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Challenges and Opportunities in Advancing CubeSat Technologies for Good Space Stewardship: A Regulatory and Technological Perspective

2025· article· W4416233731 on OpenAlex
Sajad Saraygord Afshari, Elham Baneshi, Daniel Agyei Asante, Philip Ferguson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCubeSatSoftware deploymentPayload (computing)PropulsionOrbital decaySatelliteSpace debrisOrbit (dynamics)

Abstract

fetched live from OpenAlex

The exponential growth in CubeSat deployments has revolutionized access to space, democratizing opportunities for education, research, and commercial ventures. Yet, this expansion comes at a cost—a growing concern over space debris and orbital congestion. Regulatory agencies, including Transport Canada and the US Department of Transportation, have established guidelines to ensure responsible satellite operations, mandating deorbiting within five years of mission completion and collision avoidance measures. However, these regulations often exceed the technical capabilities of current CubeSat platforms, especially in Sunsynchronous orbits (SSOs) exceeding 600 km in altitude. This paper addresses the critical disconnect between regulatory ambitions and CubeSat technologies. We analyze the impact of deorbit regulations on the design and operation of 1U, 3U, and 6U CubeSats, focusing on propulsion and passive deorbiting solutions. Orbital simulations are conducted to evaluate the ΔV requirements for compliant deorbiting from various altitudes, emphasizing the challenges of incorporating sufficient propellant within the stringent mass and volume constraints of CubeSats. The study highlights commercially available monopropellants and their integration challenges, alongside a survey of alternative mechanisms such as drag sails and electrodynamic tethers. Our findings reveal that while lower orbital altitudes facilitate passive deorbiting within regulatory timelines, they significantly constrain mission utility and operational lifespan. We demonstrate that drag sails, although effective in reducing orbital decay time, impose substantial penalties on payload mass and stowage volume. Similarly, electrodynamic tethers, though promising, face deployment reliability and power generation challenges. We also present a case study of the propulsion system of the LISSA satellite built in STARLab at the University of Manitoba to illustrate the complexities of regulatory compliance, from pressure vessel certifications to launch vehicle-specific requirements. The discussion extends to the implications of using mass dummies during vibrational testing and the logistical hurdles of on-site fueling, underscoring the interplay between engineering decisions and regulatory constraints. In light of these challenges, we propose actionable recommendations to harmonize regulatory objectives with technological advancements. These include fostering collaborations between regulatory bodies and industry stakeholders, incentivizing research into miniaturized propulsion systems, and developing standardized protocols for passive deorbiting devices. By aligning regulatory frameworks with the realities of CubeSat engineering, we can pave the way for more sustainable and responsible space operations. This paper contributes to the ongoing discourse on space stewardship by providing a comprehensive analysis of the regulatory and technological landscape for CubeSats. It underscores the urgency of addressing the existing gaps to ensure that CubeSats remain a viable and responsible tool for advancing space science and industry. The insights gained from this study will inform future CubeSat missions and regulatory policies, fostering a culture of sustainability and innovation in small satellite operations. We invite collaboration and feedback from academia, industry, and regulatory agencies to drive this critical agenda forward.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.260
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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