MétaCan
Menu
← Back to cohort
Record W3116749952 · doi:10.1002/essoar.10505629.1

Coupled shape and spin evolution of Bennu due to the YORP effect

2020· article· en· W3116749952 on OpenAlexaff
J. H. Roberts, Yun Zhang, O. S. Barnouin, Patrick Michel, D. C. Richardson, M. C. Nolan, M. G. Daly, J. A. Seabrook, E. E. Palmer, Robert E. Gaskell, J. R. Weirich, M. Al Asad, C. L. Johnson, L. Philpott, D. S. Lauretta

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsUniversity of British ColumbiaYork University
Fundersnot available
KeywordsEmail authenticationWorld Wide WebElectronic mailComputer science

Abstract

fetched live from OpenAlex

The rotation rate of (101955) Bennu has been observed to increase, providing evidence of the YORP effect in action. Bennu is a rubble pile with little strength. At the current spin-up rate, the rotation would result in large-scale disruption in <1 My. Such an extreme scenario is predicated on the YORP torque continuing to increase the rotation. However, YORP is sensitive to the shape and can change on a short timescale as small episodes of failure can increase oblateness, reduce spin rate, and redistribute rubble on the surface. A more comprehensive model of the shape and spin evolution of Bennu is required to understand its past and future. Here, we calculate the YORP torque on a shape model of Bennu. For a random distribution of rubble, the torques on individual blocks should cancel, and the large-scale structure should control the YORP response. However, we find the calculated torque is strongly dependent on the resolution of the shape model used, suggesting that the smaller material has an influence. As the surface roughness of the model increases, the magnitude of the torque and even its sign may change. Spin rate increases that more closely match measurements are obtained with increasing small-scale roughness. Simulated models that are coarser in resolution, but possess greater roughness than the equivalent lower-resolution shape model from observations, likewise are more consistent with the observed spin-up rate. We find that surface roughness with a non-random orientation controlled by large-scale structure determines the YORP torque. Following [1], we model the evolution of a rubble pile with Bennu’s shape subject to YORP using the granular modeling tool pkdgrav and explore how the torques change as the object is deformed. The YORP torques are calculated on the present shape and applied until particles begin to move. The torques are then recomputed on the new shape, and the iteration continues. We find negligible change in the torque until the rotation period decreases to 3.6 hr from its current 4.3-hr period. At 3.53 hr, the asteroid starts to lose mass from the equator. Our results suggest that the deformation of the asteroid’s shape due to YORP does not strongly alter rotation, and that if the initial shape is known to sufficient accuracy, the future shape and spin can be predicted. [1] Cotto-Figueroa D. et al. (2015) ApJ 803, 25.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicAstro and Planetary Science→French-language works237,207→