As an intern during Summer 2019, one of my tasks was to size and plan a flight for a remote-controlled aircraft testing a rotational detonation engine (RDE). The aircraft needed to reach a speed of Mach 3, remain as close to the airport as possible, and conduct maneuvers in the same fashion as a real aircraft would. To accomplish this, I used a new trajectory model developed by PSS.
After creating the RDE analytical model outputting specific fuel consumption and sizing the aircraft to carry 25 kilograms of hydrogen, I was ready to map the trajectory of the flight. I inputted dry mass, initial fuel mass, wing aspect ratio, and wing area, then plugged in the RDE specific fuel consumption function. The next step was to build flight segments for take-off, climb, turns, cruise, etc. Segments can be simulated separately allowing the user to fine tune parameters like velocity, heading, and pitch. Initial aircraft flight conditions can be set and tracked through segments using the MATLAB debugger. Here is a sample segment of a take-off followed by a turn and climb:
The trajectory I built encompasses a climb to 10 km, an acceleration to Mach 3, and several heading changes to remain in transmitting range of the airport and to set up an approach. A photo of the climb portion and deceleration from Mach 3 is included. The climb shows take-off and initial climb to 200 m, and a turn before continuing the climb. The deceleration phase shows slowing from Mach 3 and a turn to set up an approach to the airport. The total flight time is about 15 minutes. In working at PSS, I have not only learned about aircraft design and cycle analysis, but also CubeSats, space environments and disturbances and improved my coding skills. This summer has been a lot of fun and overall incredible!
I attended the 2019 International Workshop on Satellite Constellations and Formation Flying at the University of Strathclyde in Glasgow, Scotland. https://www.strath.ac.uk/engineering/iwscff/ It was a very interesting and enjoyable conference. The papers included a mix of papers from faculty, students and engineers in industry. Authors were from around in the world including Bangladesh, Brazil, Japan, China, Europe, Canada and the United States. Topics included control, orbit determination, constellation design and even the legal aspects of space operations.
Keynote speakers included Professor Simone d’Amico who talked about the work done in Stanford’s laboratories, Prof. Moriba Jah, who discussed large constellations and Dr. Timothy Maclay of OneWeb who discussed large commercial constellations such as the soon to fly OneWeb constellation.
Three students were awarded cash prizes for their papers. All of the student papers were good so it must have been a difficult decision for the judges.
My paper on cluster control was the first paper of the meeting. Other control papers focused on orbit estimation, use of environmental forces for control and even using electrostatic actuators.
The workshop reception was at the Glasgow City Chambers that has the largest marble staircase in Western Europe.
The conference dinner was the Glasgow Science Centre. Dinner was preceded by a planetarium show. After dinner, the attendees could wander around the museum that included many fun interactive exhibits.
Princeton Fusion Systems is at the ARPA-E Summit in Denver at the Gaylord Resort. The poster shows the excellent results from our recent experiments. We also have a poster about our NIAC research. We are at Booth 100. Please come by!
The PFRC made an appearance on Dr. Matthew Moynihan’s monthly investor pitch event, the Fusion Shark Tank! This event is a conference call on the first Wednesday of every month in which fusion startups pitch their businesses in a Shark-Tank-like format. It’s good practice, and forces us to think carefully about the business case of our technology.
Luckily, this is one area where the PFRC and DFD excel. The market of high-value portable power is one were the small, clean PFRC provides a clear and unique competitive advantage.
PSS physicist Charles Swanson presented to Fusion Shark Tank on June 5. Take a look below!
I grew up during the Apollo era but what really inspired me to get involved in the space business was Stanley Kubrick’s movie 2001: A Space Odyssey. My dad took me and my brother to see it at the Cinerama theater in New York City the year it was released. It was a mind-blowing experience. When I went to MIT, my intent was to go into aerospace engineering but the collapse of the aerospace industry after the cancellation of Apollo and the ending of the Vietnam war motivated me to switch to electrical engineering, which is Course VI at MIT. There I would begin my exploration of the technologies that were found in 2001.
The first exposure was Professor Patrick Winston’s course 6.034 or “Artificial Intelligence.” Researchers at MIT were working to make HAL 9000 a reality. The course covered topics such as “Blocks World,” an AI system that could reason in the context of a world consisting of nothing but a pile of blocks. We learned Lisp, an early AI language. I did my research project on AI chess, an appropriate topic as I had written an end-game chess program in high school and HAL defeats Frank Poole in chess onboard the Discovery.
After getting my SB (bachelors degree at MIT) I went to graduate school in Aernoautics and Astronautics, Course XVI, at MIT. My first spacecraft experience was working with Professor John McCarthy to design a small space station that could be lifted in one Space Shuttle launch. Professor McCarthy was a manager on the Apollo program before the Apollo I fire. He had a phenomenal amount of practical experience,
While I was at MIT fellow graduate student Dave Akin was working on space suits and astronaut in space work. MIT pioneered that idea that astronauts could do construction in space, something seen in the Discovery scenes in the movie.
After getting my Engineer of Aeronautics and Astronautics, I spent a year working on thrusters at MIT before going to the Draper Laboratory where I worked on the Space Shuttle. I learned the Shuttle programming language, HAL/S. It was named after Hal Laning. At least that is the official story. The Space Shuttle was NASA’s first approximation of the Orion Space Clipper. I also worked on several early NASA space station designs including Space Station Freedom. I looked into a space design design with rotating crew quarters though not a big wheel like Space Station V.
I then moved to New Jersey to work at GE Astro Space. I was there for 6 years where I worked on GPS IIR, Inmarsat 3 and several other spacecraft. That is where I gained experience of a wide variety of autonomous spacecraft.
I started Princeton Satellite Systems in 1992. We’ve worked on many different projects and are currently pursuing just about every element in the movie 2001: A Space Odyssey.
Our biggest project at the moment is Direct Fusion Drive, a nuclear fusion propulsion system. These are equivalent to the engines on the Discovery. We are teaming with Sam Cohen at the Princeton Plasma Physics Laboratory on this technology and have a ARPA-E grant to demonstrate ion heating, a necessary first step on the path to a fusion engine. Discovery I’s engines were Cavradyne engines – gaseous core nuclear thermal engines. Many years later NASA recreated Discovery I using hypothetical fusion engines.
Under IR&D we are developing Space Rapid Transit (SRT), a two stage to orbit launch vehicle that takes off and lands horizontally. As it happens, the Orion spacecraft was two stage to orbit with a boost from an electromagnetic launcher. SRT has an air-breathing first stage and an LH2/LO2 propelled second stage. Orion used nuclear thermal engines for both stages – something that would not be popular today. The picture below was generated by a 2001 fan based on Arthur C. Clarke’s novel. SRT is right below it.
We also did a conceptual design of a reusable lunar lander with a nuclear thermal engine for shuttling to and from lunar orbit. It would use hydrogen from lunar water. It has a Lockheed Martin Orion spacecraft on top. The entire vehicle is one piece. This is much like the Aries 1B in 2001.
We are also advancing AI technology with or work on deep learning. We have a new book coming out on the subject. We’ve also written and flown autonomous control systems for three different missions. The software can’t play chess, but does function without humans in the loop, something that HAL would have liked!
We’ve added some new tools to the Aircraft Control Toolbox for our upcoming 2019 release. The first is a new GUI for creating aircraft models. You import a Wavefront OBJ files and then you point and click to define leading edges, wing areas, engine locations and so forth. This makes it easier to import the geometric data. The GUI is shown below. It illuminates the view that you need to use for a given geometric element in red. The inertia matrix is generated from the mass and the surface geometry.
A new simulation function was added to use the data from this GUI. It has a flat Earth aircraft model with a plugins architecture. You can add your own lift, drag and thrust models or use the simple built-in models. It is much simpler than AC.m which is designed to be a comprehensive high-fidelity simulation. We’ve added a new animation GUI to show you the results of your simulations.
We expect 2019.1 to be available in June. You can get a demo with previews of the new functions now.
We are looking for a plasma physicist to join our staff in support our new ARPA-E contract on the Princeton Field Reversed Configuration (PFRC) experiment.
Candidates should be interested in both theoretical and experimental work in plasma physics related to nuclear fusion power generation. Familiarity with low- and high-temperature plasma diagnostics is desirable. Background on any magnetic fusion device is also desirable. The position includes:
Help run experiments on the PFRC-2 (located at the Princeton Plasma Physics Laboratory) and analyze data.
Analytical and numerical work, including MHD simulations and PiC simulations.
Numerical modeling of plasmas.
Work in other areas at PSS including control, estimation, machine learning and orbit dynamics.
Programming in MATLAB, Python and C/C++.
Write proposals and come up with new topics for proposals including SBIR and STTR proposals.
Ph.D in plasma physics (may be a recent or 2019 grad)
Apress has released a second edition of our textbook, MATLAB Machine Learning Recipes! New chapters include Fuzzy Logic and Expert Systems. We have also expanded our discussions of Neural Networks and Multiple Hypothesis Testing. The book provides a broad overview of machine learning including topics from adaptive control and estimation. Examples include learning control of aircraft and automobile target tracking.