Water facilities in retrospect and prospect: An illuminating tool for vehicle design

Water facilities play a fundamental role in the design of air, ground, and marine vehicles by providing a qualitative, and sometimes quantitative, description of complex flow phenomena. Water tunnels, channels, and tow tanks used as flow-diagnostic tools have experienced a renaissance in recent years in response to the increased complexity of designs suitable for advanced technology vehicles. These vehicles are frequently characterized by large regions of steady and unsteady three-dimensional flow separation and ensuing vortical flows. The visualization and interpretation of the complicated fluid motions about isolated vehicle components and complete configurations in a time and cost effective manner in hydrodynamic test facilities is a key element in the development of flow control concepts, and, hence, improved vehicle designs. A historical perspective of the role of water facilities in the vehicle design process is presented. The application of water facilities to specific aerodynamic and hydrodynamic flow problems is discussed, and the strengths and limitations of these important experimental tools are emphasized

Advanced Analysis Techniques for Intra-cardiac Flow Evaluation from 4D Flow MRI

Time-resolved 3D velocity-encoded MR imaging with velocity encoding in three directions (4D Flow) has emerged as a novel MR acquisition technique providing detailed information on flow in the cardiovascular system. In contrast to other clinically available imaging techniques such as echo-Doppler, 4D Flow MRI provides the 3D Flow velocity field within a volumetric region of interest over the cardiac cycle. This work reviews the most recent advances in the development and application of dedicated image analysis techniques for the assessment of intra-cardiac flow features from 4D Flow MRI.Novel image analysis techniques have been developed for extraction of relevant intra-cardiac flow features from 4D Flow MRI, which have been successfully applied in various patient cohorts and volunteer studies. Disturbed flow patterns have been linked with valvular abnormalities and ventricular dysfunction. Recent technical advances have resulted in reduced scan times and improvements in image quality, increasing the potential clinical applicability of 4D Flow MRI.4D Flow MRI provides unique capabilities for 3D visualization and quantification of intra-cardiac blood flow. Contemporary knowledge on 4D Flow MRI shows promise for further exploration of the potential use of the technique in research and clinical applications

Coronary CT angiography: Beyond morphological stenosis analysis

Rapid technological developments in computed tomography (CT) imaging technique have made coronary CT angiography an attractive imaging tool in the detection of coronary artery disease. Despite visualization of excellent anatomical details of the coronary lumen changes, coronary CT angiography does not provide hemodynamic changes caused by presence of plaques. Computational fluid dynamics (CFD) is a widely used method in the mechanical engineering field to solve complex problems through analysing fluid flow, heat transfer and associated phenomena by using computer simulations. In recent years, CFD is increasingly used in biomedical research due to high performance hardware and software. CFD techniques have been used to study cardiovascular hemodynamics through simulation tools to assist in predicting the behaviour of circulatory blood flow inside the human body. Blood flow plays a key role in the localization and progression of coronary artery disease. CFD simulation based on 3D luminal reconstructions can be used to analyse the local flow fields and flow profiling due to changes of vascular geometry, thus, identifying risk factors for development of coronary artery disease. The purpose of this article is to provide an overview of the coronary CT-derived CFD applications in coronary artery disease

Numerical experiments on turbulent flow using the random vortex method

Chorin's random vortex method is used to predict the growth of a large-scale coherent vortex structure in the early stages of the development of turbulence in a two-dimensional co-flowing shear layer. The numerical algorithm has been simplified to such an extent that the numerical analysis can be performed on a microcomputer. The numerical solution exhibits the same early turbulent instabilities and vorticity pairings as found in recent flow-visualization experiments. In addition the results are in reasonable agreement with experimental measurements of mean velocity, root mean square fluctuations and Reynolds stresses. One could thus test the shear layer sensitivity to initial conditions and the upsteam boundary conditions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/50096/1/1620240706_ftp.pd

Fine-grained traffic state estimation and visualisation

Tools for visualising the current traffic state are used by local authorities for strategic monitoring of the traffic network and by everyday users for planning their journey. Popular visualisations include those provided by Google Maps and by Inrix. Both employ a traffic lights colour-coding system, where roads on a map are coloured green if traffic is flowing normally and red or black if there is congestion. New sensor technology, especially from wireless sources, is allowing resolution down to lane level. A case study is reported in which a traffic micro-simulation test bed is used to generate high-resolution estimates. An interactive visualisation of the fine-grained traffic state is presented. The visualisation is demonstrated using Google Earth and affords the user a detailed three-dimensional view of the traffic state down to lane level in real time

Improving the Tractography Pipeline: on Evaluation, Segmentation, and Visualization

Recent advances in tractography allow for connectomes to be constructed in vivo. These have applications for example in brain tumor surgery and understanding of brain development and diseases. The large size of the data produced by these methods lead to a variety problems, including how to evaluate tractography outputs, development of faster processing algorithms for tractography and clustering, and the development of advanced visualization methods for verification and exploration. This thesis presents several advances in these fields. First, an evaluation is presented for the robustness to noise of multiple commonly used tractography algorithms. It employs a Monte–Carlo simulation of measurement noise on a constructed ground truth dataset. As a result of this evaluation, evidence for obustness of global tractography is found, and algorithmic sources of uncertainty are identified. The second contribution is a fast clustering algorithm for tractography data based on k–means and vector fields for representing the flow of each cluster. It is demonstrated that this algorithm can handle large tractography datasets due to its linear time and memory complexity, and that it can effectively integrate interrupted fibers that would be rejected as outliers by other algorithms. Furthermore, a visualization for the exploration of structural connectomes is presented. It uses illustrative rendering techniques for efficient presentation of connecting fiber bundles in context in anatomical space. Visual hints are employed to improve the perception of spatial relations. Finally, a visualization method with application to exploration and verification of probabilistic tractography is presented, which improves on the previously presented Fiber Stippling technique. It is demonstrated that the method is able to show multiple overlapping tracts in context, and correctly present crossing fiber configurations

ENHANCED NETWORK SLICING FOR INDUSTRIAL AND ENERGY PROTOCOLS

With the development of industry 4.0 and the recent evolution of the substation automation, as prescribed at least by the International Electrotechnical Commission (IEC) 61850 Standard, the network is becoming one of the key element of these trends. Network design and network architecture are becoming more and more complex and leading to challenging problems and issues, such as network security, multiplication of unmanaged broadcast domains, and bandwidth limitations. Recent tools have been introduced to help network engineers visualize different industrial Internet of Things (IIoT) protocol flows and characterizations for devices connected to the network. However, visualization is not enough and any help in the design and configuration of the network would be a great differentiator. Techniques herein provide for the ability to utilize sensors to build a network map of industrial and power data flows. The network map can then be used to configure different network slices with guaranteed bandwidth and flow isolation

Designing Improved Sediment Transport Visualizations

Monitoring, or more commonly, modeling of sediment transport in the coastal environment is a critical task with relevance to coastline stability, beach erosion, tracking environmental contaminants, and safety of navigation. Increased intensity and regularity of storms such as Superstorm Sandy heighten the importance of our understanding of sediment transport processes. A weakness of current modeling capabilities is the ability to easily visualize the result in an intuitive manner. Many of the available visualization software packages display only a single variable at once, usually as a two-dimensional, plan-view cross-section. With such limited display capabilities, sophisticated 3D models are undermined in both the interpretation of results and dissemination of information to the public. Here we explore a subset of existing modeling capabilities (specifically, modeling scour around man-made structures) and visualization solutions, examine their shortcomings and present a design for a 4D visualization for sediment transport studies that is based on perceptually-focused data visualization research and recent and ongoing developments in multivariate displays. Vector and scalar fields are co-displayed, yet kept independently identifiable utilizing human perception\u27s separation of color, texture, and motion. Bathymetry, sediment grain-size distribution, and forcing hydrodynamics are a subset of the variables investigated for simultaneous representation. Direct interaction with field data is tested to support rapid validation of sediment transport model results. Our goal is a tight integration of both simulated data and real world observations to support analysis and simulation of the impact of major sediment transport events such as hurricanes. We unite modeled results and field observations within a geodatabase designed as an application schema of the Arc Marine Data Model. Our real-world focus is on the Redbird Artificial Reef Site, roughly 18 nautical miles offshor- Delaware Bay, Delaware, where repeated surveys have identified active scour and bedform migration in 27 m water depth amongst the more than 900 deliberately sunken subway cars and vessels. Coincidently collected high-resolution multibeam bathymetry, backscatter, and side-scan sonar data from surface and autonomous underwater vehicle (AUV) systems along with complementary sub-bottom, grab sample, bottom imagery, and wave and current (via ADCP) datasets provide the basis for analysis. This site is particularly attractive due to overlap with the Delaware Bay Operational Forecast System (DBOFS), a model that provides historical and forecast oceanographic data that can be tested in hindcast against significant changes observed at the site during Superstorm Sandy and in predicting future changes through small-scale modeling around the individual reef objects