Certification of electronic components for space applications: Analysis of environmental factors and validation processes
Bibliographic record
Abstract
This thesis addresses the challenge of certifying electronic components for space applications, within a context where access to orbit has become increasingly democratized thanks to the rise of small satellites and the widespread use of commercial components. The main objective is to analyse the environmental factors that affect electronic systems in space, define the associated validation requirements, and propose a practical methodological framework that allows universities, startups, and SMEs to ensure reliability without relying solely on costly industrial certification processes. The methodology begins with a comprehensive study of the space environment, covering radiation, microgravity, vacuum, atomic oxygen, thermal extremes, electromagnetic interference, and the impact risks posed by micrometeoroids and debris. Building on this foundation, the thesis reviews international standards and certification protocols, focusing on environmental, electrical, functional, and reliability testing. A comparative analysis is performed between tests that can be conducted with limited infrastructure and those requiring specialized facilities, in order to establish a feasible roadmap for resource-constrained projects. The framework is then applied to a set of ten representative CubeSat components, evaluating for each case the essential tests, the dispensable ones, and the mitigation strategies available. The results are consolidated into a database summarizing the qualification level achieved and the limitations identified. Findings demonstrate that, through careful test selection, the adoption of adequate materials and mitigation strategies, and the support of European certification initiatives, commercial components can be successfully adapted for use in demanding orbital environments. In conclusion, this work provides a reference model that bridges the gap between commercial electronics and aerospace applications, offering a balanced approach that optimizes resources while maintaining acceptable levels of reliability. Strategic recommendations are presented to strengthen the competitiveness of nanosatellite projects in Europe, and future research directions are outlined regarding the certification and qualification of electronic components.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".