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Computational Modelling Group: Amit Bhave's Publications
https://como.ceb.cam.ac.uk/publications/ab349/Amit Bhave. Full List of Publications co-authored by Amit Bhave. Number of publications listed in category: 34. International Collaboration: Mainstreaming Artificial Intelligence and Cyberphysical Systems for Carbon Neutrality. Thorsten Jelinek, -
Computational Modelling Group: Publication F-111-120-130
https://como.ceb.cam.ac.uk/publications/F-111-120-130/Reference: Fuel 111, 120-130, (2013). Abstract. The ASTM D1322 smoke point test has been used for many years as a quick, convenient and easy way to characterize the sooting propensity ... The alternative test is based on the fuel uptake rate and image -
Computational Modelling Group: Preprint 172
https://como.ceb.cam.ac.uk/preprints/172/The performance of MPM is tested for 13 different test cases for different fragmentation kernels, fragment distribution functions and initial conditions. -
Computational Modelling Group: Preprint 164
https://como.ceb.cam.ac.uk/preprints/164/energy networks) at the top EIP level with the boundary conditions of economic, social and legal requirements. -
Computational Modelling Group: Rebecca Shaw's Preprints
https://como.ceb.cam.ac.uk/preprints/rcr33/Rebecca Shaw. Full List of Preprints co-authored by Rebecca Shaw. 112:and Terese Løvås, Technical Report 112, c4e-Preprint Series, Cambridge, 2012. 111:and Markus Kraft, Technical Report 111, c4e-Preprint Series, Cambridge, 2012. 86:and Markus -
Computational Modelling Group: Ning Xiao's Publications
https://como.ceb.cam.ac.uk/publications/nx201/Ning Xiao. Full List of Publications co-authored by Ning Xiao. Number of publications listed in category: 1. 2013. Tom Harris, Tim Helme,and Markus Kraft, Applied Energy 106, 262-274, (2013). 2024 Computational Modelling Group. Department of -
Computational Modelling Group: Min Loon Yong's Publications
https://como.ceb.cam.ac.uk/publications/mly22/Min Loon Yong. Full List of Publications co-authored by Min Loon Yong. Number of publications listed in category: 1. 2013. Tom Harris, Tim Helme,and Markus Kraft, Applied Energy 106, 262-274, (2013). 2024 Computational Modelling Group. Department of -
Computational Modelling Group: Preprint 239
https://como.ceb.cam.ac.uk/preprints/239/the minimum interaction energy) between two colliding particles. To test the performance of this new coagulation efficiency model, we applied it in detailed population balance modelling of soot particle size distributions -
Computational Modelling Group: Preprint 158
https://como.ceb.cam.ac.uk/preprints/158/The performance of the combined algorithm/model is assessed using three distinct granular test cases. -
Computational Modelling Group: Preprint 125
https://como.ceb.cam.ac.uk/preprints/125/The effects of fuel reactivity and intake air heating on the HCCI ranges are demonstrated by constructing the operating envelopes for the different test fuels and intake temperatures. -
Computational Modelling Group: News item 172
https://como.ceb.cam.ac.uk/news/172/The World Avatar project has been selected for the World Economic Forum (WEF)’s list of Global Use Cases as part of its Global Digital Twin Cities initiative. -
Computational Modelling Group: Preprint 310
https://como.ceb.cam.ac.uk/preprints/310/Our approach utilises ontologies to capture the data and material flows involved in design-make-test-analyse cycles, and employs autonomous agents as executable knowledge components to carry out the experimentation -
Computational Modelling Group: Engines
https://como.ceb.cam.ac.uk/research/engines/SRM. The work carried out towards simulating laminar and turbulent flames also proves to be an ideal test bed for investigating the many turbulence and reaction closure problems intrinsic to combustion -
Computational Modelling Group: Preprint 268
https://como.ceb.cam.ac.uk/preprints/268/HOPV15). It was found that the neural-based models generally performed better on the computational dataset with the Attentive FP model reaching a state of the art performance with the test -
Computational Modelling Group: Publication EES-13-744-771
https://como.ceb.cam.ac.uk/publications/EES-13-744-771/The orchestration of these novel technologies, so-called cyber-physical systems (CPS), provides further, synergetic effects that increase efficiency of energy provision and industrial production, thereby optimising economic feasibility and -
Computational Modelling Group: Pooya Azadi's Publications
https://como.ceb.cam.ac.uk/publications/pa360/Pooya Azadi. Full List of Publications co-authored by Pooya Azadi. Number of publications listed in category: 5. 2015. Immanuel Kemp, Sebastian Mosbach, John S. Dennis, and Markus Kraft, ChemCatChem (CCtC) 7(1), 137-143, (2015). and Markus Kraft, -
Computational Modelling Group: Janusz Sikorski's Preprints
https://como.ceb.cam.ac.uk/preprints/js918/Janusz Sikorski. Full List of Preprints co-authored by Janusz Sikorski. 203:Mei Qi Lim, Sushant S. Garud, Johannes Neukäufer, and Markus Kraft, Technical Report 203, c4e-Preprint Series, Cambridge, 2018. 184: Machine learning approach for -
Computational Modelling Group: Preprint 156
https://como.ceb.cam.ac.uk/preprints/156/Abstract. Soot particles formed in a system of non-premixed liquid fuel flames supported on a wick-fed, smoke point test burner (ASTM D1322-08) were characterised by in-situ visible -
Computational Modelling Group: Janusz Sikorski's Publications
https://como.ceb.cam.ac.uk/publications/js918/Janusz Sikorski. Full List of Publications co-authored by Janusz Sikorski. Number of publications listed in category: 9. 2019. Mei Qi Lim, Sushant S. Garud, Johannes Neukäufer, and Markus Kraft, Industrial & Engineering Chemistry Research 58(8), -
Computational Modelling Group: Publication EES-16-4020-4040
https://como.ceb.cam.ac.uk/publications/EES-16-4020-4040/Reference: Energy & Environmental Science 16, 4020-4040, (2023). Highlights. Techno economic modelling of wind farm co-located ESS attachments. ... Emissions reductions and economic impacts determined via imbalance market data. Developed supporting
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