In this work, wear and scratch behavior of four different bulk metallic glasses (BMGs) namely Zr41.2Cu12.5Ni10Ti13.8Be22.5 (LM 1), Zr57Cu15.4Ni12.6Al10Nb5 (LM 106), Ni60Pd20P17B3 (Ni-BMG), and Pt57.5Cu14.7Ni5.3P22.5 (Pt-BMG) were compared. Shear band formation on the edges of the scratch groove with spallation was found to be the primary failure mechanism in progressive scratch tests. The wear behavior and the scratch response of model binary Ni-P metallic glasses was systematically studied as a function of composition, with amorphous alloy formation over the narrow range of 10 at% to 20 at% phosphorus. Pulsed current electrodeposition was used to obtain these binary amorphous alloys, which offers a facile and versatile alternative to conventional melt quenching route. The electrodeposited metallic glasses (EMGs) showed hardness values in the range of 6.6-7.4 GPa, modulus in the range of 155-163 GPa, and friction coefficient around 0.50. Among the studied alloys, electrodeposited Ni80P20 showed the lowest wear rate. The wear mechanism was determined to be extensive plastic deformation along with mild ploughing, micro tears, and formation of discontinuous lubricious oxide patches. The effect of phosphorus content on the structure, mechanical properties, and the tribological response was systematically investigated for biocompatible Co-P metallic glasses. With increase in phosphorus content, there was an increase in hardness, hardness/modulus, wear resistance, and scratch resistance following the trend: Co80P20 > Co90P10 > Pure Co. The Co-P electrodeposited amorphous alloys showed enhanced wear resistance that was two orders of magnitude better than SS 316 and Ti-based alloys in simulated physiological environment. The wear mechanisms were determined to be a combination of abrasive and surface fatigue wear in both dry and physiological environments. Decreased platelet adhesion and more extracellular matrix deposition indicated that Co80P20 electrodeposited alloy had excellent blood compatibility and pre-osteoblast adhesion response. These results suggest the potential use of Co-P metallic glasses as superior bio implant materials with better durability compared to the state-of-the-art.

Rails play a significant role in transport of goods and passengers. In Australia railway transport industry contributes 1.6% of GDP with goods and services worth $AUD 8 billion each year which includes $ AUD 0.5 billion per year in exports (Australasian Railway Authority Inc, 2002). Rail track maintenance plays an important role in reliability and safety. The Office for Research and Experiments (ORE) of the Union International des Chemins de Fer (UIC) has noted that maintenance costs vary directly (60-65 per cent) with change in train speed and axle load. It was also found that the increase in these costs with increased speed and axle load was greater when the quality of the track was lower (ORR, 1999). Failures during operation are costly to rail players due to loss of service, property and loss of lives. Maintenance and servicing keep rail tracks in operating, reliable and safe condition. Therefore, technical and economical analysis is needed by rail players to reduce maintenance cost and improve reliability and safety of rail networks. Over the past few years, there have been major advances in terms of increased speed, axle loads, longer trains, along with increased traffic density in corridors. This has led to increased risks in rail operation due to rolling contact fatigue (RCF) and rail wear. The infrastructure providers have less incentive to maintain a given infrastructure standard if its access charges are rigid and rolling stock standard is not achieved. It has been estimated that between 40 to 50 per cent of wagon maintenance costs and 25 per cent of locomotive maintenance costs are related to wheel maintenance (Railway Gazette International, 2003). The economic analysis of Malmbanan indicates that about 50% of the total cost for maintenance and renewal were related to traffic on rails and 50% not related to traffic, such as signaling, electricity and snow-clearance. The results from the analysis have made it possible for the mining company LKAB to start up the 30 Tonnes traffic with new wagons and locomotives on the Malmbanan line in year 2001 (Åhrén et al 2003). The rail infrastructure providers have challenges to maintain infrastructure due to government control on access charges and limited control on rail operations. The aim of the research is to: · Develop a maintenance cost model for optimal rail grinding for various operating conditions; and · Develop integrated rail grinding and lubrication strategies for optimal maintenance decisions. In this research real life data has been collected, new models have been developed and analysed for managerial decisions. Simulation approach is used to look into the impact on various costs such as rail grinding, operating risk, down time, inspection, replacement, and lubrication. The results of the models for costs and the effect of rail grinding and lubrication strategies are provided in this thesis. In this research rail track degradation, rail failures and various factors that influence rail degradation are analysed. An integrated approach for modelling rail track degradation, rail wear, rail grinding and lubrication is developed. Simulation model and cost models for rail grinding are developed and analysed. It has been found through this research that rail grinding at 12 MGT interval is economic decision for enhancing rail life. It was also found that lubrication is most effective compared to stop/start and no lubrication strategies in steep curves. Rail grinding strategies developed in this research have been considered by Swedish National Rail for analysing the effectiveness of their existing policies on grinding intervals. Optimal grinding and lubrication decisions have huge potential for savings in maintenance costs, improving reliability and safety and enhancing rail life.

In recent years there has been continuous increase of axle loads, tonnage, train speed, and train length which has increased both the productivity in the rail sector and the risk of rail breaks and derailments. Rail operating risks have been increasing due to the increased number of axle passes, sharper curves, wear-out of rails and wheels, inadequate rail-wheel grinding and poor lubrication and maintenance. Rolling contact fatigue (RCF) and wear are significant problems for railway companies. In 2000, the Hatfield accident in the UK killed 4 people, injured 34 people and led to the cost of £ 733 million (AUD$ 1.73 billion) for repairs and compensation. In 1977, the Granville train disaster in Australia killed 83 people and injured 213 people. These accidents were related to rolling contact fatigue, wear and poor maintenance. Studies on rail wear and lubrication, rolling contact fatigue and inspection and rail grinding analyse and assess the asset condition to take corrective and preventive measures for maintaining reliability and safety of rail track. Such measures can reduce the operational risks and the costs by early detection and prevention of rail failures, rail breaks and derailments. Studies have so far been carried out in isolation and have failed to provide a practical solution to a complex problem such as rail-wheel wearfatigue-lubrication-grinding-inspection for cost effective maintenance decisions. Therefore, there is a need to develop integrated economic models to predict expected total cost and operational risks and to make informed decisions on rail track maintenance. The major challenges to rail infrastructure and rolling stock operators are to: 1. keep rolling contact fatigue and rail-wheel wear under controllable limits, 2. strike a balance between rail grinding and rail lubrication, and 3. take commercial decisions on grinding intervals, inspection intervals, lubrication placements, preventive maintenance and rail replacements. This research addresses the development and analysis of an integrated model for assessment of operational risks in rail track. Most significantly, it deals with problems associated with higher axle loads; wear; rolling contact fatigue; rail defects leading to early rail replacements; and rail breaks and derailments. The contribution of this research includes the development of: failure models with non-homogenous Poisson process and estimation of parameters. economic models and analysis of costs due to grinding, risks, downtime, inspection and replacement of rails for 23, 12, 18 and 9 Million Gross Tonnes (MGT) of traffic through curve radius 0-300, 300-450, 450-600 and 600-800 m; and application of results from this investigation to maintenance and replacement decisions of rails. Cost savings per meter per year are: * 4.58% with 12 MGT intervals compared to 23 MGT intervals for 0-300 m * 9.63% with 12 MGT intervals compared to 23 MGT intervals for 300-450 m * 15.80% with 12 MGT intervals compared to 23 MGT intervals for 450-600 m * 12.29% with 12 MGT intervals compared to 23 MGT intervals for 600-800 m. a lubrication model for optimal lubrication strategies. It includes modelling and economic analysis of rail wear, rail-wheel lubrication for various types of lubricators. Cost effectiveness of the lubricator is modelled, considering the number of curves and the total length of curves it lubricates. Cost saving per lubricator per year for the same curve length and under the same curve radius is: * 17% for solar wayside lubricators compared to standard wayside lubricators. simulation model for analysis of lubrication effectiveness. Cost savings per meter per year for: * 12 MGT grinding interval is 3 times for 0-450 m and 2 times for 450-600 m curve radius with lubrication compared to without lubrication. * 23 MGT grinding interval is 7 times for 0-450 m and 4 times for 450-600 m curve radius with lubrication compared to without lubrication. a relative performance model, total curve and segment model. an inspection model for cost effective rail inspection intervals. Cost savings per year for same track length, curves and MGT of traffic: * 27% of total maintenance costs with two inspections, compared to one inspection considering risk due to rail breaks and derailments. a risk priority number by combining probability of occurrence, probability of detection and consequences due to rail defects, rail breaks and derailments. integrated model combining decisions on grinding interval, lubrication strategies, inspection intervals, rectification strategies and replacement of rails. Cost saving per meter per year for 12 MGT is: * 5.41% of total maintenance costs with two inspections, compared to one inspection considering risk due to rail breaks and derailments. * 45.06% of total maintenance costs with lubrication for two inspections, compared to without lubrication. Cost saving per meter per year for 23 MGT is: * 5.61% of total maintenance costs with two inspections, compared to one inspection considering risk due to rail breaks and derailments. * 68.68% of total maintenance costs with lubrication for two inspections, per year compared to no lubrication. The thesis concludes with a brief summary of the contributions that it makes to this field and the scope for future research in wear-fatigue-lubrication-grinding-inspection for maintenance of rail infrastructure.

These days, automotive industries are facing intensive competition. New products should be delivered into market as soon as possible. On the other hand, customers also require new products having good reliability. Laboratory life testing is the traditional way to examine the reliability of products. Sample products should be tested till failures, which usually involve tremendous cost and time. Obviously, the reliability testing process extends the duration of 'design-to-market'. Cutting down the testing process can reduce the producing cycle properly. Currently, the accelerated life test (ALT) has been widely used in many companies as an alternative method. Although ALT reduces the cost of reliability testing through applying more severe environmental conditions than the normal ones on products, it is no longer sufficient as it does not describe the process of products' failure explicitly and it is still highly dependent on physical testing. Consequently, prediction models need to be developed for better understanding of the products' reliability.

[Truncated abstract] The development of an automated classification system of wear particles or surfaces is of great interest to the machine condition monitoring industry. The system, once developed, may also find applications in medical diagnostics. Such a tool will be able to replace human experts in the detection of the onset of early machine failure, or in the diagnosis and prognosis of, for example, joint diseases. This will improve efficiency, reliability and also reduce costs of monitoring or diagnostic systems. Current literature available on this topic has included various studies on different classification methods. However, there has been no work conducted on the development of a totally integrated automated classification system. The first part of this thesis presents a study investigating the efficiency and robustness of various pattern recognition methods currently described in literature. A special computer program was developed to test each of the classification methods against both standard image databases and tribological surface images. There are three core components of a pattern recognition system that need to be analysed: (1) feature extraction, (2) feature reduction and (3) classifier. Each of these components provides a vital link that can affect the reliability of the complete classification system. ... The optimal classifier was the Linear Support Vector Classifier. This part of research is described in Paper 2. The second part of this thesis contains work verifying the performance of the automated classification system developed using both tribological and bio-tribological surface images. Experiments were carried out to generate wear particles created under different wear mechanisms (adhesive, abrasive and fatigue wear) and various operating conditions representing different degree of wear severity. The automated classification system developed was able to successfully classify wear particles with respect to both the type of wear mechanism operating and the wear severity. The results of this classification are described in Papers 3 and 5. The success of the automated classification system was also confirmed by its ability to classify different groups of worn (osteoarthritic) cartilage surfaces (Paper 4). This could lead to potential applications of the system for early detection of the onset of osteoarthritis. In conclusion, the automated classification system developed can accurately classify both tribological and bio-tribological surface images. This system could become a vitally important tool in both machine condition monitoring and medical diagnostics.

Thesis (Ph. D.)--Oregon Graduate Center, 1989.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 211-217).

Thesis (Ph.D.)--University of Wollongong, 2005. / Typescript. Includes bibliographical references: leaf 174-189.

Thesis (Ph. D.)--Ohio State University, 2008. / Title from first page of PDF file. Includes bibliographical references (p. 181-192).

Thesis, (Ph. D.)--Oregon Graduate Institute, 1997.