Advanced Space Propulsion: Technologies, Missions, and Computer Modeling

Advanced Space Propulsion: Technologies, Missions, and Computer Modeling includes coverage of all these topics in an integrated manner. The volume, written by a team of sector-specific R&D experts, touches upon fundamentals cardinal to the understanding of [i] Orbit theory and its implications for control, estimation, and optimization of trajectory and attitude, and [ii] How each mission is designed (depending primarily on the mass of the payload, but also on how far from Earth the launch vehicle needs to go), and then succeeds in consolidating them with software and computer applications for simulations and modeling. The book continues with a discussion on the complete gamut of in-space propulsion power sources and concludes with both human and robotic mission-related case studies and future implementation examples. The outcome is a carefully calibrated and self-contained resource that will prove to be invaluable for graduate and senior undergraduate students, researchers, scientists, and engineering professionals alike.

Michael Paluszek is the President of Princeton Satellite Systems, Inc. (PSS). He received a bachelor's degree in electrical engineering from the Massachusetts Institute of Technology (MIT) in 1976. He received a Master's and Masters and an Engineer's degree from MIT in Aeronautics and Astronautics in 1979. In 1992, Mr. Paluszek founded PSS in Plainsboro, New Jersey, to provide aerospace design services. He designed the control system and simulations for the Indostar-1 geosynchronous communications satellite, which launched in 1997, as well as a Mars Ascent Vehicle for a NASA RFP. He also designed a two-stage-to-orbit vehicle which uses a turbofan in the first stage for low-Mach numbers, and a ramjet with a hydrogen-fueled combustor for high-Mach flight. His current projects include a waverider hypersonic small package delivery aircraft and the Starfire fusion reactor for energy generation and space propulsion.

Before founding PSS, Mr. Paluszek was an engineer at GE Astro Space in East Windsor, NJ. At GE, he designed the Global Geospace Sciences Polar despun platform control system and led the design of the GPS IIR attitude control system, the Inmarsat-3 attitude control systems, and the Mars Observer Delta-V control system. Mr. Paluszek flew communication satellites on over twelve satellite launches, including the GSTAR III recovery, the first transfer of a satellite to an operational orbit using electric thrusters. At Draper Laboratory, Mr. Paluszek worked on Space Shuttle and Space Station programs and on submarine navigation. His Space Station work included designing Control Moment Gyro-based attitude-control systems. He authored ``ADCS: Attitude Determination and Control Systems,'' published by Elsevier. Mr. Paluszek has also written numerous technical papers and has over a dozen U.S. Patents. He is also the lead co-author of ``MATLAB Recipes,'' ``MATLAB Machine Learning,'' ``MATLAB Machine Learning Recipes: A Problem-Solution Approach,'' ``Practical MATLAB Deep Learning Projects,'' and ``MATLAB Recipes Revised Edition,'' published by Apress.

Dr. Galea is Chief Scientist at Princeton Satellite Systems. He has an S.B. from MIT in Aerospace Engineering and Physics (2016) and a Ph.D. from Princeton University in Mechanical and Aerospace Engineering with a specialization in Applied Physics (2021).

At PSS, Dr. Galea is responsible for research and development in plasma physics for fusion applications, designing power electronics for plasmas, and aerospace technology development and modeling. He was recently the PI on the DOE SBIR project ``High-Efficiency RF Amplifiers with Plasma Accommodation for Fusion Plasma Heating,'' where he designed and developed Class-E RF amplifiers for handling plasma loads. He has additionally been supported by grants from ARPA-E and the DoD. Under ARPA-E GAMOW, Dr. Galea made a plasma-circuit model for capturing effects of plasma on power electronics, and designed and tested a Load Switch PCB board for pulse generation. On the PFRC-2 experiment, he has operated and analyzed the X-ray silicon drift detector diagnostic for electron energy distribution measurements, and has presented his work at APS Division of Plasma Physics (DPP) and High Temperature Plasma Diagnostics (HTPD) conferences.

Dr. Galea completed his Ph.D. thesis on ``Coherent Microwave Scattering from Laser-Generated Plasma in External Magnetic Field and Weakly Ionized Plasma Environments,'' where he investigated the implementation of a laser- and microwave-based diagnostic technique in novel environments relevant to plasma propulsion and remote sensing applications. A primary finding in his thesis was the discovery of magnetically induced depolarization of the microwaves when scattering from a small plasma in a magnetic field, which allows one to perform remote local vector magnetic field measurements. In summer 2020, Dr. Galea interned at Facebook Reality Labs Research as a researcher in optical engineering, where he designed and modeled technological developments for Augmented Reality glasses. During his time at MIT, Dr. Galea conducted research at the MIT Plasma Science and Fusion Center, the MIT Gas Turbine Laboratory, and the Fluid Mechanics and Aerospace Propulsion group at the Polytechnic University of Madrid in Spain. The corresponding research projects he worked on include: computational modeling and experimental testing of high-temperature superconducting tapes for fusion reactor applications, the design and construction of a surrogate stream-wise pressure gradient apparatus to model conditions in turbofan engines, and the development of a droplet vaporization model for fuel sprays in internal combustion engines. It was also during his time at MIT that he first interned at Princeton Satellite Systems, where he was introduced to the Direct Fusion Drive project that he is working on today.

Parisa Mirdamadi is expected to receive her master's degree in electrical engineering and her graduate certificate in Nuclear Power Generation from Arizona State University in 2026. She graduated cum laude and completed her bachelor's degree in electrical engineering with a concentration in Electric Power and Energy Systems from Arizona State University in 2023. During her undergraduate studies, she received the Stanley D. Duke Applied Science Award and the Gorur Family Award for her work in the electric power concentration.

Ms. Mirdamadi worked at NASA Glenn Research Center with the Technology Management division of the Radioisotope Power Systems Program as an intern in 2021. She went on to become the presenting author for ``Comparative Analysis of Thermal Conversion Technologies for Deep Space Missions'' at the American Nuclear Society's Nuclear and Emerging Technologies for Space (NETS 2022) conference. The paper presents a survey and ranking system which was developed to compare innovative thermal-to-electric energy conversion research technologies for space missions. Later, she worked on special projects with the engineering team in the power and controls unit of Collins Aerospace, a subsidiary of Raytheon Technologies Corporation (now RTX Corporation). Ms. Mirdamadi first worked with Princeton Satellite Systems as an intern in 2023, contributing to the design and development of power electronics for nuclear fusion reactors under ARPA-E GAMOW. At PSS, she also supported several white papers on topics including RF amplifiers for plasma heating, lunar navigation systems, and spacecraft engines.

Joyce Qiaoxi Mo is a PhD student at University of California, Berkeley, and University of California, San Francisco. She previously worked at Princeton Satellite Systems before pivoting to her doctorate. She graduated with a Bachelor of Science in Engineering from Princeton University in 2024 in chemical and biological engineering. Joyce Mo completed her Bachelor's thesis on ``Genetically-Encoded Biosensors for Branched Chain Amino Acid Metabolism and Branched Chain Higher Alcohol Production.'' Prior to graduation, she received the Stoll Fellowship and High Meadows Environmental Institute Scholarship for her research in the Jose Avalos laboratory. Her work also included computational modeling of yeast branched-chain amino acid gene regulatory networks. Additionally, Joyce has worked on projects in temperature control for thermally-heated outdoor spaces, reinforcement learning, and model predictive control of biological processes.

At PSS, Joyce was responsible for the design of a thermal management system for power electronics for plasmas, computational fluid dynamics analysis of varied hypersonic aircraft designs, and heat engine analysis. She was the project lead on the advancement of Space Rapid Transit, a two stage to orbit horizontal, fully-reusable launch vehicle, and a micro combined cycle power plant for spacecraft. Prior to her role at PSS, she completed internships at Sampled, Telethon Kids Institute, and a research exchange program at the Technical University of Munich in process engineering and water membrane flux analysis.

Layla Mohsen received her bachelor's degree in computer science from The American University in Cairo in 2025. As a Staff Scientist at Princeton Satellite Systems, Layla is responsible for designing and simulating a variety of aerospace systems. She has worked on the finite element analysis and control system of an induction coil gun for cold-launching deep space vehicles, which she presented at the European Conference for AeroSpace Sciences 2025. Layla has also worked on computational fluid dynamics of a Mach 4 hypersonic inlet for visualization of shock waves and flow separation. For her work in power electronics, Layla implemented predictive modeling for estimating the remaining useful life of components susceptible to failure during high power experimentation, such as power MOSFETs. Her current research involves the use of physics-informed machine learning for kinetic plasma simulations, with applications to PSS’ fusion reactor.

During her undergraduate degree, Layla specialized in artificial intelligence, embedded systems, and Internet of Things. Her undergraduate work included embedded machine learning (TinyML) for edge keyword detection on resource-constrained TinyFPGAs, machine leaning for exoplanet detection based on transit signals, and a robotic waste management system. As a research assistant, she contributed to Horizon-Europe’s Nature First initiative by working on computer vision models to monitor endangered wildlife in dark, noisy environments.