There has been a recent collaboration between the Department of Power and Propulsion at the UK's Cranfield University and a major oil and gas company addressing the challenge of rotating equipment selection for the liquefaction of natural gas (LNG). This topical study, included the use of an existing tool developed at Cranfield to aid gas turbine selection through a Techno-Economic, Environmental and Risk Analysis (TERA). This tool has seen previous successful applications in areas including civil aviation, power generation and marine propulsion.
In particular, the company required the university to investigate its existing LNG liquefaction plants whilst keeping environmental and economic criteria in mind.
With mounting pressures of emissions legislation and consequent taxes, there is an ever increasing need to systematically select the most appropriate rotating equipment. The company, like most, also has many plants where dated equipment needs replacement. Accordingly, a simple to use tool would be highly desirable to aid the procurement process. Against this background, Cranfield's TERA provides a generic multidisciplinary platform for such an assessment.
The core of TERA is a thermodynamic performance module simulated using a Cranfield 'in-house' simulation code called Turbomatch. This is a robust and flexible code used to simulate design and off design performance of gas turbines in a range of operational conditions. Simulations can be run at different loads and varying ambient conditions.
The purpose of this novel tool is to predict the failure of gas turbine components resulting from observations of the thermodynamic conditions created within the core of the engine. For this reason, both probabilistic and parametric lifting form part of the analysis; looking at failures of hot gas path components such as combustor liners, first stage turbine blades and predicting the life of thermal barrier coatings used on turbine blades. In addition, it is possible to assess the uncertainty involved in defining the likely range of operating life for each component. This information is of great use to operators and can aid in better maintenance planning.
In the interest of designing plants with high availability and reliability, the tool uses Monte Carlo simulations to analyse engines on a component-by-component basis. The measure of availability and reliability is the overall downtime that the Monte Carlo simulations predict. In this way the technology readiness levels (TRL based on the NASA scale) can be linked to the downtime associated with that particular engine, which acts as a quantitative way of measuring reliability and availability.
Predictions of emissions like NOx CO2 CO unburned hydrocarbons and water vapour are also made. These indices are then used to calculate emissions taxes given the current local legislation and provides the basis for comparison of the overall global warming potential and carbon footprint of gas turbine engines. The tool has recently been utilised to analyse a variety of cases and selected results have been published within the American Society of Mechanical Engineers (ASME).
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Dr Raja Khan is former research student of Cranfield University and Dr Kenneth W Ramsden is Consultant to the Department of Power and Propulsion, Cranfield University, Cranfield, Bedfordshire, UK. www.cranfield.ac.uk