Advice for representing experimental data

In summary, the conversation discusses a recent gravity current experiment using UDVP in fluid mechanics. The data was augmented and statistical analysis was performed. The experiment involved measuring velocities at different positions down the flume and text files were used to store the data. The speaker is struggling with how to use this velocity data effectively and is looking for advice on how to reconstruct the distance measured and analyze velocity profiles. Multiple runs of the experiment were performed and the possibility of using 3D graphs to plot the data is suggested.
  • #1
RobosaurusRex
29
1
Hi all,

I have recently done my first experiment in fluid mechanics, and it was a gravity current experiment using UDVP. I have augmented the data, as to remove noise, and performed the statistical analysis.

I have text files which contain the velocities measured by each sensor over the time period measured for. So I have 128 velocities measured over a distance in front of the sensor for each node. (then for each run of the experiment)

I am struggling with how best to use this velocity data to show anything meaningful, I am a newbie to this and I need some advice.
Any hints will be great, I need some idea of where to start and then I am sure that I can run with ideas from there.
I want to reconstruct the distance measured over and then look at the velocity profiles, but I am unsure of how to do this. Cheers!
 
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  • #2
RobosaurusRex said:
Hi all,

I have recently done my first experiment in fluid mechanics, and it was a gravity current experiment using UDVP. I have augmented the data, as to remove noise, and performed the statistical analysis.

I have text files which contain the velocities measured by each sensor over the time period measured for. So I have 128 velocities measured over a distance in front of the sensor for each node. (then for each run of the experiment)

I am struggling with how best to use this velocity data to show anything meaningful, I am a newbie to this and I need some advice.
Any hints will be great, I need some idea of where to start and then I am sure that I can run with ideas from there.
I want to reconstruct the distance measured over and then look at the velocity profiles, but I am unsure of how to do this.Cheers!
What were you measuring the fluid velocity as a function of? What were you varying in the experimental setup?
 
  • #3
berkeman said:
What were you measuring the fluid velocity as a function of? What were you varying in the experimental setup?
I measured the velocity at different positions down the flume
 
  • #4
Perhaps ask yourself what information would a typical reader be looking for?

Why were multiple runs of the experiment performed? Would the reader be interested in differences between runs or just the average of the runs?

RobosaurusRex said:
I measured the velocity at different positions down the flume

Down and across or just down? Exel can plot 3D graphs if necessary. So you could plot a graph with x and y as position and z as velocity perhaps. Bit like a contour map?

http://spreadsheetpage.com/graphics/tips/surface2.gif

Only you can decide what's important and what's irrelevant.
 

Related to Advice for representing experimental data

1. What is the best way to visually present experimental data?

The best way to present experimental data is through graphs or charts. These visual aids allow for easy comparison and identification of patterns or trends in the data. It is important to choose a graph or chart type that best represents the data and to properly label and title the axes.

2. How do I choose the appropriate scale for my graph?

The scale of your graph should be chosen based on the range and distribution of your data. If the data has a wide range, a logarithmic scale may be more appropriate. If the data is evenly distributed, a linear scale can be used. It is important to choose a scale that accurately represents the data without distorting it.

3. Is it necessary to include error bars in my graph?

Yes, it is important to include error bars in your graph to represent the uncertainty in your data. This can be done through standard deviation, standard error, or confidence intervals. Error bars help to show the reliability of the data and provide a more accurate representation of the results.

4. How should I label and title my graph?

The axes of your graph should be clearly labeled with the units of measurement. The title should be concise and accurately represent the data being presented. It should also include information about the experimental conditions, such as the date, location, and any relevant variables.

5. What is the best way to present categorical data?

Categorical data can be presented through a bar graph, pie chart, or stacked bar chart. It is important to choose a type of graph that best represents the data and to properly label the categories. If there are too many categories, it may be helpful to group them together or use a different type of graph, such as a box plot.

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