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Record W2325143215 · doi:10.2514/6.2011-7317

A Thermal Anemometer for the Mars Meteorological Sensor Network

2011· article· en· W2325143215 on OpenAlexaff
Anas Alazzam, Linh Ngo Phong, M. G. Daly

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpacecraft and Cryogenic Technologies
Canadian institutionsYork UniversityCanadian Space Agency
Fundersnot available
KeywordsAnemometerMars Exploration ProgramEnvironmental scienceMeteorologyRemote sensingThermalComputer scienceAerospace engineeringWind speedGeologyAstrobiologyPhysicsEngineering

Abstract

fetched live from OpenAlex

Details of the design and simulation of a thermal micro anemometer intended for Mars meteorological measurements are presented. The device consists of a double sided anemometer formed on thermal isolation aerogel. Thermal input to the device is provided by a set of Pt hot films distributed evenly in an octagonal area of an AlN substrate. A thin film resistance-temperature detector (RTD) is coupled to the edge of each heater for temperature reading as the thermal distribution on the substrate changes with wind speed and direction. Finite element modeling of the device showed that the temperature gradient between the upstream and downstream RTDs increases with increasing distance from the hot film and decreases with increasing wind speed. Evaluation of the device transfer function suggested that it could be suited for measuring wind speeds of up to 60 m/s with a resolution in the order of 1 m/s. These characteristics are comparable with the requirements of past Mars missions. The configuration of the device allows also the evaluation of the out-of-plane component of wind speed and of the wind direction. It was found that quadratic fitting function based on the highest temperature readings of the distributed RTDs could be used to determine more accurately the wind direction.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.569

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.201
Teacher spread0.167 · 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 designNot applicable
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

Citations1
Published2011
Admission routes1
Has abstractyes

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