On the Importance of Spacecraft Environment Analyses

The development and design of a spacecraft involves an extreme amount of analysis and testing which reflects many state-of-the-art technologies. On one side, a complex system  with the capabilities to meet mission objectives has to be designed ensuring a successful operation with the subsystems. These include a wide range of departments such as Structures, Communication, Mission Planning and Operation. 

On the other hand, the spacecraft interacts with its environment causing multiple types of physical phenomena to be addressed. In the end, the environment dictates the final configuration.

Credit: https://www.esa.int/Safety_Security/Solar_Hazards

Before the mission, the relevant space environment must be investigated and different phenomena must be studied. The spacecraft interacts with its environment through passive mechanisms such as ambient particles, energetic photons or active mechanisms such as plume interactions, outgassing effects. These include but not limited to;

  • Thermal
  • Charging 
  • Radiation
  • Plume Interaction
  • Debris
  • Atmospheric Effects

These phenomena can be studied by two major approaches;

  • On-ground experiments: These types of studies offer accurate representation of the mechanisms but require huge infrastructure which are quite expensive especially for large scale models and close modeling of actual space environment.

ESA Phenix Thermal Vacuum Chamber

  • Numerical Simulations: These types of studies offer great flexibility in terms of model scale, environment conditions. There is still a medium size investment needed for the engineering software, know-how to use such approaches. Considering the recent advances in scientific computing, considerable savings are possible that mitigates time and budget cost.

Plume Expansion from Two Thrusters Interacting with the Spacecraft

The best approach is to use a mixture of experimental and numerical studies together to get most reliable results. At Altaventus, we mainly conduct our studies through numerical simulations where we make use of well-established community software or developed in-house tools. Some examples include;

  • Sparta (Stochastic PArallel Rarefied-gas Time-accurate Analyzer), is parallel Direct Simulation Monte Carlo code for performing simulations of low-density gases in 2d or 3d developed at Sandia National Laboratories (SNL). It can be used for multiple applications such as plume interaction and outgassing
  • SPIS (Spacecraft Plasma Interaction Software), is a toolkit for spacecraft-plasma interactions and spacecraft charging modeling developed by the ESA, ONERA, Artenum and University Paris 7.
  • GMAT (General Mission Analysis Tool), is a NASA software system for trajectory optimization, mission analysis, trajectory estimation, and prediction.
  • Spenvis (Space Environment Information System), SPENVIS is a comprehensive tool providing space engineers and scientists with information on the space environment and its likely effects on space systems.
  • GAUSS (GAs-dynamics with UnStructured meshes and Scalability), is an in-house developed scientific software that can model multiscale problems and high Mach number, high temperature, plasma and low density environments developed in C++ and MPI. We will discuss the features and use cases of GAUSS in more detail in our next blog post. 

Integration of these kinds of numerical simulations into the workflow, results in many benefits in terms of;

  • Sweeping the design space efficiently
  • Modeling the actual space environment more accurately
  • Investigating failure scenarios with greater flexibility
  • Providing quantitative insights to experimental campaigns
  • Having a cost-effective and sustainable analysis framework

Most of the time, such analyses require repetitions at different configuration settings (e.g. orbit parameters, operation conditions, space activity level). These are called many-query problems and obtaining high-fidelity results require considerable hardware and computation budget. 

Within this decade, impressive leaps have been observed using optimization, uncertainty quantification and surrogate modeling. Especially, the recent advances in machine learning can  be extended to such deterministic problems, through Physics Based Machine Learning, to provide an extreme level of insight with low cost. These critical technologies enable designs which are high performance and robust, which deserve a dedicated post of their own.

Space navigation is a continuation of hundreds of years of collective navigation experience but space missions are challenged by more significant difficulties. We develop better technology, build on top of space heritage and reflect on our failures which makes it possible to expand our capabilities with ever-increasing complexities. We should bear these points in mind while reminding ourselves that in space you are as strong as your weakest link. Using numerical simulations is a powerful way to locate and reinforce such links for successful missions.

If you have a related problem in your business that require more in depth discussion, don’t hesitate to contact us. 

Contact us on LinkedIn or fill out the contact form our the front page.