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1 - 50 of 128 search results for Economics test |u:como.ceb.cam.ac.uk where 6 match all words and 122 match some words.
  1. Fully-matching results

  2. Computational Modelling Group: Andrew Smallbone's Preprints

    https://como.ceb.cam.ac.uk/preprints/ajs265/
    Andrew Smallbone. Full List of Preprints co-authored by Andrew Smallbone. 146:Richard H.S. Taylor, Paul Fennell, William R. Livingston, Nilay Shah, Niall Mac Dowell, John S. Dennis, Markus Kraft, Mohammed Pourkashanian, Mathieu Insa, Jenny Jones,
  3. Computational Modelling Group: Publication EfCE-33-36-44

    https://como.ceb.cam.ac.uk/publications/EfCE-33-36-44/
    2. combustion. Use of economic constraints to close an open-ended problem was highly valued by users. ... Subsequently, a classroom test with 45 undergraduate students with a fixed deadline was performed.
  4. Computational Modelling Group: Publication E-1-100014-

    https://como.ceb.cam.ac.uk/publications/E-1-100014-/
    Research on solar hydrogen production has advanced fast from lab-scale demonstrations to field tests of upscaled systems. ... A techno-economic analysis provides a critical comparison of the levelized cost of hydrogen output via each of the four
  5. Computational Modelling Group: Engines Preprints

    https://como.ceb.cam.ac.uk/preprints/engines/
    Engines. Full List of Preprints with a Engines theme. 298:Qiren Zhu, Yichen Zong, Jiawei Lai,Wenming Yang, and Markus Kraft, Technical Report 298, c4e-Preprint Series, Cambridge, 2022. 291:and Markus Kraft, Technical Report 291, c4e-Preprint Series,
  6. Computational Modelling Group: Full Preprint List

    https://como.ceb.cam.ac.uk/preprints/full/
    Full Listing. Full List of the Computational Modelling Group's Preprints. 324:and Markus Kraft, Technical Report 324, c4e-Preprint Series, Cambridge, 2024. 323:and Markus Kraft, Technical Report 323, c4e-Preprint Series, Cambridge, 2024. 322:Andrew
  7. Computational Modelling Group: Markus Kraft's Preprints

    https://como.ceb.cam.ac.uk/preprints/mk306/
    Markus Kraft. Full List of Preprints co-authored by Markus Kraft. 324:and Markus Kraft, Technical Report 324, c4e-Preprint Series, Cambridge, 2024. 323:and Markus Kraft, Technical Report 323, c4e-Preprint Series, Cambridge, 2024. 322:Andrew
  8. Results that match 1 of 2 words

  9. Computational Modelling Group

    https://como.ceb.cam.ac.uk/
    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.
  10. Computational Modelling Group: Andrew Smallbone

    https://como.ceb.cam.ac.uk/people/ajs265/
    Andrew Smallbone. Andrew Smallbone. Visitor. Biography. Presently Andrew is a Visiting Fellow to the group and is a Principal Engineer based at CMCL Innovations in Cambridge. Andrew is working with the CoMo group on developing advanced computational
  11. Computational Modelling Group: News item 13

    https://como.ceb.cam.ac.uk/news/13/
    As soon as the experimental rig was assembled and the piping was completed, we started to perform experiments to test the chemistry. ... Anders Selmer adjusting the reactor between two test runs. 2024 Computational Modelling Group.
  12. Computational Modelling Group: Benjamin Taylor

    https://como.ceb.cam.ac.uk/people/bjt36/
    Benjamin Taylor. Benjamin Taylor. Post Doc. Biography. Ben is a senior member of Wolfson College and Postdoctoral Researcher in the CoMo Group, Department of Chemical Engineering and Biotechnology. In addition to his work at the University of
  13. Computational Modelling Group: Publication AE-106-262-274

    https://como.ceb.cam.ac.uk/publications/AE-106-262-274/
    Under assumptions related to economics of scale, the techno-economic model is extended to account for varying industrial scales of production. ... Access options. This paper draws from preprint 119: Techno-economic assessment of carbon-negative algal
  14. Computational Modelling Group: News item 107

    https://como.ceb.cam.ac.uk/news/107/
    In collaboration with cmcl innovations, the CoMo Group will investigate the techno-economics of a C-FAST pilot plant, which aims to produce algal-derived liquid hydrocarbon fuels (e.g. ... The main objectives of the project are to. Carry out a detailed
  15. Computational Modelling Group: Publication AE-190-481-489

    https://como.ceb.cam.ac.uk/publications/AE-190-481-489/
    AE-190-481-489. Screening and techno-economic assessment of biomass-based power generation with CCS technologies to meet 2050 CO. ... Reference: Applied Energy 190, 481-489, (2017). Highlights. Techno-economics of 8 Biopower CCS technologies ranging from
  16. Computational Modelling Group: Ning Xiao

    https://como.ceb.cam.ac.uk/people/nx201/
    My research project is to develop the systematic level in algal biodiesel technology generated from renewable energy resources and assess the economic feasibility of the technology.
  17. Computational Modelling Group: News item 12

    https://como.ceb.cam.ac.uk/news/12/
    The new exercise consists of three parts:. A few preparatory questions on control enabling the students to identify the relevant variables and to calculate control parameters from open loop test data. ... P. ,. PI. and. PID. control, respectively using
  18. Computational Modelling Group: Preprint 119

    https://como.ceb.cam.ac.uk/preprints/119/
    Preprint 119. Technical Report 119, c4e-Preprint Series, Cambridge. Techno-economic assessment of carbon-negative algal biodiesel for transport solutions. ... Under assumptions related to economics of scale, the techno-economic model is extended to
  19. Computational Modelling Group: Publication BT-151-166-173

    https://como.ceb.cam.ac.uk/publications/BT-151-166-173/
    BT-151-166-173. The future viability of algae-derived biodiesel under economic and technical uncertainties. ... Reference: Bioresource Technology (BITE) 151, 166-173, (2014). Abstract. This study presents a techno-economic assessment of algae-derived
  20. Computational Modelling Group: Preprint 111

    https://como.ceb.cam.ac.uk/preprints/111/
    Preprint 111. Technical Report 111, c4e-Preprint Series, Cambridge. A virtual octane test simulator for gasoline/ethanol blends. ... emissions. A virtual octane test simulator was also developed to model new experimental data obtained in Research Octane
  21. Computational Modelling Group: Min Loon Yong

    https://como.ceb.cam.ac.uk/people/mly22/
    Min Loon Yong. Min Loon Yong. MPhil Student. Research Themes. Recent Preprints. 119:Tom Harris, Tim Helme,and Markus Kraft, Technical Report 119, c4e-Preprint Series, Cambridge, 2012. Click here for a full list ››. Recent Publications. Tom
  22. Computational Modelling Group: News item 7

    https://como.ceb.cam.ac.uk/news/7/
    Teaching Consortium Teaching Fellow Mike Goodson explains how to get the control parameters out of the open loop test data.
  23. Computational Modelling Group: Preprint 146

    https://como.ceb.cam.ac.uk/preprints/146/
    Highlights. Techno-economics of 8 Biopower CCS technologies ranging from TRL 4 to TRL 6-7. ... 2. capture were identified and as- sessed. Techno-economic characteristics such as capital and operating costs, LHV% electrical efficiencies as well as CO.
  24. Computational Modelling Group: News item 78

    https://como.ceb.cam.ac.uk/news/78/
    Firstly, a novel correlation between various tri-component blends (comprised of i-octane, n-heptane and toluene) and fuel RON and MON was obtained by carrying out standard octane tests.
  25. Computational Modelling Group: Rebecca Shaw

    https://como.ceb.cam.ac.uk/people/rcr33/
    Rebecca Shaw. Rebecca Shaw. Research Student. Biography. Rebecca Shaw graduated from Trinity Hall, Cambridge in 2009 with a BA/MEng from the Department of Chemical Engineering. Her master's project with the CoMo group focused on reduced the TiCl4 to
  26. Computational Modelling Group: Benjamin Taylor's Publications

    https://como.ceb.cam.ac.uk/publications/bjt36/
    Benjamin Taylor. Full List of Publications co-authored by Benjamin Taylor. Number of publications listed in category: 2. 2014. and Markus Kraft, Bioresource Technology (BITE) 151, 166-173, (2014). 2013. Tom Harris, Tim Helme,and Markus Kraft,
  27. Computational Modelling Group: News item 82

    https://como.ceb.cam.ac.uk/news/82/
    During the project the student will:. Extend existing Kinetic Monte Carlo models for the growth of carbonaceous nanomaterials to test different hypotheses to explain the observations made in graphene experiments.
  28. Computational Modelling Group: Jasdeep Singh

    https://como.ceb.cam.ac.uk/people/js400/
    India). Jasdeep has a B.Tech and M.Tech from IIT Delhi, India and was All India Rank-1 in GATE (Graduate Aptitude Test for Engineering) 2000.
  29. Computational Modelling Group: News item 108

    https://como.ceb.cam.ac.uk/news/108/
    th. May 2013 in Cambridge. This conference focuses on the scientific developments and techno-economic issues related to realisation of biomass (both co-fired and dedicated) based power generation both with
  30. Computational Modelling Group: Andrew Smallbone's Publications

    https://como.ceb.cam.ac.uk/publications/ajs265/
    Andrew Smallbone. Full List of Publications co-authored by Andrew Smallbone. Number of publications listed in category: 22. 2017. Richard H.S. Taylor, Paul Fennell, William R. Livingston, Nilay Shah, Niall Mac Dowell, John S. Dennis, Markus Kraft,
  31. Computational Modelling Group: John Atherton

    https://como.ceb.cam.ac.uk/people/ja685/
    Bachelor of Economics, University of Queensland, Australia. John Atherton has a background in electrical, power, software, data and chemical engineering and project management.
  32. Computational Modelling Group: Preprint 110

    https://como.ceb.cam.ac.uk/preprints/110/
    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 of aviation fuels. ... This work describes an adapted version of the test which is usually much more
  33. Computational Modelling Group: News item 151

    https://como.ceb.cam.ac.uk/news/151/
    The results indicate that the proposed approach can achieve significant economic benefits.
  34. 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
  35. Computational Modelling Group

    https://como.ceb.cam.ac.uk/resources/flpyro/
    Flame pyrometry. Colour ratio pyrometry is an economic and rapid technique to obtain soot temperatures and volume fractions from colour photographs of flames.
  36. 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.
  37. 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
  38. 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
  39. 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.
  40. Computational Modelling Group: Pooya Azadi

    https://como.ceb.cam.ac.uk/people/pa360/
    Pooya Azadi. Pooya Azadi. Post Doc. Biography. Pooya is currently a postdoctoral researcher at the CoMo Group, Department of Chemical Engineering and Biotechnology. His primary research interests fall into the areas of sustainable low carbon energy
  41. 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.
  42. 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
  43. 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
  44. 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
  45. Computational Modelling Group: Ning Xiao's Preprints

    https://como.ceb.cam.ac.uk/preprints/nx201/
    Ning Xiao. Full List of Preprints co-authored by Ning Xiao. 119:Tom Harris, Tim Helme,and Markus Kraft, Technical Report 119, c4e-Preprint Series, Cambridge, 2012. 2024 Computational Modelling Group. Department of Chemical Engineering and
  46. Computational Modelling Group: Min Loon Yong's Preprints

    https://como.ceb.cam.ac.uk/preprints/mly22/
    Min Loon Yong. Full List of Preprints co-authored by Min Loon Yong. 119:Tom Harris, Tim Helme,and Markus Kraft, Technical Report 119, c4e-Preprint Series, Cambridge, 2012. 2024 Computational Modelling Group. Department of Chemical Engineering and
  47. Computational Modelling Group: Benjamin Taylor's Preprints

    https://como.ceb.cam.ac.uk/preprints/bjt36/
    Benjamin Taylor. Full List of Preprints co-authored by Benjamin Taylor. 126:and Markus Kraft, Technical Report 126, c4e-Preprint Series, Cambridge, 2013. 119:Tom Harris, Tim Helme,and Markus Kraft, Technical Report 119, c4e-Preprint Series, Cambridge
  48. Computational Modelling Group: Amit Bhave's Preprints

    https://como.ceb.cam.ac.uk/preprints/ab349/
    Amit Bhave. Full List of Preprints co-authored by Amit Bhave. 287: The Conundrum in Smart City Governance: Interoperability and Compatibility in an ever-growing digital ecosystem. Hou Yee Quek, Franziska Sielker,Aurel von Richthofen, Pieter Herthogs,
  49. Computational Modelling Group: Preprint 287

    https://como.ceb.cam.ac.uk/preprints/287/
    We suggest that considering the technological dimension as a new addition to the trifecta of economic, environmental and social sustainability goals that guide planning processes, can help governments to address this
  50. 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,
  51. Computational Modelling Group: Preprint 150

    https://como.ceb.cam.ac.uk/preprints/150/
    The concept of Industry 4.0 translation to an EIP is introduced, which delivers an expert system allowing users to monitor, control, and optimise the social, economic and environmental repercussions of
  52. Computational Modelling Group: Publication AE-251-113363-

    https://como.ceb.cam.ac.uk/publications/AE-251-113363-/
    Abstract. This work presents an economic feasibility study of using algae and biochar burial strategies to offset carbon emission from the use of conventional fossil-derived transport fuels. ... The economic feasibility is quantified on the basis that

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