This thesis reports on the design of ultrasonic bone cutting blades and the effect of various cutting parameters such as applied load, blade tip vibration velocity and frequency on cutting speed and temperature, two performance indicators used by orthopaedic clinicians. A range of high gain blades was developed to investigate the correlation between the frequency response predicted by finite element analysis (FEA) and the frequency response measured using an experimental model analysis (EMA) technique. It has been found that FEA frequency predictions are within 1.5% of measured frequencies. FEA has also been used to develop two novel ultrasonic cutting models which allow the effect of blade progression on cutting performance to be investigated. The models have been used to predict the relationship between applied load and cutting speed in single layer and multi-layer materials, and have shown that cutting speed decreases as cortical layer thickness increases, a trend also found from cutting experiments. Ongoing developments to predict temperature from both cutting models have produced a preliminary result which locates regions of maximum cutting temperature. The result influenced the design of blades with modified tip geometries that have been used to reduce cutting temperature. Ultrasonic cutting experiments were performed on bovine bone, two bone substitute materials and various grades of wood. Deep incisions were made for a range of applied loads and cutting speeds to investigate the effect of various cutting parameters on cutting temperature. Ultrasonic cutting has been successfully applied to perform deep incisions in bone whilst maintaining substrate temperature to within critical levels. Two innovative modelling techniques have been used to simulate ultrasonic cutting and demonstrate their potential for revolutionising blade design, and surgical trials.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:479053 |
| Date | January 2006 |
| Creators | MacBeath, Alan |
| Publisher | University of Glasgow |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://theses.gla.ac.uk/2220/ |
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