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Posted 21 mar 2023, 04:09 GMT-4 Version 5.6 2 Replies

Tao Zhou
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My simulation is based on experiments, and the geometric modeling is 5mm × 8mm, while in the experiment, particle image velocimetry was used, and it was observed with a magnifying glass (2.66× 2.66mm) at 5 times the magnification , but now the speed in the entire geometry that I have obtained, the range of the rainbow bar, compared to the speed measured in the experiment, is generally smaller, with a few orders of magnitude difference. How do I handle this?If you have any suggestions,Thank you very much.

2 Replies Last Post 21 mar 2023, 23:04 GMT-4
Dave Greve
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Posted: 2 years ago 21 mar 2023, 11:47 GMT-4

This question concerns the agreement between experiment and simulation, which is beyond the scope of this forum.

All that can be said is that there is a problem with the experiment, the simulation, or both.

This question concerns the agreement between experiment and simulation, which is beyond the scope of this forum. All that can be said is that there is a problem with the experiment, the simulation, or both.
Robert Koslover Certified Consultant
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Posted: 2 years ago 21 mar 2023, 23:04 GMT-4

Dave Greve is right, but... I would indeed like to offer a suggestion! You say that you compared your computed to measured value and find "a few orders of magnitude difference." That's a huge difference! Any scientist knows that before you ever do an experiment, or before you ever create a model, you should have at least a rough idea/estimate of what the answer is going to be! So Dave is entirely right to say that "there is a problem with the experiment, the simulation, or both." But as a scientist yourself, you should be using your own knowledge of the subject to guide you in which one (that is, the experimental measurement vs. the model-based prediction) to investigate further, based on its huge disagreement from your own estimate! Good scientists typically make good estimates, by which I mean to say that their pre-experiment or pre-model estimates are not usually in error by "a few orders of magnitude." Thus, if the experimental result is fairly close to your estimate, the model is probably wrong. If the model result is fairly close to your estimate, there was probably an error in the experiment. But, if by some chance you didn't even make an estimate to begin with, you need to go back and do that. It's the way science is done. E.g., see https://en.wikipedia.org/wiki/Scientific_method#Elements_of_the_scientific_method

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Dave Greve is right, but... I would indeed like to offer a suggestion! You say that you compared your computed to measured value and find "a few orders of magnitude difference." That's a huge difference! Any scientist knows that before you ever do an experiment, or before you ever create a model, you should have at least a rough idea/estimate of what the answer is going to be! So Dave is entirely right to say that "there is a problem with the experiment, the simulation, or both." But *as a scientist* yourself, you should be using your own knowledge of the subject to guide you in which one (that is, the experimental measurement vs. the model-based prediction) to investigate further, based on its huge disagreement from your own estimate! Good scientists typically make good estimates, by which I mean to say that their pre-experiment or pre-model estimates are not *usually* in error by "a few orders of magnitude." Thus, if the experimental result is fairly close to your estimate, the model is probably wrong. If the model result is fairly close to your estimate, there was probably an error in the experiment. But, *if by some chance you didn't even make an estimate to begin with*, you need to go back and do that. It's the way science is done. E.g., see https://en.wikipedia.org/wiki/Scientific_method#Elements_of_the_scientific_method

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