In academic publications, presenting the average of multiple experimental runs is often encouraged because it demonstrates the reproducibility and reliability of the results. However, if the individual runs are highly similar, you may have other options:

Alternatives to Tripartite Averages:

Recommendation for Academic Papers:

While tripartite averaging is not strictly mandatory, demonstrating consistency and repeatability strengthens your paper. If you opt for alternative methods, clearly state your reasoning and back it up with appropriate visuals or statistics. This transparency ensures reviewers understand the reliability of your findings.

Dear Dr. Calma,

In academic papers, particularly those involving rheological measurements, it is generally considered good practice to present averaged data when multiple experimental runs are conducted under similar conditions. This provides a more reliable and representative result, especially if your measurements show small variations between runs, as you mentioned.

Main reasons are:

- Consistency: Rheological tests can exhibit slight variability due to factors like equipment calibration, environmental conditions, or sample heterogeneity. Presenting averaged data from multiple runs (like your 3 runs) helps minimize the impact of such random errors and provides a more robust interpretation of the material’s behavior.

- Statistical Relevance: Averaging data is essential to establish the reliability and repeatability of your results. In academic papers, reviewers (and readers too) expect to see statistical evidence that the measured materialproperties are consistent.

- Material properties & numerical modeling: My background is in the numerical modeling of 3D printing processes, where material rheology is a key factor to perform simulations. Often I need rheology to simulate complex phenomena because it enters in the equations that I try to solve; in this case, I reccomend to use more replications and extract the mean curve. This can then be used in a numerical model.

My consideration is that if the Haake Rheomars data manager cannot process the average data directly, you could manually calculate the averages and standard deviations using software like Excel or Python (if you’re comfortable with that), and then present the calculated values in your figures.

You can see an example of presentation of rheological curves in Fig.2 - A of the following paper:

Electromagnetic assistance enables 3D printing of silicone-based thin-walled bioinspired soft robots

DOI: 10.1016/j.addma.2024.104028

While it is not absolutely necessary to always present tripartite average data in academic publications, it is generally recommended for consistency, reliability, and statistical integrity. The inclusion of error bars or standard deviations also helps address any concerns about data variability. If the data shows little variation (i.e., low errors bars), presenting the average with appropriate statistical analysis should suffice.

Best regards,

AP

Hi, it's a good habbit and a good practice to do so, indeed. The avereging is usually done in Excel, Origin Pro, Matlab, or any other data processing software you use to plot the graphs.