Case Study Of Seven Ground Improvement Techniques Implemented At Coal Export Terminals On Kooragang Island, Australia

Ming Lai, Ondrej Synac, Iain Robertson and Derek Avalle

This paper describes a case study in which various ground improvement techniques were implemented to enable the development of one the world‟s largest coal export facilities. To service the Hunter Valley coal industry, Coal Export Terminals (CET) with associated rail and coal handling/train unloading infrastructure have been constructed on Kooragang Island, Newcastle, New South Wales, Australia, in the last decade. The coal terminal expansion has brought about fundamental geotechnical challenges. Kooragang Island was formed by dredging and infilling between and around former islands and delta features of the Hunter River estuary. The presence of recent estuarine and alluvial soft clay deposits combined with variable thicknesses of fill comprising dredged materials, coal washery reject and steel slag, introduced significant geotechnical issues in relation to bearing capacity, stability and long term total and differential settlements. To support combined stacker/reclaimers with up to 24m high coal stockpiles, rail loop realignment and a new rail flyover, Ground Improvement was required to address the above issues. In order to limit the post-construction settlements and to satisfy the settlement criteria for machinery and railway operation, a suite of seven ground improvement techniques has been employed to suit the specific performance requirements, programme and geotechnical conditions across the site. These consisted of Wick Drains, Dry Bottom-Feed Stone Columns, Wet TopFeed Stone Columns, Dynamic Replacement, Mass Soil Mixing, Deep Soil Mixing and Rigid Inclusions. All of the above methods were successfully applied over the course of an eight year development period on a design and construct basis. The process of using ground improvement techniques, their construction restraints and geotechnical design considerations are discussed. The performance based on monitoring data collected under operating conditions is presented.