Low-frequency Impedance-Based Cell Discrimination considering Ion Transport Model in Cell Suspension

2020 ◽  
pp. 1-1
Author(s):  
Daisuke Kawashima ◽  
Songshi Li ◽  
Hiromichi Obara ◽  
Masahiro Takei
Keyword(s):  
Ion Transport ◽  
Cell Suspension ◽  
Transport Model ◽  
Low Frequency ◽  
Cell Discrimination

Alpha Radioactivity Monitor Using Ionized Air Transport Technology for Large Size Uranium Waste: Part 2—Simulation Model Reinforcement for Practical Apparatus Design

2010 ◽  
Author(s):  
Takatoshi Asada ◽  
Yosuke Hirata ◽  
Susumu Naito ◽  
Mikio Izumi ◽  
Yukio Yoshimura
Keyword(s):  
Ion Transport ◽  
Simulation Model ◽  
Cfd Simulation ◽  
Transport Model ◽  
Model Simulation ◽  
Ion Density ◽  
Transport Simulation ◽  
Simulation Results ◽  
Alpha Radioactivity ◽  
Ionized Air

In alpha radioactivity measurement using ionized air transportation (AMAT), conversion from ion currents to radioactivity accurate is required. An ion transport simulation provides ways of complementarily determining conversion factors. We have developed an ion transport simulation model. Simulation results were compared with experiments with air speeds, faster than 1 m/s, achieving good agreement. In a practical AMAT apparatus, the air-flow at the alpha source may be slower than 1 m/s, and ion loss is likely to be large. Reinforcement of the ion transport model to cover the lower air speed region is effective. Ions are generated by an alpha particle in a very thin column. Since the ion density at this temporal stage is high, the recombination loss, proportional to the square of ion density, is dominant within a few milli-seconds. The spatial and temporal scales of this columnar recombination are too small for CFD simulation. We solve an ion transport equation during the period of columnar recombination with diffusion and recombination terms and incorporated the relation between ion loss and turbulent parameters into CFD. Using this model, simulations have been done for various air speeds and targets. Those for simulation results agree with experiments, showing improvement of simulation accuracy.

Ion transport model for large LArTPC

2020 ◽  
Vol 15 (03) ◽  
pp. C03034-C03034 ◽  
Author(s):  
X. Luo ◽  
F. Cavanna
Keyword(s):  
Ion Transport ◽  
Transport Model

A transient multi-ion transport model for galvanized steel corrosion protection

2012 ◽  
Vol 77 ◽  
pp. 339-347 ◽  
Author(s):  
V. Topa ◽  
A.S. Demeter ◽  
L. Hotoiu ◽  
D. Deconinck ◽  
J. Deconinck
Keyword(s):  
Ion Transport ◽  
Corrosion Protection ◽  
Transport Model ◽  
Steel Corrosion ◽  
Galvanized Steel

scholarly journals MEASURED AND COMPUTED COASTAL OCEAN BEDLOAD TRANSPORT

1982 ◽  
Vol 1 (18) ◽  
pp. 83
Author(s):  
Alan William Niedoroda ◽  
Chen-Mean Ma ◽  
Peter A. Mangarella ◽  
Ralph H. Cross ◽  
Scott R. Huntsman ◽  
...  
Keyword(s):  
Shear Stress ◽  
San Francisco ◽  
Laboratory Experiments ◽  
Transport Model ◽  
Empirical Relationship ◽  
Low Frequency ◽  
Bedload Transport ◽  
Bottom Shear Stress ◽  
Local Measurements ◽  
Ocean Outfall

A comparison is made between the measured infilling of two test pits off the coastline of San Francisco and predictions using a coastal bedload transport model. The model, based on the work of Madsen and Grant (1967), relates the bedload transport to the bottom shear stress through an empirical relationship based on laboratory experiments. The bottom shear stress is estimated from the bottom currents created by waves and low frequency currents. The model applies beyond the breaker zone in contrast to littoral transport. The test pits, dredged as part of the Southwest Ocean Outfall Project for San Francisco, were located 1.6 km (1 mi) and 3.2 km (2 mi) offshore in 13' m (42 ft) and 16 m (53 ft) of water. The depth of the pits relative to the natural seabed was about 8.4 m (25 ft). The comparison was conducted for a period up to 2 months in the fall of 1978. The paper discussed the quality and scope of available data required as input to the model and shows how regional wave data were trans formed to augment local measurements. Uncertainties in model results stemming from limitations in the input data are presented. With suitable adjustment of the scale of the gravitational term in the expression for the Shields parameter, overall agreement between computed and measured bedload was accomplished within the limits of accuracy of the bathymetric surveys. A sensitivity analysis of selected input conditions and coefficients was also conducted.

scholarly journals Analysis of Hemichannels and Gap Junctions: Application and Extension of the Passive Transmembrane Ion Transport Model

2021 ◽  
Vol 15 ◽  
Author(s):  
Qiqian Wang ◽  
Shenquan Liu
Keyword(s):  
Synaptic Transmission ◽  
Gap Junctions ◽  
Ion Transport ◽  
Numerical Simulations ◽  
Plasma Membranes ◽  
Channel Model ◽  
Transport Model ◽  
Gene Families ◽  
Adjacent Cell ◽  
Gap Junctional

Electrical synaptic transmission is an essential form of interneuronal communication which is mediated by gap junctions that permit ion flow. Three gene families (connexins, innexins, and pannexins) have evolved to form gap junctional channels. Each gap junctional channel is formed by the docking of the hemichannel of one cell with the corresponding hemichannel of an adjacent cell. To date, there has been a lack of study models to describe this structure in detail. In this study, we demonstrate that numerical simulations suggest that the passive transmembrane ion transport model, based on the generality of ion channels, also applies to hemichannels in non-junctional plasma membranes. On this basis, we established a gap junctional channel model, which describes hemichannels' docking. We simulated homotypic and heterotypic gap junctions formed by connexins, innexins, and pannexins. Based on the numerical results and our theoretical model, we discussed the physiology of hemichannels and gap junctions, including ion blockage of hemichannels, voltage gating of gap junctions, and asymmetry and delay of electrical synaptic transmission, for which the numerical simulations are first comprehensively realized.

scholarly journals Reduced Fast Ion Transport Model For The Tokamak Transport Code TRANSP

2014 ◽  
Author(s):  
, Mario Podesta ◽  
Marina Gorelenkova ◽  
Roscoe White
Keyword(s):  
Ion Transport ◽  
Transport Model ◽  
Transport Code ◽  
Fast Ion

scholarly journals Multi-scale membrane process optimization with high-fidelity ion transport models through machine learning

2020 ◽  
Author(s):  
Matthias Wessling
Keyword(s):  
Global Optimization ◽  
Ion Transport ◽  
Transport Model ◽  
Membrane Module ◽  
Process Models ◽  
Plant Design ◽  
Deterministic Global Optimization ◽  
Transport Models ◽  
Multi Scale ◽  
Process Plants

Innovative membrane technologies optimally integrated into large separation process plants are essential for economical water treatment and disposal. However, the mass transport through membranes is commonly described by nonlinear differential-algebraic mechanistic models at the nano-scale, while the process and its economics range up to large-scale. Thus, the optimal design of membranes in process plants requires decision making across multiple scales, which is not tractable using standard tools. In this work, we embed artificial neural networks (ANNs) as surrogate models in the deterministic global optimization to bridge the gap of scales. This methodology allows for deterministic global optimization of membrane processes with accurate transport models – avoiding the utilization of inaccurate approximations through heuristics or short-cut models. The ANNs are trained based on data generated by a one-dimensional extended Nernst-Planck ion transport model and extended to a more accurate two-dimensional distribution of the membrane module, that captures the filtration-related decreasing retention of salt. We simultaneously design the membrane and plant layout yielding optimal membrane module synthesis properties along with the optimal plant design for multiple objectives, feed concentrations, filtration stages, and salt mixtures. The developed process models and the optimization solver are available open-source, enabling computational resource-efficient multi-scale optimization in membrane science.

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