Computational science augments traditional research methods by accelerating and guiding experimental work and providing insight into processes and results. It is used across Shell’s businesses to predict everything from the chemistry of catalysts and batteries to capturing flow through reactors, pipelines and rocks. These are complex simulations which require high performance computing and algorithm optimisation.

A key aim of computational science is to use computer models to predict the performance of materials and systems in specific situations. One of the most striking aspects of computational science projects is their breadth of scale. This multiscale modelling covers interactions at the atomic and molecular levels to the design of reactors in industrial plants.

Our grasp of computational technology helped us to lead the way in technological developments in exploration in the 1960s, 70s and 80s. Demand for computational design and analysis has increased dramatically since mid-2000’s across increasingly varied domains. The growth in computer power from Moore’s law has made realistic catalyst modelling and complex fluid flow studies possible that were unthinkable only 15 years ago. Shell has a diverse team of chemical engineers, mechanical engineers, aerospace engineers, chemists, material scientists, mathematicians, physicists and computational scientists. This expertise in mathematics and computing is what gives us such a strong advantage today in developing and adopting digital technology.

By combining data-based models with physics/chemistry based computational models, we augment the power of both by integrating the speed and agility of AI with the interpretability and explainability of Computational Science, we move towards an era of Augmented Intelligence, where we augment our decision making manifold. Find out more in our recent publication on developing machine learning models for materials datasets.

Applications of Computational Science

  • Ferrari race car on track

    Optimising Fuel Formulation

    Shell has a long and highly successful relationship with Scuderia Ferrari. Shell leverages computational science technology to develop an advanced computer system for the Formula One fuel formulation. This system simulates a vast number of possible fuel formulations. This enables researchers to optimise fuel properties and narrow the range of possible solutions to a selection which can be tested using conventional chemical analyses in the Shell Technology Centre Hamburg, Germany. This computational pre-selection helps to accelerate the overall fuel development cycle.

  • Battery model

    Improving battery performance to increase potential for renewable energy and safety

    Chemical storage of electrical energy is an important aspect of meeting modern energy demands. It can mitigate the intermittency and spatial variability of renewable energy availability. Combining traditional physics and chemistry with simulation and advanced imaging technology enables us to compare different kinds of batteries, not only looking at which materials perform better, but also which are more sustainable. We are looking across the end-to-end life of the battery from design and use right through to materials recovery and recycling. Shell is modelling the changes in the physical state and composition of electrodes and electrolytes in batteries as well as performance at pack level. Find out more about the research conducted with University of California Berkeley.

  • Hydrogen refueling station

    Hydrogen value chain

    Hydrogen is one of many solutions we are working on as the world moves to a new energy system. •A key enabler for the hydrogen economy is the safe storage and transport of hydrogen fuel. This presents several technical challenges that Shell is addressing, for example, by developing new container designs using modern computational science methods. The aim is to increase the safety of operations and enable more widespread adoption of hydrogen as an energy vector. Find out more about our research of thermodynamic models for safe storage and mobility of hydrogen at high pressure.

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