This paper is on the different varieties of liquid jet breakup, e.g., for applications like fire hose streams and fuel sprays. At low speeds you have more regular breakup but this changes to various types of less regular breakup at higher speeds. (There are photos of each type in the preprint.) These varieties are called "regimes" in the literature. Because models are typically only valid in a particular regime, it's important to identify the correct regime. This is often done with a "regime diagram".
There's a lot I could write about what was wrong before. The easiest thing to do is compare figure 3 (old regime diagram, p. 5) and figure 4 (my new diagram, p. 13). These are in exactly the same coordinates but don't resemble each other much. If science were working correctly then the change would not be anywhere near as dramatic as it was.
Now, with the small amount of data past researchers used to construct these diagrams, they couldn't see that the diagram was wrong. The data was simply too sparse to see the big picture. But once you start adding tons of data it becomes dead obvious that the diagrams you see in textbooks and review articles are wrong. So I can't blame previous researchers that much, but compiling open data is something that should happen regularly. The current academic system does not incentivize data compilation, at least in engineering.
The most recent study mentioned in the paper used a grand total of 11 data points and claimed to have enough resolution to move some of the established boundaries slightly. This actually is a regression. The first study to construct a regime diagram had 63 data points. Mine has roughly 1200, and I still want more data! 11 data points is not scientifically acceptable, but it was enough to get a publication.
(I've since revised and extended this paper but I can't upload the new version yet due to the publisher's policies. One example: I determined that "turbulent dripping" is probably not possible so I removed it from the diagram. ;-)
I could list more if you want. There's no shortage of problems. But keep in mind that these problems are usually only obvious after you get enough data.
https://engrxiv.org/nqhs5
This paper is on the different varieties of liquid jet breakup, e.g., for applications like fire hose streams and fuel sprays. At low speeds you have more regular breakup but this changes to various types of less regular breakup at higher speeds. (There are photos of each type in the preprint.) These varieties are called "regimes" in the literature. Because models are typically only valid in a particular regime, it's important to identify the correct regime. This is often done with a "regime diagram".
There's a lot I could write about what was wrong before. The easiest thing to do is compare figure 3 (old regime diagram, p. 5) and figure 4 (my new diagram, p. 13). These are in exactly the same coordinates but don't resemble each other much. If science were working correctly then the change would not be anywhere near as dramatic as it was.
Now, with the small amount of data past researchers used to construct these diagrams, they couldn't see that the diagram was wrong. The data was simply too sparse to see the big picture. But once you start adding tons of data it becomes dead obvious that the diagrams you see in textbooks and review articles are wrong. So I can't blame previous researchers that much, but compiling open data is something that should happen regularly. The current academic system does not incentivize data compilation, at least in engineering.
The most recent study mentioned in the paper used a grand total of 11 data points and claimed to have enough resolution to move some of the established boundaries slightly. This actually is a regression. The first study to construct a regime diagram had 63 data points. Mine has roughly 1200, and I still want more data! 11 data points is not scientifically acceptable, but it was enough to get a publication.
(I've since revised and extended this paper but I can't upload the new version yet due to the publisher's policies. One example: I determined that "turbulent dripping" is probably not possible so I removed it from the diagram. ;-)
I could list more if you want. There's no shortage of problems. But keep in mind that these problems are usually only obvious after you get enough data.