Welcome from the Computational Modelling Group
Welcome to the website of the CoMo Group. We develop and apply modern numerical methods to problems arising in Chemical Engineering. The overall aim is to shorten the development period from research bench to the industrial production stage by providing insight into the underlying physics and supporting the scale-up of processes to industrial level.
The group currently consists of 19 members from various backgrounds. We are keen to collaborate with people from both within industry and academia, so please get in touch if you think you have common interests.
The group's research divides naturally into two inter-related branches. The first of these is research into mathematical methods, which consists of the development of stochastic particle methods, computational fluid dynamics and quantum chemistry. The other branch consists of research into applications, using the methods we have developed in addition to well established techniques. The main application areas are reactive flow, combustion, engine modelling, extraction, nano particle synthesis and dynamics. This research is sponsored on various levels by the UK, EU, and industry.
Recent News Subscribe
New paper - Universal Digital Twin: Integration of national-scale energy systems and climate data
Very excited to share our new paper investigating how our idea for a Universal Digital Twin can integrate national-scale energy systems and climate data!
This article applies a knowledge graph-based approach to unify multiple heterogeneous domains inherent in climate and energy supply research. Existing approaches that rely on bespoke models with spreadsheet-type inputs are noninterpretable, static and make it difficult to combine existing domain specific models. The difficulties inherent to this approach become increasingly prevalent as energy supply models gain complexity while society pursues a net-zero future. 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 integrates data describing the systems of interest and specifies respective links between domains. We represent the UK gas transmission system, and HadUK-Grid climate data set as linked data for the first time, formally associating the data with the statistical output areas used to report governmental administrative data throughout the UK. We demonstrate how computational agents contained within the World Avatar can operate on the knowledge graph, incorporating live feeds of data such as instantaneous gas flow rates, as well as parsing information into interpretable forms such as interactive visualizations. Through this approach, we enable a dynamic, interpretable, modular, and cross-domain representation of the UK that enables domain specific experts to contribute toward a national-scale digital twin.
Preprint 291 published
Preprint 291, ''Reviewing the modelling treatment of deposits in particulate filters for internal combustion emissions'', has been published!
Internal combustion in transport vehicles is still one of the biggest contributors to ultrafine particle emissions which have been proven to have many adverse effects on human health and the environment in general. To mitigate this problem a variety of particle filters have been developed and along with these filters a whole range of models aiming to optimise filter performance. This paper reviews a wide variety of particulate filter models for vehicular emission control and presents the volume of work in a unified and consistent notation. Particle filtration models are examined with respect to their filtration efficiency, the way they handle particle deposits within the filter wall, the formation of filter cake and the role of catalytic conversion and the effect of gaseous emission. Further, the impact of the chemical and physical properties of particulate deposits on the filter regeneration process is analysed and reaction pathways and rates are presented. In addition the accumulation of ash deposits and its impact on the filter behaviour is critically reviewed. Finally, various measures are identified that can potentially improve the current particle filter models.
PhD studentship available: Modelling the formation of carbon nanotubes
A PhD studentship to start in October 2022 is available in the Computational Modelling Group via the EPSRC Centre for Doctoral Training in Aerosol Science.
The project will develop a reactive molecular dynamics model to investigate the processes controlling the formation of carbon nanotubes. The model will provide important understanding to guide the production of replacements for high-carbon materials such as steel and cement. The project would suit students with a passion for programming and modelling, and with a knowledge of chemistry.
Prospective candidates should simultaneously apply to and win a partial scholarship from the University of Cambridge (selecting Professor Markus Kraft as their supervisor), and apply to the Aerosol Science CDT.
Preprint 284 published
Preprint 284, ''From Platform to Knowledge Graph: Evolution of Laboratory Automation'', has been published!
High-fidelity computer-aided experimentation is becoming more accessible with the development of computing power and artificial intelligence tools. The advancement of experimental hardware also empowers researchers to reach a level of accuracy that was not possible in the past. Marching towards the next generation of self-driving laboratories, the orchestration of both resources lies at the focal point of autonomous discovery in chemical science. To achieve such a goal, algorithmically-accessible data representations and standardised communication protocols are indispensable. In this perspective, we recategorise the recently introduced approach based on Materials Acceleration Platforms into five functional components and discuss recent case studies that focus on the data representation and exchange scheme between different components. Emerging technologies for interoperable data representation and multi-agent systems are also discussed with their recent applications in chemical automation. We hypothesise that knowledge graph technology, orchestrating semantic web technologies and multi-agent systems will be the driving force to bring data to knowledge, evolving our way of automating laboratory.
New paper - Soot inception: Carbonaceous nanoparticle formation in flames
Our new review on soot inception was just published in Progress in Energy and Combustion Science
The route by which gas-phase molecules in hydrocarbon flames form condensed-phase carbonaceous nanoparticles (incipient soot) is reviewed. These products of incomplete combustion are introduced as particulates and materials revealing both their useful applications and unwanted impacts as pollutants. Significant advances in experimental techniques in the last decade have allowed the gas phase precursors and the transformation from molecules to nanoparticles to be directly observed. These measurements combined with computational techniques allow for various mechanisms known to date to be compared and explored. Questions remain surrounding the various mechanisms that lead to nanoparticle formation. Mechanisms combining physical and chemical routes, so-called physically stabilised soot inception, are highlighted as a possible “middle way”.
Will using heat pumps for domestic heating increase or decrease inequality? We use the Universal Digital Twin to investigate...
Preprint 281, ''Universal Digital Twin – the impact of heat
pumps on inequality'', has been published!
This paper investigates how using heat pumps for domestic heating would impact fuel poverty and inequality. The analysis integrates a geospatial description of climate observations, gas and electricity infrastructure, energy consumption and fuel poverty from the base world of a Universal Digital Twin based on the World Avatar knowledge graph. Historic temperature data were used to estimate the temporal and geospatial variation of the performance of air source heat pumps in the UK. The corresponding change in gas and electricity consumption that could be achieved using heat pumps instead of gas for domestic heating was estimated. The geospatial impact of the heat pumps was assessed in terms of CO2 savings, and their effect on fuel cost and fuel poverty. Whilst heat pumps would reduce emissions, it is predicted that they would increase fuel costs. It was shown that both local and regional areas of high fuel poverty would experience some of the largest increases in fuel cost. This illustrates the potential for the transition to sustainable heating to exacerbate inequality. The analysis suggests that existing regional inequalities will increase, and that it comes down to a political choice between investments to support the most effective use of heat pumps, and delayed investments to counter inequality. The ability of the World Avatar to integrate the models and data necessary to perform this type of analysis provides a means to generate actionable information, for example, to enable local policy interventions to address the tension between social and environmental goals.
New paper - Universal Digital Twin – A Dynamic Knowledge Graph
Very excited to share our new paper proposing a design for a Universal Digital Twin!
This application of dynamic knowledge graphs presents a candidate to solve problems caused by lack of interoperability between different types of data and models. We believe that it has the potential to unify many different research streams, promoting synergistic effects that would be difficult to achieve in other ways. The paper explains how this approach is by design naturally suited to realizing the vision of a Universal Digital Twin. The dynamic knowledge graph is implemented using technologies from the Semantic Web. It is composed of concepts and instances that are defined using ontologies, and of computational agents that operate on both the concepts and instances to update the dynamic knowledge graph. By construction, it is distributed, supports cross-domain interoperability, and ensures that data are connected, portable, discoverable, and queryable via a uniform interface. The knowledge graph includes the notions of a “base world” that describes the real world and that is maintained by agents that incorporate real-time data, and of “parallel worlds” that support the intelligent exploration of alternative designs without affecting the base world. Use cases are presented that demonstrate the ability of the dynamic knowledge graph to host geospatial and chemical data, control chemistry experiments, perform cross-domain simulations, and perform scenario analysis. The questions of how to make intelligent suggestions for alternative scenarios and how to ensure alignment between the scenarios considered by the knowledge graph and the goals of society are considered. Work to extend the dynamic knowledge graph to develop a digital twin of the UK to support the decarbonization of the energy system is discussed. Important directions for future research are highlighted. A preview of some of the areas that we have investigated with our collaborators at CMCL can be found here: https://kg.cmclinnovations.com/.
CoMo group open to Feodor Lynen Research Fellows
In 2016, Prof. Markus Kraft was awarded the Friedrich Wilhelm Bessel Award and is therefore eligible to host Feodor Lynen Research Fellows sponsored by the Alexander von Humboldt Foundation. The Feodor Lynen Research Fellowship covers the salary and travel expenses of researchers from Germany to work at the host institution for 6-24 months. In addition, the fellowship enables the successful candidate to apply for alumni sponsorship from the Humboldt Foundation after the end of the fellowship and become part of their international network of academics.
If you are interested in working at the University of Cambridge and in joining the CoMo group as a post-doctoral researcher, please check your eligibility on the official Feodor Lynen Research Fellowship website and familiarise yourself with the application procedure. You will need to write a research proposal that aligns with your professional expertise. The topic might be of computational or experimental nature but should lie within the research areas of the CoMo group.