Bibliographic record
Abstract
Abstract The continuous development of space exploration technology requires more efficient and economical space transport systems, and there is an urgent need for propulsion systems that are more efficient than chemical propulsion. Solar thermal propulsion (STP) systems have a relatively small size and high specific impulse, thus offering performance advantages in specific space missions. An STP system is generally composed of a concentrator, heat exchanger core, nozzle, and propellant supply system. The concentrator typically uses parabolic mirrors to concentrate sunlight to heat the heat exchanger core at a focal point. The propellant is heated when it flows through the heat exchanger core and is finally expanded and accelerated by a Laval nozzle to generate thrust. In this propulsion mode, the propulsion system can generate a Newton-level thrust by using an expandable whirling-membrane concentrator with an area of approximately 10 m2 to collect solar radiation. Because hydrogen has a small molar mass and can generate a high exhaust velocity, it is an ideal propellant for solar thermal thrusters. The theoretical specific impulse of an STP using hydrogen as a propellant can reach 800 s. However, the low molar mass of hydrogen also reduces the thrust that the engine can provide, limiting the STP system to low-thrust space missions. The main applications of STP systems are orbit transfer and interplanetary exploration, which require a thrust level between 0.1 and 40 N. Figure 1.1 compares the thrust ranges and specific impulse ranges of several common propulsion methods. Chemical propulsion has a large thrust and a low specific impulse, and electric propulsion has a high specific impulse but a very small thrust. Within the size range of currently achievable spacecraft platforms, the specific impulse and thrust characteristics of STP systems are very attractive, and their high specific impulse and moderate thrust fill the gap between chemical and electric propulsion systems; as such, they are expected to be used to increase the payload ratio of orbital transfer vehicles (OTVs) or orbital maneuvering vehicles (OMVs).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.609 | 0.446 |
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".