Phoenix Mars Lander Mission: Thermal and CFD Modeling of the Meteorological Instrument based on Flight Data
Bibliographic record
Abstract
The Phoenix Mars Lander, launched on August 4, 2007, landed in the northern Vastitas Borealis region on May 25, 2008 and operated successfully in this harsh environment for more than five months (far beyond its planned 90-day lifespan). The Lander was equipped with instruments designed to investigate the Martian mineralogy, geochemistry and atmosphere. One of these instruments, the Canadian Meteorological Instrument (MET), has successfully measured the location and the extent of clouds, fog and dust in Mars’ lower atmosphere, as well as the gas temperature and pressure. These measurements have provided Canadian scientists a unique opportunity to study the Martian atmosphere and enhanced the understanding of Canadian expertise of the red planet. The MET instrument was composed of multiple elements in order to fulfil the science objectives. The MET Light Imaging Detection and Ranging (LIDAR) probed the atmosphere by sending out laser pulses and measuring the backscattered returns. The MET mast, instrumented with three thermocouples, measured the atmosphere temperature at three different heights; and a Telltale, installed at the tip of the mast, measured wind speed and direction. The upper Payload Electronic Box (PEB) housed the MET barometric pressure sensor and the MET main electronics. From this successful mission, substantial amounts of data were collected to satisfy the science goals, but very few data for validation and correction of the instrument measurements. In the thermal design and analysis of the MET instruments, many assumptions were made. One of the key assumptions was the determination of the proper convective heat transfer coefficients between the instrument surfaces and Martian atmosphere, applicable both inside and outside the instrument. These coefficients determined from empirical relations were then corrected using heat balance tests on Earth under simulated conditions, taking into account the difference in gravity, pressure, density and gas compositions on Mars. This paper will present the results of the thermal and Computational Fluid Dynamics (CFD) analyses of the LIDAR and the full Lander, based on environmental thermal conditions determined from meteorological measurements of the Martian atmosphere in combination with a simplified thermal atmospheric tool. Special attention will be focussed on the determination of the convective heat transfer coefficients, both through classical empirical relations and the CFD analysis.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".