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  2. Computational Modelling Group: Preprint 152

    https://como.ceb.cam.ac.uk/preprints/152/
    The issues relevant to adapting an existing park differs from those associated with constructing a new park using eco-industrial principles. ... Additional topics, such as network analysis, company motivation, confidentiality issues and introduction of
  3. Computational Modelling Group: Publication JoCP-352-373-387

    https://como.ceb.cam.ac.uk/publications/JoCP-352-373-387/
    JoCP-352-373-387. A new iterative scheme for solving the discrete Smoluchowski equation. ... Access options. This paper draws from preprint 183: A New Iterative Scheme For Solving The Discrete Smoluchowski Equation.
  4. Computational Modelling Group: Preprint 195

    https://como.ceb.cam.ac.uk/preprints/195/
    New breakage model reflects screw element geometry effects. Model captures the liquid distributing/growth promoting effects of kneading elements. ... We introduce a new twin-screw breakage model which takes into account the differing breakage dynamics
  5. Computational Modelling Group: Publication CaF-209-133-143

    https://como.ceb.cam.ac.uk/publications/CaF-209-133-143/
    CaF-209-133-143. A new methodology to calculate process rates in a kinetic Monte Carlo model of PAH growth. ... Access options. This paper draws from preprint 224: A new methodology to calculate process rates in a KMC model of PAH growth.
  6. Computational Modelling Group: Preprint 266

    https://como.ceb.cam.ac.uk/preprints/266/
    A new method that automatically generates training questions from ontologies is also implemented.
  7. Computational Modelling Group: Preprint 79

    https://como.ceb.cam.ac.uk/preprints/79/
    Abstract. In this paper, new experimentally determined octane numbers (RON & MON) of blends of a tri-component surrogate consisting of toluene, n-Heptane, i-Octane (called toluene reference fuel TRF) arranged
  8. Computational Modelling Group: Preprint 215

    https://como.ceb.cam.ac.uk/preprints/215/
    New multivariate PBM with detailed morphological description of titania aggregates. Overlapping spheres model of aggregates, resolving position of individual primaries. ... Experimental hot-wall reactor simulated. Abstract. The mathematical description
  9. Computational Modelling Group: Preprint 52

    https://como.ceb.cam.ac.uk/preprints/52/
    New rates for the reactions involved in the cyclodehydrogenation process for the formation of 6-member rings on PAHs are calculated in this work based on density functional theory simulations.
  10. Computational Modelling Group: Michael Balthasar

    https://como.ceb.cam.ac.uk/people/mb404/
    Michael Balthasar. Michael Balthasar. Post Doc. Biography. My name is Michael Balthasar and I graduated with a MA Chemistry at the University of Kaiserslautern in Germany in 1996. I made my PhD at the Department of Combustion Physics at the Lund
  11. Computational Modelling Group: Preprint 56

    https://como.ceb.cam.ac.uk/preprints/56/
    Associated Themes:. Abstract. A new multidimensional model for the wet granulation of powders is presented, which includes the transformations coalescence, compaction, reaction, penetration and breakage.
  12. Computational Modelling Group: Preprint 254

    https://como.ceb.cam.ac.uk/preprints/254/
    A new crosslinking reaction between two pentagonal rings around the periphery of aromatic molecules is proposed to produce a planar aromatic penta-linked hydrocarbon (APLH) complex. ... Abstract. A new crosslinking reaction between two pentagonal rings
  13. Computational Modelling Group: Gustavo Leon

    https://como.ceb.cam.ac.uk/people/gl413/
    in the design of new technologies.
  14. Computational Modelling Group: Preprint 309

    https://como.ceb.cam.ac.uk/preprints/309/
    We develop three new ontologies to describe and link environmental measurements and their respective reporting stations, flood events and their potential impact on population and built infrastructure as well as the
  15. Computational Modelling Group

    https://como.ceb.cam.ac.uk/resources/flpyro/
    In a recent project, our group developed a new Abel inversion method (FLiPPID) tailored to the analysis of co-flow diffusion flame images.
  16. Computational Modelling Group: Preprint 47

    https://como.ceb.cam.ac.uk/preprints/47/
    Eibeck and W. Wagner, Ann. Appl. Prob. (2001) 11:1137-1165] and allows the derivation of a range of new stochastic particle algorithms.
  17. Computational Modelling Group: Preprint 236

    https://como.ceb.cam.ac.uk/preprints/236/
    In addition, a new ontology, which we call OntoSpecies, is developed for uniquely representing chemical species.
  18. Computational Modelling Group: Preprint 111

    https://como.ceb.cam.ac.uk/preprints/111/
    emissions. A virtual octane test simulator was also developed to model new experimental data obtained in Research Octane Number (RON) tests, for the first time results were used to benchmark chemical
  19. Computational Modelling Group: Publication CaF-160-947-958

    https://como.ceb.cam.ac.uk/publications/CaF-160-947-958/
    CaF-160-947-958. A new model for silicon nanoparticle synthesis. Authors: William J. ... Access options. This paper draws from preprint 121: A new model for silicon nanoparticle synthesis.
  20. Computational Modelling Group: Preprint 46

    https://como.ceb.cam.ac.uk/preprints/46/
    A new wall-impingement sub-model is incorporated into the stochastic spray model for direct injection.
  21. Computational Modelling Group: Preprint 45

    https://como.ceb.cam.ac.uk/preprints/45/
    A second, new model is introduced, in which all growth is concentrated on the formation of a frustum between the two primary particles and used to test the importance of the
  22. Computational Modelling Group: Preprint 5

    https://como.ceb.cam.ac.uk/preprints/5/
    To describe the particle dynamics of the aerosol synthesis two different numerical techniques are studied; first, the method of moments (MoM), and second, a new stochastic particle method (SPM), which results
  23. Computational Modelling Group: Preprint 113

    https://como.ceb.cam.ac.uk/preprints/113/
    By using a new counting method and a simple collision efficiency model, experimental mass spectra has been qualitatively reproduced and the results fit well with the experimental PSDs of the various
  24. Computational Modelling Group: Preprint 48

    https://como.ceb.cam.ac.uk/preprints/48/
    The new tool is intended to be used for performing a variety of otherwise exceedingly expensive computational tasks such as multi-cycle multi-cylinder simulations, transient operation and control, optimization of
  25. Computational Modelling Group: Publication CSaT-191-747-765

    https://como.ceb.cam.ac.uk/publications/CSaT-191-747-765/
    CSaT-191-747-765. Ion-Induced Soot Nucleation Using a New Potential for Curved Aromatics. ... Access options. This paper draws from preprint 214: Ion-induced soot nucleation using a new potential for curved aromatics.
  26. Computational Modelling Group

    https://como.ceb.cam.ac.uk/vacancies/
    The fellowships target researchers holding a PhD who wish to carry out their research activities abroad, acquire new skills and develop their careers.
  27. Computational Modelling Group: Preprint 9

    https://como.ceb.cam.ac.uk/preprints/9/
    The new algorithm, MFA, exhibits significant variance reduction - and therefore improved simulation efficiency - for the prediction of higher moments, but for our test case the zeroth moment (the total number of
  28. Computational Modelling Group: Anders Selmer

    https://como.ceb.cam.ac.uk/people/as631/
    The project consists of two parts: incorporating an existing experiment from MIT in the laboratory course for the Cambridge students (together with Mike Goodson) and then to set up a new
  29. Computational Modelling Group: Preprint 25

    https://como.ceb.cam.ac.uk/preprints/25/
    We introduce a new generalized majorant kernel to exploit the method of fictitious jumps reducing the computational expense for the direct simulation algorithm.
  30. Computational Modelling Group: Preprint 134

    https://como.ceb.cam.ac.uk/preprints/134/
    Lastly, we use molecular dynamics with a new potential specifically developed for PAH interaction and the combined PAH-PP/KMC-ARS model to show that pyrene dimerisation is unlikely to be
  31. 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
  32. Computational Modelling Group: Preprint 237

    https://como.ceb.cam.ac.uk/preprints/237/
    A new mesh-based analysis showed that the global curvature was saddle-like.
  33. Computational Modelling Group: Preprint 192

    https://como.ceb.cam.ac.uk/preprints/192/
    Each stochastic jump process is presented in detail, including a new nucleation jump event capable of capturing the immersion nucleation processes in twin-screw granulation.
  34. Computational Modelling Group: Preprint 322

    https://como.ceb.cam.ac.uk/preprints/322/
    Our exploration leads us to the concept of a CreatorSpace', a distributed digital system resembling existing hackerspaces and makerspaces known for accelerating the prototyping of new technologies worldwide.
  35. Computational Modelling Group: Preprint 8

    https://como.ceb.cam.ac.uk/preprints/8/
    A new stochastic approach is introduced to model the convective heat transfer, which accounts for fluctuations and fluid-wall interaction effects.
  36. Computational Modelling Group: Preprint 150

    https://como.ceb.cam.ac.uk/preprints/150/
    technologies. Abstract. This paper presents new insights into the implementation of Industry 4.0 technologies (novel mathematical and computer-based methods) for designing and optimising the eco-industrial park (EIP) of
  37. Computational Modelling Group: Preprint 286

    https://como.ceb.cam.ac.uk/preprints/286/
    The natural language processing (NLP) models of the QA system need to be trained in order to interpret questions to be answered by new agents.
  38. Computational Modelling Group: Preprint 154

    https://como.ceb.cam.ac.uk/preprints/154/
    It is found that the new algorithms show better numerical performance over the two existing methods especially for systems with significant amount of large particles and high fragmentation rates.
  39. Computational Modelling Group: Automated Lab

    https://como.ceb.cam.ac.uk/research/weblabs/old/
    Previous Work - The MIT iLabs. In 1999. MIT. and Microsoft announced an alliance to conduct research and create new technologies to improve information technology-enabled teaching models and educational tools for ... Computational Modelling Group's
  40. Computational Modelling Group: Preprint 13

    https://como.ceb.cam.ac.uk/preprints/13/
    Abstract. In this paper new stochastic algorithms for the numerical solution of systems of ordinary differential equations (ODEs) are proposed.
  41. Computational Modelling Group: Preprint 7

    https://como.ceb.cam.ac.uk/preprints/7/
    specific case of the new algorithm.
  42. Computational Modelling Group: Preprint 29

    https://como.ceb.cam.ac.uk/preprints/29/
    A new model for the decay in the surface activity is proposed in which the activity of the soot particle depends only on the history of that particle and the local
  43. Computational Modelling Group: Raphael Shirley

    https://como.ceb.cam.ac.uk/people/ras81/
    Raphael Shirley. Raphael Shirley. Research Student. Biography. Raphael spent just over three years with the Computational Modelling Group from 2007 to 2011. He originally graduated in 2006 with a degree in physics from The Cavendish Laboratory in
  44. Computational Modelling Group: Preprint 283

    https://como.ceb.cam.ac.uk/preprints/283/
    The system of agents also visualised and analysed the model by autonomously tracking interactions with a web interface as well as enriched the model by adding new information to the knowledge
  45. Computational Modelling Group: CFD

    https://como.ceb.cam.ac.uk/research/cfd/rtds/
    Residence Time Distributions from CFD. The aim of this project was to develop a new method for first-pass validation of Computational Fluid Dynamics (. CFD. ) flow fields, by comparing calculated residence ... time distributions (. RTDs. ) with those
  46. Computational Modelling Group: Preprint 226

    https://como.ceb.cam.ac.uk/preprints/226/
    New sintering parameters, informed by molecular dynamics simulations in the literature, are introduced into the model to account for the sintering behaviour of sub-10 nm particles.
  47. Computational Modelling Group: Preprint 207

    https://como.ceb.cam.ac.uk/preprints/207/
    The results indicate that the physical interaction between fullerene-like polar aromatics and chemi-ions is critically assisting the nucleation, and opens a new route to reduce pollution and improve
  48. Computational Modelling Group: Preprint 244

    https://como.ceb.cam.ac.uk/preprints/244/
    This new approach is accurate, easy to implement and computationally cheap.
  49. Computational Modelling Group: Preprint 294

    https://como.ceb.cam.ac.uk/preprints/294/
    Abstract. In this work, a new OntoPESScan ontology is developed for the semantic representation of potential energy surfaces (PES), a central concept in computational chemistry.
  50. Computational Modelling Group: The World Avatar

    https://como.ceb.cam.ac.uk/research/twa/
    solar and wind energy, the transport system, heating of commercial and domestic buildings, in addition to considerations relating to the acceptance and adoption of new technologies by the public.
  51. Computational Modelling Group: Preprint 181

    https://como.ceb.cam.ac.uk/preprints/181/
    Secondly, JPS can be used to carry out process simulation. New process equilibrium can be evaluated after certain operation parameters change.

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