Large Bondspot RTV Adhesion for NFIRAOS OAPs
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.
Bibliographic record
Abstract
The Narrow Field Infrared Adaptive Optics System (NFIRAOS) within the Thirty Meter Telescope (TMT) will unlock new potential for ground-based astronomy. This subsystem is a series of optics that correct for atmospheric turbulence seen in the Infrared wavelength. One of the critical challenges in the NFIRAOS system is the ability to operate at -30 degrees Celsius. The use of RTV (Room Temperature Vulcanizing) silicone as an adhesive allows a more flexible bond between the optic and its mount. This material is capable of withstanding temperature changes without losing bond strength. Additionally, the large Off Axis Parabola (OAP) mirrors provide a unique technical challenge in their mounting configurations. The optics have with a mass of 90 kilograms and must be mounted able to withstand a 50-degree temperature differential from their ambient temperature bonding. This paper builds of initial conceptual and prototyping work done by ABB and provides the next steps scaling towards a final design of large RTV bondspot optical mounting. Through a combination of simulations, iterative prototyping, room temperature and operational temperature stress testing, a final design proposal is presented backed by statistical and in-house life cycle testing methods. The findings in this work have applications as the industry moves towards mounting larger optics in increasingly challenging environments.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it