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Record W2012043572 · doi:10.1117/12.914941

Control system modeling for the Thirty Meter Telescope primary mirror

2011· article· en· W2012043572 on OpenAlexfundno aff
Douglas G. MacMynowski, J. C. Shelton, Lewis C. Roberts, M. M. Colavita, Mark J. Sirota

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsnot available
FundersOntario Ministry of Research and InnovationBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaJet Propulsion LaboratoryAssociation of Canadian Universities for Research in AstronomyNational Aeronautics and Space AdministrationCalifornia Institute of TechnologyGordon and Betty Moore FoundationNational Science Foundation
KeywordsComputer sciencePrimary mirrorRobustness (evolution)Bandwidth (computing)TelescopeFocus (optics)System dynamicsVibrationRadio telescopeSimulationControl theory (sociology)OpticsAcousticsPhysicsControl (management)Artificial intelligenceTelecommunications

Abstract

fetched live from OpenAlex

The Thirty Meter Telescope primary mirror is composed of 492 segments that are controlled to high precision in the presence of wind and vibration disturbances, despite the interaction with structural dynamics. The higher bandwidth and larger number of segments compared with the Keck telescopes requires greater attention to modeling to ensure success. We focus here on the development and validation of a suite of quasi-static and dynamic modeling tools required to support the design process, including robustness verification, performance estimation, and requirements flowdown. Models are used to predict the dynamic response due to wind and vibration disturbances, estimate achievable bandwidth in the presence of control-structure-interaction (CSI) and uncertainty in the interaction matrix, and simulate and analyze control algorithms and strategies, e.g. for control of focus-mode, and sensor calibration. Representative results illustrate TMT performance scaling with parameters, but the emphasis is on the modeling framework itself.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.936
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.218
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2011
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdaptive optics and wavefront sensingFrench-language works237,207