Simulation of Space Mission Scenarios

Simulation of Space Mission Scenarios

Functieomschrijving

Background

Space is becoming increasingly crowded. With thousands of active satellites, defunct spacecraft, and pieces of debris orbiting Earth, ensuring the safety and sustainability of space operations is more critical than ever. At NLR we’re working on tools and technologies to help space operators make informed decisions in this complex environment.

One of the key challenges NLR is tackling is how to simulate space mission scenarios in a realistic, flexible, and scalable way. These simulations are essential for testing and validating the functionalities we develop, whether it’s predicting close approaches between satellites, modeling long-term orbital evolution, or optimising orbital manoeuvres. This all falls under the broader umbrella of Space Situational Awareness (SSA): The ability to detect, track, predict, and most importantly to understand the behavior of objects in orbit and their interaction with the space environment.

Assignment

The assignment consists of the development of Python code that would allow a variety of space mission scenarios to be simulated (e.g. close approaches, satellite swarms, ASAT, satellite break-up event) in order to test and validate SSA related algorithms and functionalities that NLR develops. All these algorithms and functionalities are currently available through ARGUS, a dedicated NLR software tool specifically designed and built for active engagement in SSA. The tasks that are to be foreseen throughout this internship project are as follows:

• Literature study on existing and hypothetical space mission scenarios;
• Listing the mission scenarios of interest;
• Parameterisation of missions scenarios;
• Simulating the mission scenarios;
• Embedding the simulation software in ARGUS;
• Validating the quality of the simulations.

Result

The expected result of the internship project consists of the following deliverables:

• Project plan;
• Mid-term presentation;
• Final presentation;
• Final research report;
• Software user guide.

Vereisten

Profile

• Student in the field of aerospace engineering;
• Proficient in Python coding;
• Up to date with past and current space news;
• Experienced in astrodynamics;
• Experienced in numerical integration methods;
• Creative, coming up with own ideas;
• Assertive and self-motivated, capable of being part of the project team and also proceed individually.

What we offer

• A challenging internship project in a high-tech result orientated work environment;
• A chance to closely work together with multiple (space) disciplines;
• Being part of the SSA project team in developing new space insights;
• Weekly supervision and availability of the technical staff for support;
• An internship allowance;
• Working in an actual R&D project as part of the team;
• Learn from the NLR experience and get a better understanding of working at a company such as NLR;
• Social activities outside office hours (e.g. table tennis, pool & billiards, running, bouldering);
• Results to be used in the current and future projects.

About NLR

Royal NLR has been the ambitious research organisation innovating aerospace applications for over 100 years. With that goal, the world of transportation will be safer, more sustainable, more efficient and more effective. Royal NLR is on the threshold of breakthrough innovations. Over 800 driven professionals work on research and innovation, from aircraft engineers to psychologists and from mathematicians to application experts. By combining these various backgrounds and knowledge, Royal NLR has a unique position to develop novel ideas into next generation solutions.

This assignment will be mainly managed by the Space Situational Awareness group within the Aerospace Systems and Information Supremacy (ASIS) department.