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Burdick, G. M.; Berman, Neil S.; Beaudoin, Steve

doi:10.1023/a:1012593318108

Cited by 92 publications

(68 citation statements)

References 24 publications

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“…This is also relevant for small agglomerates, see Refs. [46,58] for details. On the other hand, nano-roughness will not change the form of any of the remobilization conditions, it will only alter the numerical values of the pull-off force and the static friction coefficient.…”

Section: Generic Remobilization Conditionsmentioning

confidence: 99%

Dust remobilization in fusion plasmas under steady state conditions

Tolias

Ratynskaia

Angeli

et al. 2016

Plasma Phys. Control. Fusion

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The first combined experimental and theoretical studies of dust remobilization by plasma forces are reported. The main theoretical aspects of remobilization in fusion devices under steady state conditions are analyzed. In particular, the dominant role of adhesive forces is highlighted and generic remobilization conditions -direct lift-up, sliding, rolling -are formulated. A novel experimental technique is proposed, based on controlled adhesion of dust grains on tungsten samples combined with detailed mapping of the dust deposition profile prior and post plasma exposure. Proof-ofprinciple experiments in the TEXTOR tokamak and the EXTRAP-T2R reversed-field pinch are presented. The versatile environment of the linear device Pilot-PSI allowed for experiments with different magnetic field topologies and varying plasma conditions that were complemented with camera observations.

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Section: Generic Remobilization Conditionsmentioning

confidence: 99%

Dust remobilization in fusion plasmas under steady state conditions

Tolias

Ratynskaia

Angeli

et al. 2016

Plasma Phys. Control. Fusion

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show abstract

“…(10), (18), and (22) given by Suresh and Walz [37] are undefined, and the relatively simple model of Elimelech and O'Melia [36] does not apply. Other approaches for characterizing particle-rough surface interactions exist, but most are computationally intensive or require direct force measurement via AFM to determine model fitting parameters [38][39][40][41][42][43][44][45]. Hence, an approximate analytical model that captures the primary effects of surface roughness on particlesubstrate interactions remains desirable.…”

Section: Analytical Roughness Modelmentioning

confidence: 99%

Extended DLVO interactions between spherical particles and rough surfaces

Hoek

Agarwal²

2006

Journal of Colloid and Interface Science

492

302

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“…In medical flows, the wall-shear stress also plays a major role for the mechanical response of endothelial cells responsible for cardiovascular diseases (Buchmann et al 2011;Rossi et al 2009) or for the deposition of aerosols in lungs (Theunissen et al 2006). In the field of process engineering, the manipulation of particles or droplets (Burdick et al 2001) and the fluid droplet/bubble interaction (Champagne et al 2010) requires a deep understanding of the near-wall flow phenomena. For turbulent boundary layer research, it is as well very important to resolve the near-wall flow field precisely, as the velocity profiles are typically normalized with the local mean velocity component " uðx; yÞ or the friction velocity u s defined as:…”

Section: Introductionmentioning

confidence: 99%

On the uncertainty of digital PIV and PTV near walls

2012

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The reliable measurement of mean flow properties near walls and interfaces between different fluids or fluid and gas phases is a very important task, as well as a challenging problem, in many fields of science and technology. Due to the decreasing concentration of tracer particles and the strong flow gradients, these velocity measurements are usually biased. To investigate the reason and the effect of the bias errors systematically, a detailed theoretical analysis was performed using window-correlation, singe-pixel ensemble-correlation and particle tracking evaluation methods. The different findings were validated experimentally for microscopic, long-range microscopic and large field imaging conditions. It is shown that for constant flow gradients and homogeneous particle image density, the bias errors are usually averaged out. This legitimates the use of these techniques far away from walls or interfaces. However, for inhomogeneous seeding and/or nonconstant flow gradients, only PTV image analysis techniques give reliable results. This implies that for wall distances below half an interrogation window dimension, the singe-pixel ensemble-correlation or PTV evaluation should always be applied. For distances smaller than the particle image diameter, only PTV yields reliable results.

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Untitled

Cited by 92 publications

References 24 publications

Dust remobilization in fusion plasmas under steady state conditions

Dust remobilization in fusion plasmas under steady state conditions

Extended DLVO interactions between spherical particles and rough surfaces

On the uncertainty of digital PIV and PTV near walls

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