Numerical optimization of methane-based fuel blends under engine-relevant conditions using a multi-objective genetic algorithm
- Submitting institution
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University of Hertfordshire
- Unit of assessment
- 12 - Engineering
- Output identifier
- 19773244
- Type
- D - Journal article
- DOI
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10.1016/j.apenergy.2019.03.041
- Title of journal
- Applied Energy
- Article number
- -
- First page
- 1712
- Volume
- 242
- Issue
- -
- ISSN
- 0306-2619
- Open access status
- Deposit exception
- Month of publication
- March
- Year of publication
- 2019
- URL
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Funded by the Swiss National Foundation (SNF) (grant IZCNZ0-174833) and H2020’s European Cooperation in Science and Technology (COST), natural gas fuelled thermal propulsion systems were designed in this research particularly suited to industrial applications, using experimental data provided by Liebherr Machines Bulle SA. The paper has been expanded to form the foundation of a recent EPSRC New Investigator award won at UH (grant EP/T033800/1) in collaboration with Cardiff University, the University of Connecticut, and industrial partners Ricardo and Convergent Science, to co-optimise fuel blends and combustion systems for natural gas fuelled spark ignition engines.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -