Objective
The conventional modelling of solid fuel devolalilisation fails in the case of biomass to depict its diversity from coal as well as between different types of biomass. To alleviate this problem, extensive, repetitive and most of all very expensive combustion trials for each single type of biomass must be performed at large and full industrial scale furnaces in order to characterise its combustion behaviour.
An appealing alternative can be the use of CFD mathematical models; they are becoming increasingly popular while at the same time they receive the scepticism of the power generation and high temperature process industry. This scepticism is a result of the fact, among others, that each type of biomass fuel has a different and very complicated chemical structure thus its simulated behaviour by the relatively simple devolatilisation and combustion models currently in use by CFD codes is associated with a great degree of uncertainty. To address this problem, there are current trends to incorporate more elaborate sub-models into the codes for the thermal decomposition and combustion processes (devolatilisation, secondary cracking, soot formation etc.) for different types of coal or coal blends but they are cumbersome, and computationally uneconomical. Furthermore, biomass has been much less investigated due to the relatively recent interest in its industrial utilisation as a fuel.
This project applies the newly emerging neural network technology to enable the more generalised prediction of biomass devolatilisation behaviour. The technology will be used to predict the volatile release rate from selected key biomass characterisation parameters and the local physical and thermal conditions in the near burner field. The new formulation will be tested against bench-top data and then incorporated in a reputed in-house CFD combustion model where it will be validated against data taken in a large scale furnace.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology environmental engineering ecosystem-based management climatic change mitigation
- engineering and technology environmental engineering energy and fuels fossil energy coal
- natural sciences mathematics applied mathematics mathematical model
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
DE24 9GH Derby
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.