Dwayne Nielsen

Research Methodology for Evaluation of Top of Rail Friction Management in Australian Heavy Haul Networks

Managing the coefficient of friction at the wheel/rail interface through wheel flange/gauge face lubrication is an accepted practice in railway systems. However, the coefficient of friction between the top of rail and wheel tread is not well addressed using this method, with traction, braking and some steering forces causing significant rail and wheel damage. Top-of- rail friction management uses friction modifiers to control the coefficient of friction within a defined range, and is being used in some North American rail networks with beneficial results. In Australia, there has been limited use of top-of-rail lubrication and where it is applied, it is mainly utilised to improve steering forces and mitigate wheel squeal. This research project sought a holistic understanding of top-of-rail lubrication and management of wheel/rail friction in the Australian context. A systematic approach for experimentation and analysis of the application of a friction modifier was developed in this study. The approach utilised an engineering analysis based on experimental results and publications and a numerical study for three-dimensional analysis. Vehicle system dynamics and wheel/rail operating conditions were then modelled through GENSYS simulation to understand variations in wear index with respect to friction conditions at the wheel/rail interface.

Life cycle management for railway bridge assets

Railway bridges are long-life assets that deteriorate with age, use and poor maintenance practices. The rail industry is suffering from ever-increasing maintenance costs which are exacerbated by increased rail traffic and reduced maintenance opportunities. In addition, bridge managers are expected to maintain their assets at specified performance levels while enduring budget cuts and resource constraints. There is an increasing demand for bulk material transport leading to increased axle loads pushing bridge structures to their design loading limit. Making informed decisions for cost-effective condition assessment, maintenance, repairs, upgrades and replacements, often with inadequate and sometimes inaccurate data is a major challenge in the management of railway bridges. Due to these challenges, infrastructure planners require additional time to plan and prepare maintenance budgets, analyse, interpret and make decisions for bridge asset life management. Many of the bridge management systems utilised in Australia are generic and analyse faults at the network level. In many cases, a detailed analysis of individual elements will provide a better understanding of root causes of faults and allow for more informed decision-making on bridge life enhancement. A practical framework for life cycle management of Australian concrete and steel railway bridges was developed in this research. This framework is based on life cycle cost analysis and consists of bridge assessment, maintenance optimisation and implementation. The outcome of this research is a faster, more accurate system that improves the informed decision-making capability for life cycle cost management of railway bridges.

Model to estimate infrastructure damage costs for different train types

Abstract Generally, rail has been losing its market share of bulk freight transport. Australian railways have an opportunity to improve the performance and meet the freight transport challenges of the twenty-first century, but a particular challenge is older infrastructure and networks with lower utilisation. Railway systems constructed in the 1800s, included numerous small radius curves, steeper grades and sub-standard formation, which would nowadays likely require additional maintenance funding to ensure the track is maintained at the required standard. As each train type applies a different quantifiable level of track damage for a given track geometry, and as the cost to repair/maintain this track is known, then it is possible to develop a transparent cost model to estimate the incremental infrastructure costs for each train type. Therefore, a wear/damage model was selected based on data derived from train simulations and track degradation analysis. This model provides an indication of the expected infrastructure maintenance budget based on train types (train configurations, vehicle axle loads, bogie parameters and wheel profiles), operational requirements (volumes, speeds) and the local track characteristics (track geometry, sleeper type, ballast/formation parameters and rail profiles). While, track damage models are currently available for railway vehicles on passenger networks, comprehensive heavy haul track damage models are still in their infancy. This paper publishes a summarised review from the first phase of this project.

An Australian railway bridge management framework

A large number of Australian railway bridges were constructed over 80 years ago and have become increasingly costly to maintain. Infrastructure managers are under pressure to maintain bridge structures to a specified performance level with less maintenance funding and fewer resources. Currently, some rail operators maintain bridges through generic asset management systems which are simplistic and only address immediate operational issues. This is despite the fact that a life cycle cost analysis is proven to strategically maintain bridge assets and reduce costs over their operational life. A new bridge management system (BMS) framework which consists of a life cycle cost analysis and strategy model is proposed in this paper. The model can provide solutions at the element, bridge and network levels. A brief background is provided on Australian railway bridge operational history. Finally, a new maintenance cycle is proposed and its components are discussed.