Pilot plant studies of ion exchange for desalination of coal seam gas produced water

This paper reports a study of ion exchange (IX) as an alternative CSG water treatment to the widely used reverse osmosis (RO) desalination process. An IX pilot plant facility has been constructed and operated using both synthetic and real CSG water samples. Application of appropriate synthetic resin technology has proved the effectiveness of IX processes.

Effect of culture conditions and calcium phosphate coating on ectopic bone formation

This study investigated the effect of a calcium phosphate (CaP) coating onto a polycaprolactone melt electrospun scaffold and in vitro culture conditions on ectopic bone formation in a subcutaneous rat model. The CaP coating resulted in an increased alkaline phosphatase activity (ALP) in ovine osteoblasts regardless of the culture conditions and this was also translated into higher levels of mineralisation. A subcutaneous implantation was performed and increasing ectopic bone formation was observed over time for the CaPcoated samples previously cultured in osteogenic media whereas the corresponding non-coated samples displayed a lag phase before bone formation occurred from 4 to 8 weeks post-implantation. Histology and immunohistochemistry revealed bone fill through the scaffolds 8 weeks post-implantation for coated and non-coated specimens and that ALP, osteocalcin and collagen 1 were present at the ossification front and in the bone tissues. Vascularisation in the vicinity of the bone tissues was also observed indicating that the newly formed bone was not deprived of oxygen and nutrients.We found that in vitro osteogenic induction was essential for achieving bone formation and CaP coating accelerated the osteogenic process. We conclude that high cell density and preservation of the collagenous and mineralised extracellular matrix secreted in vitro are factors of importance for ectopic bone formation.

Integrated approach for diagnostics and prognostics of HP LNG pump based on health state probability estimation

Effective machine fault prognostic technologies can lead to elimination of unscheduled downtime and increase machine useful life and consequently lead to reduction of maintenance costs as well as prevention of human casualties in real engineering asset management. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique and historical failure knowledge embedded in the closed loop diagnostic and prognostic system. To estimate a discrete machine degradation state which can represent the complex nature of machine degradation effectively, the proposed prognostic model employed a classification algorithm which can use a number of damage sensitive features compared to conventional time series analysis techniques for accurate long-term prediction. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for the comparison of intelligent diagnostic test using five different classification algorithms. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state probability using the Support Vector Machine (SVM) classifier. The results obtained were very encouraging and showed that the proposed prognostics system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.