Masters Theses
Date of Award
12-1993
Degree Type
Thesis
Degree Name
Master of Science
Major
Engineering Science
Major Professor
J. F. Wasserman
Abstract
This thesis, entitled "Modelling Bone Fracture Behavior: The Case for Fuzzy Logic," is based on the laboratory experiments for the research project sponsored by Japan Automobile Manufacturers' Association (JAMA). The ultimate research goal is focused to develop an advanced computer code that can simulate bone fracture behaviors under impact loading. To seek possible approaches and determine the one best capable of describing bone fracture behaviors as efficiently and accurately as possible, a number of theories and methods are researched here. In this thesis, the basics of impact fracture mechanics, finite element method for crack simulation, and fuzzy logic theory are discussed. For its versatility, flexibility, and ease of application, the fuzzy logic approach appears to be the best approach to be used for bone fracture predictions. To provide the data base for the fuzzy expert system, a series of impact tests were performed on intact legs under conditions as close to real auto accident cases as possible. To generate the friction force on the foot at impact, an unique leg holding device on which weights can be put was designed. To study the effect of impact shock absorption by bumpers, a new bumper system supported by air-springs was developed. Experimental results, rules, and membership functions used for the fuzzy expert system are discussed. The designed fuzzy expert system performance can match experimental data very closely. Although the program was developed only for demonstration purposes due to its small database size, this program behaves well within the specified range of variables on the data base. As the data base grows bigger in the future, the program's accuracy and dependability are going to improve.
Recommended Citation
Akasaka, Taisuke, "Modelling bone fracture behavior : the case for fuzzy logic. " Master's Thesis, University of Tennessee, 1993.
https://trace.tennessee.edu/utk_gradthes/11820