Nanoliter-volume flow-through fluorometer

1982 ◽  
Vol 54 (4) ◽  
pp. 840-842 ◽  
Author(s):  
Gerald G. Vurek
Keyword(s):  
Volume Flow ◽  
Flow Through

scholarly journals AN EXPERIMENTAL STUDY INTO THE CAUSE OF THE INCREASED PORTAL PRESSURE IN PORTAL CIRRHOSIS

1907 ◽  
Vol 9 (1) ◽  
pp. 93-104 ◽  
Author(s):  
Frederick C. Herrick
Keyword(s):  
Arterial Pressure ◽  
Portal Pressure ◽  
Normal Liver ◽  
Volume Flow ◽  
Cirrhotic Liver ◽  
Return Flow ◽  
Hepatic Veins ◽  
Portal Cirrhosis ◽  
Arterial Inflow ◽  
Flow Through

1. In the liver of portal cirrhosis there is a far freer communication between the arterial and portal currents than in the normal liver. 2. Factors contributing to the increased portal pressure in portal cirrhosis are (1) the direct communication of the arterial pressure to the portal vessels through dilated capillaries, (2) the larger volume-flow of the hepatic artery in proportion to the portal flow in cirrhosis as compared to that in the normal liver. 3. A portal cirrhotic liver gives passage to an amount of portal fluid proportionate to .its weight. There is no obstruction to the portal vessels from fibrosis in the large portal cirrhotic liver. 4. From an arterial inflow there is a free return flow through the portal as well as through the hepatic veins in both normal and cirrhotic livers. 5. From a portal inflow the return is through the hepatic vein only. The Gad's theory of valves and the arterial capillary network account for this fact. 6. The portal pressure has a decided influence on the arterial volume-flow and vice versa. This influence is more marked in the cirrhotic than in the normal liver. 7. The communication of the arterial pressure to the portal pressure is an important factor in an explanation of the increased portal pressure in portal cirrhosis.

A High Performance PFB System for Utility Application

1987 ◽  
Author(s):  
Paul A. Berman ◽  
Jeffrey A. Hynds
Keyword(s):  
Power System ◽  
High Performance ◽  
State Of The Art ◽  
Combustion Products ◽  
Volume Flow ◽  
Power Cycle ◽  
Turbine Inlet ◽  
Alkali Vapors ◽  
Fluid Bed ◽  
Flow Through

In the traditional pressurized fluid bed (PFB) power system, the PFB is located in the highest pressure portion of the power cycle, Figure 1. This results in the smallest volume flow through the PFB, but also requires the combustion products to flow through the entire expansion train. This is not expected to be a major problem when the PFB temperature is limited to 1600°F for effective sulfur capture and to avoid alkali vapors in the products of combustion. However, when topping combustion is added ahead of the turbine so as to reach state-of-the-art turbine inlet temperatures, a major risk for turbine corrosion and fouling develops.

A new observation onHalobacterium halobium; light-induced volume flow through the whole organism

1984 ◽  
Vol 40 (7) ◽  
pp. 773-775 ◽  
Author(s):  
R. C. Srivastava ◽  
D. B. Madamwar ◽  
R. K. Sharma ◽  
A. Tandon ◽  
S. B. Bhise
Keyword(s):  
Volume Flow ◽  
Flow Through

scholarly journals Osmotic Flow of Water across Permeable Cellulose Membranes

1960 ◽  
Vol 44 (2) ◽  
pp. 315-326 ◽  
Author(s):  
Richard P. Durbin
Keyword(s):  
Hydrostatic Pressure ◽  
Biological Membrane ◽  
Volume Flow ◽  
Osmotic Gradient ◽  
Pressure Gradients ◽  
Deuterated Water ◽  
Direct Measurements ◽  
Flow Through ◽  
Cellulose Membranes ◽  
Effective Pore Radius

Direct measurements have been made of the net volume flow through cellulose membranes, due to a difference in concentration of solute across the membrane. The aqueous solutions used included solutes ranging in size from deuterated water to bovine serum albumin. For the semipermeable membrane (impermeable to the solute) the volume flow produced by the osmotic gradient is equal to the flow produced by the hydrostatic pressure RT ΔC, as given by the van't Hoff relationship. In the case in which the membrane is permeable to the solute, the net volume flow is reduced, as predicted by the theory of Staverman, based on the thermodynamics of the steady state. A means of establishing the amount of this reduction is given, depending on the size of the solute molecule and the effective pore radius of the membrane. With the help of these results, a hypothetical biological membrane moving water by osmotic and hydrostatic pressure gradients is discussed.

Measurement of volume flow through a microporous membrane by a NTC thermistor miniature bead

1994 ◽  
Vol 65 (8) ◽  
pp. 2726-2730 ◽  
Author(s):  
C. Molina ◽  
L. Victoria ◽  
J. A. Ibáñez
Keyword(s):  
Volume Flow ◽  
Microporous Membrane ◽  
Ntc Thermistor ◽  
Flow Through

Measurements of volume flow through microporous membranes by an automated fluximeter

1990 ◽  
Vol 61 (3) ◽  
pp. 1123-1126 ◽  
Author(s):  
J. Forte ◽  
L. Victoria ◽  
J. A. Ibañez
Keyword(s):  
Volume Flow ◽  
Microporous Membranes ◽  
Flow Through

scholarly journals A Neural Network Mathematical Model Design Method for Estimating Compressed Air Volume Flow through a Proportional Valve

2019 ◽  
pp. 41-49
Author(s):  
M.S. Zelenov ◽  
A.V. Chernyshev
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Volume Flow ◽  
Compressed Air ◽  
Maximum Deviation ◽  
Model Design ◽  
Proportional Valve ◽  
Air Volume ◽  
Flow Through

The article describes an approach to neural network model design for simulating processes in shut-off and control pneumatic devices. This type of model can be used for a reasoned selection of components for multi-component pneumatic system configurations. As an example, the application of the proposed approach to the development of an artificial neural network to estimate the compressed air volume flow through a proportional valve is considered. The manufacturer’s catalog is used to obtain data samples. The structure of the proposed neural network model, data preprocessing for model configuration, and the selected learning algorithm are described. A computer program for compiling train and test data samples and the subsequent neural network training is developed. The results of measurements are simulated using additional, normally distributed noise with a standard deviation of 0.02. The results obtained using two mathematical models, the neural network model and the classical one, supplemented by empirical coefficients, are compared. The maximum deviation between the two models is less than 1.5 % of the maximum volume flow rate for a particular proportional valve model.

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