It is possible to blast a box of circuits clear across the Solar System with precise accuracy.
Physicists can hazard a guess at the types of patterns you'll see in the beverage by stirring milk in your tea.
A new method of calculating the motion of fluids could make their flow more predictable.
It could make everything from weather forecasts to vehicle design vastly more accurate by using this.
Physicists from the Georgia Institute of Technology found flickers of order when turbulence reflected measurable patterns.
Turbulence has been described as a random process for nearly a century.
The first illustration of the dynamics of turbulence is provided by our results.
The way eddies form in a fluid makes predicting turbulence difficult. It's easy to predict the speed and trajectory of material flowing in a straight line. The fluid will return to itself if the path in the current becomes sluggish.
New eddies can be formed with each new curling current.
It's even more complicated because each vortex behaves at the whim of a number of factors, adding up to a tempest in a teacup that no computer could keep track of.
It all looks random up close. Statistics show that the process remains firmly embedded in the same rules that govern every other moving object in the universe.
Grigoriev says thatTurbulence can be thought of as a car.
A train that follows a railway on a timetable but also has the same shape as the railway it is following is an even better analogy.
Turbulence can be described as either a numerical simulation or a physical model. The only way to get reliable predictions is to stick to a mathematical approach, just as a train timetable is helpful for getting you to work on time.
All of those numbers can quickly add up and make computations expensive.
The team set up a tank with transparent walls and a fluid with fluorescent particles to see if they could make predictions simpler. Keeping track of the glowing contents was like watching trains roll through the station.
It was necessary for the researchers to come up with timetables first so that they could see which ones were similar to what they were seeing.
The computations were done to a set of equations that were created nearly 200 years ago. The team was able to identify when certain patterns of turbulence appeared by aligning the experiment with the results.
The timing of coherent structures is not predictable. In this setup, the structures were made up of two frequencies, one of which was pitched around the axis of symmetry of the flow.
It is not a simple set of equations that can describe turbulence in all its forms, but it shows the role coherent structures can play in making them more predictable.
Future research could make turbulence's timetables more dynamic by describing them in more detail than they currently do.
Grigoriev says that it can give us the ability to dramatically improve the accuracy of weather forecasts.
Dynamic framework is essential for our ability to engineer flows with desired properties, for example, reduced drag around vehicles to improve fuel efficiency, or enhanced mass transport to help remove more carbon dioxide from the atmosphere in the emerging direct air capture industry.
It might give you an idea of what to expect when you drink tea.
The research was published in a journal.
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