Evidence map›Paper›PMID 35265590›Full record

ArticleFrontiers in bioengineering and biotechnology2022

A Coupled Biomechanical-Smoothed Particle Hydrodynamics Model for Horse Racing Tracks.

Simon M Harrison, R Chris Whitton, Susan M Stover, Jennifer E Symons, Paul W Cleary

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Simon M HarrisonData61, CSIRO, Clayton, VIC, Australia.
R Chris WhittonFaculty of Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, VIC, Australia.
Susan M StoverSchool of Veterinary Medicine, University of California, Davis, Davis, CA, United States.
Jennifer E SymonsUniversity of Portland, Portland, OR, United States.
Paul W ClearyData61, CSIRO, Clayton, VIC, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Distal limb injuries are common in racing horses and track surface properties have been associated with injury risk. To better understand how track surfaces may contribute to equine limb injury, we developed the first 3D computational model of the equine hoof interacting with a racetrack and simulated interactions with model representations of 1) a dirt surface and 2) an all-weather synthetic track. First, a computational track model using the Smoothed Particle Hydrodynamics (SPH) method with a Drucker-Prager (D-P) elastoplastic material model was developed. It was validated against analytical models and published data and then calibrated using results of a custom track testing device applied to the two racetrack types. Second, a sensitivity analysis was performed to determine which model parameters contribute most significantly to the mechanical response of the track under impact-type loading. Third, the SPH track model was coupled to a biomechanical model of the horse forelimb and applied to hoof-track impact for a horse galloping on each track surface. We found that 1) the SPH track model was well validated and it could be calibrated to accurately represent impact loading of racetrack surfaces at two angles of impact; 2) the amount of harrowing applied to the track had the largest effect on impact loading, followed by elastic modulus and cohesion; 3) the model is able to accurately simulate hoof-ground interaction and enables study of the relationship between track surface parameters and the loading on horses' distal forelimbs.

Indexed as

biomechanicselastoplasticequinegaitlarge deformationquadruped

Identifiers

PMID35265590
PMCPMC8899468

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.