Numerical burnback analysis of three dimensional solid propellant grains

Download
2015
Ata, Yusuf
This study consists of developing of a three-dimensional grain burnback simulation with minimum distance method using STL (Standard Template Library) geometry output for accurate and efficient grain burnback analysis and internal ballistic solver for simulation and also prediction of solid rocket motor performance. In this work the, the new burnback simulation tool named F3DBT (Fast 3 Dimensional Burnback Tool) developed at the Propulsion System Design Department of Roketsan Missiles Industries Inc. and developed ballistic solver based on a steady quasi-zero dimensional model of the internal flow field conditions of solid rocket motors are presented. The main aim of the newly developed burnback simulation is to perform regression of all kind of grain geometries in short run time with more accurate results relative to other 3D burnback simulation tools. Moreover internal ballistic solver is developed in order to obtain burning area of propellant grain by using static firing data. The burnback analysis is compared with reference SRMs (Solid Rocket Motor) in terms of burning area. Finally the results obtained from static firings of the motor and obtained from numerical study are presented and discussed.

Suggestions

Ballistic design optimization of three-dimensional grains using genetic algorithms
Yücel, Osman; Aksel, Mehmet Haluk; Department of Mechanical Engineering (2012)
Within the scope of this thesis study, an optimization tool for the ballistic design of three-dimensional grains in solid propellant rocket motors is developed. The modeling of grain geometry and burnback analysis is performed analytically by using basic geometries like cylinder, cone, sphere, ellipsoid, prism and torus. For the internal ballistic analysis, a quasi-steady zero-dimensional flow solver is used. Genetic algorithms have been studied and implemented to the design process as an optimization algor...
Analysis of double-negative materials with surface integral equations and the multilevel fast multipole algorithm
Ergül, Özgür Salih (2011-08-13)
We present a fast and accurate analysis of double-negative materials (DNMs) with surface integral equations and the multilevel fast multipole algorithm (MLFMA). DNMs are commonly used as simplified models of metamaterials at resonance frequencies and are suitable to be formulated with surface integral equations. However, realistic metamaterials and their models are usually very large with respect to wavelength and their accurate solutions require fast algorithms, such as MLFMA. We consider iterative solutio...
Fast and accurate analysis of optical metamaterials using surface integral equations and the parallel multilevel fast multipole algorithm
Ergül, Özgür Salih (2013-09-13)
We present fast and accurate simulations of optical metamaterials using surface integral equations and the multilevel fast multipole algorithm (MLFMA). Problems are formulated with the electric and magnetic current combined-field integral equation and solved iteratively with MLFMA, which is parallelized using the hierarchical strategy on distributed-memory architectures. Realistic metamaterials involving dielectric, perfectly conducting, and plasmonic regions of finite extents are solved rigorously with the...
Discretization of Parametrizable Signal Manifolds
Vural, Elif (Institute of Electrical and Electronics Engineers (IEEE), 2011-12-01)
Transformation-invariant analysis of signals often requires the computation of the distance from a test pattern to a transformation manifold. In particular, the estimation of the distances between a transformed query signal and several transformation manifolds representing different classes provides essential information for the classification of the signal. In many applications, the computation of the exact distance to the manifold is costly, whereas an efficient practical solution is the approximation of ...
Distance-based discretization of parametric signal manifolds
Vural, Elif (2010-06-28)
The characterization of signals and images in manifolds often lead to efficient dimensionality reduction algorithms based on manifold distance computation for analysis or classification tasks. We propose in this paper a method for the discretization of signal manifolds given in a parametric form. We present an iterative algorithm for the selection of samples on the manifold that permits to minimize the average error in the manifold distance computation. Experimental results with image appearance manifolds d...
Citation Formats
Y. Ata, “Numerical burnback analysis of three dimensional solid propellant grains,” M.S. - Master of Science, Middle East Technical University, 2015.