VisIVO - Integrated Tools and Services for Large-Scale Astrophysical Visualization

VisIVO is an integrated suite of tools and services specifically designed for the Virtual Observatory. This suite constitutes a software framework for effective visual discovery in currently available (and next-generation) very large-scale astrophysical datasets. VisIVO consists of VisiVO Desktop - a stand alone application for interactive visualization on standard PCs, VisIVO Server - a grid-enabled platform for high performance visualization and VisIVO Web - a custom designed web portal supporting services based on the VisIVO Server functionality. The main characteristic of VisIVO is support for high-performance, multidimensional visualization of very large-scale astrophysical datasets. Users can obtain meaningful visualizations rapidly while preserving full and intuitive control of the relevant visualization parameters. This paper focuses on newly developed integrated tools in VisIVO Server allowing intuitive visual discovery with 3D views being created from data tables. VisIVO Server can be installed easily on any web server with a database repository. We discuss briefly aspects of our implementation of VisiVO Server on a computational grid and also outline the functionality of the services offered by VisIVO Web. Finally we conclude with a summary of our work and pointers to future developments

Adaptive mesh and geodesically sliced Schwarzschild spacetime in 3+1 dimensions

We present first results obtained with a 3+1 dimensional adaptive mesh code in numerical general relativity. The adaptive mesh is used in conjunction with a standard ADM code for the evolution of a dynamically sliced Schwarzschild spacetime (geodesic slicing). We argue that adaptive mesh is particularly natural in the context of general relativity, where apart from adaptive mesh refinement for numerical efficiency one may want to use the built in flexibility to do numerical relativity on coordinate patches.Comment: 21 pages, LaTeX, 7 figures included with eps

Non-axisymmetric instabilities in self-gravitating tori around black holes, and solving Einstein constraints with superconvergent finite element methods

This thesis contains results on two related projects. In the first project, we explore non-axisymmetric instabilities in general relativistic accretion disks around black holes. Such disks are created as transient structures in several astrophysical scenarios, including mergers of compact objects and core collapse of massive stars. These disks are suggested for the role of cenral engines of gamma-ray bursts. We address the stability of these objects against the runaway and non-axisymmetric instabilities in the three-dimensional hydrodynamical fully general relativistic treatment. We explore three slender and moderately slender disk models with varying disk-to-black hole mass ratio. None of the models that we consider develop the runaway instability during the time span of the simulations, despite large radial axisymmetric oscillations, induced in the disks by the initial data construction procedure. All models develop unstable non-axisymmetric modes on a dynamical timescale. In simulations with dynamical general relativistic treatment, we observe two distinct types of instabilities: the Papaloizou-Pringle instability and the so-called Intermediate instability. The development of the nonaxisymmetric mode with azimuthal number m=1 is enhanced by the outspiraling motion of the black hole. The overall picture of the unstable modes in our disk models is similar to the Newtonian case. In the second project, we experiment with solving the Einstein constraint equations using finite elements on semistructured triangulations of multiblock grids. We illustrate our approach with a simple example of Brill wave initial data, with the constraints reducing to a single linear elliptic equation for the conformal factor $\psi$. We use quadratic Lagrange elements on semi-structured simplicial meshes, obtained by triangulation of multi-block grids. In the case of uniform refinement the scheme is superconvergent at most mesh vertices, due to local symmetry of the finite element basis with respect to local spatial inversions. We show that in the superconvergent case subsequent unstructured mesh refinements do not improve the quality of our initial data. As proof of concept that this approach is feasible for generating multi-block initial data in three dimensions, we evolve the constructed initial data using a high order finite-differencing multi-block approach and extract gravitational waves from the numerical solution

GRChombo : Numerical Relativity with Adaptive Mesh Refinement

In this work, we introduce GRChombo: a new numerical relativity code which incorporates full adaptive mesh refinement (AMR) using block structured Berger-Rigoutsos grid generation. The code supports non-trivial "many-boxes-in-many-boxes" mesh hierarchies and massive parallelism through the Message Passing Interface (MPI). GRChombo evolves the Einstein equation using the standard BSSN formalism, with an option to turn on CCZ4 constraint damping if required. The AMR capability permits the study of a range of new physics which has previously been computationally infeasible in a full 3+1 setting, whilst also significantly simplifying the process of setting up the mesh for these problems. We show that GRChombo can stably and accurately evolve standard spacetimes such as binary black hole mergers and scalar collapses into black holes, demonstrate the performance characteristics of our code, and discuss various physics problems which stand to benefit from the AMR technique.Comment: 48 pages, 24 figure

Image-based Modeling of Flow through Porous Media: Development of Multiscale Techniques for the Pore Level

Increasingly, imaging technology allows porous media problems to be modeled at microscopic and sub-microscopic levels with finer resolution. However, the physical domain size required to be representative of the media prohibits comprehensive micro-scale simulation. A hybrid or multiscale approach is necessary to overcome this challenge. In this work, a technique was developed for determining the characteristic scales of porous materials, and a multiscale modeling methodology was developed to better understand the interaction/dependence of phenomena occurring at different microscopic scales. The multiscale method couples microscopic simulations at the pore and sub-pore scales. Network modeling is a common pore-scale technique which employs severe assumptions, making it more computationally efficient than direct numerical simulation, enabling simulation over larger length scales. However, microscopic features of the medium are lost in the discretization of a material into a network of interconnected pores and throats. In contrast, detailed microstructure and flow patterns can be captured by modern meshing and direct numerical simulation techniques, but these models are computationally expensive. In this study, a data-driven multiscale technique has been developed that couples the two types of models, taking advantage of the benefits of each. Specifically, an image-based physically-representative pore network model is coupled to an FEM (finite element method) solver that operates on unstructured meshes capable of resolving details orders of magnitude smaller than the pore size. In addition to allowing simulation at multiple scales, the current implementation couples the models using a machine learning approach, where results from the FEM model are used to learn network model parameters. Examples of the model operating on real materials are given that demonstrate improvements in network modeling enabled by the multiscale framework. The framework enables more advanced multiscale and multiphysics modeling – an application to particle straining problems is shown. More realistic network filtration simulations are possible by incorporating information from the sub-pore-scale. New insights into the size exclusion mechanism of particulate filtration were gained in the process of generating data for machine learning of conductivity reduction due to particle trapping. Additional tests are required to validate the multiscale network filtration model, and compare with experimental findings in literature

Performance analysis of a runner for gravitational water vortex power plant

This research article published by Wiley & Sons Ltd, 2022Micro-hydropower can be used to meet the needs of both isolated and rural com munities for electricity. Due to its inexpensive initial investment, simple design, easy maintenance and low-head utilisation, the gravitational water vortex power plant (GWVPP) has recently piqued interest. The findings of numerical work employing a numerical simulation and analytical approach for the GWVPP are presented in this study. To understand the influence of each on the efficiency of GWVPP, four parameters (speed, hub-blade angle, number of blades and run ner profile) were explored. Design-Expert software was used to investigate the interplay of each parameter/factor in order to maximise the contribution of each. Design-Optimal Expert's (custom) design tool was used to construct twenty-four experimental runs. To calculate the system efficiency, these runs were simulated in commercial computational fluid dynamics (CFD) software called Ansys CFX. The numerical results were in good agreement with the experimental results, which yieldedR2 values of 0.9507 and0.9603 forflat andcurvedprofiles,respectively.Furthermore, the findings show that the chosen parameters have an impact on the GWVPP's efficiency via interaction as seen in response surface methodology (RSM). Furthermore, numerical analysis increased the curved blade profile runner's total efficiency by 3.65%. In compari son with the unoptimised scenarios, the efficiency of the flat runner profile increased by 1.69%