[Faculty] Fwd: [CSRC.COLLOQUIUM] "Quantifying Particle Departure from Axisymmetry in Multiphase Cylindrical Detonation"

[Jose Castillo]

Please note the chance of time and place

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DATE:  *Friday, May 10, 2019*


TITLE:


*Quantifying Particle Departure from Axisymmetry in Multiphase Cylindrical
Detonation *


TIME:  *3:00PM*



LOCATION:
*Donald P. Shiley Bioscience Center Auditorium*



SPEAKER/BIO:


*Dr. **M. Giselle Fernandez, Posdoctoral Researcher,*


*Los Alamos National Laboratory*




ABSTRACT:
Dense layers of solid particles surrounding a high-energy explosive
generate instabilities after detonation. Conjectures as to the cause of
these instabilities include imperfections in the casing, inhomogeneities in
the initial distribution of particles, characteristics of the particles,
and others. In particular, a multiphase detonation with a cylindrical
configuration where the initial distribution of particles is initially
highly axisymmetric is studied. The main physical mechanism responsible for
the instabilities observed in the experiments is assumed to be the initial
distribution of particles. Therefore, the particle volume is perturbed in
the simulations using azimuthal sinusoidal waves and the final distribution
of the particles is observed quantifying the amplification of the departure
from axisymmetry.

An instability mechanism, that is possibly partially the result of
non-classical Raleigh-Taylor and/or Richmyer-Meshkov instabilities, is
observed. We have called it channeling instability and it has two main
effects (i) accelerate particles located in low particle volume radial
sectors and (ii) push particles from low particle volume sectors to high
particle volume sectors.

To quantify the particles departure from axisymmetry, a metric based on
energy is constructed, which depends on the parameters of a trimodal
sinusoidal perturbation (amplitudes, wavelengths, and relative phases). The
metric dependence on the relative phases was found to be negligible and
unimodal perturbations were found to amplify the metric the most.

The simulations considered are expensive and surrogate models can achieve
accurate predictions of the metric dependence on the amplitudes and the
wavelengths at a low computational cost. Linear regression is used to
construct low-fidelity, high-fidelity, and multi-fidelity surrogate models.
It was found that for this problem with this particular surrogate and basis
functions, multi-fidelity models have better performance compared with
single-fidelity models.

Options for reducing the number of simulation used to construct surrogates
while maintaining accuracy by taking advantage of parametric symmetries
were also explored. The inherent parametric symmetries of the model were
imposed while building the multi-fidelity surrogate and the performance
compared with the multi-fidelity surrogate without imposing symmetries. For
a small number of high-fidelity points it was found that the performance of
the surrogate using symmetries is much better, however, for more than 100
HF data points their performance is indistinguishable.



Host: Satchi Venkataraman
May 2

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