Modeling the Formation of Debossed Features on a Pharmaceutical Tablet

Swaminathan, Shrikant; Hilden, Jon; Ramey, Brian; Wassgren, Carl

doi:10.1007/s12247-016-9257-6

Cited by 19 publications

(25 citation statements)

References 39 publications

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“…The bulk elastic modulus E and Poisson's ratio υ determined for this condition were 3.65 MPa and 0.065, respectively. Previous work has shown that the Poisson's ratio υ is typically small at relative densities near the poured relative density for a variety of different materials, which is consistent with the value measured in the current work . As mentioned previously, the bulk material flow behavior is insensitive to the elastic modulus and Poisson's ratio so the variation in elastic properties is expected have little influence on the results.…”

Section: Discrete Element Methods Simulationssupporting

confidence: 91%

“…The initial slope of the unloading curves were used to compute both parameters

υ = \frac{\frac{d σ_{rr}}{d ɛ_{z z}^{e}}}{\frac{d σ_{rr}}{d ɛ_{z z}^{e}} + \frac{d σ_{zz}}{d ɛ_{z z}^{e}}}

E = \frac{d σ_{zz}}{d ɛ_{z z}^{e}} - 2 υ \frac{d σ_{rr}}{d ɛ_{z z}^{e}}

where σ zz is the axial stress, σ rr is the radial stress, and ɛ e zz is the elastic axial strain. Details of this method can be found in the work of Swaminathan et al…”

Section: Discrete Element Methods Simulationsmentioning

confidence: 99%

“…Figure shows the compression and decompression curves from the DEM simulation using the properties listed in Table . Previous work has shown that the bulk elastic properties are functions of the relative density, which in turn is a function of the applied stress . From the FEM simulation, the stresses acting on material vary throughout the drum.…”

Section: Discrete Element Methods Simulationsmentioning

confidence: 99%

See 2 more Smart Citations

Modeling granular material blending in a rotating drum using a finite element method and advection‐diffusion equation multiscale model

Gonzalez

Wassgren

2018

AIChE Journal

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A multiscale model is presented for predicting the magnitude and rate of powder blending in a rotating drum blender. The model combines particle diffusion coefficient correlations from the literature with advective flow field information from blender finite element method simulations. The multiscale model predictions for overall mixing and local concentration variance closely match results from discrete element method (DEM) simulations for a rotating drum, but take only hours to compute as opposed to taking days of computation time for the DEM simulations. Parametric studies were performed using the multiscale model to investigate the influence of various parameters on mixing behavior. The multiscale model is expected to be more amenable to predicting mixing in complex geometries and scale more efficiently to industrial-scale blenders than DEM simulations or analytical solutions. V C 2018 American Institute of Chemical Engineers AIChE J, 00: 000-000, 2018

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Section: Discrete Element Methods Simulationssupporting

confidence: 91%

“…The initial slope of the unloading curves were used to compute both parameters

υ = \frac{\frac{d σ_{rr}}{d ɛ_{z z}^{e}}}{\frac{d σ_{rr}}{d ɛ_{z z}^{e}} + \frac{d σ_{zz}}{d ɛ_{z z}^{e}}}

E = \frac{d σ_{zz}}{d ɛ_{z z}^{e}} - 2 υ \frac{d σ_{rr}}{d ɛ_{z z}^{e}}

where σ zz is the axial stress, σ rr is the radial stress, and ɛ e zz is the elastic axial strain. Details of this method can be found in the work of Swaminathan et al…”

Section: Discrete Element Methods Simulationsmentioning

confidence: 99%

Section: Discrete Element Methods Simulationsmentioning

confidence: 99%

See 1 more Smart Citation

Modeling granular material blending in a rotating drum using a finite element method and advection‐diffusion equation multiscale model

Gonzalez

Wassgren

2018

AIChE Journal

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“…The specific densityindependent DPC powder properties used in these studies are provided in Tables 3.2 and 3.3 and correspond to a particular brand of microcrystalline cellulose (Avicel PH-102, FMC-BioPolymer, PA, USA) as reported by Muliadi et al [5]. The density-dependent DPC properties used in simulations for the same material were collected by Swaminathan et al [19] and are given in Tables 3.4 and 3.5. In order to compare to the maximum relative density predictions of the Johanson model, the material relative density at the minimum gap location is calculated in the FEM model using the total volumetric plastic strain as proposed by Gurson [20],…”

Section: Materials Propertiesmentioning

confidence: 99%

Modifications to Johanson's roll compaction model for improved relative density predictions

Liu

Wassgren

2016

Powder Technology

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“…The Young's modulus of the compacted solid, obtained from central one-third of the unloading curve using Hooke's law [28,76], is given by…”

Section: Young's Modulus and Poisson's Ratio Of The Compacted Solidmentioning

confidence: 99%

Generalized loading-unloading contact laws for elasto-plastic spheres with bonding strength

Gonzalez¹

2019

Journal of the Mechanics and Physics of Solids

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We present generalized loading-unloading contact laws for elasto-plastic spheres with bonding strength. The proposed mechanistic contact laws are continuous at the onset of unloading by means of a regularization term, in the spirit of a cohesive zone model, that introduces a small and controllable error in the conditions for interparticle breakage. This continuity property is in sharp contrast with the behavior of standard mechanistic loading and unloading contact theories, which exhibit a discontinuity at the onset of unloading when particles form solid bridges during plastic deformation. The formulation depends on five material properties, namely two elastic properties (Young's modulus and Poisson's ratio), two plastic properties (a plastic stiffness and a power-law hardening exponent) and one fracture mechanics property (fracture toughness), and its predictions are in agreement with detailed finite-element simulations. The numerical robustness and efficiency of the proposed formulation are borne out by performing three-dimensional particle mechanics static calculations of microstructure evolution during the three most important steps of powder die-compaction, namely during compaction, unloading, and ejection. These simulations reveal the evolution, up to relative densities close to one, of microstructural features, process variables and compact mechanical attributes which are quantitatively similar to those experimentally observed and in remarkable agreement with the (semi-)empirical formulae reported in the literature.

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Modeling the Formation of Debossed Features on a Pharmaceutical Tablet

Cited by 19 publications

References 39 publications

Modeling granular material blending in a rotating drum using a finite element method and advection‐diffusion equation multiscale model

Modeling granular material blending in a rotating drum using a finite element method and advection‐diffusion equation multiscale model

Modifications to Johanson's roll compaction model for improved relative density predictions

Generalized loading-unloading contact laws for elasto-plastic spheres with bonding strength

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