System Integration and Verification Approach for Large-Scale Space Power Systems
Bibliographic record
Abstract
When we define a large-scale system, a typical example would be a space development project. When we talk about large-scale systems in space development, there is the International Space Station (ISS), which was proposed by NASA in the 1980s as a manned space station, and which Japan, ESA, Canada, and later Russia joined as international partners. Japan's unique space transportation system, rocket development, began in the 1970s, and has a history of development of the H-1, H-2, and the new H-3, making it a largescale system promoted by Japan. In addition, the satellite carried on the third H-3 is called ALOS-4, which has an earth observation mission, and is a large satellite that weighs 3 tons and is 20 meters long when the solar paddles are deployed, so it can be said to be a large-scale system. In this paper, the author looks back on and explains the integration and verification of the International Space Station from development to operation, focusing on the development of large-scale space power systems, their integration, and verification. In addition, from a comparative perspective, the integration and verification of Japanese rocket development is compared with the ISS. The conceptual and basic design of the International Space Station began in the 1980s, and in-orbit assembly began in 1998. It is scheduled to be completed in 2011 and to end its role in 2030. Looking back at the history of the ISS, there are broadly a design phase, a development phase, and an assembly phase, and the operation phase began after in-orbit assembly began. In these phases, test verification and integration tests were conducted according to the phase at that time. The International Space Station, a large-scale space system, initially had an extremely high-risk assembly scenario in which elements and modules from each country were launched, connected in orbit, and element-to-element integration and verification tests were conducted for the first time. In this paper, the author describes how the problems and challenges of integration and verification of the International Space Station, an international collaborative program, have been solved, and attempts an overall evaluation of the development of such a large-scale system.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".