Mass-velocity and size-velocity distributions of ejecta cloud from shock-loaded tin surface using atomistic simulations

Durand, Olivier; Soulard, Laurent

doi:10.1063/1.4918537

Cited by 64 publications

(22 citation statements)

References 41 publications

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“…Distinct defects may generate thin jets (which is sometimes referred to as microjetting) while a global roughness can lead to the expansion of a cloud of fine particles (sometimes called material ejection). Because this cloud may disrupt surface diagnostics used in shock physics (velocity interferometry, pyrometry, reflectivity) and because the impact of the ejecta can cause severe damage to nearby equipment in practical, engineering applications, this process has been widely studied both theoretically and experimentally under impact or explosive loading [1][2][3][4][5][6][7][8][9][10][11][12][13]. In a recent paper, we used laser driven shock loading to investigate microjetting from triangular, individual grooves of micrometric dimensions in several metals, both below and above shockinduced melting [14].…”

Section: Introductionmentioning

confidence: 99%

Influence of edge conditions on material ejection from periodic grooves in laser shock-loaded tin

Rességuier

Roland

Prudhomme

et al. 2016

Journal of Applied Physics

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Abstract. In a material subjected to high dynamic compression, the breakout of a shock wave at a rough free surface can lead to the ejection of high velocity debris. Anticipating the ballistic properties of such debris is a key safety issue in many applications involving shock loading, including pyrotechnics and inertial confinement fusion experiments. In this paper, we use laser driven shocks to investigate particle ejection from calibrated grooves of micrometric dimensions and approximately sinusoidal profile in tin samples, with various boundary conditions at the groove edges, including single groove and periodic patterns. Fast transverse shadowgraphy provides ejection velocities after shock breakout. They are found to depend not only on the groove depth and wavelength, as predicted theoretically and already observed in the past, but also, unexpectedly, on the edge conditions, with a jet tip velocity significantly lower in the case of a single groove than behind a periodic pattern.

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Section: Introductionmentioning

confidence: 99%

Influence of edge conditions on material ejection from periodic grooves in laser shock-loaded tin

Rességuier

Roland

Prudhomme

et al. 2016

Journal of Applied Physics

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“…For the first dynamic test of the auto-balancing algorithm, the ejection from a rough metal surface produced by shock wave arrival is chosen [25,26,27,28]. Surface grooves on metal may have small sizes of the order of 10-100 µm depending on experimental setup.…”

Section: Parallel Performance In Dynamic Tests With Materials In Extrmentioning

confidence: 99%

Parallel SPH modeling using dynamic domain decomposition and load balancing displacement of Voronoi subdomains

Егорова

Dyachkov

Паршиков

et al. 2019

Computer Physics Communications

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A highly adaptive load balancing algorithm for parallel simulations using particle methods, such as molecular dynamics and smoothed particle hydrodynamics (SPH), is developed. Our algorithm is based on the dynamic spatial decomposition of simulated material samples between Voronoi subdomains, where each subdomain with all its particles is handled by a single computational process which is typically run on a single CPU core of a multiprocessor computing cluster.The algorithm displaces the positions of neighbor Voronoi subdomains in accordance with the local load imbalance between the corresponding processes. It results in particle transfers from heavy-loaded processes to less-loaded ones. Iteration of the algorithm puts into alignment the processor loads. Convergence to a well-balanced decomposition from imbalanced one is improved by the usage of multi-body terms in the balancing displacements.The high adaptability of the balancing algorithm to simulation conditions is illustrated by SPH modeling of the dynamic behavior of materials under extreme conditions, which are characterized by large pressure and velocity gradients, as a result of which the spatial distribution of particles varies greatly in time. The higher parallel efficiency of our algorithm in such conditions is demonstrated by comparison with the corresponding static decomposition of the computational domain. Our algorithm shows almost perfect strong scalability in tests using from tens to several thousand processes.

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“…• Velocities and particle sizes are uncorrelated. This may only be true 23 for the high-velocity region of the spectrum (region visible to PDV). For the estimation of the optical extinction in each slab, a mean particle diameter d p and a mean extinction efficiency Q ext will be inferred from the size distribution.…”

Section: A a General Simulation Of Pdv Spectrogramsmentioning

confidence: 99%

PDV-based estimation of ejecta particles’ mass-velocity function from shock-loaded tin experiment

Franzkowiak

Prudhomme

Mercier

et al. 2018

Review of Scientific Instruments

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A metallic tin plate with a given surface finish of wavelength λ ≃ 60 μm and amplitude h ≃ 8 μm is explosively driven by an electro-detonator with a shock-induced breakout pressure PSB = 28 GPa (unsupported). The resulting dynamic fragmentation process, the so-called “micro-jetting,” is the creation of high-speed jets of matter moving faster than the bulk metallic surface. Hydrodynamic instabilities result in the fragmentation of these jets into micron-sized metallic particles constituting a self-expanding cloud of droplets, whose areal mass, velocity, and particle size distributions are unknown. Lithium-niobate-piezoelectric sensor measured areal mass and Photonic Doppler Velocimetry (PDV) was used to get a time-velocity spectrogram of the cloud. In this article, we present both experimental mass and velocity results and we relate the integrated areal mass of the cloud to the PDV power spectral density with the assumption of a power law particle size distribution. Two models of PDV spectrograms are described. The first one accounts for the speckle statistics of the spectrum and the second one describes an average spectrum for which speckle fluctuations are removed. Finally, the second model is used for a maximum likelihood estimation of the cloud’s parameters from PDV data. The estimated integrated areal mass from PDV data is found to agree well with piezoelectric results. We highlight the relevance of analyzing PDV data and correlating different diagnostics to retrieve the physical properties of ejecta particles.

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Mass-velocity and size-velocity distributions of ejecta cloud from shock-loaded tin surface using atomistic simulations

Cited by 64 publications

References 41 publications

Influence of edge conditions on material ejection from periodic grooves in laser shock-loaded tin

Influence of edge conditions on material ejection from periodic grooves in laser shock-loaded tin

Parallel SPH modeling using dynamic domain decomposition and load balancing displacement of Voronoi subdomains

PDV-based estimation of ejecta particles’ mass-velocity function from shock-loaded tin experiment

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