2018 Wahid Ferdous

Post Graduate Thesis Award 2018


2018 Post Graduate Thesis Award


Dr. Wahid Ferdous

Doctor of Philosophy

Place of Study: University of Southern Queensland

This thesis investigates the behaviour of epoxy polymer matrix and composite sandwich panels for manufacturing a new alternative sleeper for conventional timber counterparts.  To replace more than 2.5 million deteriorated timber sleepers per year the Australian railway industry is now looking for alternative sleeper technologies that are highly durable, cost effective and environmentally friendly. Therefore, an improved understanding of sleeper materials, their effective usage and manufacturing technique needs to be developed to meet the performance requirements and to reduce the overall cost. In this study, experimental and numerical approaches were implemented to determine an optimal design and to evaluate the structural performance under static loads. The optimal sleeper required only 50 percent volume of material but performed similarly to that of a rectangular timber sleeper. With further evaluation of in track performance and dynamic behaviour, this timber replacement composite sleeper is expected to save approximately 470 mature trees for each kilometre of rail-track construction, reduce carbon footprint, decrease track maintenance, and provide a sustainable sleeper technology.


Runner Up

Dr. Dwayne Nielsen

Thesis: Decision support system for railway bridge maintenance management

Doctor of Philosophy

Place of Study: Central Queensland University

This thesis describes a powerful novel approach to manage railway bridge assets. This approach expands upon existing condition monitoring results by applying predictive analysis to each bridge component. This methodology analyses all bridges in the network, each with thousands of components, and each component with multiple maintenance options, each with its own cost, improvement parameters and deterioration model. This study presents an innovative bridge maintenance planning approach through a complex multi-objective optimisation of maintenance responses weighted for bridge importance and constrained by budget. An application of the approach was conducted with a random selection of bridges and condition information from three Australian railway organisations. Maintenance plans and estimated annual budgets were predicted for a forward planning timeframe of 100 years using life cycle costing, residual value, cost benefit and minimum cost objective functions.