Computational Granular Dynamics

doi:10.1007/3-540-27720-x

Cited by 20 publications

(26 citation statements)

References 189 publications

(365 reference statements)

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“…One approach is to perform "corrections" to ensure that particles numerically transfer to the correct side of the discontinuity. This may be achieved through the addition or subtraction of a small quantity to the time of the next event [7]. Alternatively, the position may be directly changed to "nudge" the particles over the corresponding discontinuity after processing the current event (e.g., see the source code of Ref.…”

Section: Ambiguity Of Particle Statementioning

confidence: 99%

Stable algorithm for event detection in event-driven particle dynamics: logical states

Strobl¹,

Bannerman²,

Pöschel³

2016

Comp. Part. Mech.

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Following the recent development of a stable event-detection algorithm for hard-sphere systems, the implications of more complex interaction models are examined. The relative location of particles leads to ambiguity when it is used to determine the interaction state of a particle in stepped potentials, such as the square-well model. To correctly predict the next event in these systems, the concept of an additional state that is tracked separately from the particle position is introduced and integrated into the stable algorithm for event detection.

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Section: Ambiguity Of Particle Statementioning

confidence: 99%

Stable algorithm for event detection in event-driven particle dynamics: logical states

Strobl¹,

Bannerman²,

Pöschel³

2016

Comp. Part. Mech.

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“…The time-evolution of granular discs is calculated using the event-driven (ED) method [17], because the conventional molecular dynamics requires the vast calculation time, when forces between -N N 2 2 ( ) paired granular discs are calculated. Figures 7-9 show time-evolutions of the granular discs inside the SQ boundary at N=10 4 , 5×10 4 and 10 5 , respectively.…”

Section: Results In Case Of Sq Boundarymentioning

confidence: 99%

“…The calculation of the velocity of the granular particle post-collision with the elastic wall is calculated in a similar way to equation (4) [17].…”

Section: Event-driven Methods To Simulate Granular Particlesmentioning

confidence: 99%

Topological analysis of pattern formation in cooling granular gases confined by elastic wall

Yano

Kim

2020

J. Phys. Commun.

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In this paper, we investigate the topological characteristics of the pattern formation in the cooling granular gases confined by the elastic wall. The persistent homology and Voronoi's analysis and its derivative analyses are applied to accomplish our aim. The growth of the pattern formation can be identified by the switch between the logarithmic concave and logarithmic convex in the life-spandistribution obtained using the persistence diagram. Furthermore, three phases are identified by the zeroth or first order Betti number, when a form of the wall is the square. Finally, the characteristics of the coordination of granular particles condensing around the elastic wall are investigated by the Voronoi's analysis, bond-angle analysis, and polyhedral template matching. We confirm that some clusters of the granular particles condensing around the elastic spherical-wall certainly attribute to their crystallization categorized as the typical coordination.

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“…The divergence of φ HS (σ) implies that at this point, there is an infinite repelling force which in turn implies that the duration of the interaction approaches zero, that is, at this point the velocities alter instantaneously. Performing a momentum and energy balance over two colliding hard spheres [29] yields the collision rule for the evolution of the particle velocity, v i :…”

Section: Basic Event-driven Algorithm For Identical Hard Spheresmentioning

confidence: 99%

“…Unfortunately, this iterative approach is expensive and will limit the computational speed of EDPD. A more efficient scheme to prevent overlaps by biasing the movement of particles by (temporarily) modifying the particle diameter so that detected interactions occur at a small distance from the invalid state is proposed by Pöschel and Schwager [29]. Unortunately, this approach does not exactly simulate the desired system but a slightly different system following a slightly different dynamics.…”

Section: Event Calculation Errorsmentioning

confidence: 99%

Stable algorithm for event detection in event-driven particle dynamics

et al. 2014

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Event-Driven Particle Dynamics is a fast and precise method to simulate particulate systems of all scales. In this work it is demonstrated that, despite the high accuracy of the method, the finite machine precision leads to simulations entering invalid states where the dynamics are undefined. A general event-detection algorithm is proposed which handles these situations in a stable and efficient manner. This requires a definition of the dynamics of invalid states and leads to improved algorithms for event-detection in hard-sphere systems

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Computational Granular Dynamics

Cited by 20 publications

References 189 publications

Stable algorithm for event detection in event-driven particle dynamics: logical states

Stable algorithm for event detection in event-driven particle dynamics: logical states

Topological analysis of pattern formation in cooling granular gases confined by elastic wall

Stable algorithm for event detection in event-driven particle dynamics

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