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Record W4322010012 · doi:10.5194/egusphere-egu23-10164

Where curling stones collide with rock physics: Cyclical damage accumulation and fatigue in granitoids

2023· preprint· en· W4322010012 on OpenAlexaff
Derek D.V. Leung, Florian Fußeis, Ian S. Butler

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsLaurentian University
Fundersnot available
KeywordsCurlingGeologyGeotechnical engineeringMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Fatigue and damage accumulation in granitoids are classical, but poorly characterised, rock mechanics problems. In order to explore these phenomena, we consider colliding curling stones as a rock physics experiment. Curling stones are made using granitoids from either Ailsa Craig (Scotland) or Trevor (North Wales), which are chosen for their uniformity, strength, and durability. During a curling game, stones are slid over an ice sheet and made to collide along a circumferential striking band. From a rock physics perspective, the collision of curling stones can be modelled as unconfined uniaxial compression of two convex surfaces under well defined boundary conditions. A curling stone experiences about 2900 collisions per season and is played for 10-15 years before refurbishment, which provides a unique long-term opportunity to study fatigue and damage accumulation under cyclic loading.Here, we first determine the stress magnitudes and strain rates of head-on curling stone impacts using a series of on-ice experiments involving a high speed camera and pressure-sensitive films. We then characterise the observed damage that these collisions produce on the centimetre and micrometre scale using photogrammetry, synchrotron microtomography, optical microscopy, and backscattered electron imaging. We show that during each impact, a curling stone is stressed to at least 300-680 MPa (for a maximum-velocity scenario of 2.9±0.1 ms-1), which exceeds the unconfined compressive strength of the rocks (232-395 MPa; Nichol, 2001, J. Gemm. 27/5). Over its lifetime, a curling stone thus experiences thousands of impacts that will cause damage. The strain rates of these impacts (24±4 s-1) most closely resemble seismic magnitudes, suggesting that the impacts are dynamic in nature. This is supported by the type of damage observed in aged curling stones: (1) Hertzian cone fractures, (2) ejection of rock powder during collisions, and (3) minor spalling microcracks. Most samples show damage being confined to macroscopic Hertzian cone fractures and their immediate collet zones in the relatively narrow striking band. Within the striking band, the circumferential density of cone fractures is limited to about 2-2.5 fractures/cm. Surprisingly, damage does not appear to extend beyond about 3-5 cm into the stones along a radial direction.Our observations allow us to formulate a model for damage evolution in curling stones. We infer that high-velocity/high-stress impacts initiate cone fractures up to a specific spatial density. As they mature over repeated impacts in the same regions of the striking band, cone fractures progressively propagate and coarsen with subsequent collisions, concentrating and channelling the accumulating damage. This damage geometry is surprisingly effective in shielding the rest of the stones from the reaching critical stress levels for damage. Our findings are significant for applications where rocks are exposed to large numbers of high-stress impacts and suggest that a relatively narrow damage zone can dampen even high-impact stresses over a relatively moderate network of fractures.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.043
GPT teacher head0.294
Teacher spread0.251 · 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 designBench or experimental
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

Citations0
Published2023
Admission routes1
Has abstractyes

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