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Advanced modelling for two-phase reacting flows

Reference Number
EP/I004564/1
Title
Advanced modelling for two-phase reacting flows
Status
Completed
Energy Categories
Energy Efficiency(Transport)
Not Energy Related
Fossil Fuels: Oil Gas and Coal(Oil and Gas, Oil and gas combustion)
Renewable Energy Sources(Bio-Energy, Other bio-energy)
Research Types
Basic and strategic applied research
Science and Technology Fields
ENGINEERING AND TECHNOLOGY (Mechanical, Aeronautical and Manufacturing Engineering)
UKERC Cross Cutting Characterisation
Not Cross-cutting
Principal Investigator
Dr ES Richardson
Electronics and Computer Science
University of Southampton
Award Type
Standard
Funding Source
EPSRC
Start Date
01 October 2010
End Date
13 November 2015
Duration
61 months
Total Grant Value
£598,558
Industrial Sectors
Mechanical engineering
Region
South East
Programme
Energy : Engineering
Investigators
Principal Investigator
Dr ES Richardson, Electronics and Computer Science, University of Southampton
Industrial Collaborator
Project Contact, Rolls-Royce PLC
Project Contact, Sandia National Laboratories, USA
Web Site
Objectives
Abstract
Burning oil-based fuels accounts for approximately 31% of UK greenhouse gas emission as well as being a major culprit in toxic, irritant and carcinogenic pollutants on a national scale (www.naei.org.uk). Nearly all forms of transport currently rely on liquid fossil fuels, and this use of liquid fuel is likely to continue; the storage technology for electricity and hydrogen is not good enough completely to replace all use of energy-dense liquid fuels in heavy goods vehicles and aircrafts. It is necessary, therefore, to explore ways of reducing emissions and raising efficiency in the combustion of liquid fuel.Engine designers want computer programs to help them invent ways to use less fuel and produce less pollution. But the computational models currently available are not adequate to predict some important effects: such as how blends of future carbon-neutral bio-fuels will change engine performance.When a liquid fuel is injected in an engine, three interacting processes take place. First the liquid and gas display turbulence, i.e. they swirl and mix chaotically. Second, there is evaporation of the many compounds in the liquid fuel into gaseous fuel vapour. Third, there is combustion, i.e. the fuel combines with oxygen to form hundreds of different intermediate and final combustion products.Turbulence, evaporation and combustion are fundamentally difficult to compute. One reason is that they happen among a wide range of spatial and temporal scales and therefore need to be calculated with a very fine resolution. Another is that so many different chemical compounds are involved. As a result, simulating even a few milliseconds of a highly turbulent combustion process far exceeds the resources of the largest supercomputers in the world.This research proposal aims to solve these problems by providing an accurate, practical and rigorous model for the injection and combustion of liquid fuel blends. High-resolution simulation data will be analysed to provide fundamental information on the coupling among gasses and liquids. The resultant data will be used to devise a model that synthesises turbulence, evaporation and combustion processes into a unifying framework. This new model has great potential because it can describe evaporation and mixing processes, even those occurring at the smallest scales of the flow, in detail and at an acceptable computational cost.The proposed model will not only be useful for designing advanced combustion systems. The challenging combination of physics found in spray combustion is also found in a number of industrial processes, including spray-drying in food and chemical industries, spray-painting, and spray-forming of metal components. This research will also demonstrate how the new modelling can be used to improve design of more efficient industrial processes.Finally some processes that play a role in turbulent spray combustion also play a critical role in environmental processes affecting local air quality and global climate change. Environmental regulators at present often have to make high-impact environmental policy decisions without an accurate way to predict the consequences. The proposed model will be applied in this arena to help to provide this badly needed information to policy-makers, thus contributing to sound environmental policy
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Added to Database
09/07/10