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March 21, 2026Journal of Electric Propulsion0 citationsOpen Access

Surrogate Modeling and Optimization of Propellant Mixtures for Hall Thrusters

Surrogate modeling and real-time optimization of propellant mixtures for hall thrusters

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Authors

PTPeter ThoreauAJA. JohansenMHMichael Holmes

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Overview

Autonomous modeling optimizes propellant mixtures in thrusters, highlighting cost-saving opportunities.

Key Points

  • The aim is to optimize propellant mixtures for Hall effect thrusters to minimize mission costs.
  • Applied Bayesian optimization using a Gaussian Process Regression model
  • Utilized experimental telemetry data for real-time model updates
  • Considered a notional asteroid-rendezvous mission for optimization goals
  • Found a mixture ratio of 11:87:2 reduces total mission cost by 7% compared to pure xenon
  • Identified dependence of optimal mixtures on storage technologies and price fluctuations
  • Results align with trends in commercial market towards cheaper propellants

Cite This Study

Thoreau et al. (2026) studied this question.

synapsesocial.com/papers/69be36bf6e48c4981c675dd2https://doi.org/10.1007/s44205-026-00188-8
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