Nature of packs used in propellant modeling

Maggi, F.; Stafford, Shad; Jackson, T. L.; Buckmaster, J.

doi:10.1103/physreve.77.046107

Cited by 49 publications

(37 citation statements)

References 31 publications

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“…For example, higher growth rates reduce the packing capability while slower ones enable higher packing fractions. In this respect, close-pack condition represents an asymptotic state that can be reached only after an infinite simulation time [27]. The simplest possible stopping criterion consists of comparing f against a target packing fraction.…”

Section: Packing Fraction and Stopping Criteriamentioning

confidence: 99%

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Parallel packing code for propellant microstructure analysis

Baietta

Maggi

2015

Aerospace Science and Technology

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Please cite this article in press as: A. Baietta, F. Maggi, Parallel packing code for propellant microstructure analysis, Aerosp. Sci. Technol. (2015), http://dx.doi.org/10.1016/j.ast. 2015.08.012 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Parallel AbstractIn recent years, packing codes have become a successful alternative to experimental data collection for microstructure investigation of heterogeneous materials. Composite solid rocket propellants are interesting representatives of this category, consisting of a mix of fuel and oxidizer powders embedded in a polymeric binder. Their macroscopic properties are strictly dependent on the peculiar microstructure, which influences mechanical, combustion, as well as physical features. This work addresses algorithm development, validation, and scalability of POLIPack, a parallel packing code based on the Lubachevsky-Stillinger algorithm, developed at the Space Propulsion Laboratory (SPLab) of Politecnico di Milano. The application can reproduce the organization of spheres of any diameter inside a cube with periodic boundary. In addition to the general code description, the paper identifies a collision condition not addressed by the original Lubachevsky's algorithm (here called back impact), introduces a novel post-impact handling granting a minimum separation velocity between particles, and presents a parallelization approach based on OpenMP shared memory paradigm. Monomodal and bimodal packs have been compared to experimental data through statistic descriptors and packing maps.

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Section: Packing Fraction and Stopping Criteriamentioning

confidence: 99%

“…Rocpack [20]). The comparison with experimental tomographic data through spatial statistics for some of the aforementioned techniques have demonstrated that different algorithms do not always generate equivalent microstrucures [27].…”

Section: Introductionmentioning

confidence: 99%

Parallel packing code for propellant microstructure analysis

Baietta

Maggi

2015

Aerospace Science and Technology

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“…To study the effect of inclusion shape on the effective material properties, the packing code Rocpack [61][62][63] is used to generate statistically isotropic systems of Platonic solids. The algorithm is a hybrid of the Lubachevsky-Stillinger [44] and Adaptive Shrinking Cell [64,65] packing algorithms, where infinitesimal particles are randomly distributed within a volume and allowed to grow until a desired volume fraction is reached.…”

Section: (I) Generation Of Microstructuresmentioning

confidence: 99%

Third-order thermo-mechanical properties for packs of Platonic solids using statistical micromechanics

et al. 2015

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“…These microstructures can allow trends in material behavior to be explored. More realistic generation of 3D microstructures (see, e.g.,) 46,47 is not the focus of this study. Regardless, the simulation framework adopted here lends itself to studies which could use microstructures generated using other methods.…”

Section: Energetic Molecular Crystalsmentioning

confidence: 99%

Analysis of thermomechanical response of polycrystalline HMX under impact loading through mesoscale simulations

Hardin¹,

Rimoli²,

Zhou³

2014

AIP Advances

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We investigate the response of polycrystalline HMX 3,5,3,5, under impact loading through a 3-dimensional mesoscale model that explicitly accounts for anisotropic elasticity, crystalline plasticity, and heat conduction. This model is used to quantify the variability in temperature and stress fields due to random distributions of the orientations of crystalline grains in HMX under the loading scenarios considered. The simulations carried out concern the response of fully dense HMX polycrystalline ensembles under impact loading at imposed boundary velocities from 50 to 400 m/s. The polycrystalline ensemble studied consists of a geometrically arranged distribution of bi-modally sized and shaped grains. To quantify the effect of crystalline slip, two models with different numbers of available slip systems are used, reflecting differing characterizations of the slip systems of the HMX molecular crystal in the literature. The effects of microstructure and anisotropy on the distribution of heating and stress evolution are investigated. The results obtained indicate that crystalline response anisotropy at the microstructure level plays an important role in influencing both the overall response and the localization of stress and temperature. The overall longitudinal stress is up to 16% higher and the average temperature rise is only half in the material with fewer potential slip systems compared to those in the material with more available slip systems. Local stresses can be as high as twice the average stresses. The results show that crystalline anisotropy induces significant heterogeneities in both mechanical and thermal fields that previously have been neglected in the analyses of the behavior of HMX-based energetic materials. C 2014 Author(s)

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Nature of packs used in propellant modeling

Cited by 49 publications

References 31 publications

Parallel packing code for propellant microstructure analysis

Parallel packing code for propellant microstructure analysis

Third-order thermo-mechanical properties for packs of Platonic solids using statistical micromechanics

Analysis of thermomechanical response of polycrystalline HMX under impact loading through mesoscale simulations

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