Primary mirror dynamic disturbance models for TMT: vibration and wind
Bibliographic record
Abstract
The principal dynamic disturbances acting on a telescope segmented primary mirror are unsteady wind pressure (turbulence) and narrowband vibration from rotating equipment. Understanding these disturbances is essential for the design of the segment support assembly (SSA), segment actuators, and primary mirror control system (M1CS). The wind disturbance is relatively low frequency, and is partially compensated by M1CS; the response depends on the control bandwidth and the quasi-static stiffness of the actuator and SSA. Equipment vibration is at frequencies higher than the M1CS bandwidth; the response depends on segment damping, and the proximity of segment support resonances to dominant vibration tones. We present here both disturbance models and parametric response. Wind modeling is informed by CFD and based on propagation of a von Karman pressure screen. The vibration model is informed by analysis of accelerometer and adaptive optics data from Keck. This information is extrapolated to TMT and applied to the telescope structural model to understand the response dependence on actuator design parameters in particular. Whether the vibration response or the wind response is larger depends on these design choices; "soft" (e.g. voice-coil) actuators provide better vibration reduction but require high servo bandwidth for wind rejection, while "hard" (e.g. piezo-electric) actuators provide good wind rejection but require damping to avoid excessive vibration transmission to the primary mirror segments. The results for both nominal and worst-case disturbances and design parameters are incorporated into the TMT actuator performance assessment.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".