Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-05T06:37:52.406Z Has data issue: false hasContentIssue false
  • English
  • Français

Adaptive Cloud Refinement (ACR) - Adaptation in Meshless Framework

Published online by Cambridge University Press:  20 August 2015

M. Somasekhar ,
S. Vivek ,
Keshav. S. Malagi ,
V. Ramesh  and
S. M. Deshpande
M. Somasekhar*
Affiliation:
CTFD, CSIR – National Aerospace Laboratories, Bangalore, India
S. Vivek*
Affiliation:
Dept. of Mechanical Engineering, Indian Institute of Technology Madras, Chennai, India
Keshav. S. Malagi*
Affiliation:
CTFD, CSIR – National Aerospace Laboratories, Bangalore, India
V. Ramesh*
Affiliation:
CTFD, CSIR – National Aerospace Laboratories, Bangalore, India
S. M. Deshpande*
Affiliation:
Engineering Mechanics Unit, JNCASR, Bangalore, India
*
Corresponding author.Email:[email protected]
Email:[email protected]
Email:[email protected]
Email:[email protected]
Email:[email protected]
Get access

Abstract

In the present work adaptation in meshless framework is proposed. The grid adaptation or mesh adaptation is quite well developed area in case of conventional grid based solvers and is popularly known as Adaptive mesh refinement (AMR). In such cases the adaptation is done by subdividing the cells or elements into finer cells or elements. In case of meshless methods there are no cells or elements but only a cloud of points. In this work we propose to achieve the meshless adaptation by locally refining the point density in the regions demanding higher resolution. This results into an adaptive enriched cloud of points. We call this method as Adaptive Cloud Refinement (ACR). The meshless solvers need connectivity information, which is a set of neighboring nodes. It is crucial part of meshless solvers. Obviously because of refining point density, the connectivity of nodes in such regions gets modified and hence has to be updated. An efficient connectivity update must exploit the fact that the node distribution would be largely unaffected except the region of adaptation. Hence connectivity updating needs to be done locally, only in these regions. In this paper we also present an extremely fast algorithm to update connectivity over adapted cloud called as ACU (Automatic Connectivity Update).

Keywords

76-0476M2565M50KFVSLSKUMmeshless methodsadaptationACRACU
Type
Research Article
Information
Communications in Computational Physics , Volume 11 , Issue 4 , April 2012 , pp. 1372 - 1385
Copyright
Copyright © Global Science Press Limited 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1]Berger, M.J., Colella, P., Local adaptive mesh refinement for shock hydrodynamics, J. Comput. Phys., 82, pp. 67–84, 1989.Google Scholar
[2]Lohner, R., Mesh adaptation in fluid mechanics, Eng. Fract. Mech., 50(5), pp. 819–847, 1995.Google Scholar
[3]Harish, G., Pavanakumar, M., Anandhanarayanan, K., Store separation dynamics using grid-free Euler solver, 24th Applied Aerodynamics Conference, AIAA 2006–3650, June 2006.Google Scholar
[4]Deshpande, S.M., Theory and Application of Kinetic Method to Aerospace CFD, Keynote lecture in East West Speed Flow Field Conference (EWSFF 2005), Beijing, Oct 19–22, 2005.Google Scholar
[5]Ramesh, V., Deshpande, S.M., Unsteady flow computations for flow past multiple moving boundaries using LSKUM, Comput. Fluids, 36(10), pp. 1592–1608, 2007.CrossRefGoogle Scholar
[6]Ghosh, A.K., Deshpande, S.M., Least squares kinetic upwind method for inviscid compressible flows, AIAA Paper 95–1735, 1995.Google Scholar
[7]Mandal, J.C., Deshpande, S.M., Kinetic flux vector splitting for Euler equations, Comput. Fluids, 23(2), pp. 447–478, 1994.Google Scholar
[8]Deshpande, S.M., Anandanarayanan, , Praveen, C., Ramesh, V., Theory and applications of 3-D LSKUM based on entropy variables, Int. J. Numer. Meth. Fluids, 40(1-2), pp. 47–62, 2002.Google Scholar
[9]Ramesh, V., Deshpande, S.M., Low dissipation grid free upwind kinetic scheme with modified CIR splitting, Fluid Mechanics Report, (2004), FM 20, Centre of Excellence in Aerospace CFD, Dept. of Aero. Eng., Indian Institute of Science, Bangalore.Google Scholar
[10]Arora, K., Rajan, N.K.S., Deshpande, S.M., Weighted Least Squares Kinetic Upwind Method (WLSKUM) for computation of flowthrough blade passage with Kinetic Periodic Boundary Condition (KPBC), CFD J., 16(3), pp. 31–48, 2005.Google Scholar
[11]Praveen, C., Ghosh, A.K., Deshpande, S.M., Positivity preservation, stencil selection and applications of LSKUM to 3-D inviscid flows, Comput. Fluids, 38(8), pp. 1481–1494, 2009.Google Scholar
[12]Ramesh, V., Least Squares Grid Free Kinetic Upwind Method, Ph.D Thesis, Indian Institute of Science, Bangalore, July 2001.Google Scholar
[13] AGARD-AR-211, Test cases for inviscid flow field methods.Google Scholar
[14]Raghavendra, N.V., D2-Distance bases 3-D Grid Adaptation for a Generic Fighter Aircraft Wing, ME Thesis, Indian Institute of Science, Bangalore, 2000.Google Scholar
[15]Wang, Z.J., A fast nested multi-grid viscous flow solver for adaptive Cartesian/Quad grids, Int. J. Numer. Meth. Fluids, 33, pp. 657–680, 2000.3.0.CO;2-G>CrossRefGoogle Scholar
[16]Kallinderis, Y., Kavouklis, C., A dynamic adaptation for general 3-D hybrid meshes, Comput. Meth. App. Mech. Eng., 194, pp. 5019–5050, 2005.Google Scholar
[17]Mavriplis, D.J., Adaptive meshing techniques for viscous flow calculations on mixed element unstructured meshes, Int. J. Numer. Meth. Fluids, 34, pp. 93–111, 2000.Google Scholar