Visualization of Input Parameters for Stream and Pathline Seeding

Uncertainty arises in all stages of the visualization pipeline. However, the majority of flow visualization applications convey no uncertainty information to the user. In tools where uncertainty is conveyed, the focus is generally on data, such as error that stems from numerical methods used to generate a simulation or on uncertainty associated with mapping visualiza-tion primitives to data. Our work is aimed at another source of uncertainty - that associated with user-controlled input param-eters. The navigation and stability analysis of user-parameters has received increasing attention recently. This work presents an investigation of this topic for flow visualization, specifically for three-dimensional streamline and pathline seeding. From a dynamical systems point of view, seeding can be formulated as a predictability problem based on an initial condition. Small perturbations in the initial value may result in large changes in the streamline in regions of high unpredictability. Analyzing this predictability quantifies the perturbation a trajectory is subjugated to by the flow. In other words, some predictions are less certain than others as a function of initial conditions. We introduce novel techniques to visualize important user input parameters such as streamline and pathline seeding position in both space and time, seeding rake position and orientation, and inter-seed spacing. The implementation is based on a metric which quantifies similarity between stream and pathlines. This is important for Computational Fluid Dynamics (CFD) engineers as, even with the variety of seeding strategies available, manual seeding using a rake is ubiquitous. We present methods to quantify and visualize the effects that changes in user-controlled input parameters have on the resulting stream and pathlines. We also present various visualizations to help CFD scientists to intuitively and effectively navigate this parameter space. The reaction from a domain expert in fluid dynamics is also reported. - See more at: http://thesai.org/Publications/ViewPaper?Volume=6&Issue=4&Code=IJACSA&SerialNo=17#sthash.PNlUBslJ.dpu

A motif-based approach to network epidemics

Networks have become an indispensable tool in modelling infectious diseases, with the structure of epidemiologically relevant contacts known to affect both the dynamics of the infection process and the efficacy of intervention strategies. One of the key reasons for this is the presence of clustering in contact networks, which is typically analysed in terms of prevalence of triangles in the network. We present a more general approach, based on the prevalence of different four-motifs, in the context of ODE approximations to network dynamics. This is shown to outperform existing models for a range of small world networks

Computational Fluid Dynamics and Visualisation of Coastal Flows in Tidal Channels Supporting Ocean Energy Development

Flow characteristics in coastal regions are strongly influenced by the topography of the seabed and understanding the fluid dynamics is necessary before installation of tidal stream turbines (TST). In this paper, the bathymetry of a potential TST deployment site is used in the development of the a CFD (Computational Fluid Dynamics) model. The steady state k-ϵ and transient Large Eddy Simulation (LES) turbulence methods are employed and compared. The simulations are conducted with a fixed representation of the ocean surface, i.e., a rigid lid representation. In the vicinity of Horse Rock a study of the pressure difference shows that the small change in height of the water column is negligible, providing confidence in the simulation results. The stream surface method employed to visualise the results has important inherent characteristics that can enhance the visual perception of complex flow structures. The results of all cases are compared with the flow data transect gathered by an Acoustic Doppler Current Profiler (ADCP). It has been understood that the k-ϵ method can predict the flow pattern relatively well near the main features of the domain and the LES model has the ability to simulate some important flow patterns caused by the bathymetry

Absence of Evidence of Rift Valley Fever Infection in Eulemur fulvus (Brown Lemur) in Mayotte During an Interepidemic Period.

The potential role of Eulemur fulvus (brown lemur) in the epidemiology of Rift Valley fever (RVF) in Mayotte, during an interepidemic period, was explored. In February and March 2016, 72 animals were blood sampled and tested for RVF. No evidence of RVF genome or antibodies was found in the samples. The role of other wild mammals on the island should, however, be further investigated

A Comparison of Numerical Modelling Techniques for Tidal Stream Turbine Analysis

To fully understand the performance of tidal stream turbines for the development of ocean renewable energy, a range of computational models is required. We review and compare results from several models of horizontal axis turbines at different spatial scales. Models under review include blade element momentum theory (BEMT), blade element actuator disk, Reynolds averaged Navier Stokes (RANS) CFD (BEM-CFD), blade-resolved moving reference frame and coastal models based on the shallow water equations. To evaluate the BEMT, a comparison is made to experiments with three different rotors. We demonstrate that, apart from the near-field wake, there are similarities in the results between the BEM-CFD approach and a coastal area model using a simplified turbine fence at a headland case

Surface-Based Flow Visualization

With increasing computing power, it is possible to process more complex fluid simulations. However, a gap between increasing data size and our ability to visualize them still remains. Despite the great amount of progress that has been made in the field of flow visualization over the last two decades, a number of challenges remain. Whilst the visualization of 2D flow has many good solutions, the visualization of 3D flow still poses many problems. Challenges such as domain coverage, speed of computation, and perception remain key directions for further research. Flow visualization with a focus on surface-based techniques forms the basis of this literature survey, including surface construction techniques and visualization methods applied to surfaces. We detail our investigation into these algorithms with discussions of their applicability and their relative strengths and drawbacks. We review the most important challenges when considering such visualizations. The result is an up-to-date overview of the current state-of-the-art that highlights both solved and unsolved problems in this rapidly evolving branch of research.Keywords: Flow visualization, Survey, Surface

Comparison of ADCP observations and 3D model simulations of turbulence at a tidal energy site

Field measurement of turbulence in strong tidal currents is difficult and expensive, but the tidal energy industry needs to accurately quantify turbulence for adequate resource characterisation and device design. Models that can predict such turbulence could reduce measurement costs. We compare a Regional Ocean Modelling System (ROMS) simulation with acoustic Doppler current profiler (ADCP) measurements from a highly-energetic tidal site. This comparison shows the extent to which turbulence can be quantified by ROMS, using the conventional k−ε turbulence closure model. Both model and observations covered the same time period, encompassing two spring-neap cycles. Turbulent kinetic energy (TKE) density was calculated from measurements using the variance method; turbulent dissipation, ε, was calculated using the structure function method. Measurements show that wave action dominates turbulent fluctuations in the upper half of the water column; comparing results for deeper water, however, shows very strong agreement. A best fit between ROMS and ADCP results for mean velocity yields R2=0.98; for TKE, R2 is 0.84 when strongly wave-dominated times are excluded. Dissipation agrees less well: although time series of ε are well-correlated at similar depths, ROMS estimates a greater magnitude of dissipation than is measured, by a factor of up to 4.8

Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach

Rift Valley fever (RVF) is a major zoonotic and arboviral hemorrhagic fever. The conditions leading to RVF epidemics are still unclear, and the relative role of climatic and anthropogenic factors may vary between ecosystems. Here, we estimate the most likely scenario that led to RVF emergence on the island of Mayotte, following the 2006–2007 African epidemic. We developed the first mathematical model for RVF that accounts for climate, animal imports and livestock susceptibility, which is fitted to a 12-years dataset. RVF emergence was found to be triggered by the import of infectious animals, whilst transmissibility was approximated as a linear or exponential function of vegetation density. Model forecasts indicated a very low probability of virus endemicity in 2017, and therefore of re-emergence in a closed system (i.e. without import of infected animals). However, the very high proportion of naive animals reached in 2016 implies that the island remains vulnerable to the import of infectious animals. We recommend reinforcing surveillance in livestock, should RVF be reported is neighbouring territories. Our model should be tested elsewhere, with ecosystem-specific data

Ground water and climate change

As the world’s largest distributed store of fresh water, ground water plays a central part in sustaining ecosystems and enabling human adaptation to climate variability and change. The strategic importance of ground water for global water and food security will probably intensify under climate change as more frequent and intense climate extremes (droughts and floods) increase variability in precipitation, soil moisture and surface water. Here we critically review recent research assessing the impacts of climate on ground water through natural and human-induced processes as well as through groundwater-driven feedbacks on the climate system. Furthermore, we examine the possible opportunities and challenges of using and sustaining groundwater resources in climate adaptation strategies, and highlight the lack of groundwater observations, which, at present, limits our understanding of the dynamic relationship between ground water and climate