Space Environment

Learning Outcomes

Full CEng Programme Level Learning Outcomes

Having successfully completed this module you will be able to:

• Design solutions for complex problems that evidence some originality and meet a combination of societal, user, business and customer needs as appropriate. This will involve consideration of applicable health & safety, diversity, inclusion, cultural, societal, environmental and commercial matters, codes of practice and industry standards: For the summative assignment tasks students must develop an overall methodology for evaluating a space mission design, taking into account aspects of space sustainability that include economic and societal factors, including some related to equality, diversity, and safety. Students will also gain an understanding of cultural factors within the scope of space sustainability, including the importance of astronomical observations within Indigenous cultures, and will apply this to their over evaluation. Part of the evaluation will address the implications for different peoples and cultures, including customers, and the role of codes of practice and space industry standards in mitigating adverse impacts.
• Apply an integrated or systems approach to the solution of complex problems: Students will gain an understanding of systems thinking approaches for addressing the complexity associated with designing space systems to operate in a safe and sustainable manner. For the summative assessment tasks students must adopt an appropriate modelling methodology to perform an evaluation of a space system design and must recognise and address the interdependencies between the space system and the environments it interacts with.
• Communicate effectively on complex engineering matters with technical and non-technical audiences, evaluating the effectiveness of the methods used: For the summative assessment tasks students must provide a written and oral summary of their approach to a space system assessment, the results obtained, and a reflection on the effectiveness of the methods used. The tasks also include the provision of a lay summary, aimed at a general audience.
• Apply a comprehensive knowledge of mathematics, statistics, natural science and engineering principles to the solution of complex problems: Near-Earth space is arguably a human environment and, as such, is connected to and interacts with the more familiar terrestrial environments and human socio-economic systems. Consequently, it can be seen as (part of) a complex system of systems. When designing human and robotic missions to the space environment one must consider the implications of the space environment on the mission design and vice versa. The commercialisation of space and particularly the growth of large constellations of satellites has made understanding these implications an important and topical task. For the summative assessment tasks students must demonstrate their ability to understand these issues comprehensively, using mathematical and statistical models that make use of engineering principles to solve or evaluate key challenges associated with operating in the space environment.
• Formulate and analyse complex problems to reach substantiated conclusions. This will involve evaluating available data using first principles of mathematics, statistics, natural science and engineering principles, and using engineering judgment to work with information that may be uncertain or incomplete, discussing the limitations of the techniques employed: For the summative assessment tasks students must present a working hypothesis associated with the impact of a space environmental factor (or factors) on a space system design, identify an appropriate modelling methodology to test their hypothesis, generate results and present their conclusions, taking into account the limitations of the techniques employed. This will require analysis using available data and data generated through the chosen methodology using first principles of mathematics, statistics, natural science, and engineering principles. It will require use of engineering judgement to work with information, data, and results that may be uncertain or incomplete.
• Select and apply appropriate computational and analytical techniques to model complex problems, discussing the limitations of the techniques employed: Students are provided with an understanding of models and modelling, and of specific computational modelling approaches for understanding and making predictions of space environmental factors. They also have access to a set of simple computational models (in Microsoft Excel) for addressing some aspects of spacecraft or mission design. Students are assessed based on an appropriate selection and application of modelling techniques to perform an evaluation of a space system design in the context of different space environmental factors. Students must provide a rationale for the approaches adopted and a reflection on their limitations.

1. The Space Environment: Natural and Anthropogenic Factors:

• Launch, Vacuum, Microgravity, and Radiation
• -- Effects on materials and spacecraft design
• -- Effects on human physiology and countermeasures
• Space Debris
• -- Remote and in-situ measurement
• -- Hazards, including re-entry
• -- Impacts on spacecraft design and operation:
• ----- Space debris mitigation, protection, and remediation
• ----- Large constellations of satellites
• -- Safety of spaceflight and space traffic management
• Space Weather
• -- Types of space weather
• -- Impacts of space weather on spacecraft design and operation
• Space Climate
• -- Space climate drivers, solar and anthropogenic
• -- Impacts of space climate change on spacecraft design and operation
• -- Impacts of space climate change on space debris

2. Space Sustainability:

• Definitions and understanding of space sustainability
• Orbital carrying capacity
• Environmental, economic, and social factors:
• ----- Investment, insurance, and the role of ESG
• ----- Spacecraft operational burdens
• ----- Dark and Quiet Skies
• ----- Environmental pollution
• Impacts on spacecraft design and operation
• Implications for and of large constellations of satellites
• Case studies

3. Computational Modelling for Space Debris and Space Sustainability:

• Introduction to modelling
• Kessler's models:
• ----- Collision frequency of artificial satellites and the 'Kessler Syndrome'
• ----- Critical number of objects in low Earth orbit
• System dynamics, Particles-in-a-Box, and source-sink models
• Engineering models and assessment models
• Evolutionary models
• ----- Monte Carlo Simulation
• ----- Support models for orbital propagation, collisions, and breakups
• ----- Other support models including concepts of operation and satellite reflection
• Re-entry models
• Case studies

Teaching methods include:

Lectures and Seminars with discussions

Tutorials (focused on assessment tasks)

Learning activities include:

Directed reading

Discussions focused on challenging topics

Computer-based activities

Formative

This is how we’ll give you feedback as you are learning. It is not a formal test or exam.

Paper proposal

• Assessment Type: Formative
• Feedback: Written feedback will be provided
• Final Assessment: No
• Group Work: No

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.