Proving the Concept of Cold Spray as a Technology for Repair and Additive Manufacturing in Space Environment
Bibliographic record
Abstract
Cold spray is increasingly emerging as a breakthrough technology for repairing damaged parts and ad- ditive manufacturing. In this solid-state process, a heated and pressurized inlet gas accelerates metallic particles to very high speeds through a supersonic expansion in a convergent-divergent De Laval nozzle. The plastic deformation of particles upon impact with a substrate activates the adhesion mechanisms. The stacking of deformed particles forms the deposited material. Compared to other additive manufacturing technologies, cold spray equipment (especially the low-pressure version) is relatively compact, making it suitable not only for repairing and producing space components on Earth but also for direct use in space. This study aims to investigate the behavior of low-pressure cold spray equipment under vacuum condi- tions, simulating the space environment through both numerical and experimental analyses. When cold spray is operated under ambient pressure, the jet flow exiting the nozzle is over-expanded. However, in a low-pressure environment, the jet flow becomes under-expanded, further increasing particle velocity. Consequently, the deposition process, primarily driven by the kinetic energy of accelerated particles, be- comes more efficient in vacuum conditions. Nevertheless, the unique challenges of the space environment, such as material recovery, recycling, and maintaining spacecraft attitude control during the process must be addressed to ensure successful implementation. Computational Fluid Dynamics (CFD) simulations, employing a validated approach for multiphase flows in solid rocket nozzles, are being conducted to inves- tigate the effects of reduced ambient pressure on cold spray flow conditions. The two-phase flow consists of nitrogen as the carrier gas and spherical aluminum particles of 50μm diameter. On the experimental side, cold spray deposition is performed in a vacuum chamber at an operating pressure of 6 kPa. For com- parison, the system is also operated under standard conditions (ambient pressure in the chamber), to assess the influence of external pressure on deposition efficiency and on the quality of the deposited material. Finally, microstructural characterizations and mechanical testing will be carried out to compare samples produced under standard atmospheric conditions with those created in a vacuum. These analyses provide valuable insights into the effects of low-pressure environments on the properties of cold sprayed materials, paving the way for the optimization of the process for space applications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".