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Enregistrement W1552349969

The effect of hockey stick stiffness and energy transfer on puck velocity for wrist and slap shots

2013· article· en· W1552349969 sur OpenAlexaffvenue
Rosemary Grover

Notice bibliographique

RevueJournal of undergraduate research in Alberta · 2013
Typearticle
Langueen
DomaineEngineering
ThématiqueSports Dynamics and Biomechanics
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésStiffnessDeflection (physics)Shot (pellet)Structural engineeringStrain gaugeEngineeringMaterials sciencePhysics
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

INTRODUCTION Constructing a hockey stick shaft from composite materials has allowed for altering the stiffness of the stick, thereby enabling increased storage and return of elastic energy. However, previous studies examining the effects of shaft stiffness on performance have had mixed results [1,2]. In these studies, stick stiffness appeared to influence the storage and return of energy but the athlete’s ability to transfer this energy from the stick to the puck was not optimized. It is believed that the stick-puck contact interface may be a critical link between this energy transfer. Therefore, the purpose of this study was to determine the effects that stick stiffness, shaft deformation, blade-puck contact time and energy transferred from the stick to the puck have on maximum puck velocity. METHODS AND MATERIALS 22 ice hockey players performed eight slap shots and eight wrist shots with three composite Easton Synergy ST sticks of varying stiffness; 85 flex (6400 N/m), 100 flex (7400 N/m) and 110 flex (8000 N/m). This report is based on results from 14 subjects. Players performed shots on a synthetic ice surface into a hockey net approximately five meters away. Two 350 ohm resistance strain gauge sensors were attached to each shaft to measure the stick deflection during each shot and to calculate the total energy storage and return of the stick. Six force sensors were placed evenly beneath the taped blade to measure the contact time between the stick and puck. The puck velocity during each shot was measured using a Stalker ATS professional radar gun. All data was analyzed using custom made software (MATLAB 2012a, Mathworks). The average of the eight trials for each subject was compared between conditions using a repeated measures ANOVA at a significance level of α=0.05. RESULTS On average, stick stiffness had an influence on puck velocity for both the wrist and slap shot. For the wrist shot, the most flexible stick resulted in a 2.7% higher velocity  (α<0.05) and a 28.3% greater peak deflection (α<0.05) than the stiffest stick. For the slap shot, the stiffest stick resulted in a 3.2% greater puck velocity (α<0.05) and a 11.3% lower shaft deflection (α<0.05) than the most flexible stick. Eight athletes performed their best wrist shots with the 85 flex stick and 11 performed their best slap shots with the 110 flex stick. Optimal stick stiffness varied among subjects. Athletes were therefore divided into groups based on their best and worst stiffness in order to analyze their performance (Figure 1). Under these groupings, significant differences were seen in puck velocity (for both wrist and slap shots) and peak shaft deflection (for wrist shots) while a trend of increased impulse for both the wrist and slap shot was also seen. Figure 1. Results from athletes’ best (blue) and worst (red) stick stiffness for the wrist and slap shot (n=14). Best stiffness was defined as the stick in which the player had the highest puck velocity. DISCUSSION AND CONCLUSIONS This study found that stick shaft stiffness can influence puck velocity during both a wrist and slap shot. When athletes were grouped based on their best and worst stiffness of stick, a trend was seen indicating that when an athlete is shooting with a stick of optimal stiffness, the impulse that the stick imparts on the puck is increased. This increased impulse may be due to the timing of the release of energy from the stick to the puck. To optimize this energy transfer, future studies may consider using blade-puck contact information to provide further insight into the relationship between the timing of puck release and a deflected stick’s returns to equilibrium. REFERENCES Worobets, J.T., et al. Sports Eng, 9 , 191-200, 2006. Hannon, A., et al. Sports Eng , 47, 57-65, 2011.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,790
Score d'incertitude au seuil0,308

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,272
Écart entre enseignants0,257 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2013
Routes d'admission2
Résumé présentoui

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