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Title: TERA for rotating equipment selection
Author: Khan, Raja S. R.
Awarding Body: Cranfield University
Current Institution: Cranfield University
Date of Award: 2012
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This thesis looks at creating a multidisciplinary simulation tool for rotating plant equipment selection, specifically gas turbines, for the liquefaction of natural gas (LNG). This is a collaborative project between Shell Global Solutions and Cranfield University in the UK. The TERA LNG tool uses a Techno-economic, Environmental and Risk Analysis (TERA) approach in order to satisfy the multidisciplinary nature of the investigation. The benefits of the tool are to act as an aid to selection, operations and maintenance planning and it also acts as a sensitivity tool for assessing the impact of changes in performance, environmental and financial parameters to the overall economic impact of technology selection. The aim is to not only select technology on the basis of techno-economics but also on the basis of risk analysis. The LNG TERA tool is composed of a number of modules starting with the performance simulation which calculates the thermodynamic conditions in the core of the engine. Next, life estimates of the hot gas path components are made using a mixture of parametric and probabilistic lifing models for the turbine first stage blades, coatings, and combustor liner. This allows for a risk analysis to be conducted before maintenance and economics issues are dealt with. In parallel, emissions estimations are made based on empirical correlations. The modelling exemplifies a methodology which is uniquely applied to this application and there are no studies previous to this which look at so many aspects before making conclusions on plant machinery selection. Comparisons have been done between industrial frame engines based on the General Electric Frame 9E (130 MW) and Frame 7EA (87 MW) engines as well as more complex cycles involving aero-derivation and inter-cooling such as the LM 6000 (42 MW) and LMS 100 (100 MW). Work has also been carried out to integrate the tool to Shell based systems in order to utilise the database of information on failure and maintenance of machinery as well as its performance. The results of the integrated TERA show a clear favour for the aero-derivative engines and the main benefit is the fuel saving, though the life of the hot gas path components is deteriorated much faster. The risk results show that the industrial frame engines have a wider variation in expected life compared to aero-derivatives, though the industrial frames have longer component lives. In the context of maintenance and economics, the aero-derivative engines are better suited to LNG applications. The modular change out design of the aero- derivatives also meant that time to repair was lower, thus reducing lost production. Application of the LNG TERA tool was extended to power generation whereby a series of 6 engines were simulated. The changes required to the modelling were minimal and it shows the flexibility of the TERA philosophy. This study was carried out assuming a given ratio of load split between the engines and hence is sensitive to the way an operator demands power of the engine as opposed to LNG application where the operator tries to drive the engine as hard as possible to get the most production out of the train. The study was limited in the modes of failure which were investigated, a major further work would be to extend the methodology to more components and incorporate fatigue failure. Further, the blade creep and probabilistic coating models were very sensitive to changes in their respective control parameters such as coating thickness allowances and firing temperature. The contribution to the project from the MBA is the statistical techniques used to conduct the risk analysis and data handling as well as financial management techniques such as the Net Present Value (NPV) methodology for project evaluations.
Supervisor: Pilidis, Pericles; Ogaji, S.; Bennett, Ian; Nicholls, John Sponsor: Not available
Qualification Name: Thesis (D.Eng.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available