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  1. Results that match 1 of 2 words

  2. Computational Modelling Group: Publication SAE-2010-01-0572

    https://como.ceb.cam.ac.uk/publications/SAE-2010-01-0572/
    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.
  3. Computational Modelling Group: Publication EP-75-1536-1541

    https://como.ceb.cam.ac.uk/publications/EP-75-1536-1541/
    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
  4. Computational Modelling Group: Publication AE-175-305-323

    https://como.ceb.cam.ac.uk/publications/AE-175-305-323/
    energy networks) at the top EIP level with the boundary conditions of economic, social and legal requirements.
  5. Computational Modelling Group: Publication CaF-164-250-258

    https://como.ceb.cam.ac.uk/publications/CaF-164-250-258/
    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
  6. Computational Modelling Group: Publication AJ-66-17039-

    https://como.ceb.cam.ac.uk/publications/AJ-66-17039-/
    Moreover, we find that ignoring performance degradation leads to an over‐estimation of 2.3-13.7% in system economic performance.
  7. Computational Modelling Group: Publication IToSE-11-448-456

    https://como.ceb.cam.ac.uk/publications/IToSE-11-448-456/
    Different sets of simulations are run for a small 5-bus test case and a larger model of Jurong Island in Singapore.
  8. Computational Modelling Group: Publication AE-298-117117-

    https://como.ceb.cam.ac.uk/publications/AE-298-117117-/
    Primarily due to CCGT generators typically being closer to larger southern loads than northern coal, transmission losses and the economic disincentive of a carbon tax combine in encouraging this transition.
  9. Computational Modelling Group: Publication RaSER-185-113591-

    https://como.ceb.cam.ac.uk/publications/RaSER-185-113591-/
    Recommendations for techno-economic and storage modelling. Abstract. The expansion of variable renewable energy (VRE) generation propagates numerous challenges for national energy systems.
  10. Computational Modelling Group: Publication EP-142-4092-4097

    https://como.ceb.cam.ac.uk/publications/EP-142-4092-4097/
    A single-cylinder research version of the Great Wall 4D20 diesel engine with exhaust gas recirculation is modelled for two test cases with different injection timings, injection pressures and fuel consumptions.
  11. Computational Modelling Group: Publication SAE-2004-01-2998

    https://como.ceb.cam.ac.uk/publications/SAE-2004-01-2998/
    Abstract. Modern engine developments result in very different gas pressure-temperature histories to those in RON/MON determination tests and strain the usefulness of those knock scales and their applicability in
  12. Computational Modelling Group: Publication SAE-2010-01-1245

    https://como.ceb.cam.ac.uk/publications/SAE-2010-01-1245/
    The control method was developed and implemented in the test engine, and resulted in much reduced NIMEP fluctuations during the switch.
  13. Computational Modelling Group: Publication IToICS-2-26-34

    https://como.ceb.cam.ac.uk/publications/IToICS-2-26-34/
    Electrification with renewables introduces complexity in systems in the deployment, integration, and efficient orchestration of electrified economic systems.
  14. Computational Modelling Group: Publication SAE-2011-26-0080

    https://como.ceb.cam.ac.uk/publications/SAE-2011-26-0080/
    Historically these targets have been achieved through on-going technological development using an iterative process of computational modelling, design, build and test.
  15. Computational Modelling Group: Engines Publications

    https://como.ceb.cam.ac.uk/publications/engines/
    Engines. Full List of Publications with a Engines theme. Number of publications listed in category: 78. 2023. Qiren Zhu, Yichen Zong, Maurin Salamanca, Jiawei Lai, Jethro Akroyd, Wenming Yang, and Markus Kraft, Fuel 338, 127296, (2023). Effects of
  16. Computational Modelling Group: Publication IECR-59-18991-19000

    https://como.ceb.cam.ac.uk/publications/IECR-59-18991-19000/
    To evaluate the performance of the proposed approach, the energy conversion efficiencies of more than 20,000 organic photovoltaics are used to train and test the model.
  17. Computational Modelling Group: Jethro Akroyd's Preprints

    https://como.ceb.cam.ac.uk/preprints/jwja2/
    Jethro Akroyd. Full List of Preprints co-authored by Jethro Akroyd. 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 Breeson
  18. Computational Modelling Group: Jethro Akroyd's Publications

    https://como.ceb.cam.ac.uk/publications/jwja2/
    Jethro Akroyd. Full List of Publications co-authored by Jethro Akroyd. Number of publications listed in category: 113. 2024. Yi-Kai Tsai, Magnus Müller, Karthik Nagarajan,and Markus Kraft, Energy and AI 17, 100376, (2024). and Markus Kraft, Energy
  19. Computational Modelling Group: Full Publication List

    https://como.ceb.cam.ac.uk/publications/full/
    Full Listing. Full List of the Computational Modelling Group's Publications. Number of publications listed in category: 365. 2024. Yi-Kai Tsai, Magnus Müller, Karthik Nagarajan,and Markus Kraft, Energy and AI 17, 100376, (2024). and Markus Kraft,
  20. 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
  21. 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
  22. Computational Modelling Group: Markus Kraft's Publications

    https://como.ceb.cam.ac.uk/publications/mk306/
    Markus Kraft. Full List of Publications co-authored by Markus Kraft. Number of publications listed in category: 344. 2024. Yi-Kai Tsai, Magnus Müller, Karthik Nagarajan,and Markus Kraft, Energy and AI 17, 100376, (2024). and Markus Kraft, Energy
  23. 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.
  24. 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.
  25. Weblabs_pressrelease2_final

    https://como.ceb.cam.ac.uk/media/resources/Weblabs_pressrelease.pdf
    15 Nov 2023: It is likely that interest will spread around Europe and the rest of the world as successful use of the system yields great educational and economic benefits.
  26. 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
  27. Computational Modelling Group: Preprint 216

    https://como.ceb.cam.ac.uk/preprints/216/
    Highlights. Economic feasibility study of using algae and biochar burial strategies to offset carbon emission from the use of conventional fossil-derived transport fuels. ... Abstract. This work presents an economic feasibility study of using algae and
  28. 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
  29. 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
  30. Computational Modelling Group: Preprint 127

    https://como.ceb.cam.ac.uk/preprints/127/
    Full-coupling to the gas-phase is achieved through operator-splitting. The convergence of the stochastic particle algorithm in test networks is evaluated as a function of network size, recycle fraction ... These test cases are used to identify methods
  31. Computational Modelling Group: Preprint 9

    https://como.ceb.cam.ac.uk/preprints/9/
    Numerical investigation of the performance of the two algorithms is carried out by applying them both to a test case, for which an analytical solution is calculated. ... The new algorithm, MFA, exhibits significant variance reduction - and therefore
  32. 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
  33. Computational Modelling Group: Preprint 185

    https://como.ceb.cam.ac.uk/preprints/185/
    Extensive numerical evaluation of smart sampling algorithm (SSA) is performed using a diverse test bed of analytical functions. ... Our numerical evaluation shows that SSA outperforms Sobol sampling (QS) for polynomial and kriging surrogates on a diverse
  34. Computational Modelling Group: Preprint 215

    https://como.ceb.cam.ac.uk/preprints/215/
    Particles evolve under inception, condensation, coagulation and sintering. Convergence behaviour investigated for a batch reactor test case. ... A numerical study is performed by simulating a simple batch reactor test case to investigate the convergence
  35. Computational Modelling Group: Preprint 273

    https://como.ceb.cam.ac.uk/preprints/273/
    We comprehensively evaluated, repaired and refined an existing CityGML ontology to produce an improved version that could pass the necessary tests and complete unit test development.
  36. A virtual octane test simulator for gasoline/ethanol blends

    https://como.ceb.cam.ac.uk/media/preprints/c4e-Preprint-111.pdf
    1 May 2019: b) Experimental and Computed Critical Com-pression Ratios. Figure 7: Simulations of the RON test [4]. ... 4] ANSI. Standard test method for research octane number of spark-ignition enginefuel.
  37. Computational Modelling Group: Preprint 179

    https://como.ceb.cam.ac.uk/preprints/179/
    Method is applied to test cases from organic and inorganic chemistry, including transition metal complexes. ... The application of the framework is demonstrated for test cases from organic and inorganic chemistry, including transition metal complexes.
  38. Computational Modelling Group: Preprint 305

    https://como.ceb.cam.ac.uk/preprints/305/
    Highlights. Techno economic modelling of wind farm co-located ESS attachments. Emissions reductions and economic impacts determined via imbalance market data.
  39. 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.
  40. Computational Modelling Group: Preprint 126

    https://como.ceb.cam.ac.uk/preprints/126/
    Abstract. We present a techno-economic assessment of algae-derived biodiesel under economic and technical uncertainties currently associated with the development of algal biorefineries.
  41. Computational Modelling Group: Preprint 248

    https://como.ceb.cam.ac.uk/preprints/248/
    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
  42. Developing Equipment for Remote Operation

    https://como.ceb.cam.ac.uk/media/resources/ted_sansom_ws.pdf
    15 Nov 2023: Centrifugal Pump Test Rig. • Coming soon! Innovators in Engineering Education TechnologyInnovators in Engineering Education Technology. ... General Considerations. Heat Transfer Equipment. Centrifugal Pump Test Rig. Future Software Developments.
  43. 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,
  44. 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.
  45. 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
  46. Computational Modelling Group: Preprint 94

    https://como.ceb.cam.ac.uk/preprints/94/
    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.
  47. 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.
  48. 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
  49. 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,
  50. 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.
  51. Computational Modelling Group: News item 161

    https://como.ceb.cam.ac.uk/news/161/
    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

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