow near the endwall of a plane cascade with blade shapes used in high-performance turbine stages. The wires are positioned parallel to the endwall and ahead of the cascade, within and outside the endwall boundary layer. The traces of the smoke generated by the wires are visualized with a laser light sheet illuminating various cross sections around the cascade. During the experiment, a periodically fluctuating horseshoe vortex system of varying number of vortices is observed near the leading edge of the cascade. A series of photographs and video tapes was taken in the cascade to trace these vortices. The development and evolution of the horseshoe vortex and the passage vortex are clearly resolved in the photographs. The interation between the suction side leg of the horseshoe vortex and the passage vortex is also observed in the experiment. A vortex induced by the passage vortex, starting about one-fourth of the curvilinear distance along the blade on the suction surface, is also found. This vortex stays close to the suction surface and above the passage vortex in the laminar flow region on the blade. From this flow visualization, a model describing the secondary flows in a cascade is proposed and compared with previous published models. Some naphthalene mass transfer results from a blade near an endwall are cited and compared with the current model. The flows inferred from the two techniques are in good agreement.

SUMMARYThis paper reports the design of sliding-mode control laws for controlling multiple small-sized autonomous helicopters in arbitrary formations. Two control schemes, which are required for defining arbitrary three-dimensional formation meshes, are discussed. In the presented leader–follower formation control schemes, each helicopter only needs to receive motion information from at most two neighboring helicopters. A nonlinear six-degree-of-freedom dynamic model has been used for each helicopter. Four control inputs, the main and the tail rotor thrusts, and the roll and pitch moments, are assumed. Parameter uncertainty in the dynamic model and wind disturbance are considered in designing the controllers. The effectiveness and robustness of these control laws in the presence of parameter uncertainty in the dynamic model and wind disturbances are demonstrated by computer simulations.

High-order discretization techniques offer the potential to significantly reduce the computational costs necessary to obtain accurate predictions when compared to lower-order methods. However, efficient, universallyapplicable, high-order discretizations remain somewhat illusive, especially for more arbitrary unstructured meshes and for large-eddy simulation (LES) of turbulent reacting flows. A novel, high-order, central essentially non-oscillatory (CENO), cell-centered, finite-volume scheme is proposed for the solution of the conservation equations of turbulent, reactive, low speed flows on three-dimensional unstructured meshes. The proposed scheme is applied to the pseudo-compressibility formulation of the Favre-filtered governing equations and the resulting discretized equations are solved with a parallel implicit Newton-Krylov algorithm. Temporal derivatives are discretized using the family of high-order backward difference formulas (BDF) and the resulting equations are solved via a dual-time stepping approach. Large-eddy simulations of a laboratory-scale turbulent flame is carried out and the proposed finite-volume scheme is validated against experimental measurements. The high-order scheme is demonstrated to provide both reliable and accurate solutions for complex turbulent reactive flows.

Numerical evaluation of 3-D SIF for arbitrary finite element meshes