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  2. 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.
  3. Computational Modelling Group: Preprint 308

    https://como.ceb.cam.ac.uk/preprints/308/
    It builds on the idea of connected digital twins based on the World Avatar dynamic knowledge graph to deploy an ecosystem of autonomous software agents to continuously ingest new real-world
  4. Computational Modelling Group: Preprint 313

    https://como.ceb.cam.ac.uk/preprints/313/
    This new approach offers significant advantages over the prior implementation that relied on knowledge graph embedding.
  5. Computational Modelling Group: Preprint 225

    https://como.ceb.cam.ac.uk/preprints/225/
    Pericondensed aromatics with different symmetries were calculated with this improved functional providing new scaling relationships for the OBG versus size.
  6. Computational Modelling Group: Preprint 160

    https://como.ceb.cam.ac.uk/preprints/160/
    An analysis of ethanol formation via silicates is also performed resulting in the addition of 27 new silica species to the model.
  7. Computational Modelling Group: Organised Conferences

    https://como.ceb.cam.ac.uk/conferences/organised/
    Organised. Full List of the Computational Modelling Group's Organised Conferences. Biomass Fuelled Power Generation with CO2 CaptureThe Moller Centre, Cambridge, 24th May 2013. Organised and chaired by Markus Kraft andCambridge, UK, 17th May 2012.
  8. Computational Modelling Group: Preprint 293

    https://como.ceb.cam.ac.uk/preprints/293/
    We introduce AutoCal, a new instance matcher which does not require labelled data and runs out of the box for a wide range of domains without tuning method-specific parameters.
  9. Computational Modelling Group: Preprint 208

    https://como.ceb.cam.ac.uk/preprints/208/
    A new model has been developed to describe the size-dependent effects that are responsible for transient particle mass (PM) and particle number (PN) emissions observed during experiments of the active
  10. Computational Modelling Group: Preprint 253

    https://como.ceb.cam.ac.uk/preprints/253/
    The model includes new processes to form seven-member rings via hydrogen-abstraction-acetylene-addition and bay closure reactions on sites containing partially embedded five-member rings.
  11. Computational Modelling Group: Preprint 315

    https://como.ceb.cam.ac.uk/preprints/315/
    The role of software agents in populating these ontologies is highlighted, showcasing how they transform raw data into meaningful structured knowledge and generate new insights within the TWA ecosystem.
  12. Computational Modelling Group: Numerics

    https://como.ceb.cam.ac.uk/research/algorithms/pbm/
    alternative. In this project we develop new numerical methods for the solution of multidimensional population balances with and without spatial dependence.
  13. Computational Modelling Group: CFD

    https://como.ceb.cam.ac.uk/research/cfd/spraydrying/
    Spray Dryer Modelling. A new project in partnership with Proctor and Gamble (P&G) aims to produce a detailed model of a spray-drying tower. ... The new particle-drying model currently under development will predict particle morphology, or ‘puffing’,
  14. Computational Modelling Group: Publication DP-5-6-

    https://como.ceb.cam.ac.uk/publications/DP-5-6-/
    Semantic approaches present a new opportunity for bidirectional data flows that can inform both governance processes and technological systems to co-create, cross-pollinate, and support optimal outcomes. ... Building on this opportunity, we suggest that
  15. Computational Modelling Group: Publication DE-3-23-

    https://como.ceb.cam.ac.uk/publications/DE-3-23-/
    In this work, we develop new ontologies to extend the World Avatar knowledge graph to represent gas grids, gas consumption statistics, and climate data. ... Using a combination of the new and existing ontologies we construct a Universal Digital Twin that
  16. Computational Modelling Group: Past Seminars

    https://como.ceb.cam.ac.uk/seminars/past/
    Past Seminars. Fuel anti-knock quality and fuel requirements of future SI engines. Dr Gautam Kalghatgi (Shell Global Solutions). Board Room, Department of Chemical Engineering. 14:00, 17th September 2008. Reaction Mechanism Generation (RNG) and the
  17. Computational Modelling Group: Publication DE-4-20-

    https://como.ceb.cam.ac.uk/publications/DE-4-20-/
    We designed a Distance Agent to track the interactions with the model members on the web, calculate distances between objects of interest, and add new knowledge to the Cities Knowledge Graph. ... This new era of GeoWeb 2.5 systems lowers the risk of
  18. Computational Modelling Group: Publication CCE-75-1-13

    https://como.ceb.cam.ac.uk/publications/CCE-75-1-13/
    Then, a new numerical method to solve stochastic reactor networks is devised. ... Lastly, the performance of the new compartmental model is then investigated by comparing the predicted particle size distribution against an experimentally measured size
  19. Computational Modelling Group: Experiments

    https://como.ceb.cam.ac.uk/research/experiments/
    In the spring of 2017, the Department of Chemical Engineering and Biotechnology relocated to a new building, providing the CoMo group with new laboratories. ... transform). Our group developed a new Abel inversion methodology specifically for co-flow
  20. Computational Modelling Group: Nanoparticles

    https://como.ceb.cam.ac.uk/research/nano/soot/
    The method makes use of the new concept of fictitious jumps employing a majorant kernel and hence is much more efficient than previously used Monte-Carlo methods.
  21. Computational Modelling Group: Publication JoCP-330-960-980

    https://como.ceb.cam.ac.uk/publications/JoCP-330-960-980/
    Abstract. A new method of moments for solving the population balance equation is developed and presented. ... The new method predicts mean quantities which are almost as accurate as a high-precision stochastic method calculated using the established
  22. Computational Modelling Group: Publication JoAS-140-105478-

    https://como.ceb.cam.ac.uk/publications/JoAS-140-105478-/
    Better agreement between the computed PSDs and PPSDs with measured ones was obtained with this new model. ... Moreover, the agreement between the computed and the measured primary particle size distribution (PPSD) was also improved with the new
  23. Computational Modelling Group: Publication AE-155-599-612

    https://como.ceb.cam.ac.uk/publications/AE-155-599-612/
    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
  24. Computational Modelling Group: Publication CES-203-358-379

    https://como.ceb.cam.ac.uk/publications/CES-203-358-379/
    Novel compartment residence time model developed. New breakage model reflects screw element geometry effects. ... Additionally, a new sub-model for the layering of primary particles onto larger agglomerates is presented.
  25. Computational Modelling Group: Publication DE-5-14-

    https://como.ceb.cam.ac.uk/publications/DE-5-14-/
    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
  26. Computational Modelling Group: Publication JoCP-397-108799-

    https://como.ceb.cam.ac.uk/publications/JoCP-397-108799-/
    Abstract. The mathematical description of a new detailed particle model for polydisperse aggregate particles is presented. ... The new particle description is used to model the aerosol synthesis of titanium dioxide (TiO.
  27. Computational Modelling Group: Publication AO-58-2662-2670

    https://como.ceb.cam.ac.uk/publications/AO-58-2662-2670/
    Reference: Applied Optics 58(10), 2662-2670, (2019). Highlights. New regression based methodology (FLiPPID) for performing the inverse Abel transform is reported. ... Abstract. A new method is presented for performing the Abel inversion by fitting the
  28. Computational Modelling Group: Nanoparticles

    https://como.ceb.cam.ac.uk/research/nano/particledynamics/
    In the nanophase however, these properties become superparamagnetic which has led to new applications in. ... Particle inception is the addition of new mass to the system from the gas phase in the form of a monomer particle:.
  29. Computational Modelling Group: Publication CES-188-18-33

    https://como.ceb.cam.ac.uk/publications/CES-188-18-33/
    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.
  30. 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,
  31. Computational Modelling Group: Publication DCE-3-100032-

    https://como.ceb.cam.ac.uk/publications/DCE-3-100032-/
    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.
  32. Computational Modelling Group: Publication JoCP-303-1-18

    https://como.ceb.cam.ac.uk/publications/JoCP-303-1-18/
    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.
  33. Computational Modelling Group: Publication EaA-8-100137-

    https://como.ceb.cam.ac.uk/publications/EaA-8-100137-/
    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
  34. Computational Modelling Group: Publication GMD-14-4509-4534

    https://como.ceb.cam.ac.uk/publications/GMD-14-4509-4534/
    The new model is integrated into the chemistry transport model EPISODE-CityChem v1.3. ... In the new model, ship parameters, especially speed and direction, are included to simulate the instantaneous ship positions and then the emission dispersion at
  35. Computational Modelling Group: Publication C-10-1071-1083

    https://como.ceb.cam.ac.uk/publications/C-10-1071-1083/
    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.
  36. Computational Modelling Group: Publication JoAS-76-188-199

    https://como.ceb.cam.ac.uk/publications/JoAS-76-188-199/
    A new model for silicon nanoparticle synthesis, Combustion & Flame, 160:947-958].
  37. Computational Modelling Group: Publication PRL-123-116105-

    https://como.ceb.cam.ac.uk/publications/PRL-123-116105-/
    A new mesh-based analysis showed that the global curvature was saddle-like.
  38. Computational Modelling Group: Publication PotCI-38-1525-1532

    https://como.ceb.cam.ac.uk/publications/PotCI-38-1525-1532/
    Reference: Proceedings of the Combustion Institute 38(1), 1525-1532, (2021). Highlights. A new crosslinking reaction between two pentagonal rings around the periphery of aromatic molecules is proposed to produce a ... Abstract. A new crosslinking
  39. Computational Modelling Group: Publication JotACS-144-11713-11728

    https://como.ceb.cam.ac.uk/publications/JotACS-144-11713-11728/
    Ontological representation of MOPs and their related concepts. Knowledge-based rational derivation of new MOP designs by a software agent. ... Our result provides rapid and automated instantiation of MOPs in TWA and unveils the immediate chemical space
  40. Computational Modelling Group: Engines

    https://como.ceb.cam.ac.uk/research/engines/conventional/
    The CoMo group utilizes demonstrated turbulent combustion sub-models within. CFD. in addition to the in-house development of new methods to account for the turbulent closure issues.
  41. Computational Modelling Group: Publication EP-75-1536-1541

    https://como.ceb.cam.ac.uk/publications/EP-75-1536-1541/
    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
  42. Computational Modelling Group: Publication AO-8-2462-2475

    https://como.ceb.cam.ac.uk/publications/AO-8-2462-2475/
    Abstract. In this work, a new OntoPESScan ontology is developed for the semantic representation of one-dimensional potential energy surface (PES) scans, a central concept in computational chemistry.
  43. Computational Modelling Group: Publication AE-258-114083-

    https://como.ceb.cam.ac.uk/publications/AE-258-114083-/
    This new approach is accurate, easy to implement and computationally cheap.
  44. Computational Modelling Group: Publication CaF-166-243-254

    https://como.ceb.cam.ac.uk/publications/CaF-166-243-254/
    An analysis of ethanol formation via silicates is also performed resulting in the addition of 27 new silica species to the model.
  45. Computational Modelling Group: Publication AJ-66-17039-

    https://como.ceb.cam.ac.uk/publications/AJ-66-17039-/
    This article proposes a new mixed‐integer linear programming (MILP) model for simultaneous design and operation optimization of a renewable CCHP system, considering component nonlinear operating characteristics and performance degradation with
  46. Computational Modelling Group: Publication CCE-131-106586-

    https://como.ceb.cam.ac.uk/publications/CCE-131-106586-/
    In this paper, we demonstrate the interoperability between different applications in JPS, introduce new domain ontologies into the JPS, and integrate live data.
  47. Computational Modelling Group: Publication CCE-137-106813-

    https://como.ceb.cam.ac.uk/publications/CCE-137-106813-/
    In addition, a new ontology, which we call OntoSpecies, is developed for uniquely representing chemical species.
  48. Computational Modelling Group: Publication AE-209-8-19

    https://como.ceb.cam.ac.uk/publications/AE-209-8-19/
    It incorporates blockchain technology to address ETS's management and fraud issues whilst it utilizes a reputation system in a new approach to improve ETS efficacy.
  49. Computational Modelling Group: Publication PotCI-38-2083-2091

    https://como.ceb.cam.ac.uk/publications/PotCI-38-2083-2091/
    Reference: Proceedings of the Combustion Institute 38(2), 2083-2091, (2021). Highlights. New measurements of CH and temperature are reported as 2D fields. ... Abstract. New experimental 2D measurements are reported to characterise the flame location,
  50. Computational Modelling Group: Publication JoAS-138-105451-

    https://como.ceb.cam.ac.uk/publications/JoAS-138-105451-/
    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.
  51. Computational Modelling Group: Publication JoWS-80-100815-

    https://como.ceb.cam.ac.uk/publications/JoWS-80-100815-/
    We introduce AutoCal, a new instance matcher which does not require labelled data and runs out of the box for a wide range of domains without tuning method-specific parameters.

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