Abstract:
In this thesis we outline the formulation, implementation and validation of Adaptive
Particle Resolution (APR) in Smoothed Particle Hydrodynamics (SPH). Traditionally,
SPH systems are modelled with unifrom mass distribution, through our approach we in-
troduce a run time re nement and de-re nement algorithm for both 2D and 3D systems.
Each particle represents a mass of
uid in its local region. Particles are re ned into
several particles for ner sampling in regions of complex
ow. In regions of smooth
ow,
neighboring particles are merged. This new development o ers the capability of doing
multi-resolution simulations in SPH framework. We have implemented various kinds of
APR such as domain based, dynamic (based on the distance between solid and
uid
particles) or multiphase
ows in open channels and these implementations in the SPH
method provide a simple yet powerful framework for applications like o -shore structures
and reactor modelling In general, the current APR implementation can be applied for
simulating multiscale models or systems that develop a wide spectrum of length scales.
We have clearly shown the reduction in computational cost in the APR-SPH simulations
without losing the accuracy.
All of our simulations were run in single machine and multiple cores (shared memory).
A multi-machine approach is possible, but less e cient with the given memory archi-
tecture of the simulator. For further optimizations a review of the memory allocation
strategy in the simulator is required.
Description:
Increasing efficiency in a computational fluid dyanmics tool. Languages used: C++, Python, PvPython, Matlab