In an age when computers are commonplace, two professors at the University of Wisconsin are harnessing their power to run real-world scenario simulations.
Professor Leigh Orf has been using computer models to better understand thunderstorms for over 30 years. He works to understand how thunderstorms behave, how they work and how to better predict them. Orf said there’s still a lot scientists don’t understand about what happens in a thunderstorm, but using supercomputers to model them can add new clarity to their inner workings, even at a very small size. ladder.
“I am using an atmospheric model that simulates a cloud with very, very high fidelity, high quality and high resolution. So all the small-scale, complex things that take place inside the cloud are revealed in the simulation, ”Orf said.
Orf said past events are often inspirations for simulations in his work. Orf also pointed out that the weather in the field is very important, because the atmospheric and physical information of a storm cannot be collected in any other way. From a particular storm, he got the atmospheric data collected just before the storm formed and ran it as a simulation, which then successfully produced the thunderstorm and tornado that occurred during the storm. real event.
“I was able to study the simulation independently of the actual event. But I can also compare it to the actual event because it is based on an actual event, ”Orf said.
Orf’s work has recently been published on the cover of Science magazine. He, along with colleagues at Stanford University, found answers to an unknown atmospheric phenomenon by running a simulation of the event. Orf said these computer models can sometimes provide information about real-world scenarios and allow scientists to discover things on the computer before they are discovered in the atmosphere.
He said that a growing area that will likely become more important in the future of computer modeling is machine learning. As more data is collected from simulations, processing that data will be a vital task for artificial intelligence.
“We’re going to have robots at some point and self-driving cars, and that stuff will be AI,” Orf said. “So this is an area that I would say is really interesting and important.”
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Self-driving cars are precisely what Professor Dan Negrut uses to study computer models. As the technical lead of the simulation-based engineering lab, Negrut is currently working on two projects that involve running computer simulations of an autonomous car and a lunar rover to determine how they would perform in a field situation. unique.
Negrut said computer models offer a safer and more cost-effective way to analyze the reactions of autonomous vehicles. The simulations allow researchers to create a virtual environment in which they can test the vehicle millions of times with no real consequences from running the tests.
“It’s really hard to generate these kinds of fake scenarios in the real world. How would you take a Tesla and really hit it with a patch of ice? What if you wanted to do it ten times? What if you wanted to do it ten times? What if you wanted to change the “brain” of the vehicle and hit it again? Said Negrut.
For the lunar rover experience, this advantage is even more relevant. Negrut said it was essential to test the capabilities of the rover before the very expensive process of sending it into space. In this case, running computer simulations means scientists can test the rover on different terrains and obstacles in an environment – including a difference in gravity – that looks exactly like that of the moon without having to send it multiple times. .
As part of a larger project to bring humans to the moon, the VIPER rover will be tasked with determining where the water is on the moon and how difficult it will be to extract it, Negrut said.
Negrut said that running a computer simulation is essentially about solving a large number of equations representing the physical system you are working with. For something like the rover project with so many components, the number of equations needed to represent the environment can run into the billions, he added.
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Orf said that a key aspect of computer modeling is being able to write code that harnesses the full power of the computer. Programming the computer to do what you want is not an easy process, especially when supercomputers are involved, Orf said.
“Supercomputers are really just a ton of computers all networked together. Imagine a warehouse full of really powerful desktops, ”Orf said. “How do I write a program that runs on all of them and runs all at the same time?” It is not easy. And even to gain access to these computers, you have to prove that you have code that will work effectively on them.
Orf said that using computer modeling for meteorological research requires a very specific skill set. Someone who is only computer literate may not know enough physics to determine if the model is reasonable. But an observational meteorologist may not have the knowledge to run the computer programs necessary to create even a model.
Orf and Negrut both use computer modeling to help improve safety and people’s lives. Whether it’s ensuring that self-driving cars behave in predictable ways or helping people better prepare for dangerous storms, computers contribute to our society on much deeper levels than we realize.