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Small but mighty: A mini plasma-powered satellite under construction may launch a new era in space exploration

Small but mighty: A mini plasma-powered satellite under construction may launch a new era in space exploration

The CubeSat’s thruster, whose development is led by PPPL physicist Yevgeny Raitses, holds the promise of increased flexibility for the tiny satellites, more than a thousand of which have been launched by universities, research centers and commercial interests around the world. The proposed propulsion device — powered by plasma — could raise and lower the orbits of CubeSats circling the Earth, a capability not broadly available to small spacecraft today, and would hold the potential for exploration of deep space.

“Essentially, we will be able to use these miniature thrusters for many missions,” Raitses said.

A fleet of CubeSats

One example: A fleet made up of hundreds of such micropowered CubeSats could capture in fine detail the reconnection process in the magnetosphere, the magnetic field that surrounds the Earth, said physicist Masaaki Yamada. Yamada is the principal investigator of the PPPL Magnetic Reconnection Experiment, which studies magnetic reconnection — the separation and explosive snapping together of magnetic field lines in plasma that triggers auroras, solar flares and geomagnetic storms that can disrupt cell phone service and power grids on Earth.

Key advantage

The miniaturized engine scales down a cylindrical thruster with a high volume-to-surface geometry developed at the PPPL Hall Thruster Experiment, which Raitses leads and launched with PPPL physicist Nat Fisch in 1999. The experiment investigates the use of plasma — the state of matter composed of free-floating electrons and atomic nuclei, or ions — for space propulsion.

A key advantage of the miniaturized cylindrical Hall thruster will be its ability to produce a higher density of rocket thrust than existing plasma thrusters used for most CubeSats now orbiting Earth. The miniaturized thruster can achieve both increased density and a high specific impulse — the technical term for how efficiently a rocket burns fuel — that will be many times greater than that produced by chemical rockets and cold-gas thrusters typically used on small satellites.

High specific-impulse thrusters use much less fuel and can lengthen satellite missions, making them more cost-effective. Equally important is the fact that a high specific impulse can produce a large enough increase in a satellite’s momentum to enable the spacecraft to change orbits — a feature not available on currently orbiting CubeSats. Finally, high thrust density will enable satellites to accomplish complex fuel-optimized orbits in a reasonable time.

These capabilities provide many benefits. For example, a CubeSat might descend to lower orbit to track hurricanes or monitor shoreline changes and return to a higher orbit where the drag force on a satellite is weaker, requiring less fuel for propulsion.

The foot-long CubeSat, which Princeton has dubbed a “TigerSat,” consists of three 4-inch aluminum cubes stacked vertically together. Sensors, batteries, radio equipment and other instruments will fill the CubeSat, with a miniaturized thruster roughly equal in diameter to two U.S. quarters housed at either end. A thruster will fire to change orbits when the satellite passes the Earth’s equator.

Mechanical and aerospace engineering students

Building the CubeSat are some 10 Princeton graduate and undergraduate students in the Department of Mechanical and Aerospace Engineering, with Daniel Marlow, the Evans Crawford 1911 Professor of Physics, serving as faculty advisor. Undergraduates include Andrew Redd (Class of 2020), who leads design and construction of the CubeSat, and Seth Freeman (Class of 2022), who is working full-time on the project over the summer. Working on thruster development is Jacob Simmonds, a third-year graduate engineering student, whose thesis advisors are Raitses and Yamada. “This project began as a prototype of Yamada’s CubeSat and has evolved into its own project as a testbed for the plasma thruster,” Simmonds said.

Also under construction at PPPL is a test facility designed to simulate key aspects of the CubeSat’s operation. Undergraduates working on their own time are building the satellite and this facility. “To the extent that students and their advisors have identified well-defined questions associated with the TigerSat project, they can get independent work credit,” Marlow said.  “Also, some problem sets in the introductory physics course for undergraduates that I teach have questions related to the TigerSat flight plan.”

Simmonds, while working on the thruster, is drafting a proposal for NASA’s Cubic Satellite Launch Initiative that is due in November. Projects selected by the Initiative, which promotes public-private technology partnerships and low-cost technology development, have launch costs covered on commercial and NASA vehicles. Plans call for a TigerSat launch in the fall of 2021.

Value of collaboration

For Raitses, this project demonstrates the value of Princeton engineering students collaborating with PPPL and of University faculty cooperating with the Laboratory. “This is something that is mutually beneficial,” he said, “and something that we want to encourage.”

Materials provided by Princeton University

galactic clusters plasma

Scientists use X-rays from faraway galaxy cluster to reveal secrets of plasma

Most visible matter in the universe doesn’t look like our textbook picture of a nucleus surrounded by tethered electrons. Out beyond our borders, inside massive clusters, galaxies swim in a sea of plasma—a form of matter in which electrons and nuclei wander unmoored.

Though it makes up the majority of the visible matter in the universe, this plasma remains poorly understood; scientists do not have a theory that fully describes its behavior, especially at small scales.

However, a University of Chicago astrophysicist led a study that provides a brand-new glimpse of the small-scale physics of such plasma. Using NASA’s Chandra X-ray Observatory, scientists took a detailed look at the plasma in a distant galaxy cluster and discovered the flow of plasma is much less viscous than expected and, therefore, turbulence occurs on relatively small scales—an important finding for our numerical models of the largest objects in the universe.

“High-resolution X-ray observations allowed us to learn some surprising truths about the viscosity of these plasmas,” said Irina Zhuravleva, an assistant professor of astrophysics and first author of the study, published June 17 in Nature Astronomy. “One might expect that variations in density that arise in the plasma are quickly erased by viscosity; however, we saw the opposite—the plasma finds ways to maintain them.”

Scattered around the universe are massive clusters of galaxies, some of them millions of light-years across containing thousands of galaxies. They sit in a type of plasma that we cannot recreate on Earth. It is extremely sparse—on the order of a sextillion times less dense than air on Earth—and has very weak magnetic fields, tens of thousands of times weaker than we experience on the Earth’s surface. To study this plasma, therefore, scientists must rely on cosmic laboratories such as clusters of galaxies.

Scientists used NASA’s Chandra X-ray Observatory to take a detailed look at the plasma in a distant galaxy cluster. (Courtesy of NASA/CXC/SAO)

Zhuravleva and the team chose a relatively nearby galaxy cluster called the Coma Cluster, a gigantic, bright cluster made up of more than 1,000 galaxies. They chose a less dense region away from the cluster center, where they hoped to be able to capture the average distance that particles travel between interactions with NASA’s Chandra X-ray Observatory. In order to build a high-quality map of the plasma, they observed the Coma cluster for almost 12 days—much longer than a typical observing run.

One thing that jumped out was how viscous the plasma was—how easily it’s stirred. “One could expect to see the viscosity resisting chaotic motions of plasma as we zoom in to smaller and smaller scales,” Zhuravleva said. But that didn’t happen; the plasma was clearly turbulent even on such small scales.

“It turned out that plasma behavior is more similar to the swirling motions of milk stirred in a coffee mug than the smoother ones that honey makes,” she said.

Such low viscosity means that microscopic processes in plasma cause small irregularities in the magnetic field, causing particles to collide more frequently and making the plasma less viscous. Alternately, Zhuravleva said, viscosity could be different along and perpendicular to magnetic field lines.

Understanding the physics of such plasmas is essential for improving our models of how galaxies and galaxy clusters form and evolve with time.

“Plasma behavior is more similar to the swirling motions of milk stirred in a coffee mug than the smoother ones that honey makes.”—Asst. Prof. Irina Zhuravleva Click To Tweet

“It is exciting that we were able to use observations of clusters of galaxies to understand fundamental properties of intergalactic plasmas,” said Zhuravleva. “Our observations confirm that clusters are great laboratories that can sharpen theoretical views on plasmas.”

Materials provided by the University of Chicago

Magnificent CME Solar eruption of plasma

Researchers discover mystery of exotic material in Sun’s atmosphere

A group of researchers from Ireland and France have declared an important finding on the behaviour of matter in the highly extreme conditions of the atmosphere of Sun. They used radio telescopes and UV cameras on a spacecraft of NASA for knowing about the exotic “fourth state of matter” about which very less is known. This state of matter called plasma may be significant in the development of safe, green and environment-friendly nuclear generator. The results of the study have been published in the Nature Communications journal.

Although the matter we encounter in our daily lives can be differentiated to either solid, liquid or gas, the Universe is majorly made of plasma. It is an extremely unstable fluid which is also highly electrical in nature. Even the Sun is composed of plasma. However, the irony lies in the fact that although the plasma is the most common state of matter in the Universe, human beings have a vague idea of it. Reason being its scarcity on Earth, which makes it difficult to understand.

Laboratories on Earth try to simulate the conditions of space however the Sun is the natural laboratory in which the behaviour of plasma can be understood, which is not possible for the ones attempted on Earth.

Dr Eoin Carley, a Postdoc researcher at the Trinity College Dublin who led the joint collaboration said that the sun’s atmosphere has very extreme conditions with the temperatures of plasma soaring to excess of one million degrees Celsius and particles travelling very close to the speed of light. These particles shine very brightly at the radio wavelengths, hence the behaviour of the plasma can be monitored with the aid of large radio telescopes.

Scientists worked with the researchers at the Paris Observatory and the observations of the Sun were performed by a radio telescope situated in Nançay, central France. These observations were combined with the UV cameras mounted on the Solar Dynamics Observatory spacecraft. It was then seen that plasma on the Sun can eject pulses resembling those from the light house. Scientists were aware of this for many years but could observe it directly for the first time with the help of these highly advanced equipments.

The problem with nuclear fusion plasmas is that they are highly unstable. When the plasma starts producing energy, the reaction is switched off by natural processes. This indicates that it is difficult to produce energy while keeping the plasma stable. By learning about the instability of plasma on the Sun, scientists can learn how to control plasma.


Researchers use machine learning models for capturing fusion energy

Machine learning is a type of artificial intelligence which helps in face recognition, language identification, translation. Apart from this, now machine learning can help in bringing the clean fusion energy, which helps in lighting the stars, to the Earth.

Now, a group of researchers from Princeton Plasma Physics Laboratory(PPPL) are taking the help of machine learning for creating a model to enable rapid control of plasma. It is the state of matter which consists of free electrons, ions and is responsible for fusion reactions. The biggest examples of such reactions are sun and many other stars which are themselves giant plasmic balls.

Scientists under the leadership of physicist Dan Boyer have trained neural networks which is the essential core of any machine learning software on the dataset produced by National Spherical Torus Experiment-Upgrade at PPPL. This model is quite accurate in reproducing the predictions of the behaviour exhibited by the particles produced by the neutral beam injection (NBI). It is used in fueling the NSTX-U plasmas and reaching upto million degrees of temperature.

The predictions are conventionally done with the help of NUBEAM. It is a program to incorporate the information about the impact made by the beam on the plasma. The calculations are performed a hundred times each second to determine the behaviour of the plasma. But since each calculation takes minutes to complete, researchers can know the result only after the experiment is over.

This problem is solved by the machine learning software as it reduces the time of calculation to less than 150 microseconds. As a result, the outcomes will be visible to the scientists during the experiment. The plasma control system will be able to make better decisions on how to control the injection of the beam for efficient performance.

With such fast evaluations, the operators will be able to make the needed adjustments for the experiments. Boyer, who is also the principal author on a paper of Nuclear Fusion commented that the rapid modelling capacities can guide the operators in changing the NBI settings for the next experiment.

Along with scientist Stan Kaye, he generated a database with NUBEAM results for a specific range of conditions resembling the ones during the initial NSTX-U operations. This was used by the scientists in training a neural network for predicting the effects of the beam on plasma like heating. After that, it was implemented by software engineers on a computer for controlling the experiment and finding out the calculation time. Scientists plan on expanding this modelling approach for other plasma phenomena.