scholarly journals Linking the differential permeability and loss coefficients in Bertotti’s approach

2020 ◽  
Vol 503 ◽  
pp. 166540
Author(s):  
Sylvain Shihab ◽  
Abdelkader Benabou
Keyword(s):  
Loss Coefficients ◽  
Differential Permeability

CFD MODELLING AND VALIDATION OF LOSS COEFFICIENTS FOR PENSTOCK BIFURCATIONS IN HYDROPOWER SCHEMES

2018 ◽  
Author(s):  
Kasturi Sukhapure ◽  
Alan Burns ◽  
Tariq Mahmud ◽  
Jake Spooner
Keyword(s):  
Cfd Modelling ◽  
Loss Coefficients

Do We have a Satisfactory Cell Viability Assay? Review of the Currently Commercially-Available Assays

2020 ◽  
Vol 17 (1) ◽  
pp. 2-22 ◽  
Author(s):  
Abdel-Baset Halim
Keyword(s):  
Cell Viability ◽  
Data Interpretation ◽  
Positive Control ◽  
Live Cells ◽  
Proof Of Concept ◽  
Cell Viability Assay ◽  
Viability Assay ◽  
Current Cell ◽  
Dying Cells ◽  
Differential Permeability

:Cell-based assays are an important part of the drug discovery process and clinical research. One of the main hurdles is to design sufficiently robust assays with adequate signal to noise parameters while maintaining the inherent physiology of the cells and not interfering with the pharmacology of target being investigated.:A plethora of assays that assess cell viability (or cell heath in general) are commercially available and can be classified under different categories according to their concepts and principle of reactions. The assays are valuable tools, however, suffer from a large number of limitations. Some of these limitations can be procedural or operational, but others can be critical as those related to a poor concept or the lack of proof of concept of an assay, e.g. those relying on differential permeability of dyes in-and-out of viable versus compromised cell membranes. While the assays can differentiate between dead and live cells, most, if not all, of them can just assess the relative performance of cells rather than providing a clear distinction between healthy and dying cells. The possible impact of relatively high molecular weight dyes, used in most of the assay, on cell viability has not been addressed. More innovative assays are needed, and until better alternatives are developed, setup of current cell-based studies and data interpretation should be made with the limitations in mind. Negative and positive control should be considered whenever feasible. Also, researchers should use more than one orthogonal method for better assessment of cell health.

scholarly journals Turbulence model performance for ventilation components pressure losses

2021 ◽  
Author(s):  
Karsten Tawackolian ◽  
Martin Kriegel
Keyword(s):  
Reynolds Number ◽  
Turbulence Model ◽  
Pressure Loss ◽  
Low Reynolds Number ◽  
Turbulence Models ◽  
Reynolds Numbers ◽  
Test Case ◽  
Pressure Losses ◽  
Loss Coefficients ◽  
Near Wall

AbstractThis study looks to find a suitable turbulence model for calculating pressure losses of ventilation components. In building ventilation, the most relevant Reynolds number range is between 3×104 and 6×105, depending on the duct dimensions and airflow rates. Pressure loss coefficients can increase considerably for some components at Reynolds numbers below 2×105. An initial survey of popular turbulence models was conducted for a selected test case of a bend with such a strong Reynolds number dependence. Most of the turbulence models failed in reproducing this dependence and predicted curve progressions that were too flat and only applicable for higher Reynolds numbers. Viscous effects near walls played an important role in the present simulations. In turbulence modelling, near-wall damping functions are used to account for this influence. A model that implements near-wall modelling is the lag elliptic blending k-ε model. This model gave reasonable predictions for pressure loss coefficients at lower Reynolds numbers. Another example is the low Reynolds number k-ε turbulence model of Wilcox (LRN). The modification uses damping functions and was initially developed for simulating profiles such as aircraft wings. It has not been widely used for internal flows such as air duct flows. Based on selected reference cases, the three closure coefficients of the LRN model were adapted in this work to simulate ventilation components. Improved predictions were obtained with new coefficients (LRNM model). This underlined that low Reynolds number effects are relevant in ventilation ductworks and give first insights for suitable turbulence models for this application. Both the lag elliptic blending model and the modified LRNM model predicted the pressure losses relatively well for the test case where the other tested models failed.

scholarly journals Aerodynamic Losses in Turbines with and without Film Cooling, as Influenced by Mainstream Turbulence, Surface Roughness, Airfoil Shape, and Mach Number

2012 ◽  
Vol 2012 ◽  
pp. 1-28 ◽  
Author(s):  
Phil Ligrani
Keyword(s):  
Surface Roughness ◽  
Mach Number ◽  
Film Cooling ◽  
Total Pressure ◽  
High Speed ◽  
Density Ratio ◽  
Aerodynamic Loss ◽  
Pressure Losses ◽  
Loss Coefficients ◽  
Exit Mach Number

The influences of a variety of different physical phenomena are described as they affect the aerodynamic performance of turbine airfoils in compressible, high-speed flows with either subsonic or transonic Mach number distributions. The presented experimental and numerically predicted results are from a series of investigations which have taken place over the past 32 years. Considered are (i) symmetric airfoils with no film cooling, (ii) symmetric airfoils with film cooling, (iii) cambered vanes with no film cooling, and (iv) cambered vanes with film cooling. When no film cooling is employed on the symmetric airfoils and cambered vanes, experimentally measured and numerically predicted variations of freestream turbulence intensity, surface roughness, exit Mach number, and airfoil camber are considered as they influence local and integrated total pressure losses, deficits of local kinetic energy, Mach number deficits, area-averaged loss coefficients, mass-averaged total pressure loss coefficients, omega loss coefficients, second law loss parameters, and distributions of integrated aerodynamic loss. Similar quantities are measured, and similar parameters are considered when film-cooling is employed on airfoil suction surfaces, along with film cooling density ratio, blowing ratio, Mach number ratio, hole orientation, hole shape, and number of rows of holes.

scholarly journals Entrance loss coefficients and exit coefficients for a physical model of the glottis with convergent angles

2014 ◽  
Vol 136 (3) ◽  
pp. 1312-1319 ◽  
Author(s):  
Lewis P. Fulcher ◽  
Ronald C. Scherer ◽  
Nicholas V. Anderson
Keyword(s):  
Physical Model ◽  
Loss Coefficients

On Combining Loss Coefficients

1966 ◽  
pp. 21-22
Author(s):  
Robert P. Benedict ◽  
Nicola A. Carlucci
Keyword(s):  
Loss Coefficients

Internal Flow Losses: A Fresh Look at Old Concepts

2011 ◽  
Vol 133 (5) ◽  
Author(s):  
Bastian Schmandt ◽  
Heinz Herwig
Keyword(s):  
Flow Field ◽  
Entropy Generation ◽  
Mechanical Energy ◽  
Internal Flow ◽  
Second Law Of Thermodynamics ◽  
Head Loss ◽  
Local Entropy ◽  
Flow Losses ◽  
Loss Coefficients ◽  
Local Entropy Generation

Losses in a flow field due to single conduit components often are characterized by experimentally determined head loss coefficients K. These coefficients are defined and determined with the pressure as the critical quantity. A thermodynamic definition, given here as an alternative, is closer to the physics of flow losses, however. This definition is based upon the dissipation of mechanical energy as main quantity. With the second law of thermodynamics this dissipation can be linked to the local entropy generation in the flow field. For various conduit components K values are determined and physically interpreted by determining the entropy generation in the component as well as upstream and downstream of it. It turns out that most of the losses occur downstream of the components what carefully has to be taken into account when several components are combined in a flow network.

Sign in / Sign up

Export Citation Format

Share Document