Time-dependence in mantle convection models featuring dynamically evolving plates
Bibliographic record
Abstract
We present the findings from a study of 2-D Cartesian geometry mantle convection simulations carried out to determine how plate velocities and the surface and basal heat flux respond to an evolving plate geometry. We model flow for periods equating to hundreds of millions of years and find that while calculations that feature fixed plate geometries exhibit regular reversals in plate motion, this behaviour is absent in models featuring evolving plate boundaries. However, simulations featuring evolving plate boundaries and plates with either a fixed-thickness or temporally varying thickness are highly time-dependent and their globally averaged mean plate velocities are higher than in simulations featuring static plate geometries. Our models featuring evolving plate geometries assume that (1) young plates override old plates with the velocity of the younger plate and (2) that symmetric seafloor spreading occurs at divergent plate boundaries. Plate velocities are dynamically determined in accord with a force-balance modelling approach and the plate velocities determine the dynamic evolution of the plate boundaries according to criteria (1) and (2), above. Plates in our calculations are highly viscous and are treated as rigid blocks for the purpose of determining whether they will break according to a yield stress criterion. The modelling of plate rifting means that both the number and mean size of the plates in our calculations are time-dependent. We focus on isolating the influence of plate thickness on time-dependent flows and examine the time-dependence of global plate velocities and mantle and core heat flow. In an initial study of unit aspect ratio models we find that there is a transition in the character of time-dependent behaviour as the model plate thickness is increased. Plates that are comparable in thickness to the mean thickness of the thermal boundary layer exhibit periodic reversals. Plates that are much thinner than the thermal boundary layer exhibit no reversals. Intermediate thickness plates reverse intermittently. In aspect ratio 12 calculations, we find that the mean global plate velocity can exhibit variations of more than a factor of two over periods of tens of millions of years. We also find that the mean surface velocity of the plates and the mean global heat flux rise and fall in tandem (although high frequency variations in the global velocity are not reflected in the heat flux time-series). In a simulation spanning almost 3 Gyr we observe several instances of surface heat flux fluctuations of 40–50 per cent occurring within periods of 75–200 Myr.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".