Tool will help protect satellites, other spacecraft in radiation belts
Tool will help protect satellites, other spacecraft in radiation belts
Tool will help protect satellites, other spacecraft in radiation belts
A new kind of space technology is being developed in New Hampshire to help protect satellites and other spacecraft.
Scientists from the University of New Hampshire and Rogue Space Systems in Laconia have teamed up to develop a model that will track radiation levels in space.
The goal of the partnership is to build a new model that will predict weather in space, monitoring what are known as electron flux levels.
“We want to be able to better predict when they arrive and what type of influence they will have on radiation belts specifically for protecting satellites in that area,” said Reka Winslow, UNH Space Tech Hub director.
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If the levels are high, satellites and other spacecraft in the area can be damaged.
“Certain subsystems within satellites are more vulnerable to electronic fluxes than others,” said Jon Beam, of Rogue Space Systems.
The model will study and predict the levels. That information will then be used to know when to turn off systems to avoid damage.
“So you can say, ‘OK, I had an anomaly. I experienced this. I’m going to wait for another hour before I turn back on, because I know that if I turn back on right now, I’m still more vulnerable,'” Winslow said.
Beam said being able to tell what’s behind an unexpected event could be helpful in determining if something else damaged a spacecraft, such as foul play from another nation.
“I think that’s a real important aspect that can’t be understated, as well,” he said.
This won’t be the first model to predict electron flux levels in the radiation belts, but it will offer an improved forecast over current models, officials said.
The model is expected to take about six months to develop. Winslow said UNH scientists are well versed in the area and will be using previous models that are similar but use different data.
“And so we’re going to be applying this machine learning model that we already have in a different area to something that we haven’t modeled yet,” she said.
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