Thermal performance prediction of the TMT telescope structure
Bibliographic record
Abstract
Thermal analysis for the Thirty Meter Telescope (TMT) structure was performed using finite element analysis in ANSYS and I-DEAS. In the thermal analysis, the telescope structural parts with simplified optical assembly systems were modeled for various thermal conditions including air convections, conductions, heat flux loadings, and radiations. Thermal responses of the TMT telescope structure were predicted and the temperature distributions of the optical assembly systems were calculated under sample thermal loading conditions. The thermo-elastic analysis was made to obtain the thermal deformation based on the resulting temperature distributions. The line of sight calculation was made using the thermally induced structural deformations. The goal of this thermal analysis is to establish thermal models by the FEA programs to simulate for an adequate thermal environment. These thermal models can be utilized for estimating the thermal responses of the TMT structure. Thermal performance prediction of the TMT structure will be able to guide us to control and maintain the system from the "seeing" effects.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".