On the representation of random packings of spheres for sintering simulations

Aparicio, N.D.; Cocks, A.C.F.

doi:10.1016/0956-7151(95)90170-1

Cited by 37 publications

(16 citation statements)

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“…The packing fractions observed and modelled are consistent with previous studies which report the "loose" packing fraction for monosized spheres to be between 0.55 and 0.58, depending upon the friction conditions and the limit of random dense packing for monosized spheres, under frictionless conditions, which is 0.64 [14,16,17,26,27]. The effect of a distribution in particle size (in this case a standard deviation of roughly 10%) for the "monosized" case is unlikely to enhance the packing behaviour, with benefits only thought to be likely for deviations greater than 30% [18,27].…”

Section: Overview Of Cast Porous Metal Structuressupporting

confidence: 79%

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Discrete element modelling of the packing of spheres and its application to the structure of porous metals made by infiltration of packed beds of NaCl beads

Langston

Kennedy

2014

Powder Technology

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Discrete element modelling of the packing of spheres and its application to the structure of porous metals made by infiltration of packed beds of NaCl beads. Powder Technology, Access from the University of Nottingham repository: http://eprints.nottingham.ac.uk/34443/7/DEM%20porous%20metals%20-%20Powder %20Technology.pdf Copyright and reuse:The Nottingham ePrints service makes this work by researchers of the University of Nottingham available open access under the following conditions. This article is made available under the Creative Commons Attribution Non-commercial No Derivatives licence and may be reused according to the conditions of the licence. For more details see: http://creativecommons.org/licenses/by-nc-nd/2.5/ A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. AbstractA numerical model, using the discrete element method, has been developed to quantify specific parameters that are pertinent to the packing behaviour of relatively large, spherical NaCl beads and mixtures of beads of different sizes. These parameters have been compared with porosity and connectivity measurements made on porous aluminium castings made by molten metal infiltration into packed beds of such beads, after removal of the NaCl by dissolution. DEM has been found to accurately predict the packing fraction for salt beads with both monosized and binary size distributions and from this the pore fractions in castings made by infiltration into packed beds of beads could be predicted. Through simple development of the condition for contacting of neighbouring beads, the number of windows linking neighbouring pores, and their size, could also be predicted across a wide range of small bead additions. The model also enables an insight into the mixing quality and changes in connectivity introduced through the addition of small beads. This work presents significant progress towards the delivery of a 2 simulation-based approach to designing preform architectures in order to tailor the resulting porous structures to best suit specific applications. KeywordsDiscrete element method; particle packing; coordination number; porous metals; IntroductionPorous metals exhibit important characteristics which enable them to perform well in heat transfer applications. The high thermal conductivity of solid ligaments, the large surface area to volume ratios and their tortuous flow paths, which generate turbulence and high level-mixing in the cooling fluid, offer the potential for devices made from porous metals (for example high power electronic devices [1,2], heat shields, regenerators for thermal engines and thermal energy storage devices incorporating phase change materials [3]) to be compact, efficient and light weight.Experimental measurement and modelling [4][5][6][7] have sho...

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Section: Overview Of Cast Porous Metal Structuressupporting

confidence: 79%

“…The effect of a distribution in particle size (in this case a standard deviation of roughly 10%) for the "monosized" case is unlikely to enhance the packing behaviour, with benefits only thought to be likely for deviations greater than 30% [18,27].…”

Section: Overview Of Cast Porous Metal Structuresmentioning

confidence: 99%

Discrete element modelling of the packing of spheres and its application to the structure of porous metals made by infiltration of packed beds of NaCl beads

Langston

Kennedy

2014

Powder Technology

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“…Different geometric algorithms were developed to generate sphere assemblies for example in cylindrical [29], cubical [16] or conical [18] containers. The well-known ballistic deposition algorithm [1,17,18] consists in adding spheres one by one in a geometrically stable position at the surface of an evenly packed set of spheres. The texture of the packing can be controlled when using this very efficient method [42], but dynamic algorithms show some limitations when producing complex shapes.…”

Section: Introductionmentioning

confidence: 99%

Packing spherical discrete elements for large scale simulations

Jérier

Richefeu

Imbault

et al. 2010

Computer Methods in Applied Mechanics and Engineering

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“…In the author's papers [8][9][10][11][12][13] some chosen random properties of PM material characteristics were discussed, but they do not concern Poisson processes in PM materials. The use of other statistical representations of powders and granular materials are undertaken for instance in [14][15][16]. The main novelty of this paper is to show how point processes can be used to evaluate the powder metallurgy processing and powder metallurgy materials.…”

Section: Introductionmentioning

confidence: 99%

Stochastic characteristics of powder metallurgy processing

Służalec

2015

Applied Mathematical Modelling

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a b s t r a c tStochastic characteristics of powder metallurgy processing are analyzed. Theoretical formulation is described which presents probabilistic distributions of material constituents. The described method is based on Poisson processes. Examples of stochastic characteristics of powder metallurgy processing are presented and discussed. The results derived can be used for evaluation of powder metallurgy materials and the subsequent quantitative stochastic design as well as stochastic optimization of powder materials and powder processing.

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On the representation of random packings of spheres for sintering simulations

Cited by 37 publications

References 56 publications

Discrete element modelling of the packing of spheres and its application to the structure of porous metals made by infiltration of packed beds of NaCl beads

Discrete element modelling of the packing of spheres and its application to the structure of porous metals made by infiltration of packed beds of NaCl beads

Packing spherical discrete elements for large scale simulations

Stochastic characteristics of powder metallurgy processing

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