How can we accurately compare air flow data in an open system?

Click For Summary
SUMMARY

This discussion focuses on normalizing air flow data in an open system with variable line pressures and temperatures. The normalization equation used is QN = Q × (Pa / Pref) × (Tref / T), which adjusts flow rates based on reference conditions. The challenge lies in comparing datasets generated under different line pressures and temperatures to achieve uniformity. The user seeks clarity on whether the normalization process can yield accurate comparisons despite these variabilities.

PREREQUISITES
  • Understanding of fluid dynamics principles, specifically in open systems.
  • Familiarity with pressure measurement techniques, including line pressure and differential pressure.
  • Knowledge of normalization equations and their application in flow measurement.
  • Experience with data analysis methods for comparing variable datasets.
NEXT STEPS
  • Research advanced normalization techniques for flow data under varying pressures and temperatures.
  • Explore the impact of backpressure on flow measurements in open systems.
  • Learn about statistical methods for comparing datasets with different conditions.
  • Investigate software tools for modeling and simulating flow data under controlled conditions.
USEFUL FOR

Engineers, data analysts, and researchers involved in fluid dynamics, particularly those working with air flow measurements in open systems and seeking to standardize data for accurate comparisons.

xXDeltaXx
Messages
2
Reaction score
0
Hi, I have a question relating to normalizing air flow data in an open system…

The system comprises of a regulator feeding 2barg line pressure to a valve (controlling the downstream flow), a variable restriction, a second valve (normally open) and a flow meter. Pressure readings are taken upstream and downstream of the restriction – these generate the line pressure and differential pressure readouts.

Because of the layout, the restriction in the pipe work generates backpressure as the flow increases – as such, a ‘0 barg’ test can end up with 1 barg of line pressure…

We apply a calculation to the data to ‘normalize’ it at the generated temperatures and pressures.
This is the equation to normalize the data used: QN = Q × (Pa / Pref) × (Tref / T) - sourced from
The problem is that we wish to compare the data to other data sets on a uniform scale (set temperature and set pressure)…
As the generated data is produced with a variable line pressure, I presume that another calculation is needed to remove this variability before entering the uniform values into the normalizing calculation…??

For example:
I wish to compare the following data at 0.5barg line pressure and 15°C to create a flow curve
0 l/min, 0mbar dP at 0barg line pressure, 10°C
20 l/min, 226mbar dP at 0.2bar line pressure, 9°C
42 l/min, 502mbar dP at 0.38bar line pressure, 9°C
The equation can be applied to each line – generating a ‘normalized’ value.
The desired conditions can be applied to each line – generating ‘normalized’ values… but would these really be accurate for comparison as the dP was generated with different line pressures?

(I'm finding this a little difficult to explain exactly what I mean...)

Thanks for your time :smile:
 
Science news on Phys.org
Hopefully this will explain a little better...

http://img268.imageshack.us/img268/5466/query1.jpg
(Illustrative results)
The actual data shows an increase in line pressure and a decrease in temperature during the test where the flow rate and differential pressure are recorded.
The ideal conditions are set at a static temperature and line pressure.
The Nm3/hr in each data table shows the difference changing these values makes.

My query is: because the temperature and line pressure recorded are not static, are the generated results accurate? Or does the calculation work regardless as each point is individually converted? - the fact that the data is part of a data set and across different temperatures and pressures does not matter...
 
Last edited by a moderator:

Similar threads

Replies
1
Views
1K
  • · Replies 7 ·
Replies
7
Views
2K
Replies
5
Views
2K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 11 ·
Replies
11
Views
3K
  • · Replies 2 ·
Replies
2
Views
4K
  • · Replies 10 ·
Replies
10
Views
7K
Replies
6
Views
5K
Replies
1
Views
2K
Replies
3
Views
3K