Untitled

Полевой, В. В.; Bilova, Tatiana; Shevtsov, Iu I

doi:10.1023/a:1023285121361

Cited by 11 publications

(3 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The volume-averaged electron density, <n e > is set as 10.1 with <n e >/n G = 0.753 where n G is the Greenwald density limit. The injected external heating powers are limited to 33 MW for negative-ion based NBI [14] and 11.5 MW for prescribed ion cyclotron resonance heating (ICRH) [15]. A physicsbased transport model, Multi-Mode Model (MMM) [16], is employed for anomalous transport calculations combined with neoclassical transport.…”

Section: Transport Modeling Of Type-i Elmy H-mode In Itermentioning

confidence: 99%

Effects of pellet ELM pacing on mitigation of type-I ELM energy loss in KSTAR and ITER

Kim¹,

Na²,

Yi³

et al. 2011

Nucl. Fusion

View full text Add to dashboard Cite

Control of type-I ELMy H-mode by pellet injection has been numerically investigated in this work for KSTAR and ITER. A predictive transport modeling on ELMy H-mode in KSTAR reproduces consistent plasma dynamics compared with the experiments in other tokamaks, and provides a reasonable scaling between H-mode pedestal and ELM characteristics. The numerical simulation results of pellet ELM pacing in KSTAR show that the pellet induced ELMs release reduced energy bursts compared to spontaneous ELMs, which supports the necessity of highfrequency pellet injection for the mitigation of ELMs in tokamaks. A pellet-induced density perturbation model is applied to the ITER reference ELMy H-mode scenario so that the control of type-I ELMy H-mode by pellet injection can be demonstrated to check an availability of the pellet ELM pacing for mitigating ELM peaks in ITER. Even though the pellet ELM pacing is predicted to reduce the ELM peak by a factor of 2 compared to spontaneous ELMs in ITER, further enhancement of mitigation performance is required to satisfy engineering restrictions of PFCs for fully controlled ELMy H-mode plasmas. An ongoing MHD modeling on spontaneous and pellet-induced ELMs is introduced for better understanding of ELM physics and its control.

show abstract

Section: Transport Modeling Of Type-i Elmy H-mode In Itermentioning

confidence: 99%

Effects of pellet ELM pacing on mitigation of type-I ELM energy loss in KSTAR and ITER

Kim¹,

Na²,

Yi³

et al. 2011

Nucl. Fusion

View full text Add to dashboard Cite

show abstract

“…ζ-potentials of particulate objects have been determined by electrophoretic techniques 11–17. Electroosmotic flow in thin samples, such as plant tissue can be determined by flux through the tissue 18. Electroosmotic flow is described and quantitated as an influential parameter in transdermal iontophoresis19–25 and transdermal sampling (reverse iontophoresis24, 26).…”

mentioning

confidence: 99%

“…A potential difference can be generated across the film-like sample. Electrokinetic phenomena then occurs perpendicular to the film-like sample, carrying fluid from one side of the film-like sample to the other 18. Quantifying ζ-potential and electroosmotic flow in a heterogeneous tissue matrix, on the other hand, is technically challenging.…”

mentioning

confidence: 99%

Determination of ζ-Potential and Tortuosity in Rat Organotypic Hippocampal Cultures from Electroosmotic Velocity Measurements under Feedback Control

et al. 2009

View full text Add to dashboard Cite

Extracellular translational motion in the brain is generally considered to be governed by diffusion and tortuosity. However, the brain as a whole has a significant ζ-potential, thus translational motion is also governed by electrokinetic effects under a naturally occurring or applied electric field. We have previously measured ζ-potential and tortuosity in intact brain tissue, however the method was tedious. In this work, we use a four-electrode potentiostat to control the potential difference between two microreference electrodes in the tissue, creating a constant electric field. Additionally, some alterations have been made simplify our previous procedure. The method entails simultaneously injecting two 70 kDa dextran conjugated fluorophores into rat organotypic hippocampal cultures and observing their mobility using fluorescence microscopy. We further present two methods of data analysis: regression and two-probe analysis. Statistical comparisons are made between the previous and current methods as well as between the two data analysis methods. In comparison to the previous method, the current, simpler method with data analysis by regression gives statistically indistinguishable mean values of ζ-potential and tortuosity, with a similar variability for ζ-potential, −21.3 ± 2.8 mV, and a larger variability for the tortuosity, 1.98 ± 0.12. On the other hand, we find that the current method combined with the two-probe analysis produces accurate and more precise results, with a ζ-potential of −22.8 ± 0.8 mV and a tortuosity of 2.24 ± 0.10.Translational motion of molecules in the extracellular space of functioning tissues is typically viewed as being governed by diffusion and tortuosity. 1 Although not as well studied, electroosmotic effects occur in tissues due to natural processes 2 or experimentally applied fields. [3][4][5][6][7][8][9] Electroosmotic flow is the bulk fluid flow created by an electric field in a heterogeneous medium with a non-zero ζ-potential. In the brain for example, fixed charges on cell-surface functional groups and constituents of the extracellular matrix create a ζ-potential. 10 The electroosmotic velocity is governed by the magnitude of the ζ-potential.In order to determine the electroosmotic velocity in brain tissue, it is necessary to know the ζ-potential. Some methods exist for determining the ζ-potentials of particulate objects (e.g., cells) and film-like objects (e.g., skin). ζ-potentials of particulate objects have been determined by electrophoretic techniques. [11][12][13][14][15][16][17] Electroosmotic flow in thin samples, such as plant tissue can be determined by flux through the tissue. 18 Electroosmotic flow is described and quantitated as an influential parameter in transdermal iontophoresis [19][20][21][22][23][24][25] and transdermal sampling (reverse iontophoresis 24,26 applying an oscillating electric potential 27 or by scanning electrochemical microscopy. 25 The experimental arrangement for determining the electroosmotic velocity through pores, such as in skin ...

show abstract

Thermo‐electrokinetic rotating non‐Newtonian hybrid nanofluid flow from an accelerating vertical surface

Prakash¹,

Tripathi

Bég

et al. 2021

Heat Trans

View full text Add to dashboard Cite

This paper explores the combined effects of Coriolis force and electric force on the rotating boundary layer flow and heat transfer in a viscoplastic hybrid nanofluid from a vertical exponentially accelerated plate. The hybrid nanofluid comprises two different types of metallic nanoparticles, namely silver (Ag) and magnesium oxide (MgO) suspended in an aqueous base fluid. The Casson model is deployed for non-Newtonian effects. An empirical model is implemented to determine the thermal conductivity of the hybrid nanofluid. Rosseland's radiative diffusion flux model is also utilized. An axial electrical field is considered and the Poisson-Boltzmann equation is linearized via the Debye-Hückel approach. The resulting coupled differential equations subject to prescribed boundary conditions are solved with Laplace transforms. Numerical evaluation of solutions is achieved via MATLAB symbolic software. Aparametric study of the impact of key parameters on axial velocity, transverse velocity, nanoparticle temperature and Nusselt number is conducted for both the hybrid (Ag-MgO)-water nanofluid and also unitary (Ag)-water nanofluid. With increasing volume fraction of silver nanoparticles, there is a reduction in both axial velocity and temperatures, whereas there is a distinct elevation in transverse velocity for both unitary and hybrid nanofluids.

show abstract

Untitled

Cited by 11 publications

References 10 publications

Effects of pellet ELM pacing on mitigation of type-I ELM energy loss in KSTAR and ITER

Effects of pellet ELM pacing on mitigation of type-I ELM energy loss in KSTAR and ITER

Determination of ζ-Potential and Tortuosity in Rat Organotypic Hippocampal Cultures from Electroosmotic Velocity Measurements under Feedback Control

Thermo‐electrokinetic rotating non‐Newtonian hybrid nanofluid flow from an accelerating vertical surface

Contact Info

Product

Resources

About