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A MECHANICS-BASED APPROACH FOR PUTT DISTANCE OPTIMIZATION

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Date Issued:
2015
Abstract/Description:
Quantifying the core mechanics of putting is imperative to developing a reliable model that predicts post-collision ball behavior. A preliminary model for the stroking motion of putting and putter-ball collision is developed alongside experiments, establishing an empirical model that supports the theory. The goal of the present study is to develop a correlation between the backstroke of a putt, or the pre-impact translation of the putter, and the post-impact displacement of the golf ball. This correlation is subsequently utilized to generate an algorithm that predicts the two-dimensional ball trajectory based on putt displacement and putting surface texture by means of finite element analysis. In generating a model that accurately describes the putting behavior, the principles of classical mechanics were utilized. As a result, the putt displacement was completely described as a function of backstroke and some environmental parameters, such as: friction, slope of the green, and the elasticity of the putter-ball collision. In support of the preliminary model, experimental data were gathered from golfers of all levels. The collected data demonstrated a linear correlation between backstroke and putt distance, with the environmental parameters factoring in as a constant value; moreover, the data showed that experienced golfers tend to have a constant acceleration through ball impact. Combining the empirical results with the trajectory prediction algorithm will deliver an accurate predictor of ball behavior that can be easily implemented by golfers under most practical applications. Putt distance to backstroke ratios were developed under a variety of conditions
Title: A MECHANICS-BASED APPROACH FOR PUTT DISTANCE OPTIMIZATION.
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Name(s): Santiago-Martinez, Pascual, Author
Gordon, Ali, Committee Chair
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2015
Publisher: University of Central Florida
Language(s): English
Abstract/Description: Quantifying the core mechanics of putting is imperative to developing a reliable model that predicts post-collision ball behavior. A preliminary model for the stroking motion of putting and putter-ball collision is developed alongside experiments, establishing an empirical model that supports the theory. The goal of the present study is to develop a correlation between the backstroke of a putt, or the pre-impact translation of the putter, and the post-impact displacement of the golf ball. This correlation is subsequently utilized to generate an algorithm that predicts the two-dimensional ball trajectory based on putt displacement and putting surface texture by means of finite element analysis. In generating a model that accurately describes the putting behavior, the principles of classical mechanics were utilized. As a result, the putt displacement was completely described as a function of backstroke and some environmental parameters, such as: friction, slope of the green, and the elasticity of the putter-ball collision. In support of the preliminary model, experimental data were gathered from golfers of all levels. The collected data demonstrated a linear correlation between backstroke and putt distance, with the environmental parameters factoring in as a constant value; moreover, the data showed that experienced golfers tend to have a constant acceleration through ball impact. Combining the empirical results with the trajectory prediction algorithm will deliver an accurate predictor of ball behavior that can be easily implemented by golfers under most practical applications. Putt distance to backstroke ratios were developed under a variety of conditions
Identifier: CFH0004764 (IID), ucf:45340 (fedora)
Note(s): 2015-05-01
B.S.M.E.
Engineering and Computer Science, Dept. of Mechanical, Materials and Aerospace Engineering
Bachelors
This record was generated from author submitted information.
Subject(s): putt
putting
golf
golfing
mechanics
dynamics
sports
matlab
fem
finite element analysis
algorithm
green
green speed
stimpmeter
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFH0004764
Restrictions on Access: public
Host Institution: UCF

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